A Data Colocation Grid Framework for Big Data Medical Image Processing: Backend Design

PubMed Central

Huo, Yuankai; Parvathaneni, Prasanna; Plassard, Andrew J.; Bermudez, Camilo; Yao, Yuang; Lyu, Ilwoo; Gokhale, Aniruddha; Landman, Bennett A.

2018-01-01

When processing large medical imaging studies, adopting high performance grid computing resources rapidly becomes important. We recently presented a "medical image processing-as-a-service" grid framework that offers promise in utilizing the Apache Hadoop ecosystem and HBase for data colocation by moving computation close to medical image storage. However, the framework has not yet proven to be easy to use in a heterogeneous hardware environment. Furthermore, the system has not yet validated when considering variety of multi-level analysis in medical imaging. Our target design criteria are (1) improving the framework’s performance in a heterogeneous cluster, (2) performing population based summary statistics on large datasets, and (3) introducing a table design scheme for rapid NoSQL query. In this paper, we present a heuristic backend interface application program interface (API) design for Hadoop & HBase for Medical Image Processing (HadoopBase-MIP). The API includes: Upload, Retrieve, Remove, Load balancer (for heterogeneous cluster) and MapReduce templates. A dataset summary statistic model is discussed and implemented by MapReduce paradigm. We introduce a HBase table scheme for fast data query to better utilize the MapReduce model. Briefly, 5153 T1 images were retrieved from a university secure, shared web database and used to empirically access an in-house grid with 224 heterogeneous CPU cores. Three empirical experiments results are presented and discussed: (1) load balancer wall-time improvement of 1.5-fold compared with a framework with built-in data allocation strategy, (2) a summary statistic model is empirically verified on grid framework and is compared with the cluster when deployed with a standard Sun Grid Engine (SGE), which reduces 8-fold of wall clock time and 14-fold of resource time, and (3) the proposed HBase table scheme improves MapReduce computation with 7 fold reduction of wall time compare with a naïve scheme when datasets are relative small. The source code and interfaces have been made publicly available. PMID:29887668

DESPIC: Detecting Early Signatures of Persuasion in Information Cascades

DTIC Science & Technology

2015-08-27

over NoSQL Databases, Proceedings of the 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2014). 26-MAY-14, . : , P...over NoSQL Databases. Proceedings of the 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2014). Chicago, IL, USA...distributed NoSQL databases including HBase and Riak, we finalized the requirements of the optimal computational architecture to support our framework

Design and implementation of spatial knowledge grid for integrated spatial analysis

NASA Astrophysics Data System (ADS)

Liu, Xiangnan; Guan, Li; Wang, Ping

2006-10-01

Supported by spatial information grid(SIG), the spatial knowledge grid (SKG) for integrated spatial analysis utilizes the middleware technology in constructing the spatial information grid computation environment and spatial information service system, develops spatial entity oriented spatial data organization technology, carries out the profound computation of the spatial structure and spatial process pattern on the basis of Grid GIS infrastructure, spatial data grid and spatial information grid (specialized definition). At the same time, it realizes the complex spatial pattern expression and the spatial function process simulation by taking the spatial intelligent agent as the core to establish space initiative computation. Moreover through the establishment of virtual geographical environment with man-machine interactivity and blending, complex spatial modeling, network cooperation work and spatial community decision knowledge driven are achieved. The framework of SKG is discussed systematically in this paper. Its implement flow and the key technology with examples of overlay analysis are proposed as well.

An Advanced Framework for Improving Situational Awareness in Electric Power Grid Operation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yousu; Huang, Zhenyu; Zhou, Ning

With the deployment of new smart grid technologies and the penetration of renewable energy in power systems, significant uncertainty and variability is being introduced into power grid operation. Traditionally, the Energy Management System (EMS) operates the power grid in a deterministic mode, and thus will not be sufficient for the future control center in a stochastic environment with faster dynamics. One of the main challenges is to improve situational awareness. This paper reviews the current status of power grid operation and presents a vision of improving wide-area situational awareness for a future control center. An advanced framework, consisting of parallelmore » state estimation, state prediction, parallel contingency selection, parallel contingency analysis, and advanced visual analytics, is proposed to provide capabilities needed for better decision support by utilizing high performance computing (HPC) techniques and advanced visual analytic techniques. Research results are presented to support the proposed vision and framework.« less

A coarse-grid-projection acceleration method for finite-element incompressible flow computations

NASA Astrophysics Data System (ADS)

Kashefi, Ali; Staples, Anne; FiN Lab Team

2015-11-01

Coarse grid projection (CGP) methodology provides a framework for accelerating computations by performing some part of the computation on a coarsened grid. We apply the CGP to pressure projection methods for finite element-based incompressible flow simulations. Based on it, the predicted velocity field data is restricted to a coarsened grid, the pressure is determined by solving the Poisson equation on the coarse grid, and the resulting data are prolonged to the preset fine grid. The contributions of the CGP method to the pressure correction technique are twofold: first, it substantially lessens the computational cost devoted to the Poisson equation, which is the most time-consuming part of the simulation process. Second, it preserves the accuracy of the velocity field. The velocity and pressure spaces are approximated by Galerkin spectral element using piecewise linear basis functions. A restriction operator is designed so that fine data are directly injected into the coarse grid. The Laplacian and divergence matrices are driven by taking inner products of coarse grid shape functions. Linear interpolation is implemented to construct a prolongation operator. A study of the data accuracy and the CPU time for the CGP-based versus non-CGP computations is presented. Laboratory for Fluid Dynamics in Nature.

Economic models for management of resources in peer-to-peer and grid computing

NASA Astrophysics Data System (ADS)

Buyya, Rajkumar; Stockinger, Heinz; Giddy, Jonathan; Abramson, David

2001-07-01

The accelerated development in Peer-to-Peer (P2P) and Grid computing has positioned them as promising next generation computing platforms. They enable the creation of Virtual Enterprises (VE) for sharing resources distributed across the world. However, resource management, application development and usage models in these environments is a complex undertaking. This is due to the geographic distribution of resources that are owned by different organizations or peers. The resource owners of each of these resources have different usage or access policies and cost models, and varying loads and availability. In order to address complex resource management issues, we have proposed a computational economy framework for resource allocation and for regulating supply and demand in Grid computing environments. The framework provides mechanisms for optimizing resource provider and consumer objective functions through trading and brokering services. In a real world market, there exist various economic models for setting the price for goods based on supply-and-demand and their value to the user. They include commodity market, posted price, tenders and auctions. In this paper, we discuss the use of these models for interaction between Grid components in deciding resource value and the necessary infrastructure to realize them. In addition to normal services offered by Grid computing systems, we need an infrastructure to support interaction protocols, allocation mechanisms, currency, secure banking, and enforcement services. Furthermore, we demonstrate the usage of some of these economic models in resource brokering through Nimrod/G deadline and cost-based scheduling for two different optimization strategies on the World Wide Grid (WWG) testbed that contains peer-to-peer resources located on five continents: Asia, Australia, Europe, North America, and South America.

A System for Monitoring and Management of Computational Grids

NASA Technical Reports Server (NTRS)

Smith, Warren; Biegel, Bryan (Technical Monitor)

2002-01-01

As organizations begin to deploy large computational grids, it has become apparent that systems for observation and control of the resources, services, and applications that make up such grids are needed. Administrators must observe the operation of resources and services to ensure that they are operating correctly and they must control the resources and services to ensure that their operation meets the needs of users. Users are also interested in the operation of resources and services so that they can choose the most appropriate ones to use. In this paper we describe a prototype system to monitor and manage computational grids and describe the general software framework for control and observation in distributed environments that it is based on.

Uniformity on the grid via a configuration framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Igor V Terekhov et al.

2003-03-11

As Grid permeates modern computing, Grid solutions continue to emerge and take shape. The actual Grid development projects continue to provide higher-level services that evolve in functionality and operate with application-level concepts which are often specific to the virtual organizations that use them. Physically, however, grids are comprised of sites whose resources are diverse and seldom project readily onto a grid's set of concepts. In practice, this also creates problems for site administrators who actually instantiate grid services. In this paper, we present a flexible, uniform framework to configure a grid site and its facilities, and otherwise describe the resourcesmore » and services it offers. We start from a site configuration and instantiate services for resource advertisement, monitoring and data handling; we also apply our framework to hosting environment creation. We use our ideas in the Information Management part of the SAM-Grid project, a grid system which will deliver petabyte-scale data to the hundreds of users. Our users are High Energy Physics experimenters who are scattered worldwide across dozens of institutions and always use facilities that are shared with other experiments as well as other grids. Our implementation represents information in the XML format and includes tools written in XQuery and XSLT.« less

Distributed data mining on grids: services, tools, and applications.

PubMed

Cannataro, Mario; Congiusta, Antonio; Pugliese, Andrea; Talia, Domenico; Trunfio, Paolo

2004-12-01

Data mining algorithms are widely used today for the analysis of large corporate and scientific datasets stored in databases and data archives. Industry, science, and commerce fields often need to analyze very large datasets maintained over geographically distributed sites by using the computational power of distributed and parallel systems. The grid can play a significant role in providing an effective computational support for distributed knowledge discovery applications. For the development of data mining applications on grids we designed a system called Knowledge Grid. This paper describes the Knowledge Grid framework and presents the toolset provided by the Knowledge Grid for implementing distributed knowledge discovery. The paper discusses how to design and implement data mining applications by using the Knowledge Grid tools starting from searching grid resources, composing software and data components, and executing the resulting data mining process on a grid. Some performance results are also discussed.

A Roadmap for caGrid, an Enterprise Grid Architecture for Biomedical Research

PubMed Central

Saltz, Joel; Hastings, Shannon; Langella, Stephen; Oster, Scott; Kurc, Tahsin; Payne, Philip; Ferreira, Renato; Plale, Beth; Goble, Carole; Ervin, David; Sharma, Ashish; Pan, Tony; Permar, Justin; Brezany, Peter; Siebenlist, Frank; Madduri, Ravi; Foster, Ian; Shanbhag, Krishnakant; Mead, Charlie; Hong, Neil Chue

2012-01-01

caGrid is a middleware system which combines the Grid computing, the service oriented architecture, and the model driven architecture paradigms to support development of interoperable data and analytical resources and federation of such resources in a Grid environment. The functionality provided by caGrid is an essential and integral component of the cancer Biomedical Informatics Grid (caBIG™) program. This program is established by the National Cancer Institute as a nationwide effort to develop enabling informatics technologies for collaborative, multi-institutional biomedical research with the overarching goal of accelerating translational cancer research. Although the main application domain for caGrid is cancer research, the infrastructure provides a generic framework that can be employed in other biomedical research and healthcare domains. The development of caGrid is an ongoing effort, adding new functionality and improvements based on feedback and use cases from the community. This paper provides an overview of potential future architecture and tooling directions and areas of improvement for caGrid and caGrid-like systems. This summary is based on discussions at a roadmap workshop held in February with participants from biomedical research, Grid computing, and high performance computing communities. PMID:18560123

A roadmap for caGrid, an enterprise Grid architecture for biomedical research.

PubMed

Saltz, Joel; Hastings, Shannon; Langella, Stephen; Oster, Scott; Kurc, Tahsin; Payne, Philip; Ferreira, Renato; Plale, Beth; Goble, Carole; Ervin, David; Sharma, Ashish; Pan, Tony; Permar, Justin; Brezany, Peter; Siebenlist, Frank; Madduri, Ravi; Foster, Ian; Shanbhag, Krishnakant; Mead, Charlie; Chue Hong, Neil

2008-01-01

caGrid is a middleware system which combines the Grid computing, the service oriented architecture, and the model driven architecture paradigms to support development of interoperable data and analytical resources and federation of such resources in a Grid environment. The functionality provided by caGrid is an essential and integral component of the cancer Biomedical Informatics Grid (caBIG) program. This program is established by the National Cancer Institute as a nationwide effort to develop enabling informatics technologies for collaborative, multi-institutional biomedical research with the overarching goal of accelerating translational cancer research. Although the main application domain for caGrid is cancer research, the infrastructure provides a generic framework that can be employed in other biomedical research and healthcare domains. The development of caGrid is an ongoing effort, adding new functionality and improvements based on feedback and use cases from the community. This paper provides an overview of potential future architecture and tooling directions and areas of improvement for caGrid and caGrid-like systems. This summary is based on discussions at a roadmap workshop held in February with participants from biomedical research, Grid computing, and high performance computing communities.

Development of a Flexible Framework of Common Hypersonic Navier-Strokes Meshes for the Space Shuttle Orbiter

NASA Technical Reports Server (NTRS)

Alter, Stephen J.; Reuthler, James J.; McDaniel, Ryan D.

2003-01-01

A flexible framework for the development of block structured volume grids for hypersonic Navier-Stokes flow simulations was developed for analysis of the Shuttle Orbiter Columbia. The development of the flexible framework, resulted in an ability to quickly generate meshes to directly correlate solutions contributed by participating groups on a common surface mesh, providing confidence for the extension of the envelope of solutions and damage scenarios. The framework draws on the experience of NASA Langely and NASA Ames Research Centers in structured grid generation, and consists of a grid generation process that is implemented through a division of responsibilities. The nominal division of labor consisted of NASA Johnson Space Center coordinating the damage scenarios to be analyzed by the Aerothermodynamics Columbia Accident Investigation (CAI) team, Ames developing the surface grids that described the computational volume about the orbiter, and Langely improving grid quality of Ames generated data and constructing the final volume grids. Distributing the work among the participants in the Aerothermodynamic CIA team resulted in significantly less time required to construct complete meshes than possible by any individual participant. The approach demonstrated that the One-NASA grid generation team could sustain the demand for new meshes to explore new damage scenarios within a aggressive timeline.

Cyberinfrastructure for End-to-End Environmental Explorations

NASA Astrophysics Data System (ADS)

Merwade, V.; Kumar, S.; Song, C.; Zhao, L.; Govindaraju, R.; Niyogi, D.

2007-12-01

The design and implementation of a cyberinfrastructure for End-to-End Environmental Exploration (C4E4) is presented. The C4E4 framework addresses the need for an integrated data/computation platform for studying broad environmental impacts by combining heterogeneous data resources with state-of-the-art modeling and visualization tools. With Purdue being a TeraGrid Resource Provider, C4E4 builds on top of the Purdue TeraGrid data management system and Grid resources, and integrates them through a service-oriented workflow system. It allows researchers to construct environmental workflows for data discovery, access, transformation, modeling, and visualization. Using the C4E4 framework, we have implemented an end-to-end SWAT simulation and analysis workflow that connects our TeraGrid data and computation resources. It enables researchers to conduct comprehensive studies on the impact of land management practices in the St. Joseph watershed using data from various sources in hydrologic, atmospheric, agricultural, and other related disciplines.

A Framework for Control and Observation in Distributed Environments

NASA Technical Reports Server (NTRS)

Smith, Warren

2001-01-01

As organizations begin to deploy large computational grids, it has become apparent that systems for observation and control of the resources, services, and applications that make up such grids are needed. Administrators must observe the operation of resources and services to ensure that they are operating correctly and they must control the resources and services to ensure that their operation meets the needs of users. Further, users need to observe the performance of their applications so that this performance can be improved and control how their applications execute in a dynamic grid environment. In this paper we describe our software framework for control and observation of resources, services, and applications that supports such uses and we provide examples of how our framework can be used.

A Taxonomy on Accountability and Privacy Issues in Smart Grids

NASA Astrophysics Data System (ADS)

Naik, Ameya; Shahnasser, Hamid

2017-07-01

Cyber-Physical Systems (CPS) are combinations of computation, networking, and physical processes. Embedded computers and networks monitor control the physical processes, which affect computations and vice versa. Two applications of cyber physical systems include health-care and smart grid. In this paper, we have considered privacy aspects of cyber-physical system applicable to smart grid. Smart grid in collaboration with different stockholders can help in the improvement of power generation, communication, circulation and consumption. The proper management with monitoring feature by customers and utility of energy usage can be done through proper transmission and electricity flow; however cyber vulnerability could be increased due to an increased assimilation and linkage. This paper discusses various frameworks and architectures proposed for achieving accountability in smart grids by addressing privacy issues in Advance Metering Infrastructure (AMI). This paper also highlights additional work needed for accountability in more precise specifications such as uncertainty or ambiguity, indistinct, unmanageability, and undetectably.

Job Scheduling in a Heterogeneous Grid Environment

NASA Technical Reports Server (NTRS)

Shan, Hong-Zhang; Smith, Warren; Oliker, Leonid; Biswas, Rupak

2004-01-01

Computational grids have the potential for solving large-scale scientific problems using heterogeneous and geographically distributed resources. However, a number of major technical hurdles must be overcome before this potential can be realized. One problem that is critical to effective utilization of computational grids is the efficient scheduling of jobs. This work addresses this problem by describing and evaluating a grid scheduling architecture and three job migration algorithms. The architecture is scalable and does not assume control of local site resources. The job migration policies use the availability and performance of computer systems, the network bandwidth available between systems, and the volume of input and output data associated with each job. An extensive performance comparison is presented using real workloads from leading computational centers. The results, based on several key metrics, demonstrate that the performance of our distributed migration algorithms is significantly greater than that of a local scheduling framework and comparable to a non-scalable global scheduling approach.

Information Power Grid: Distributed High-Performance Computing and Large-Scale Data Management for Science and Engineering

NASA Technical Reports Server (NTRS)

Johnston, William E.; Gannon, Dennis; Nitzberg, Bill; Feiereisen, William (Technical Monitor)

2000-01-01

The term "Grid" refers to distributed, high performance computing and data handling infrastructure that incorporates geographically and organizationally dispersed, heterogeneous resources that are persistent and supported. The vision for NASN's Information Power Grid - a computing and data Grid - is that it will provide significant new capabilities to scientists and engineers by facilitating routine construction of information based problem solving environments / frameworks that will knit together widely distributed computing, data, instrument, and human resources into just-in-time systems that can address complex and large-scale computing and data analysis problems. IPG development and deployment is addressing requirements obtained by analyzing a number of different application areas, in particular from the NASA Aero-Space Technology Enterprise. This analysis has focussed primarily on two types of users: The scientist / design engineer whose primary interest is problem solving (e.g., determining wing aerodynamic characteristics in many different operating environments), and whose primary interface to IPG will be through various sorts of problem solving frameworks. The second type of user if the tool designer: The computational scientists who convert physics and mathematics into code that can simulate the physical world. These are the two primary users of IPG, and they have rather different requirements. This paper describes the current state of IPG (the operational testbed), the set of capabilities being put into place for the operational prototype IPG, as well as some of the longer term R&D tasks.

A Modeling Framework for Optimal Computational Resource Allocation Estimation: Considering the Trade-offs between Physical Resolutions, Uncertainty and Computational Costs

NASA Astrophysics Data System (ADS)

Moslehi, M.; de Barros, F.; Rajagopal, R.

2014-12-01

Hydrogeological models that represent flow and transport in subsurface domains are usually large-scale with excessive computational complexity and uncertain characteristics. Uncertainty quantification for predicting flow and transport in heterogeneous formations often entails utilizing a numerical Monte Carlo framework, which repeatedly simulates the model according to a random field representing hydrogeological characteristics of the field. The physical resolution (e.g. grid resolution associated with the physical space) for the simulation is customarily chosen based on recommendations in the literature, independent of the number of Monte Carlo realizations. This practice may lead to either excessive computational burden or inaccurate solutions. We propose an optimization-based methodology that considers the trade-off between the following conflicting objectives: time associated with computational costs, statistical convergence of the model predictions and physical errors corresponding to numerical grid resolution. In this research, we optimally allocate computational resources by developing a modeling framework for the overall error based on a joint statistical and numerical analysis and optimizing the error model subject to a given computational constraint. The derived expression for the overall error explicitly takes into account the joint dependence between the discretization error of the physical space and the statistical error associated with Monte Carlo realizations. The accuracy of the proposed framework is verified in this study by applying it to several computationally extensive examples. Having this framework at hand aims hydrogeologists to achieve the optimum physical and statistical resolutions to minimize the error with a given computational budget. Moreover, the influence of the available computational resources and the geometric properties of the contaminant source zone on the optimum resolutions are investigated. We conclude that the computational cost associated with optimal allocation can be substantially reduced compared with prevalent recommendations in the literature.

A Framework for Managing Inter-Site Storage Area Networks using Grid Technologies

NASA Technical Reports Server (NTRS)

Kobler, Ben; McCall, Fritz; Smorul, Mike

2006-01-01

The NASA Goddard Space Flight Center and the University of Maryland Institute for Advanced Computer Studies are studying mechanisms for installing and managing Storage Area Networks (SANs) that span multiple independent collaborating institutions using Storage Area Network Routers (SAN Routers). We present a framework for managing inter-site distributed SANs that uses Grid Technologies to balance the competing needs to control local resources, share information, delegate administrative access, and manage the complex trust relationships between the participating sites.

A perspective on unstructured grid flow solvers

NASA Technical Reports Server (NTRS)

Venkatakrishnan, V.

1995-01-01

This survey paper assesses the status of compressible Euler and Navier-Stokes solvers on unstructured grids. Different spatial and temporal discretization options for steady and unsteady flows are discussed. The integration of these components into an overall framework to solve practical problems is addressed. Issues such as grid adaptation, higher order methods, hybrid discretizations and parallel computing are briefly discussed. Finally, some outstanding issues and future research directions are presented.

Climate simulations and services on HPC, Cloud and Grid infrastructures

NASA Astrophysics Data System (ADS)

Cofino, Antonio S.; Blanco, Carlos; Minondo Tshuma, Antonio

2017-04-01

Cloud, Grid and High Performance Computing have changed the accessibility and availability of computing resources for Earth Science research communities, specially for Climate community. These paradigms are modifying the way how climate applications are being executed. By using these technologies the number, variety and complexity of experiments and resources are increasing substantially. But, although computational capacity is increasing, traditional applications and tools used by the community are not good enough to manage this large volume and variety of experiments and computing resources. In this contribution, we evaluate the challenges to run climate simulations and services on Grid, Cloud and HPC infrestructures and how to tackle them. The Grid and Cloud infrastructures provided by EGI's VOs ( esr , earth.vo.ibergrid and fedcloud.egi.eu) will be evaluated, as well as HPC resources from PRACE infrastructure and institutional clusters. To solve those challenges, solutions using DRM4G framework will be shown. DRM4G provides a good framework to manage big volume and variety of computing resources for climate experiments. This work has been supported by the Spanish National R&D Plan under projects WRF4G (CGL2011-28864), INSIGNIA (CGL2016-79210-R) and MULTI-SDM (CGL2015-66583-R) ; the IS-ENES2 project from the 7FP of the European Commission (grant agreement no. 312979); the European Regional Development Fund—ERDF and the Programa de Personal Investigador en Formación Predoctoral from Universidad de Cantabria and Government of Cantabria.

Service-Oriented Architecture for NVO and TeraGrid Computing

NASA Technical Reports Server (NTRS)

Jacob, Joseph; Miller, Craig; Williams, Roy; Steenberg, Conrad; Graham, Matthew

2008-01-01

The National Virtual Observatory (NVO) Extensible Secure Scalable Service Infrastructure (NESSSI) is a Web service architecture and software framework that enables Web-based astronomical data publishing and processing on grid computers such as the National Science Foundation's TeraGrid. Characteristics of this architecture include the following: (1) Services are created, managed, and upgraded by their developers, who are trusted users of computing platforms on which the services are deployed. (2) Service jobs can be initiated by means of Java or Python client programs run on a command line or with Web portals. (3) Access is granted within a graduated security scheme in which the size of a job that can be initiated depends on the level of authentication of the user.

Combinatorial-topological framework for the analysis of global dynamics.

PubMed

Bush, Justin; Gameiro, Marcio; Harker, Shaun; Kokubu, Hiroshi; Mischaikow, Konstantin; Obayashi, Ippei; Pilarczyk, Paweł

2012-12-01

We discuss an algorithmic framework based on efficient graph algorithms and algebraic-topological computational tools. The framework is aimed at automatic computation of a database of global dynamics of a given m-parameter semidynamical system with discrete time on a bounded subset of the n-dimensional phase space. We introduce the mathematical background, which is based upon Conley's topological approach to dynamics, describe the algorithms for the analysis of the dynamics using rectangular grids both in phase space and parameter space, and show two sample applications.

Combinatorial-topological framework for the analysis of global dynamics

NASA Astrophysics Data System (ADS)

Bush, Justin; Gameiro, Marcio; Harker, Shaun; Kokubu, Hiroshi; Mischaikow, Konstantin; Obayashi, Ippei; Pilarczyk, Paweł

2012-12-01

We discuss an algorithmic framework based on efficient graph algorithms and algebraic-topological computational tools. The framework is aimed at automatic computation of a database of global dynamics of a given m-parameter semidynamical system with discrete time on a bounded subset of the n-dimensional phase space. We introduce the mathematical background, which is based upon Conley's topological approach to dynamics, describe the algorithms for the analysis of the dynamics using rectangular grids both in phase space and parameter space, and show two sample applications.

Structured Overlapping Grid Simulations of Contra-rotating Open Rotor Noise

NASA Technical Reports Server (NTRS)

Housman, Jeffrey A.; Kiris, Cetin C.

2015-01-01

Computational simulations using structured overlapping grids with the Launch Ascent and Vehicle Aerodynamics (LAVA) solver framework are presented for predicting tonal noise generated by a contra-rotating open rotor (CROR) propulsion system. A coupled Computational Fluid Dynamics (CFD) and Computational AeroAcoustics (CAA) numerical approach is applied. Three-dimensional time-accurate hybrid Reynolds Averaged Navier-Stokes/Large Eddy Simulation (RANS/LES) CFD simulations are performed in the inertial frame, including dynamic moving grids, using a higher-order accurate finite difference discretization on structured overlapping grids. A higher-order accurate free-stream preserving metric discretization with discrete enforcement of the Geometric Conservation Law (GCL) on moving curvilinear grids is used to create an accurate, efficient, and stable numerical scheme. The aeroacoustic analysis is based on a permeable surface Ffowcs Williams-Hawkings (FW-H) approach, evaluated in the frequency domain. A time-step sensitivity study was performed using only the forward row of blades to determine an adequate time-step. The numerical approach is validated against existing wind tunnel measurements.

Impact of surface coupling grids on tropical cyclone extremes in high-resolution atmospheric simulations

DOE PAGES

Zarzycki, Colin M.; Reed, Kevin A.; Bacmeister, Julio T.; ...

2016-02-25

This article discusses the sensitivity of tropical cyclone climatology to surface coupling strategy in high-resolution configurations of the Community Earth System Model. Using two supported model setups, we demonstrate that the choice of grid on which the lowest model level wind stress and surface fluxes are computed may lead to differences in cyclone strength in multi-decadal climate simulations, particularly for the most intense cyclones. Using a deterministic framework, we show that when these surface quantities are calculated on an ocean grid that is coarser than the atmosphere, the computed frictional stress is misaligned with wind vectors in individual atmospheric gridmore » cells. This reduces the effective surface drag, and results in more intense cyclones when compared to a model configuration where the ocean and atmosphere are of equivalent resolution. Our results demonstrate that the choice of computation grid for atmosphere–ocean interactions is non-negligible when considering climate extremes at high horizontal resolution, especially when model components are on highly disparate grids.« less

A framework for WRF to WRF-IBM grid nesting to enable multiscale simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wiersema, David John; Lundquist, Katherine A.; Chow, Fotini Katapodes

With advances in computational power, mesoscale models, such as the Weather Research and Forecasting (WRF) model, are often pushed to higher resolutions. As the model’s horizontal resolution is refined, the maximum resolved terrain slope will increase. Because WRF uses a terrain-following coordinate, this increase in resolved terrain slopes introduces additional grid skewness. At high resolutions and over complex terrain, this grid skewness can introduce large numerical errors that require methods, such as the immersed boundary method, to keep the model accurate and stable. Our implementation of the immersed boundary method in the WRF model, WRF-IBM, has proven effective at microscalemore » simulations over complex terrain. WRF-IBM uses a non-conforming grid that extends beneath the model’s terrain. Boundary conditions at the immersed boundary, the terrain, are enforced by introducing a body force term to the governing equations at points directly beneath the immersed boundary. Nesting between a WRF parent grid and a WRF-IBM child grid requires a new framework for initialization and forcing of the child WRF-IBM grid. This framework will enable concurrent multi-scale simulations within the WRF model, improving the accuracy of high-resolution simulations and enabling simulations across a wide range of scales.« less

An Exact Dual Adjoint Solution Method for Turbulent Flows on Unstructured Grids

NASA Technical Reports Server (NTRS)

Nielsen, Eric J.; Lu, James; Park, Michael A.; Darmofal, David L.

2003-01-01

An algorithm for solving the discrete adjoint system based on an unstructured-grid discretization of the Navier-Stokes equations is presented. The method is constructed such that an adjoint solution exactly dual to a direct differentiation approach is recovered at each time step, yielding a convergence rate which is asymptotically equivalent to that of the primal system. The new approach is implemented within a three-dimensional unstructured-grid framework and results are presented for inviscid, laminar, and turbulent flows. Improvements to the baseline solution algorithm, such as line-implicit relaxation and a tight coupling of the turbulence model, are also presented. By storing nearest-neighbor terms in the residual computation, the dual scheme is computationally efficient, while requiring twice the memory of the flow solution. The scheme is expected to have a broad impact on computational problems related to design optimization as well as error estimation and grid adaptation efforts.

A practical approach to virtualization in HEP

NASA Astrophysics Data System (ADS)

Buncic, P.; Aguado Sánchez, C.; Blomer, J.; Harutyunyan, A.; Mudrinic, M.

2011-01-01

In the attempt to solve the problem of processing data coming from LHC experiments at CERN at a rate of 15PB per year, for almost a decade the High Enery Physics (HEP) community has focused its efforts on the development of the Worldwide LHC Computing Grid. This generated large interest and expectations promising to revolutionize computing. Meanwhile, having initially taken part in the Grid standardization process, industry has moved in a different direction and started promoting the Cloud Computing paradigm which aims to solve problems on a similar scale and in equally seamless way as it was expected in the idealized Grid approach. A key enabling technology behind Cloud computing is server virtualization. In early 2008, an R&D project was established in the PH-SFT group at CERN to investigate how virtualization technology could be used to improve and simplify the daily interaction of physicists with experiment software frameworks and the Grid infrastructure. In this article we shall first briefly compare Grid and Cloud computing paradigms and then summarize the results of the R&D activity pointing out where and how virtualization technology could be effectively used in our field in order to maximize practical benefits whilst avoiding potential pitfalls.

Description of the F-16XL Geometry and Computational Grids Used in CAWAPI

NASA Technical Reports Server (NTRS)

Boelens, O. J.; Badcock, K. J.; Gortz, S.; Morton, S.; Fritz, W.; Karman, S. L., Jr.; Michal, T.; Lamar, J. E.

2009-01-01

The objective of the Cranked-Arrow Wing Aerodynamics Project International (CAWAPI) was to allow a comprehensive validation of Computational Fluid Dynamics methods against the CAWAP flight database. A major part of this work involved the generation of high-quality computational grids. Prior to the grid generation an IGES file containing the air-tight geometry of the F-16XL aircraft was generated by a cooperation of the CAWAPI partners. Based on this geometry description both structured and unstructured grids have been generated. The baseline structured (multi-block) grid (and a family of derived grids) has been generated by the National Aerospace Laboratory NLR. Although the algorithms used by NLR had become available just before CAWAPI and thus only a limited experience with their application to such a complex configuration had been gained, a grid of good quality was generated well within four weeks. This time compared favourably with that required to produce the unstructured grids in CAWAPI. The baseline all-tetrahedral and hybrid unstructured grids has been generated at NASA Langley Research Center and the USAFA, respectively. To provide more geometrical resolution, trimmed unstructured grids have been generated at EADS-MAS, the UTSimCenter, Boeing Phantom Works and KTH/FOI. All grids generated within the framework of CAWAPI will be discussed in the article. Both results obtained on the structured grids and the unstructured grids showed a significant improvement in agreement with flight test data in comparison with those obtained on the structured multi-block grid used during CAWAP.

A tool for optimization of the production and user analysis on the Grid, C. Grigoras for the ALICE Collaboration

NASA Astrophysics Data System (ADS)

Grigoras, Costin; Carminati, Federico; Vladimirovna Datskova, Olga; Schreiner, Steffen; Lee, Sehoon; Zhu, Jianlin; Gheata, Mihaela; Gheata, Andrei; Saiz, Pablo; Betev, Latchezar; Furano, Fabrizio; Mendez Lorenzo, Patricia; Grigoras, Alina Gabriela; Bagnasco, Stefano; Peters, Andreas Joachim; Saiz Santos, Maria Dolores

2011-12-01

With the LHC and ALICE entering a full operation and production modes, the amount of Simulation and RAW data processing and end user analysis computational tasks are increasing. The efficient management of all these tasks, all of which have large differences in lifecycle, amounts of processed data and methods to analyze the end result, required the development and deployment of new tools in addition to the already existing Grid infrastructure. To facilitate the management of the large scale simulation and raw data reconstruction tasks, ALICE has developed a production framework called a Lightweight Production Manager (LPM). The LPM is automatically submitting jobs to the Grid based on triggers and conditions, for example after a physics run completion. It follows the evolution of the job and publishes the results on the web for worldwide access by the ALICE physicists. This framework is tightly integrated with the ALICE Grid framework AliEn. In addition to the publication of the job status, LPM is also allowing a fully authenticated interface to the AliEn Grid catalogue, to browse and download files, and in the near future will provide simple types of data analysis through ROOT plugins. The framework is also being extended to allow management of end user jobs.

DOE Office of Scientific and Technical Information (OSTI.GOV)

McKinnon, Archibald D.; Thompson, Seth R.; Doroshchuk, Ruslan A.

mart grid technologies are transforming the electric power grid into a grid with bi-directional flows of both power and information. Operating millions of new smart meters and smart appliances will significantly impact electric distribution systems resulting in greater efficiency. However, the scale of the grid and the new types of information transmitted will potentially introduce several security risks that cannot be addressed by traditional, centralized security techniques. We propose a new bio-inspired cyber security approach. Social insects, such as ants and bees, have developed complex-adaptive systems that emerge from the collective application of simple, light-weight behaviors. The Digital Ants frameworkmore » is a bio-inspired framework that uses mobile light-weight agents. Sensors within the framework use digital pheromones to communicate with each other and to alert each other of possible cyber security issues. All communication and coordination is both localized and decentralized thereby allowing the framework to scale across the large numbers of devices that will exist in the smart grid. Furthermore, the sensors are light-weight and therefore suitable for implementation on devices with limited computational resources. This paper will provide a brief overview of the Digital Ants framework and then present results from test bed-based demonstrations that show that Digital Ants can identify a cyber attack scenario against smart meter deployments.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

von Laszewski, G.; Foster, I.; Gawor, J.

In this paper we report on the features of the Java Commodity Grid Kit. The Java CoG Kit provides middleware for accessing Grid functionality from the Java framework. Java CoG Kit middleware is general enough to design a variety of advanced Grid applications with quite different user requirements. Access to the Grid is established via Globus protocols, allowing the Java CoG Kit to communicate also with the C Globus reference implementation. Thus, the Java CoG Kit provides Grid developers with the ability to utilize the Grid, as well as numerous additional libraries and frameworks developed by the Java community tomore » enable network, Internet, enterprise, and peer-to peer computing. A variety of projects have successfully used the client libraries of the Java CoG Kit to access Grids driven by the C Globus software. In this paper we also report on the efforts to develop server side Java CoG Kit components. As part of this research we have implemented a prototype pure Java resource management system that enables one to run Globus jobs on platforms on which a Java virtual machine is supported, including Windows NT machines.« less

Grid Computing at GSI for ALICE and FAIR - present and future

NASA Astrophysics Data System (ADS)

Schwarz, Kilian; Uhlig, Florian; Karabowicz, Radoslaw; Montiel-Gonzalez, Almudena; Zynovyev, Mykhaylo; Preuss, Carsten

2012-12-01

The future FAIR experiments CBM and PANDA have computing requirements that fall in a category that could currently not be satisfied by one single computing centre. One needs a larger, distributed computing infrastructure to cope with the amount of data to be simulated and analysed. Since 2002, GSI operates a tier2 center for ALICE@CERN. The central component of the GSI computing facility and hence the core of the ALICE tier2 centre is a LSF/SGE batch farm, currently split into three subclusters with a total of 15000 CPU cores shared by the participating experiments, and accessible both locally and soon also completely via Grid. In terms of data storage, a 5.5 PB Lustre file system, directly accessible from all worker nodes is maintained, as well as a 300 TB xrootd-based Grid storage element. Based on this existing expertise, and utilising ALICE's middleware ‘AliEn’, the Grid infrastructure for PANDA and CBM is being built. Besides a tier0 centre at GSI, the computing Grids of the two FAIR collaborations encompass now more than 17 sites in 11 countries and are constantly expanding. The operation of the distributed FAIR computing infrastructure benefits significantly from the experience gained with the ALICE tier2 centre. A close collaboration between ALICE Offline and FAIR provides mutual advantages. The employment of a common Grid middleware as well as compatible simulation and analysis software frameworks ensure significant synergy effects.

Integrating Xgrid into the HENP distributed computing model

NASA Astrophysics Data System (ADS)

Hajdu, L.; Kocoloski, A.; Lauret, J.; Miller, M.

2008-07-01

Modern Macintosh computers feature Xgrid, a distributed computing architecture built directly into Apple's OS X operating system. While the approach is radically different from those generally expected by the Unix based Grid infrastructures (Open Science Grid, TeraGrid, EGEE), opportunistic computing on Xgrid is nonetheless a tempting and novel way to assemble a computing cluster with a minimum of additional configuration. In fact, it requires only the default operating system and authentication to a central controller from each node. OS X also implements arbitrarily extensible metadata, allowing an instantly updated file catalog to be stored as part of the filesystem itself. The low barrier to entry allows an Xgrid cluster to grow quickly and organically. This paper and presentation will detail the steps that can be taken to make such a cluster a viable resource for HENP research computing. We will further show how to provide to users a unified job submission framework by integrating Xgrid through the STAR Unified Meta-Scheduler (SUMS), making tasks and jobs submission effortlessly at reach for those users already using the tool for traditional Grid or local cluster job submission. We will discuss additional steps that can be taken to make an Xgrid cluster a full partner in grid computing initiatives, focusing on Open Science Grid integration. MIT's Xgrid system currently supports the work of multiple research groups in the Laboratory for Nuclear Science, and has become an important tool for generating simulations and conducting data analyses at the Massachusetts Institute of Technology.

Comparative analysis of existing models for power-grid synchronization

NASA Astrophysics Data System (ADS)

Nishikawa, Takashi; Motter, Adilson E.

2015-01-01

The dynamics of power-grid networks is becoming an increasingly active area of research within the physics and network science communities. The results from such studies are typically insightful and illustrative, but are often based on simplifying assumptions that can be either difficult to assess or not fully justified for realistic applications. Here we perform a comprehensive comparative analysis of three leading models recently used to study synchronization dynamics in power-grid networks—a fundamental problem of practical significance given that frequency synchronization of all power generators in the same interconnection is a necessary condition for a power grid to operate. We show that each of these models can be derived from first principles within a common framework based on the classical model of a generator, thereby clarifying all assumptions involved. This framework allows us to view power grids as complex networks of coupled second-order phase oscillators with both forcing and damping terms. Using simple illustrative examples, test systems, and real power-grid datasets, we study the inherent frequencies of the oscillators as well as their coupling structure, comparing across the different models. We demonstrate, in particular, that if the network structure is not homogeneous, generators with identical parameters need to be modeled as non-identical oscillators in general. We also discuss an approach to estimate the required (dynamical) system parameters that are unavailable in typical power-grid datasets, their use for computing the constants of each of the three models, and an open-source MATLAB toolbox that we provide for these computations.

Integration of a neuroimaging processing pipeline into a pan-canadian computing grid

NASA Astrophysics Data System (ADS)

Lavoie-Courchesne, S.; Rioux, P.; Chouinard-Decorte, F.; Sherif, T.; Rousseau, M.-E.; Das, S.; Adalat, R.; Doyon, J.; Craddock, C.; Margulies, D.; Chu, C.; Lyttelton, O.; Evans, A. C.; Bellec, P.

2012-02-01

The ethos of the neuroimaging field is quickly moving towards the open sharing of resources, including both imaging databases and processing tools. As a neuroimaging database represents a large volume of datasets and as neuroimaging processing pipelines are composed of heterogeneous, computationally intensive tools, such open sharing raises specific computational challenges. This motivates the design of novel dedicated computing infrastructures. This paper describes an interface between PSOM, a code-oriented pipeline development framework, and CBRAIN, a web-oriented platform for grid computing. This interface was used to integrate a PSOM-compliant pipeline for preprocessing of structural and functional magnetic resonance imaging into CBRAIN. We further tested the capacity of our infrastructure to handle a real large-scale project. A neuroimaging database including close to 1000 subjects was preprocessed using our interface and publicly released to help the participants of the ADHD-200 international competition. This successful experiment demonstrated that our integrated grid-computing platform is a powerful solution for high-throughput pipeline analysis in the field of neuroimaging.

DEM Based Modeling: Grid or TIN? The Answer Depends

NASA Astrophysics Data System (ADS)

Ogden, F. L.; Moreno, H. A.

2015-12-01

The availability of petascale supercomputing power has enabled process-based hydrological simulations on large watersheds and two-way coupling with mesoscale atmospheric models. Of course with increasing watershed scale come corresponding increases in watershed complexity, including wide ranging water management infrastructure and objectives, and ever increasing demands for forcing data. Simulations of large watersheds using grid-based models apply a fixed resolution over the entire watershed. In large watersheds, this means an enormous number of grids, or coarsening of the grid resolution to reduce memory requirements. One alternative to grid-based methods is the triangular irregular network (TIN) approach. TINs provide the flexibility of variable resolution, which allows optimization of computational resources by providing high resolution where necessary and low resolution elsewhere. TINs also increase required effort in model setup, parameter estimation, and coupling with forcing data which are often gridded. This presentation discusses the costs and benefits of the use of TINs compared to grid-based methods, in the context of large watershed simulations within the traditional gridded WRF-HYDRO framework and the new TIN-based ADHydro high performance computing watershed simulator.

Framework for Service Composition in G-Lite

NASA Astrophysics Data System (ADS)

Goranova, R.

2011-11-01

G-Lite is a Grid middleware, currently the main middleware installed on all clusters in Bulgaria. The middleware is used by scientists for solving problems, which require a large amount of storage and computational resources. On the other hand, the scientists work with complex processes, where job execution in Grid is just a step of the process. That is why, it is strategically important g-Lite to provide a mechanism for service compositions and business process management. Such mechanism is not specified yet. In this article we propose a framework for service composition in g-Lite. We discuss business process modeling, deployment and execution in this Grid environment. The examples used to demonstrate the concept are based on some IBM products.

Nonlinear Fluid Computations in a Distributed Environment

NASA Technical Reports Server (NTRS)

Atwood, Christopher A.; Smith, Merritt H.

1995-01-01

The performance of a loosely and tightly-coupled workstation cluster is compared against a conventional vector supercomputer for the solution the Reynolds- averaged Navier-Stokes equations. The application geometries include a transonic airfoil, a tiltrotor wing/fuselage, and a wing/body/empennage/nacelle transport. Decomposition is of the manager-worker type, with solution of one grid zone per worker process coupled using the PVM message passing library. Task allocation is determined by grid size and processor speed, subject to available memory penalties. Each fluid zone is computed using an implicit diagonal scheme in an overset mesh framework, while relative body motion is accomplished using an additional worker process to re-establish grid communication.

DOE Office of Scientific and Technical Information (OSTI.GOV)

von Laszewski, G.; Gawor, J.; Lane, P.

In this paper we report on the features of the Java Commodity Grid Kit (Java CoG Kit). The Java CoG Kit provides middleware for accessing Grid functionality from the Java framework. Java CoG Kit middleware is general enough to design a variety of advanced Grid applications with quite different user requirements. Access to the Grid is established via Globus Toolkit protocols, allowing the Java CoG Kit to also communicate with the services distributed as part of the C Globus Toolkit reference implementation. Thus, the Java CoG Kit provides Grid developers with the ability to utilize the Grid, as well asmore » numerous additional libraries and frameworks developed by the Java community to enable network, Internet, enterprise and peer-to-peer computing. A variety of projects have successfully used the client libraries of the Java CoG Kit to access Grids driven by the C Globus Toolkit software. In this paper we also report on the efforts to develop serverside Java CoG Kit components. As part of this research we have implemented a prototype pure Java resource management system that enables one to run Grid jobs on platforms on which a Java virtual machine is supported, including Windows NT machines.« less

Magnetohydrodynamic Simulations of Black Hole Accretion Flows Using PATCHWORK, a Multi-Patch, multi-code approach

NASA Astrophysics Data System (ADS)

Avara, Mark J.; Noble, Scott; Shiokawa, Hotaka; Cheng, Roseanne; Campanelli, Manuela; Krolik, Julian H.

2017-08-01

A multi-patch approach to numerical simulations of black hole accretion flows allows one to robustly match numerical grid shape and equations solved to the natural structure of the physical system. For instance, a cartesian gridded patch can be used to cover coordinate singularities on a spherical-polar grid, increasing computational efficiency and better capturing the physical system through natural symmetries. We will present early tests, initial applications, and first results from the new MHD implementation of the PATCHWORK framework.

The Impact of Varying the Physics Grid Resolution Relative to the Dynamical Core Resolution in CAM-SE-CSLAM

NASA Astrophysics Data System (ADS)

Herrington, A. R.; Lauritzen, P. H.; Reed, K. A.

2017-12-01

The spectral element dynamical core of the Community Atmosphere Model (CAM) has recently been coupled to an approximately isotropic, finite-volume grid per implementation of the conservative semi-Lagrangian multi-tracer transport scheme (CAM-SE-CSLAM; Lauritzen et al. 2017). In this framework, the semi-Lagrangian transport of tracers are computed on the finite-volume grid, while the adiabatic dynamics are solved using the spectral element grid. The physical parameterizations are evaluated on the finite-volume grid, as opposed to the unevenly spaced Gauss-Lobatto-Legendre nodes of the spectral element grid. Computing the physics on the finite-volume grid reduces numerical artifacts such as grid imprinting, possibly because the forcing terms are no longer computed at element boundaries where the resolved dynamics are least smooth. The separation of the physics grid and the dynamics grid allows for a unique opportunity to understand the resolution sensitivity in CAM-SE-CSLAM. The observed large sensitivity of CAM to horizontal resolution is a poorly understood impediment to improved simulations of regional climate using global, variable resolution grids. Here, a series of idealized moist simulations are presented in which the finite-volume grid resolution is varied relative to the spectral element grid resolution in CAM-SE-CSLAM. The simulations are carried out at multiple spectral element grid resolutions, in part to provide a companion set of simulations, in which the spectral element grid resolution is varied relative to the finite-volume grid resolution, but more generally to understand if the sensitivity to the finite-volume grid resolution is consistent across a wider spectrum of resolved scales. Results are interpreted in the context of prior ideas regarding resolution sensitivity of global atmospheric models.

A Unified Framework for Periodic, On-Demand, and User-Specified Software Information

NASA Technical Reports Server (NTRS)

Kolano, Paul Z.

2004-01-01

Although grid computing can increase the number of resources available to a user; not all resources on the grid may have a software environment suitable for running a given application. To provide users with the necessary assistance for selecting resources with compatible software environments and/or for automatically establishing such environments, it is necessary to have an accurate source of information about the software installed across the grid. This paper presents a new OGSI-compliant software information service that has been implemented as part of NASA's Information Power Grid project. This service is built on top of a general framework for reconciling information from periodic, on-demand, and user-specified sources. Information is retrieved using standard XPath queries over a single unified namespace independent of the information's source. Two consumers of the provided software information, the IPG Resource Broker and the IPG Neutralization Service, are briefly described.

AMP: a science-driven web-based application for the TeraGrid

NASA Astrophysics Data System (ADS)

Woitaszek, M.; Metcalfe, T.; Shorrock, I.

The Asteroseismic Modeling Portal (AMP) provides a web-based interface for astronomers to run and view simulations that derive the properties of Sun-like stars from observations of their pulsation frequencies. In this paper, we describe the architecture and implementation of AMP, highlighting the lightweight design principles and tools used to produce a functional fully-custom web-based science application in less than a year. Targeted as a TeraGrid science gateway, AMP's architecture and implementation are intended to simplify its orchestration of TeraGrid computational resources. AMP's web-based interface was developed as a traditional standalone database-backed web application using the Python-based Django web development framework, allowing us to leverage the Django framework's capabilities while cleanly separating the user interface development from the grid interface development. We have found this combination of tools flexible and effective for rapid gateway development and deployment.

The Future of Electronic Device Design: Device and Process Simulation Find Intelligence on the World Wide Web

NASA Technical Reports Server (NTRS)

Biegel, Bryan A.

1999-01-01

We are on the path to meet the major challenges ahead for TCAD (technology computer aided design). The emerging computational grid will ultimately solve the challenge of limited computational power. The Modular TCAD Framework will solve the TCAD software challenge once TCAD software developers realize that there is no other way to meet industry's needs. The modular TCAD framework (MTF) also provides the ideal platform for solving the TCAD model challenge by rapid implementation of models in a partial differential solver.

Online production validation in a HEP environment

NASA Astrophysics Data System (ADS)

Harenberg, T.; Kuhl, T.; Lang, N.; Mättig, P.; Sandhoff, M.; Schwanenberger, C.; Volkmer, F.

2017-03-01

In high energy physics (HEP) event simulations, petabytes of data are processed and stored requiring millions of CPU-years. This enormous demand for computing resources is handled by centers distributed worldwide, which form part of the LHC computing grid. The consumption of such an important amount of resources demands for an efficient production of simulation and for the early detection of potential errors. In this article we present a new monitoring framework for grid environments, which polls a measure of data quality during job execution. This online monitoring facilitates the early detection of configuration errors (specially in simulation parameters), and may thus contribute to significant savings in computing resources.

Complete distributed computing environment for a HEP experiment: experience with ARC-connected infrastructure for ATLAS

NASA Astrophysics Data System (ADS)

Read, A.; Taga, A.; O-Saada, F.; Pajchel, K.; Samset, B. H.; Cameron, D.

2008-07-01

Computing and storage resources connected by the Nordugrid ARC middleware in the Nordic countries, Switzerland and Slovenia are a part of the ATLAS computing Grid. This infrastructure is being commissioned with the ongoing ATLAS Monte Carlo simulation production in preparation for the commencement of data taking in 2008. The unique non-intrusive architecture of ARC, its straightforward interplay with the ATLAS Production System via the Dulcinea executor, and its performance during the commissioning exercise is described. ARC support for flexible and powerful end-user analysis within the GANGA distributed analysis framework is also shown. Whereas the storage solution for this Grid was earlier based on a large, distributed collection of GridFTP-servers, the ATLAS computing design includes a structured SRM-based system with a limited number of storage endpoints. The characteristics, integration and performance of the old and new storage solutions are presented. Although the hardware resources in this Grid are quite modest, it has provided more than double the agreed contribution to the ATLAS production with an efficiency above 95% during long periods of stable operation.

Dynamic optimization of chemical processes using ant colony framework.

PubMed

Rajesh, J; Gupta, K; Kusumakar, H S; Jayaraman, V K; Kulkarni, B D

2001-11-01

Ant colony framework is illustrated by considering dynamic optimization of six important bench marking examples. This new computational tool is simple to implement and can tackle problems with state as well as terminal constraints in a straightforward fashion. It requires fewer grid points to reach the global optimum at relatively very low computational effort. The examples with varying degree of complexities, analyzed here, illustrate its potential for solving a large class of process optimization problems in chemical engineering.

Low Boom Configuration Analysis with FUN3D Adjoint Simulation Framework

NASA Technical Reports Server (NTRS)

Park, Michael A.

2011-01-01

Off-body pressure, forces, and moments for the Gulfstream Low Boom Model are computed with a Reynolds Averaged Navier Stokes solver coupled with the Spalart-Allmaras (SA) turbulence model. This is the first application of viscous output-based adaptation to reduce estimated discretization errors in off-body pressure for a wing body configuration. The output adaptation approach is compared to an a priori grid adaptation technique designed to resolve the signature on the centerline by stretching and aligning the grid to the freestream Mach angle. The output-based approach produced good predictions of centerline and off-centerline measurements. Eddy viscosity predicted by the SA turbulence model increased significantly with grid adaptation. Computed lift as a function of drag compares well with wind tunnel measurements for positive lift, but predicted lift, drag, and pitching moment as a function of angle of attack has significant differences from the measured data. The sensitivity of longitudinal forces and moment to grid refinement is much smaller than the differences between the computed and measured data.

Efficient Load Balancing and Data Remapping for Adaptive Grid Calculations

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Biswas, Rupak

1997-01-01

Mesh adaption is a powerful tool for efficient unstructured- grid computations but causes load imbalance among processors on a parallel machine. We present a novel method to dynamically balance the processor workloads with a global view. This paper presents, for the first time, the implementation and integration of all major components within our dynamic load balancing strategy for adaptive grid calculations. Mesh adaption, repartitioning, processor assignment, and remapping are critical components of the framework that must be accomplished rapidly and efficiently so as not to cause a significant overhead to the numerical simulation. Previous results indicated that mesh repartitioning and data remapping are potential bottlenecks for performing large-scale scientific calculations. We resolve these issues and demonstrate that our framework remains viable on a large number of processors.

Tempest - Efficient Computation of Atmospheric Flows Using High-Order Local Discretization Methods

NASA Astrophysics Data System (ADS)

Ullrich, P. A.; Guerra, J. E.

2014-12-01

The Tempest Framework composes several compact numerical methods to easily facilitate intercomparison of atmospheric flow calculations on the sphere and in rectangular domains. This framework includes the implementations of Spectral Elements, Discontinuous Galerkin, Flux Reconstruction, and Hybrid Finite Element methods with the goal of achieving optimal accuracy in the solution of atmospheric problems. Several advantages of this approach are discussed such as: improved pressure gradient calculation, numerical stability by vertical/horizontal splitting, arbitrary order of accuracy, etc. The local numerical discretization allows for high performance parallel computation and efficient inclusion of parameterizations. These techniques are used in conjunction with a non-conformal, locally refined, cubed-sphere grid for global simulations and standard Cartesian grids for simulations at the mesoscale. A complete implementation of the methods described is demonstrated in a non-hydrostatic setting.

A GPU-based incompressible Navier-Stokes solver on moving overset grids

NASA Astrophysics Data System (ADS)

Chandar, Dominic D. J.; Sitaraman, Jayanarayanan; Mavriplis, Dimitri J.

2013-07-01

In pursuit of obtaining high fidelity solutions to the fluid flow equations in a short span of time, graphics processing units (GPUs) which were originally intended for gaming applications are currently being used to accelerate computational fluid dynamics (CFD) codes. With a high peak throughput of about 1 TFLOPS on a PC, GPUs seem to be favourable for many high-resolution computations. One such computation that involves a lot of number crunching is computing time accurate flow solutions past moving bodies. The aim of the present paper is thus to discuss the development of a flow solver on unstructured and overset grids and its implementation on GPUs. In its present form, the flow solver solves the incompressible fluid flow equations on unstructured/hybrid/overset grids using a fully implicit projection method. The resulting discretised equations are solved using a matrix-free Krylov solver using several GPU kernels such as gradient, Laplacian and reduction. Some of the simple arithmetic vector calculations are implemented using the CU++: An Object Oriented Framework for Computational Fluid Dynamics Applications using Graphics Processing Units, Journal of Supercomputing, 2013, doi:10.1007/s11227-013-0985-9 approach where GPU kernels are automatically generated at compile time. Results are presented for two- and three-dimensional computations on static and moving grids.

Slat Noise Predictions Using Higher-Order Finite-Difference Methods on Overset Grids

NASA Technical Reports Server (NTRS)

Housman, Jeffrey A.; Kiris, Cetin

2016-01-01

Computational aeroacoustic simulations using the structured overset grid approach and higher-order finite difference methods within the Launch Ascent and Vehicle Aerodynamics (LAVA) solver framework are presented for slat noise predictions. The simulations are part of a collaborative study comparing noise generation mechanisms between a conventional slat and a Krueger leading edge flap. Simulation results are compared with experimental data acquired during an aeroacoustic test in the NASA Langley Quiet Flow Facility. Details of the structured overset grid, numerical discretization, and turbulence model are provided.

Beam Dynamics Simulation Platform and Studies of Beam Breakup in Dielectric Wakefield Structures

NASA Astrophysics Data System (ADS)

Schoessow, P.; Kanareykin, A.; Jing, C.; Kustov, A.; Altmark, A.; Gai, W.

2010-11-01

A particle-Green's function beam dynamics code (BBU-3000) to study beam breakup effects is incorporated into a parallel computing framework based on the Boinc software environment, and supports both task farming on a heterogeneous cluster and local grid computing. User access to the platform is through a web browser.

GLOFRIM v1.0 - A globally applicable computational framework for integrated hydrological-hydrodynamic modelling

NASA Astrophysics Data System (ADS)

Hoch, Jannis M.; Neal, Jeffrey C.; Baart, Fedor; van Beek, Rens; Winsemius, Hessel C.; Bates, Paul D.; Bierkens, Marc F. P.

2017-10-01

We here present GLOFRIM, a globally applicable computational framework for integrated hydrological-hydrodynamic modelling. GLOFRIM facilitates spatially explicit coupling of hydrodynamic and hydrologic models and caters for an ensemble of models to be coupled. It currently encompasses the global hydrological model PCR-GLOBWB as well as the hydrodynamic models Delft3D Flexible Mesh (DFM; solving the full shallow-water equations and allowing for spatially flexible meshing) and LISFLOOD-FP (LFP; solving the local inertia equations and running on regular grids). The main advantages of the framework are its open and free access, its global applicability, its versatility, and its extensibility with other hydrological or hydrodynamic models. Before applying GLOFRIM to an actual test case, we benchmarked both DFM and LFP for a synthetic test case. Results show that for sub-critical flow conditions, discharge response to the same input signal is near-identical for both models, which agrees with previous studies. We subsequently applied the framework to the Amazon River basin to not only test the framework thoroughly, but also to perform a first-ever benchmark of flexible and regular grids on a large-scale. Both DFM and LFP produce comparable results in terms of simulated discharge with LFP exhibiting slightly higher accuracy as expressed by a Kling-Gupta efficiency of 0.82 compared to 0.76 for DFM. However, benchmarking inundation extent between DFM and LFP over the entire study area, a critical success index of 0.46 was obtained, indicating that the models disagree as often as they agree. Differences between models in both simulated discharge and inundation extent are to a large extent attributable to the gridding techniques employed. In fact, the results show that both the numerical scheme of the inundation model and the gridding technique can contribute to deviations in simulated inundation extent as we control for model forcing and boundary conditions. This study shows that the presented computational framework is robust and widely applicable. GLOFRIM is designed as open access and easily extendable, and thus we hope that other large-scale hydrological and hydrodynamic models will be added. Eventually, more locally relevant processes would be captured and more robust model inter-comparison, benchmarking, and ensemble simulations of flood hazard on a large scale would be allowed for.

caGrid 1.0: An Enterprise Grid Infrastructure for Biomedical Research

PubMed Central

Oster, Scott; Langella, Stephen; Hastings, Shannon; Ervin, David; Madduri, Ravi; Phillips, Joshua; Kurc, Tahsin; Siebenlist, Frank; Covitz, Peter; Shanbhag, Krishnakant; Foster, Ian; Saltz, Joel

2008-01-01

Objective To develop software infrastructure that will provide support for discovery, characterization, integrated access, and management of diverse and disparate collections of information sources, analysis methods, and applications in biomedical research. Design An enterprise Grid software infrastructure, called caGrid version 1.0 (caGrid 1.0), has been developed as the core Grid architecture of the NCI-sponsored cancer Biomedical Informatics Grid (caBIG™) program. It is designed to support a wide range of use cases in basic, translational, and clinical research, including 1) discovery, 2) integrated and large-scale data analysis, and 3) coordinated study. Measurements The caGrid is built as a Grid software infrastructure and leverages Grid computing technologies and the Web Services Resource Framework standards. It provides a set of core services, toolkits for the development and deployment of new community provided services, and application programming interfaces for building client applications. Results The caGrid 1.0 was released to the caBIG community in December 2006. It is built on open source components and caGrid source code is publicly and freely available under a liberal open source license. The core software, associated tools, and documentation can be downloaded from the following URL: https://cabig.nci.nih.gov/workspaces/Architecture/caGrid. Conclusions While caGrid 1.0 is designed to address use cases in cancer research, the requirements associated with discovery, analysis and integration of large scale data, and coordinated studies are common in other biomedical fields. In this respect, caGrid 1.0 is the realization of a framework that can benefit the entire biomedical community. PMID:18096909

caGrid 1.0: an enterprise Grid infrastructure for biomedical research.

PubMed

Oster, Scott; Langella, Stephen; Hastings, Shannon; Ervin, David; Madduri, Ravi; Phillips, Joshua; Kurc, Tahsin; Siebenlist, Frank; Covitz, Peter; Shanbhag, Krishnakant; Foster, Ian; Saltz, Joel

2008-01-01

To develop software infrastructure that will provide support for discovery, characterization, integrated access, and management of diverse and disparate collections of information sources, analysis methods, and applications in biomedical research. An enterprise Grid software infrastructure, called caGrid version 1.0 (caGrid 1.0), has been developed as the core Grid architecture of the NCI-sponsored cancer Biomedical Informatics Grid (caBIG) program. It is designed to support a wide range of use cases in basic, translational, and clinical research, including 1) discovery, 2) integrated and large-scale data analysis, and 3) coordinated study. The caGrid is built as a Grid software infrastructure and leverages Grid computing technologies and the Web Services Resource Framework standards. It provides a set of core services, toolkits for the development and deployment of new community provided services, and application programming interfaces for building client applications. The caGrid 1.0 was released to the caBIG community in December 2006. It is built on open source components and caGrid source code is publicly and freely available under a liberal open source license. The core software, associated tools, and documentation can be downloaded from the following URL: https://cabig.nci.nih.gov/workspaces/Architecture/caGrid. While caGrid 1.0 is designed to address use cases in cancer research, the requirements associated with discovery, analysis and integration of large scale data, and coordinated studies are common in other biomedical fields. In this respect, caGrid 1.0 is the realization of a framework that can benefit the entire biomedical community.

High-Maneuverability Airframe: Initial Investigation of Configuration’s Aft End for Increased Stability, Range, and Maneuverability

DTIC Science & Technology

2013-09-01

including the interaction effects between the fins and canards. 2. Solution Technique 2.1 Computational Aerodynamics The double-precision solver of a...and overset grids (unified-grid). • Total variation diminishing discretization based on a new multidimensional interpolation framework. • Riemann ... solvers to provide proper signal propagation physics including versions for preconditioned forms of the governing equations. • Consistent and

HappyFace as a generic monitoring tool for HEP experiments

NASA Astrophysics Data System (ADS)

Kawamura, Gen; Magradze, Erekle; Musheghyan, Haykuhi; Quadt, Arnulf; Rzehorz, Gerhard

2015-12-01

The importance of monitoring on HEP grid computing systems is growing due to a significant increase in their complexity. Computer scientists and administrators have been studying and building effective ways to gather information on and clarify a status of each local grid infrastructure. The HappyFace project aims at making the above-mentioned workflow possible. It aggregates, processes and stores the information and the status of different HEP monitoring resources into the common database of HappyFace. The system displays the information and the status through a single interface. However, this model of HappyFace relied on the monitoring resources which are always under development in the HEP experiments. Consequently, HappyFace needed to have direct access methods to the grid application and grid service layers in the different HEP grid systems. To cope with this issue, we use a reliable HEP software repository, the CernVM File System. We propose a new implementation and an architecture of HappyFace, the so-called grid-enabled HappyFace. It allows its basic framework to connect directly to the grid user applications and the grid collective services, without involving the monitoring resources in the HEP grid systems. This approach gives HappyFace several advantages: Portability, to provide an independent and generic monitoring system among the HEP grid systems. Eunctionality, to allow users to perform various diagnostic tools in the individual HEP grid systems and grid sites. Elexibility, to make HappyFace beneficial and open for the various distributed grid computing environments. Different grid-enabled modules, to connect to the Ganga job monitoring system and to check the performance of grid transfers among the grid sites, have been implemented. The new HappyFace system has been successfully integrated and now it displays the information and the status of both the monitoring resources and the direct access to the grid user applications and the grid collective services.

OVERSMART Reporting Tool for Flow Computations Over Large Grid Systems

NASA Technical Reports Server (NTRS)

Kao, David L.; Chan, William M.

2012-01-01

Structured grid solvers such as NASA's OVERFLOW compressible Navier-Stokes flow solver can generate large data files that contain convergence histories for flow equation residuals, turbulence model equation residuals, component forces and moments, and component relative motion dynamics variables. Most of today's large-scale problems can extend to hundreds of grids, and over 100 million grid points. However, due to the lack of efficient tools, only a small fraction of information contained in these files is analyzed. OVERSMART (OVERFLOW Solution Monitoring And Reporting Tool) provides a comprehensive report of solution convergence of flow computations over large, complex grid systems. It produces a one-page executive summary of the behavior of flow equation residuals, turbulence model equation residuals, and component forces and moments. Under the automatic option, a matrix of commonly viewed plots such as residual histograms, composite residuals, sub-iteration bar graphs, and component forces and moments is automatically generated. Specific plots required by the user can also be prescribed via a command file or a graphical user interface. Output is directed to the user s computer screen and/or to an html file for archival purposes. The current implementation has been targeted for the OVERFLOW flow solver, which is used to obtain a flow solution on structured overset grids. The OVERSMART framework allows easy extension to other flow solvers.

Single block three-dimensional volume grids about complex aerodynamic vehicles

NASA Technical Reports Server (NTRS)

Alter, Stephen J.; Weilmuenster, K. James

1993-01-01

This paper presents an alternate approach for the generation of volumetric grids for supersonic and hypersonic flows about complex configurations. The method uses parametric two dimensional block face grid definition within the framework of GRIDGEN2D. The incorporation of face decomposition reduces complex surfaces to simple shapes. These simple shapes are combined to obtain the final face definition. The advantages of this method include the reduction of overall grid generation time through the use of vectorized computer code, the elimination of the need to generate matching block faces, and the implementation of simplified boundary conditions. A simple axisymmetric grid is used to illustrate this method. In addition, volume grids for two complex configurations, the Langley Lifting Body (HL-20) and the Space Shuttle Orbiter, are shown.

An Integrated Software Package to Enable Predictive Simulation Capabilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yousu; Fitzhenry, Erin B.; Jin, Shuangshuang

The power grid is increasing in complexity due to the deployment of smart grid technologies. Such technologies vastly increase the size and complexity of power grid systems for simulation and modeling. This increasing complexity necessitates not only the use of high-performance-computing (HPC) techniques, but a smooth, well-integrated interplay between HPC applications. This paper presents a new integrated software package that integrates HPC applications and a web-based visualization tool based on a middleware framework. This framework can support the data communication between different applications. Case studies with a large power system demonstrate the predictive capability brought by the integrated software package,more » as well as the better situational awareness provided by the web-based visualization tool in a live mode. Test results validate the effectiveness and usability of the integrated software package.« less

SuperB Simulation Production System

NASA Astrophysics Data System (ADS)

Tomassetti, L.; Bianchi, F.; Ciaschini, V.; Corvo, M.; Del Prete, D.; Di Simone, A.; Donvito, G.; Fella, A.; Franchini, P.; Giacomini, F.; Gianoli, A.; Longo, S.; Luitz, S.; Luppi, E.; Manzali, M.; Pardi, S.; Paolini, A.; Perez, A.; Rama, M.; Russo, G.; Santeramo, B.; Stroili, R.

2012-12-01

The SuperB asymmetric e+e- collider and detector to be built at the newly founded Nicola Cabibbo Lab will provide a uniquely sensitive probe of New Physics in the flavor sector of the Standard Model. Studying minute effects in the heavy quark and heavy lepton sectors requires a data sample of 75 ab-1 and a peak luminosity of 1036 cm-2 s-1. The SuperB Computing group is working on developing a simulation production framework capable to satisfy the experiment needs. It provides access to distributed resources in order to support both the detector design definition and its performance evaluation studies. During last year the framework has evolved from the point of view of job workflow, Grid services interfaces and technologies adoption. A complete code refactoring and sub-component language porting now permits the framework to sustain distributed production involving resources from two continents and Grid Flavors. In this paper we will report a complete description of the production system status of the art, its evolution and its integration with Grid services; in particular, we will focus on the utilization of new Grid component features as in LB and WMS version 3. Results from the last official SuperB production cycle will be reported.

Dynamic Load Balancing for Grid Partitioning on a SP-2 Multiprocessor: A Framework

NASA Technical Reports Server (NTRS)

Sohn, Andrew; Simon, Horst; Lasinski, T. A. (Technical Monitor)

1994-01-01

Computational requirements of full scale computational fluid dynamics change as computation progresses on a parallel machine. The change in computational intensity causes workload imbalance of processors, which in turn requires a large amount of data movement at runtime. If parallel CFD is to be successful on a parallel or massively parallel machine, balancing of the runtime load is indispensable. Here a framework is presented for dynamic load balancing for CFD applications, called Jove. One processor is designated as a decision maker Jove while others are assigned to computational fluid dynamics. Processors running CFD send flags to Jove in a predetermined number of iterations to initiate load balancing. Jove starts working on load balancing while other processors continue working with the current data and load distribution. Jove goes through several steps to decide if the new data should be taken, including preliminary evaluate, partition, processor reassignment, cost evaluation, and decision. Jove running on a single EBM SP2 node has been completely implemented. Preliminary experimental results show that the Jove approach to dynamic load balancing can be effective for full scale grid partitioning on the target machine IBM SP2.

Dynamic Load Balancing For Grid Partitioning on a SP-2 Multiprocessor: A Framework

NASA Technical Reports Server (NTRS)

Sohn, Andrew; Simon, Horst; Lasinski, T. A. (Technical Monitor)

1994-01-01

Computational requirements of full scale computational fluid dynamics change as computation progresses on a parallel machine. The change in computational intensity causes workload imbalance of processors, which in turn requires a large amount of data movement at runtime. If parallel CFD is to be successful on a parallel or massively parallel machine, balancing of the runtime load is indispensable. Here a framework is presented for dynamic load balancing for CFD applications, called Jove. One processor is designated as a decision maker Jove while others are assigned to computational fluid dynamics. Processors running CFD send flags to Jove in a predetermined number of iterations to initiate load balancing. Jove starts working on load balancing while other processors continue working with the current data and load distribution. Jove goes through several steps to decide if the new data should be taken, including preliminary evaluate, partition, processor reassignment, cost evaluation, and decision. Jove running on a single IBM SP2 node has been completely implemented. Preliminary experimental results show that the Jove approach to dynamic load balancing can be effective for full scale grid partitioning on the target machine IBM SP2.

High-resolution subgrid models: background, grid generation, and implementation

NASA Astrophysics Data System (ADS)

Sehili, Aissa; Lang, Günther; Lippert, Christoph

2014-04-01

The basic idea of subgrid models is the use of available high-resolution bathymetric data at subgrid level in computations that are performed on relatively coarse grids allowing large time steps. For that purpose, an algorithm that correctly represents the precise mass balance in regions where wetting and drying occur was derived by Casulli (Int J Numer Method Fluids 60:391-408, 2009) and Casulli and Stelling (Int J Numer Method Fluids 67:441-449, 2010). Computational grid cells are permitted to be wet, partially wet, or dry, and no drying threshold is needed. Based on the subgrid technique, practical applications involving various scenarios were implemented including an operational forecast model for water level, salinity, and temperature of the Elbe Estuary in Germany. The grid generation procedure allows a detailed boundary fitting at subgrid level. The computational grid is made of flow-aligned quadrilaterals including few triangles where necessary. User-defined grid subdivision at subgrid level allows a correct representation of the volume up to measurement accuracy. Bottom friction requires a particular treatment. Based on the conveyance approach, an appropriate empirical correction was worked out. The aforementioned features make the subgrid technique very efficient, robust, and accurate. Comparison of predicted water levels with the comparatively highly resolved classical unstructured grid model shows very good agreement. The speedup in computational performance due to the use of the subgrid technique is about a factor of 20. A typical daily forecast can be carried out in less than 10 min on a standard PC-like hardware. The subgrid technique is therefore a promising framework to perform accurate temporal and spatial large-scale simulations of coastal and estuarine flow and transport processes at low computational cost.

Using Python to generate AHPS-based precipitation simulations over CONUS using Amazon distributed computing

NASA Astrophysics Data System (ADS)

Machalek, P.; Kim, S. M.; Berry, R. D.; Liang, A.; Small, T.; Brevdo, E.; Kuznetsova, A.

2012-12-01

We describe how the Climate Corporation uses Python and Clojure, a language impleneted on top of Java, to generate climatological forecasts for precipitation based on the Advanced Hydrologic Prediction Service (AHPS) radar based daily precipitation measurements. A 2-year-long forecasts is generated on each of the ~650,000 CONUS land based 4-km AHPS grids by constructing 10,000 ensembles sampled from a 30-year reconstructed AHPS history for each grid. The spatial and temporal correlations between neighboring AHPS grids and the sampling of the analogues are handled by Python. The parallelization for all the 650,000 CONUS stations is further achieved by utilizing the MAP-REDUCE framework (http://code.google.com/edu/parallel/mapreduce-tutorial.html). Each full scale computational run requires hundreds of nodes with up to 8 processors each on the Amazon Elastic MapReduce (http://aws.amazon.com/elasticmapreduce/) distributed computing service resulting in 3 terabyte datasets. We further describe how we have productionalized a monthly run of the simulations process at full scale of the 4km AHPS grids and how the resultant terabyte sized datasets are handled.

A framework supporting the development of a Grid portal for analysis based on ROI.

PubMed

Ichikawa, K; Date, S; Kaishima, T; Shimojo, S

2005-01-01

In our research on brain function analysis, users require two different simultaneous types of processing: interactive processing to a specific part of data and high-performance batch processing to an entire dataset. The difference between these two types of processing is in whether or not the analysis is for data in the region of interest (ROI). In this study, we propose a Grid portal that has a mechanism to freely assign computing resources to the users on a Grid environment according to the users' two different types of processing requirements. We constructed a Grid portal which integrates interactive processing and batch processing by the following two mechanisms. First, a job steering mechanism controls job execution based on user-tagged priority among organizations with heterogeneous computing resources. Interactive jobs are processed in preference to batch jobs by this mechanism. Second, a priority-based result delivery mechanism that administrates a rank of data significance. The portal ensures a turn-around time of interactive processing by the priority-based job controlling mechanism, and provides the users with quality of services (QoS) for interactive processing. The users can access the analysis results of interactive jobs in preference to the analysis results of batch jobs. The Grid portal has also achieved high-performance computation of MEG analysis with batch processing on the Grid environment. The priority-based job controlling mechanism has been realized to freely assign computing resources to the users' requirements. Furthermore the achievement of high-performance computation contributes greatly to the overall progress of brain science. The portal has thus made it possible for the users to flexibly include the large computational power in what they want to analyze.

Planning low-carbon electricity systems under uncertainty considering operational flexibility and smart grid technologies.

PubMed

Moreno, Rodrigo; Street, Alexandre; Arroyo, José M; Mancarella, Pierluigi

2017-08-13

Electricity grid operators and planners need to deal with both the rapidly increasing integration of renewables and an unprecedented level of uncertainty that originates from unknown generation outputs, changing commercial and regulatory frameworks aimed to foster low-carbon technologies, the evolving availability of market information on feasibility and costs of various technologies, etc. In this context, there is a significant risk of locking-in to inefficient investment planning solutions determined by current deterministic engineering practices that neither capture uncertainty nor represent the actual operation of the planned infrastructure under high penetration of renewables. We therefore present an alternative optimization framework to plan electricity grids that deals with uncertain scenarios and represents increased operational details. The presented framework is able to model the effects of an array of flexible, smart grid technologies that can efficiently displace the need for conventional solutions. We then argue, and demonstrate via the proposed framework and an illustrative example, that proper modelling of uncertainty and operational constraints in planning is key to valuing operationally flexible solutions leading to optimal investment in a smart grid context. Finally, we review the most used practices in power system planning under uncertainty, highlight the challenges of incorporating operational aspects and advocate the need for new and computationally effective optimization tools to properly value the benefits of flexible, smart grid solutions in planning. Such tools are essential to accelerate the development of a low-carbon energy system and investment in the most appropriate portfolio of renewable energy sources and complementary enabling smart technologies.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'. © 2017 The Author(s).

Enhancing adaptive sparse grid approximations and improving refinement strategies using adjoint-based a posteriori error estimates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jakeman, J.D., E-mail: jdjakem@sandia.gov; Wildey, T.

2015-01-01

In this paper we present an algorithm for adaptive sparse grid approximations of quantities of interest computed from discretized partial differential equations. We use adjoint-based a posteriori error estimates of the physical discretization error and the interpolation error in the sparse grid to enhance the sparse grid approximation and to drive adaptivity of the sparse grid. Utilizing these error estimates provides significantly more accurate functional values for random samples of the sparse grid approximation. We also demonstrate that alternative refinement strategies based upon a posteriori error estimates can lead to further increases in accuracy in the approximation over traditional hierarchicalmore » surplus based strategies. Throughout this paper we also provide and test a framework for balancing the physical discretization error with the stochastic interpolation error of the enhanced sparse grid approximation.« less

Towards Dynamic Authentication in the Grid — Secure and Mobile Business Workflows Using GSet

NASA Astrophysics Data System (ADS)

Mangler, Jürgen; Schikuta, Erich; Witzany, Christoph; Jorns, Oliver; Ul Haq, Irfan; Wanek, Helmut

Until now, the research community mainly focused on the technical aspects of Grid computing and neglected commercial issues. However, recently the community tends to accept that the success of the Grid is crucially based on commercial exploitation. In our vision Foster's and Kesselman's statement "The Grid is all about sharing." has to be extended by "... and making money out of it!". To allow for the realization of this vision the trust-worthyness of the underlying technology needs to be ensured. This can be achieved by the use of gSET (Gridified Secure Electronic Transaction) as a basic technology for trust management and secure accounting in the presented Grid based workflow. We present a framework, conceptually and technically, from the area of the Mobile-Grid, which justifies the Grid infrastructure as a viable platform to enable commercially successful business workflows.

Fibonacci Grids

NASA Technical Reports Server (NTRS)

Swinbank, Richard; Purser, James

2006-01-01

Recent years have seen a resurgence of interest in a variety of non-standard computational grids for global numerical prediction. The motivation has been to reduce problems associated with the converging meridians and the polar singularities of conventional regular latitude-longitude grids. A further impetus has come from the adoption of massively parallel computers, for which it is necessary to distribute work equitably across the processors; this is more practicable for some non-standard grids. Desirable attributes of a grid for high-order spatial finite differencing are: (i) geometrical regularity; (ii) a homogeneous and approximately isotropic spatial resolution; (iii) a low proportion of the grid points where the numerical procedures require special customization (such as near coordinate singularities or grid edges). One family of grid arrangements which, to our knowledge, has never before been applied to numerical weather prediction, but which appears to offer several technical advantages, are what we shall refer to as "Fibonacci grids". They can be thought of as mathematically ideal generalizations of the patterns occurring naturally in the spiral arrangements of seeds and fruit found in sunflower heads and pineapples (to give two of the many botanical examples). These grids possess virtually uniform and highly isotropic resolution, with an equal area for each grid point. There are only two compact singular regions on a sphere that require customized numerics. We demonstrate the practicality of these grids in shallow water simulations, and discuss the prospects for efficiently using these frameworks in three-dimensional semi-implicit and semi-Lagrangian weather prediction or climate models.

Enhancing adaptive sparse grid approximations and improving refinement strategies using adjoint-based a posteriori error estimates

DOE PAGES

Jakeman, J. D.; Wildey, T.

2015-01-01

In this paper we present an algorithm for adaptive sparse grid approximations of quantities of interest computed from discretized partial differential equations. We use adjoint-based a posteriori error estimates of the interpolation error in the sparse grid to enhance the sparse grid approximation and to drive adaptivity. We show that utilizing these error estimates provides significantly more accurate functional values for random samples of the sparse grid approximation. We also demonstrate that alternative refinement strategies based upon a posteriori error estimates can lead to further increases in accuracy in the approximation over traditional hierarchical surplus based strategies. Throughout this papermore » we also provide and test a framework for balancing the physical discretization error with the stochastic interpolation error of the enhanced sparse grid approximation.« less

Gradient-based optimization with B-splines on sparse grids for solving forward-dynamics simulations of three-dimensional, continuum-mechanical musculoskeletal system models.

PubMed

Valentin, J; Sprenger, M; Pflüger, D; Röhrle, O

2018-05-01

Investigating the interplay between muscular activity and motion is the basis to improve our understanding of healthy or diseased musculoskeletal systems. To be able to analyze the musculoskeletal systems, computational models are used. Albeit some severe modeling assumptions, almost all existing musculoskeletal system simulations appeal to multibody simulation frameworks. Although continuum-mechanical musculoskeletal system models can compensate for some of these limitations, they are essentially not considered because of their computational complexity and cost. The proposed framework is the first activation-driven musculoskeletal system model, in which the exerted skeletal muscle forces are computed using 3-dimensional, continuum-mechanical skeletal muscle models and in which muscle activations are determined based on a constraint optimization problem. Numerical feasibility is achieved by computing sparse grid surrogates with hierarchical B-splines, and adaptive sparse grid refinement further reduces the computational effort. The choice of B-splines allows the use of all existing gradient-based optimization techniques without further numerical approximation. This paper demonstrates that the resulting surrogates have low relative errors (less than 0.76%) and can be used within forward simulations that are subject to constraint optimization. To demonstrate this, we set up several different test scenarios in which an upper limb model consisting of the elbow joint, the biceps and triceps brachii, and an external load is subjected to different optimization criteria. Even though this novel method has only been demonstrated for a 2-muscle system, it can easily be extended to musculoskeletal systems with 3 or more muscles. Copyright © 2018 John Wiley & Sons, Ltd.

NREL Partnership Develops Off-Grid Energy Access through Quality Assurance

Science.gov Websites

Framework for Mini-Grids | Integrated Energy Solutions | NREL Partnership Develops Off-Grid Energy Access through Quality Assurance Framework for Mini-Grids NREL Partnership Develops Off-Grid Energy Access through Quality Assurance Framework for Mini-Grids NREL has teamed with the Global Lighting

Optimization and validation of accelerated golden-angle radial sparse MRI reconstruction with self-calibrating GRAPPA operator gridding.

PubMed

Benkert, Thomas; Tian, Ye; Huang, Chenchan; DiBella, Edward V R; Chandarana, Hersh; Feng, Li

2018-07-01

Golden-angle radial sparse parallel (GRASP) MRI reconstruction requires gridding and regridding to transform data between radial and Cartesian k-space. These operations are repeatedly performed in each iteration, which makes the reconstruction computationally demanding. This work aimed to accelerate GRASP reconstruction using self-calibrating GRAPPA operator gridding (GROG) and to validate its performance in clinical imaging. GROG is an alternative gridding approach based on parallel imaging, in which k-space data acquired on a non-Cartesian grid are shifted onto a Cartesian k-space grid using information from multicoil arrays. For iterative non-Cartesian image reconstruction, GROG is performed only once as a preprocessing step. Therefore, the subsequent iterative reconstruction can be performed directly in Cartesian space, which significantly reduces computational burden. Here, a framework combining GROG with GRASP (GROG-GRASP) is first optimized and then compared with standard GRASP reconstruction in 22 prostate patients. GROG-GRASP achieved approximately 4.2-fold reduction in reconstruction time compared with GRASP (∼333 min versus ∼78 min) while maintaining image quality (structural similarity index ≈ 0.97 and root mean square error ≈ 0.007). Visual image quality assessment by two experienced radiologists did not show significant differences between the two reconstruction schemes. With a graphics processing unit implementation, image reconstruction time can be further reduced to approximately 14 min. The GRASP reconstruction can be substantially accelerated using GROG. This framework is promising toward broader clinical application of GRASP and other iterative non-Cartesian reconstruction methods. Magn Reson Med 80:286-293, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

DIRAC3 - the new generation of the LHCb grid software

NASA Astrophysics Data System (ADS)

Tsaregorodtsev, A.; Brook, N.; Casajus Ramo, A.; Charpentier, Ph; Closier, J.; Cowan, G.; Graciani Diaz, R.; Lanciotti, E.; Mathe, Z.; Nandakumar, R.; Paterson, S.; Romanovsky, V.; Santinelli, R.; Sapunov, M.; Smith, A. C.; Seco Miguelez, M.; Zhelezov, A.

2010-04-01

DIRAC, the LHCb community Grid solution, was considerably reengineered in order to meet all the requirements for processing the data coming from the LHCb experiment. It is covering all the tasks starting with raw data transportation from the experiment area to the grid storage, data processing up to the final user analysis. The reengineered DIRAC3 version of the system includes a fully grid security compliant framework for building service oriented distributed systems; complete Pilot Job framework for creating efficient workload management systems; several subsystems to manage high level operations like data production and distribution management. The user interfaces of the DIRAC3 system providing rich command line and scripting tools are complemented by a full-featured Web portal providing users with a secure access to all the details of the system status and ongoing activities. We will present an overview of the DIRAC3 architecture, new innovative features and the achieved performance. Extending DIRAC3 to manage computing resources beyond the WLCG grid will be discussed. Experience with using DIRAC3 by other user communities than LHCb and in other application domains than High Energy Physics will be shown to demonstrate the general-purpose nature of the system.

Performance of a Heterogeneous Grid Partitioner for N-body Applications

NASA Technical Reports Server (NTRS)

Harvey, Daniel J.; Das, Sajal K.; Biswas, Rupak

2003-01-01

An important characteristic of distributed grids is that they allow geographically separated multicomputers to be tied together in a transparent virtual environment to solve large-scale computational problems. However, many of these applications require effective runtime load balancing for the resulting solutions to be viable. Recently, we developed a latency tolerant partitioner, called MinEX, specifically for use in distributed grid environments. This paper compares the performance of MinEX to that of METIS, a popular multilevel family of partitioners, using simulated heterogeneous grid configurations. A solver for the classical N-body problem is implemented to provide a framework for the comparisons. Experimental results show that MinEX provides superior quality partitions while being competitive to METIS in speed of execution.

Optimization of computations for adjoint field and Jacobian needed in 3D CSEM inversion

NASA Astrophysics Data System (ADS)

Dehiya, Rahul; Singh, Arun; Gupta, Pravin K.; Israil, M.

2017-01-01

We present the features and results of a newly developed code, based on Gauss-Newton optimization technique, for solving three-dimensional Controlled-Source Electromagnetic inverse problem. In this code a special emphasis has been put on representing the operations by block matrices for conjugate gradient iteration. We show how in the computation of Jacobian, the matrix formed by differentiation of system matrix can be made independent of frequency to optimize the operations at conjugate gradient step. The coarse level parallel computing, using OpenMP framework, is used primarily due to its simplicity in implementation and accessibility of shared memory multi-core computing machine to almost anyone. We demonstrate how the coarseness of modeling grid in comparison to source (comp`utational receivers) spacing can be exploited for efficient computing, without compromising the quality of the inverted model, by reducing the number of adjoint calls. It is also demonstrated that the adjoint field can even be computed on a grid coarser than the modeling grid without affecting the inversion outcome. These observations were reconfirmed using an experiment design where the deviation of source from straight tow line is considered. Finally, a real field data inversion experiment is presented to demonstrate robustness of the code.

Partners | Integrated Energy Solutions | NREL

Science.gov Websites

Develops Off-Grid Energy Access through Quality Assurance Framework for Mini-Grids NREL has teamed with the Africa to develop a Quality Assurance Framework for isolated mini-grids. NREL Enhances Energy Resiliency Partnership Develops Off-Grid Energy Access through Quality Assurance Framework for Mini-Grids NREL has teamed

Grist : grid-based data mining for astronomy

NASA Technical Reports Server (NTRS)

Jacob, Joseph C.; Katz, Daniel S.; Miller, Craig D.; Walia, Harshpreet; Williams, Roy; Djorgovski, S. George; Graham, Matthew J.; Mahabal, Ashish; Babu, Jogesh; Berk, Daniel E. Vanden;

Grist: Grid-based Data Mining for Astronomy

NASA Astrophysics Data System (ADS)

Jacob, J. C.; Katz, D. S.; Miller, C. D.; Walia, H.; Williams, R. D.; Djorgovski, S. G.; Graham, M. J.; Mahabal, A. A.; Babu, G. J.; vanden Berk, D. E.; Nichol, R.

2005-12-01

The Grist project is developing a grid-technology based system as a research environment for astronomy with massive and complex datasets. This knowledge extraction system will consist of a library of distributed grid services controlled by a workflow system, compliant with standards emerging from the grid computing, web services, and virtual observatory communities. This new technology is being used to find high redshift quasars, study peculiar variable objects, search for transients in real time, and fit SDSS QSO spectra to measure black hole masses. Grist services are also a component of the ``hyperatlas'' project to serve high-resolution multi-wavelength imagery over the Internet. In support of these science and outreach objectives, the Grist framework will provide the enabling fabric to tie together distributed grid services in the areas of data access, federation, mining, subsetting, source extraction, image mosaicking, statistics, and visualization.

Factorizable Upwind Schemes: The Triangular Unstructured Grid Formulation

NASA Technical Reports Server (NTRS)

Sidilkover, David; Nielsen, Eric J.

2001-01-01

The upwind factorizable schemes for the equations of fluid were introduced recently. They facilitate achieving the Textbook Multigrid Efficiency (TME) and are expected also to result in the solvers of unparalleled robustness. The approach itself is very general. Therefore, it may well become a general framework for the large-scale, Computational Fluid Dynamics. In this paper we outline the triangular grid formulation of the factorizable schemes. The derivation is based on the fact that the factorizable schemes can be expressed entirely using vector notation. without explicitly mentioning a particular coordinate frame. We, describe the resulting discrete scheme in detail and present some computational results verifying the basic properties of the scheme/solver.

A Framework for Parallel Unstructured Grid Generation for Complex Aerodynamic Simulations

NASA Technical Reports Server (NTRS)

Zagaris, George; Pirzadeh, Shahyar Z.; Chrisochoides, Nikos

2009-01-01

A framework for parallel unstructured grid generation targeting both shared memory multi-processors and distributed memory architectures is presented. The two fundamental building-blocks of the framework consist of: (1) the Advancing-Partition (AP) method used for domain decomposition and (2) the Advancing Front (AF) method used for mesh generation. Starting from the surface mesh of the computational domain, the AP method is applied recursively to generate a set of sub-domains. Next, the sub-domains are meshed in parallel using the AF method. The recursive nature of domain decomposition naturally maps to a divide-and-conquer algorithm which exhibits inherent parallelism. For the parallel implementation, the Master/Worker pattern is employed to dynamically balance the varying workloads of each task on the set of available CPUs. Performance results by this approach are presented and discussed in detail as well as future work and improvements.

An infrastructure for the integration of geoscience instruments and sensors on the Grid

NASA Astrophysics Data System (ADS)

Pugliese, R.; Prica, M.; Kourousias, G.; Del Linz, A.; Curri, A.

2009-04-01

The Grid, as a computing paradigm, has long been in the attention of both academia and industry[1]. The distributed and expandable nature of its general architecture result to scalability and more efficient utilisation of the computing infrastructures. The scientific community, including that of geosciences, often handles problems with very high requirements in data processing, transferring, and storing[2,3]. This has raised the interest on Grid technologies but these are often viewed solely as an access gateway to HPC. Suitable Grid infrastructures could provide the geoscience community with additional benefits like those of sharing, remote access and control of scientific systems. These systems can be scientific instruments, sensors, robots, cameras and any other device used in geosciences. The solution for practical, general, and feasible Grid-enabling of such devices requires non-intrusive extensions on core parts of the current Grid architecture. We propose an extended version of an architecture[4] that can serve as the solution to the problem. The solution we propose is called Grid Instrument Element (IE) [5]. It is an addition to the existing core Grid parts; the Computing Element (CE) and the Storage Element (SE) that serve the purposes that their name suggests. The IE that we will be referring to, and the related technologies have been developed in the EU project on the Deployment of Remote Instrumentation Infrastructure (DORII1). In DORII, partners of various scientific communities including those of Earthquake, Environmental science, and Experimental science, have adopted the technology of the Instrument Element in order to integrate to the Grid their devices. The Oceanographic and coastal observation and modelling Mediterranean Ocean Observing Network (OGS2), a DORII partner, is in the process of deploying the above mentioned Grid technologies on two types of observational modules: Argo profiling floats and a novel Autonomous Underwater Vehicle (AUV). In this paper i) we define the need for integration of instrumentation in the Grid, ii) we introduce the solution of the Instrument Element, iii) we demonstrate a suitable end-user web portal for accessing Grid resources, iv) we describe from the Grid-technological point of view the process of the integration to the Grid of two advanced environmental monitoring devices. References [1] M. Surridge, S. Taylor, D. De Roure, and E. Zaluska, "Experiences with GRIA—Industrial Applications on a Web Services Grid," e-Science and Grid Computing, First International Conference on e-Science and Grid Computing, 2005, pp. 98-105. [2] A. Chervenak, I. Foster, C. Kesselman, C. Salisbury, and S. Tuecke, "The data grid: Towards an architecture for the distributed management and analysis of large scientific datasets," Journal of Network and Computer Applications, vol. 23, 2000, pp. 187-200. [3] B. Allcock, J. Bester, J. Bresnahan, A.L. Chervenak, I. Foster, C. Kesselman, S. Meder, V. Nefedova, D. Quesnel, and S. Tuecke, "Data management and transfer in high-performance computational grid environments," Parallel Computing, vol. 28, 2002, pp. 749-771. [4] E. Frizziero, M. Gulmini, F. Lelli, G. Maron, A. Oh, S. Orlando, A. Petrucci, S. Squizzato, and S. Traldi, "Instrument Element: A New Grid component that Enables the Control of Remote Instrumentation," Proceedings of the Sixth IEEE International Symposium on Cluster Computing and the Grid (CCGRID'06)-Volume 00, IEEE Computer Society Washington, DC, USA, 2006. [5] R. Ranon, L. De Marco, A. Senerchia, S. Gabrielli, L. Chittaro, R. Pugliese, L. Del Cano, F. Asnicar, and M. Prica, "A Web-based Tool for Collaborative Access to Scientific Instruments in Cyberinfrastructures." 1 The DORII project is supported by the European Commission within the 7th Framework Programme (FP7/2007-2013) under grant agreement no. RI-213110. URL: http://www.dorii.eu 2 Istituto Nazionale di Oceanografia e di Geofisica Sperimentale. URL: http://www.ogs.trieste.it

Stability assessment of structures under earthquake hazard through GRID technology

NASA Astrophysics Data System (ADS)

Prieto Castrillo, F.; Boton Fernandez, M.

2009-04-01

This work presents a GRID framework to estimate the vulnerability of structures under earthquake hazard. The tool has been designed to cover the needs of a typical earthquake engineering stability analysis; preparation of input data (pre-processing), response computation and stability analysis (post-processing). In order to validate the application over GRID, a simplified model of structure under artificially generated earthquake records has been implemented. To achieve this goal, the proposed scheme exploits the GRID technology and its main advantages (parallel intensive computing, huge storage capacity and collaboration analysis among institutions) through intensive interaction among the GRID elements (Computing Element, Storage Element, LHC File Catalogue, federated database etc.) The dynamical model is described by a set of ordinary differential equations (ODE's) and by a set of parameters. Both elements, along with the integration engine, are encapsulated into Java classes. With this high level design, subsequent improvements/changes of the model can be addressed with little effort. In the procedure, an earthquake record database is prepared and stored (pre-processing) in the GRID Storage Element (SE). The Metadata of these records is also stored in the GRID federated database. This Metadata contains both relevant information about the earthquake (as it is usual in a seismic repository) and also the Logical File Name (LFN) of the record for its later retrieval. Then, from the available set of accelerograms in the SE, the user can specify a range of earthquake parameters to carry out a dynamic analysis. This way, a GRID job is created for each selected accelerogram in the database. At the GRID Computing Element (CE), displacements are then obtained by numerical integration of the ODE's over time. The resulting response for that configuration is stored in the GRID Storage Element (SE) and the maximum structure displacement is computed. Then, the corresponding Metadata containing the response LFN, earthquake magnitude and maximum structure displacement is also stored. Finally, the displacements are post-processed through a statistically-based algorithm from the available Metadata to obtain the probability of collapse of the structure for different earthquake magnitudes. From this study, it is possible to build a vulnerability report for the structure type and seismic data. The proposed methodology can be combined with the on-going initiatives to build a European earthquake record database. In this context, Grid enables collaboration analysis over shared seismic data and results among different institutions.

Theoretical and Empirical Comparison of Big Data Image Processing with Apache Hadoop and Sun Grid Engine.

PubMed

Bao, Shunxing; Weitendorf, Frederick D; Plassard, Andrew J; Huo, Yuankai; Gokhale, Aniruddha; Landman, Bennett A

2017-02-11

The field of big data is generally concerned with the scale of processing at which traditional computational paradigms break down. In medical imaging, traditional large scale processing uses a cluster computer that combines a group of workstation nodes into a functional unit that is controlled by a job scheduler. Typically, a shared-storage network file system (NFS) is used to host imaging data. However, data transfer from storage to processing nodes can saturate network bandwidth when data is frequently uploaded/retrieved from the NFS, e.g., "short" processing times and/or "large" datasets. Recently, an alternative approach using Hadoop and HBase was presented for medical imaging to enable co-location of data storage and computation while minimizing data transfer. The benefits of using such a framework must be formally evaluated against a traditional approach to characterize the point at which simply "large scale" processing transitions into "big data" and necessitates alternative computational frameworks. The proposed Hadoop system was implemented on a production lab-cluster alongside a standard Sun Grid Engine (SGE). Theoretical models for wall-clock time and resource time for both approaches are introduced and validated. To provide real example data, three T1 image archives were retrieved from a university secure, shared web database and used to empirically assess computational performance under three configurations of cluster hardware (using 72, 109, or 209 CPU cores) with differing job lengths. Empirical results match the theoretical models. Based on these data, a comparative analysis is presented for when the Hadoop framework will be relevant and non-relevant for medical imaging.

Theoretical and empirical comparison of big data image processing with Apache Hadoop and Sun Grid Engine

NASA Astrophysics Data System (ADS)

Bao, Shunxing; Weitendorf, Frederick D.; Plassard, Andrew J.; Huo, Yuankai; Gokhale, Aniruddha; Landman, Bennett A.

2017-03-01

The field of big data is generally concerned with the scale of processing at which traditional computational paradigms break down. In medical imaging, traditional large scale processing uses a cluster computer that combines a group of workstation nodes into a functional unit that is controlled by a job scheduler. Typically, a shared-storage network file system (NFS) is used to host imaging data. However, data transfer from storage to processing nodes can saturate network bandwidth when data is frequently uploaded/retrieved from the NFS, e.g., "short" processing times and/or "large" datasets. Recently, an alternative approach using Hadoop and HBase was presented for medical imaging to enable co-location of data storage and computation while minimizing data transfer. The benefits of using such a framework must be formally evaluated against a traditional approach to characterize the point at which simply "large scale" processing transitions into "big data" and necessitates alternative computational frameworks. The proposed Hadoop system was implemented on a production lab-cluster alongside a standard Sun Grid Engine (SGE). Theoretical models for wall-clock time and resource time for both approaches are introduced and validated. To provide real example data, three T1 image archives were retrieved from a university secure, shared web database and used to empirically assess computational performance under three configurations of cluster hardware (using 72, 109, or 209 CPU cores) with differing job lengths. Empirical results match the theoretical models. Based on these data, a comparative analysis is presented for when the Hadoop framework will be relevant and nonrelevant for medical imaging.

An interpolation-free ALE scheme for unsteady inviscid flows computations with large boundary displacements over three-dimensional adaptive grids

NASA Astrophysics Data System (ADS)

Re, B.; Dobrzynski, C.; Guardone, A.

2017-07-01

A novel strategy to solve the finite volume discretization of the unsteady Euler equations within the Arbitrary Lagrangian-Eulerian framework over tetrahedral adaptive grids is proposed. The volume changes due to local mesh adaptation are treated as continuous deformations of the finite volumes and they are taken into account by adding fictitious numerical fluxes to the governing equation. This peculiar interpretation enables to avoid any explicit interpolation of the solution between different grids and to compute grid velocities so that the Geometric Conservation Law is automatically fulfilled also for connectivity changes. The solution on the new grid is obtained through standard ALE techniques, thus preserving the underlying scheme properties, such as conservativeness, stability and monotonicity. The adaptation procedure includes node insertion, node deletion, edge swapping and points relocation and it is exploited both to enhance grid quality after the boundary movement and to modify the grid spacing to increase solution accuracy. The presented approach is assessed by three-dimensional simulations of steady and unsteady flow fields. The capability of dealing with large boundary displacements is demonstrated by computing the flow around the translating infinite- and finite-span NACA 0012 wing moving through the domain at the flight speed. The proposed adaptive scheme is applied also to the simulation of a pitching infinite-span wing, where the bi-dimensional character of the flow is well reproduced despite the three-dimensional unstructured grid. Finally, the scheme is exploited in a piston-induced shock-tube problem to take into account simultaneously the large deformation of the domain and the shock wave. In all tests, mesh adaptation plays a crucial role.

Virtual Control Systems Environment (VCSE)

ScienceCinema

Atkins, Will

2018-02-14

Will Atkins, a Sandia National Laboratories computer engineer discusses cybersecurity research work for process control systems. Will explains his work on the Virtual Control Systems Environment project to develop a modeling and simulation framework of the U.S. electric grid in order to study and mitigate possible cyberattacks on infrastructure.

GridPP - Preparing for LHC Run 2 and the Wider Context

NASA Astrophysics Data System (ADS)

Coles, Jeremy

2015-12-01

This paper elaborates upon the operational status and directions within the UK Computing for Particle Physics (GridPP) project as it approaches LHC Run 2. It details the pressures that have been gradually reshaping the deployed hardware and middleware environments at GridPP sites - from the increasing adoption of larger multicore nodes to the move towards alternative batch systems and cloud alternatives - as well as changes being driven by funding considerations. The paper highlights work being done with non-LHC communities and describes some of the early outcomes of adopting a generic DIRAC based job submission and management framework. The paper presents results from an analysis of how GridPP effort is distributed across various deployment and operations tasks and how this may be used to target further improvements in efficiency.

IGMS: An Integrated ISO-to-Appliance Scale Grid Modeling System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Palmintier, Bryan; Hale, Elaine; Hansen, Timothy M.

This paper describes the Integrated Grid Modeling System (IGMS), a novel electric power system modeling platform for integrated transmission-distribution analysis that co-simulates off-the-shelf tools on high performance computing (HPC) platforms to offer unprecedented resolution from ISO markets down to appliances and other end uses. Specifically, the system simultaneously models hundreds or thousands of distribution systems in co-simulation with detailed Independent System Operator (ISO) markets and AGC-level reserve deployment. IGMS uses a new MPI-based hierarchical co-simulation framework to connect existing sub-domain models. Our initial efforts integrate opensource tools for wholesale markets (FESTIV), bulk AC power flow (MATPOWER), and full-featured distribution systemsmore » including physics-based end-use and distributed generation models (many instances of GridLAB-D[TM]). The modular IGMS framework enables tool substitution and additions for multi-domain analyses. This paper describes the IGMS tool, characterizes its performance, and demonstrates the impacts of the coupled simulations for analyzing high-penetration solar PV and price responsive load scenarios.« less

Predictive Model for Particle Residence Time Distributions in Riser Reactors. Part 1: Model Development and Validation

DOE PAGES

Foust, Thomas D.; Ziegler, Jack L.; Pannala, Sreekanth; ...

2017-02-28

Here in this computational study, we model the mixing of biomass pyrolysis vapor with solid catalyst in circulating riser reactors with a focus on the determination of solid catalyst residence time distributions (RTDs). A comprehensive set of 2D and 3D simulations were conducted for a pilot-scale riser using the Eulerian-Eulerian two-fluid modeling framework with and without sub-grid-scale models for the gas-solids interaction. A validation test case was also simulated and compared to experiments, showing agreement in the pressure gradient and RTD mean and spread. For simulation cases, it was found that for accurate RTD prediction, the Johnson and Jackson partialmore » slip solids boundary condition was required for all models and a sub-grid model is useful so that ultra high resolutions grids that are very computationally intensive are not required. Finally, we discovered a 2/3 scaling relation for the RTD mean and spread when comparing resolved 2D simulations to validated unresolved 3D sub-grid-scale model simulations.« less

Cellular computational generalized neuron network for frequency situational intelligence in a multi-machine power system.

PubMed

Wei, Yawei; Venayagamoorthy, Ganesh Kumar

2017-09-01

To prevent large interconnected power system from a cascading failure, brownout or even blackout, grid operators require access to faster than real-time information to make appropriate just-in-time control decisions. However, the communication and computational system limitations of currently used supervisory control and data acquisition (SCADA) system can only deliver delayed information. However, the deployment of synchrophasor measurement devices makes it possible to capture and visualize, in near-real-time, grid operational data with extra granularity. In this paper, a cellular computational network (CCN) approach for frequency situational intelligence (FSI) in a power system is presented. The distributed and scalable computing unit of the CCN framework makes it particularly flexible for customization for a particular set of prediction requirements. Two soft-computing algorithms have been implemented in the CCN framework: a cellular generalized neuron network (CCGNN) and a cellular multi-layer perceptron network (CCMLPN), for purposes of providing multi-timescale frequency predictions, ranging from 16.67 ms to 2 s. These two developed CCGNN and CCMLPN systems were then implemented on two different scales of power systems, one of which installed a large photovoltaic plant. A real-time power system simulator at weather station within the Real-Time Power and Intelligent Systems (RTPIS) laboratory at Clemson, SC, was then used to derive typical FSI results. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Role of Discrete Global Grid Systems in the Global Statistical Geospatial Framework

NASA Astrophysics Data System (ADS)

Purss, M. B. J.; Peterson, P.; Minchin, S. A.; Bermudez, L. E.

2016-12-01

The United Nations Committee of Experts on Global Geospatial Information Management (UN-GGIM) has proposed the development of a Global Statistical Geospatial Framework (GSGF) as a mechanism for the establishment of common analytical systems that enable the integration of statistical and geospatial information. Conventional coordinate reference systems address the globe with a continuous field of points suitable for repeatable navigation and analytical geometry. While this continuous field is represented on a computer in a digitized and discrete fashion by tuples of fixed-precision floating point values, it is a non-trivial exercise to relate point observations spatially referenced in this way to areal coverages on the surface of the Earth. The GSGF states the need to move to gridded data delivery and the importance of using common geographies and geocoding. The challenges associated with meeting these goals are not new and there has been a significant effort within the geospatial community to develop nested gridding standards to tackle these issues over many years. These efforts have recently culminated in the development of a Discrete Global Grid Systems (DGGS) standard which has been developed under the auspices of Open Geospatial Consortium (OGC). DGGS provide a fixed areal based geospatial reference frame for the persistent location of measured Earth observations, feature interpretations, and modelled predictions. DGGS address the entire planet by partitioning it into a discrete hierarchical tessellation of progressively finer resolution cells, which are referenced by a unique index that facilitates rapid computation, query and analysis. The geometry and location of the cell is the principle aspect of a DGGS. Data integration, decomposition, and aggregation is optimised in the DGGS hierarchical structure and can be exploited for efficient multi-source data processing, storage, discovery, transmission, visualization, computation, analysis, and modelling. During the 6th Session of the UN-GGIM in August 2016 the role of DGGS in the context of the GSGF was formally acknowledged. This paper proposes to highlight the synergies and role of DGGS in the Global Statistical Geospatial Framework and to show examples of the use of DGGS to combine geospatial statistics with traditional geoscientific data.

A heterogeneous and parallel computing framework for high-resolution hydrodynamic simulations

NASA Astrophysics Data System (ADS)

Smith, Luke; Liang, Qiuhua

2015-04-01

Shock-capturing hydrodynamic models are now widely applied in the context of flood risk assessment and forecasting, accurately capturing the behaviour of surface water over ground and within rivers. Such models are generally explicit in their numerical basis, and can be computationally expensive; this has prohibited full use of high-resolution topographic data for complex urban environments, now easily obtainable through airborne altimetric surveys (LiDAR). As processor clock speed advances have stagnated in recent years, further computational performance gains are largely dependent on the use of parallel processing. Heterogeneous computing architectures (e.g. graphics processing units or compute accelerator cards) provide a cost-effective means of achieving high throughput in cases where the same calculation is performed with a large input dataset. In recent years this technique has been applied successfully for flood risk mapping, such as within the national surface water flood risk assessment for the United Kingdom. We present a flexible software framework for hydrodynamic simulations across multiple processors of different architectures, within multiple computer systems, enabled using OpenCL and Message Passing Interface (MPI) libraries. A finite-volume Godunov-type scheme is implemented using the HLLC approach to solving the Riemann problem, with optional extension to second-order accuracy in space and time using the MUSCL-Hancock approach. The framework is successfully applied on personal computers and a small cluster to provide considerable improvements in performance. The most significant performance gains were achieved across two servers, each containing four NVIDIA GPUs, with a mix of K20, M2075 and C2050 devices. Advantages are found with respect to decreased parametric sensitivity, and thus in reducing uncertainty, for a major fluvial flood within a large catchment during 2005 in Carlisle, England. Simulations for the three-day event could be performed on a 2m grid within a few hours. In the context of a rapid pluvial flood event in Newcastle upon Tyne during 2012, the technique allows simulation of inundation for a 31km2 of the city centre in less than an hour on a 2m grid; however, further grid refinement is required to fully capture important smaller flow pathways. Good agreement between the model and observed inundation is achieved for a variety of dam failure, slow fluvial inundation, rapid pluvial inundation, and defence breach scenarios in the UK.

76 FR 66040 - NIST Framework and Roadmap for Smart Grid Interoperability Standards, Release 2.0 (Draft...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-25

...-01] NIST Framework and Roadmap for Smart Grid Interoperability Standards, Release 2.0 (Draft... draft version of the NIST Framework and Roadmap for Smart Grid Interoperability Standards, Release 2.0... Roadmap for Smart Grid Interoperability Standards, Release 2.0 (Release 2.0) (Draft) for public review and...

Framework Resources Multiply Computing Power

NASA Technical Reports Server (NTRS)

2010-01-01

As an early proponent of grid computing, Ames Research Center awarded Small Business Innovation Research (SBIR) funding to 3DGeo Development Inc., of Santa Clara, California, (now FusionGeo Inc., of The Woodlands, Texas) to demonstrate a virtual computer environment that linked geographically dispersed computer systems over the Internet to help solve large computational problems. By adding to an existing product, FusionGeo enabled access to resources for calculation- or data-intensive applications whenever and wherever they were needed. Commercially available as Accelerated Imaging and Modeling, the product is used by oil companies and seismic service companies, which require large processing and data storage capacities.

caGrid 1.0 : an enterprise Grid infrastructure for biomedical research.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oster, S.; Langella, S.; Hastings, S.

To develop software infrastructure that will provide support for discovery, characterization, integrated access, and management of diverse and disparate collections of information sources, analysis methods, and applications in biomedical research. Design: An enterprise Grid software infrastructure, called caGrid version 1.0 (caGrid 1.0), has been developed as the core Grid architecture of the NCI-sponsored cancer Biomedical Informatics Grid (caBIG{trademark}) program. It is designed to support a wide range of use cases in basic, translational, and clinical research, including (1) discovery, (2) integrated and large-scale data analysis, and (3) coordinated study. Measurements: The caGrid is built as a Grid software infrastructure andmore » leverages Grid computing technologies and the Web Services Resource Framework standards. It provides a set of core services, toolkits for the development and deployment of new community provided services, and application programming interfaces for building client applications. Results: The caGrid 1.0 was released to the caBIG community in December 2006. It is built on open source components and caGrid source code is publicly and freely available under a liberal open source license. The core software, associated tools, and documentation can be downloaded from the following URL: .« less

Cause and Cure-Deterioration in Accuracy of CFD Simulations with Use of High-Aspect-Ratio Triangular/Tetrahedral Grids

NASA Technical Reports Server (NTRS)

Chang, Sin-Chung; Chang, Chau-Lyan; Venkatachari, Balaji

2017-01-01

In the multi-dimensional space-time conservation element and solution element16 (CESE) method, triangles and tetrahedral mesh elements turn out to be the most natural building blocks for 2D and 3D spatial grids, respectively. As such, the CESE method is naturally compatible with the simplest 2D and 3D unstructured grids and thus can be easily applied to solve problems with complex geometries. However, because (a) accurate solution of a high-Reynolds number flow field near a solid wall requires that the grid intervals along the direction normal to the wall be much finer than those in a direction parallel to the wall and, as such, the use of grid cells with extremely high aspect ratio (103 to 106) may become mandatory, and (b) unlike quadrilateral hexahedral grids, it is well-known that accuracy of gradient computations involving triangular tetrahedral grids tends to deteriorate rapidly as cell aspect ratio increases. As a result, the use of triangular tetrahedral grid cells near a solid wall has long been deemed impractical by CFD researchers. In view of (a) the critical role played by triangular tetrahedral grids in the CESE development, and (b) the importance of accurate resolution of high-Reynolds number flow field near a solid wall, as will be presented in the main paper, a comprehensive and rigorous mathematical framework that clearly identifies the reasons behind the accuracy deterioration as described above has been developed for the 2D case involving triangular cells. By avoiding the pitfalls identified by the 2D framework, and its 3D extension, it has been shown numerically.

Theoretical and Empirical Comparison of Big Data Image Processing with Apache Hadoop and Sun Grid Engine

PubMed Central

Bao, Shunxing; Weitendorf, Frederick D.; Plassard, Andrew J.; Huo, Yuankai; Gokhale, Aniruddha; Landman, Bennett A.

2016-01-01

The field of big data is generally concerned with the scale of processing at which traditional computational paradigms break down. In medical imaging, traditional large scale processing uses a cluster computer that combines a group of workstation nodes into a functional unit that is controlled by a job scheduler. Typically, a shared-storage network file system (NFS) is used to host imaging data. However, data transfer from storage to processing nodes can saturate network bandwidth when data is frequently uploaded/retrieved from the NFS, e.g., “short” processing times and/or “large” datasets. Recently, an alternative approach using Hadoop and HBase was presented for medical imaging to enable co-location of data storage and computation while minimizing data transfer. The benefits of using such a framework must be formally evaluated against a traditional approach to characterize the point at which simply “large scale” processing transitions into “big data” and necessitates alternative computational frameworks. The proposed Hadoop system was implemented on a production lab-cluster alongside a standard Sun Grid Engine (SGE). Theoretical models for wall-clock time and resource time for both approaches are introduced and validated. To provide real example data, three T1 image archives were retrieved from a university secure, shared web database and used to empirically assess computational performance under three configurations of cluster hardware (using 72, 109, or 209 CPU cores) with differing job lengths. Empirical results match the theoretical models. Based on these data, a comparative analysis is presented for when the Hadoop framework will be relevant and non-relevant for medical imaging. PMID:28736473

Challenges to Software/Computing for Experimentation at the LHC

NASA Astrophysics Data System (ADS)

Banerjee, Sunanda

The demands of future high energy physics experiments towards software and computing have led the experiments to plan the related activities as a full-fledged project and to investigate new methodologies and languages to meet the challenges. The paths taken by the four LHC experiments ALICE, ATLAS, CMS and LHCb are coherently put together in an LHC-wide framework based on Grid technology. The current status and understandings have been broadly outlined.

Information Power Grid: Distributed High-Performance Computing and Large-Scale Data Management for Science and Engineering

NASA Technical Reports Server (NTRS)

Johnston, William E.; Gannon, Dennis; Nitzberg, Bill

2000-01-01

We use the term "Grid" to refer to distributed, high performance computing and data handling infrastructure that incorporates geographically and organizationally dispersed, heterogeneous resources that are persistent and supported. This infrastructure includes: (1) Tools for constructing collaborative, application oriented Problem Solving Environments / Frameworks (the primary user interfaces for Grids); (2) Programming environments, tools, and services providing various approaches for building applications that use aggregated computing and storage resources, and federated data sources; (3) Comprehensive and consistent set of location independent tools and services for accessing and managing dynamic collections of widely distributed resources: heterogeneous computing systems, storage systems, real-time data sources and instruments, human collaborators, and communications systems; (4) Operational infrastructure including management tools for distributed systems and distributed resources, user services, accounting and auditing, strong and location independent user authentication and authorization, and overall system security services The vision for NASA's Information Power Grid - a computing and data Grid - is that it will provide significant new capabilities to scientists and engineers by facilitating routine construction of information based problem solving environments / frameworks. Such Grids will knit together widely distributed computing, data, instrument, and human resources into just-in-time systems that can address complex and large-scale computing and data analysis problems. Examples of these problems include: (1) Coupled, multidisciplinary simulations too large for single systems (e.g., multi-component NPSS turbomachine simulation); (2) Use of widely distributed, federated data archives (e.g., simultaneous access to metrological, topological, aircraft performance, and flight path scheduling databases supporting a National Air Space Simulation systems}; (3) Coupling large-scale computing and data systems to scientific and engineering instruments (e.g., realtime interaction with experiments through real-time data analysis and interpretation presented to the experimentalist in ways that allow direct interaction with the experiment (instead of just with instrument control); (5) Highly interactive, augmented reality and virtual reality remote collaborations (e.g., Ames / Boeing Remote Help Desk providing field maintenance use of coupled video and NDI to a remote, on-line airframe structures expert who uses this data to index into detailed design databases, and returns 3D internal aircraft geometry to the field); (5) Single computational problems too large for any single system (e.g. the rotocraft reference calculation). Grids also have the potential to provide pools of resources that could be called on in extraordinary / rapid response situations (such as disaster response) because they can provide common interfaces and access mechanisms, standardized management, and uniform user authentication and authorization, for large collections of distributed resources (whether or not they normally function in concert). IPG development and deployment is addressing requirements obtained by analyzing a number of different application areas, in particular from the NASA Aero-Space Technology Enterprise. This analysis has focussed primarily on two types of users: the scientist / design engineer whose primary interest is problem solving (e.g. determining wing aerodynamic characteristics in many different operating environments), and whose primary interface to IPG will be through various sorts of problem solving frameworks. The second type of user is the tool designer: the computational scientists who convert physics and mathematics into code that can simulate the physical world. These are the two primary users of IPG, and they have rather different requirements. The results of the analysis of the needs of these two types of users provides a broad set of requirements that gives rise to a general set of required capabilities. The IPG project is intended to address all of these requirements. In some cases the required computing technology exists, and in some cases it must be researched and developed. The project is using available technology to provide a prototype set of capabilities in a persistent distributed computing testbed. Beyond this, there are required capabilities that are not immediately available, and whose development spans the range from near-term engineering development (one to two years) to much longer term R&D (three to six years). Additional information is contained in the original.

Trends in life science grid: from computing grid to knowledge grid.

PubMed

Konagaya, Akihiko

2006-12-18

Grid computing has great potential to become a standard cyberinfrastructure for life sciences which often require high-performance computing and large data handling which exceeds the computing capacity of a single institution. This survey reviews the latest grid technologies from the viewpoints of computing grid, data grid and knowledge grid. Computing grid technologies have been matured enough to solve high-throughput real-world life scientific problems. Data grid technologies are strong candidates for realizing "resourceome" for bioinformatics. Knowledge grids should be designed not only from sharing explicit knowledge on computers but also from community formulation for sharing tacit knowledge among a community. Extending the concept of grid from computing grid to knowledge grid, it is possible to make use of a grid as not only sharable computing resources, but also as time and place in which people work together, create knowledge, and share knowledge and experiences in a community.

Trends in life science grid: from computing grid to knowledge grid

PubMed Central

Konagaya, Akihiko

2006-01-01

Background Grid computing has great potential to become a standard cyberinfrastructure for life sciences which often require high-performance computing and large data handling which exceeds the computing capacity of a single institution. Results This survey reviews the latest grid technologies from the viewpoints of computing grid, data grid and knowledge grid. Computing grid technologies have been matured enough to solve high-throughput real-world life scientific problems. Data grid technologies are strong candidates for realizing "resourceome" for bioinformatics. Knowledge grids should be designed not only from sharing explicit knowledge on computers but also from community formulation for sharing tacit knowledge among a community. Conclusion Extending the concept of grid from computing grid to knowledge grid, it is possible to make use of a grid as not only sharable computing resources, but also as time and place in which people work together, create knowledge, and share knowledge and experiences in a community. PMID:17254294

Global computing for bioinformatics.

PubMed

Loewe, Laurence

2002-12-01

Global computing, the collaboration of idle PCs via the Internet in a SETI@home style, emerges as a new way of massive parallel multiprocessing with potentially enormous CPU power. Its relations to the broader, fast-moving field of Grid computing are discussed without attempting a review of the latter. This review (i) includes a short table of milestones in global computing history, (ii) lists opportunities global computing offers for bioinformatics, (iii) describes the structure of problems well suited for such an approach, (iv) analyses the anatomy of successful projects and (v) points to existing software frameworks. Finally, an evaluation of the various costs shows that global computing indeed has merit, if the problem to be solved is already coded appropriately and a suitable global computing framework can be found. Then, either significant amounts of computing power can be recruited from the general public, or--if employed in an enterprise-wide Intranet for security reasons--idle desktop PCs can substitute for an expensive dedicated cluster.

Air Pollution Monitoring and Mining Based on Sensor Grid in London

PubMed Central

Ma, Yajie; Richards, Mark; Ghanem, Moustafa; Guo, Yike; Hassard, John

2008-01-01

In this paper, we present a distributed infrastructure based on wireless sensors network and Grid computing technology for air pollution monitoring and mining, which aims to develop low-cost and ubiquitous sensor networks to collect real-time, large scale and comprehensive environmental data from road traffic emissions for air pollution monitoring in urban environment. The main informatics challenges in respect to constructing the high-throughput sensor Grid are discussed in this paper. We present a two-layer network framework, a P2P e-Science Grid architecture, and the distributed data mining algorithm as the solutions to address the challenges. We simulated the system in TinyOS to examine the operation of each sensor as well as the networking performance. We also present the distributed data mining result to examine the effectiveness of the algorithm. PMID:27879895

Air Pollution Monitoring and Mining Based on Sensor Grid in London.

PubMed

Ma, Yajie; Richards, Mark; Ghanem, Moustafa; Guo, Yike; Hassard, John

2008-06-01

In this paper, we present a distributed infrastructure based on wireless sensors network and Grid computing technology for air pollution monitoring and mining, which aims to develop low-cost and ubiquitous sensor networks to collect real-time, large scale and comprehensive environmental data from road traffic emissions for air pollution monitoring in urban environment. The main informatics challenges in respect to constructing the high-throughput sensor Grid are discussed in this paper. We present a twolayer network framework, a P2P e-Science Grid architecture, and the distributed data mining algorithm as the solutions to address the challenges. We simulated the system in TinyOS to examine the operation of each sensor as well as the networking performance. We also present the distributed data mining result to examine the effectiveness of the algorithm.

A MATLAB based 3D modeling and inversion code for MT data

NASA Astrophysics Data System (ADS)

Singh, Arun; Dehiya, Rahul; Gupta, Pravin K.; Israil, M.

2017-07-01

The development of a MATLAB based computer code, AP3DMT, for modeling and inversion of 3D Magnetotelluric (MT) data is presented. The code comprises two independent components: grid generator code and modeling/inversion code. The grid generator code performs model discretization and acts as an interface by generating various I/O files. The inversion code performs core computations in modular form - forward modeling, data functionals, sensitivity computations and regularization. These modules can be readily extended to other similar inverse problems like Controlled-Source EM (CSEM). The modular structure of the code provides a framework useful for implementation of new applications and inversion algorithms. The use of MATLAB and its libraries makes it more compact and user friendly. The code has been validated on several published models. To demonstrate its versatility and capabilities the results of inversion for two complex models are presented.

Lattice Boltzmann and Navier-Stokes Cartesian CFD Approaches for Airframe Noise Predictions

NASA Technical Reports Server (NTRS)

Barad, Michael F.; Kocheemoolayil, Joseph G.; Kiris, Cetin C.

2017-01-01

Lattice Boltzmann (LB) and compressible Navier-Stokes (NS) equations based computational fluid dynamics (CFD) approaches are compared for simulating airframe noise. Both LB and NS CFD approaches are implemented within the Launch Ascent and Vehicle Aerodynamics (LAVA) framework. Both schemes utilize the same underlying Cartesian structured mesh paradigm with provision for local adaptive grid refinement and sub-cycling in time. We choose a prototypical massively separated, wake-dominated flow ideally suited for Cartesian-grid based approaches in this study - The partially-dressed, cavity-closed nose landing gear (PDCC-NLG) noise problem from AIAA's Benchmark problems for Airframe Noise Computations (BANC) series of workshops. The relative accuracy and computational efficiency of the two approaches are systematically compared. Detailed comments are made on the potential held by LB to significantly reduce time-to-solution for a desired level of accuracy within the context of modeling airframes noise from first principles.

Intelligent sensor and controller framework for the power grid

DOEpatents

Akyol, Bora A.; Haack, Jereme Nathan; Craig, Jr., Philip Allen; Tews, Cody William; Kulkarni, Anand V.; Carpenter, Brandon J.; Maiden, Wendy M.; Ciraci, Selim

2015-07-28

Disclosed below are representative embodiments of methods, apparatus, and systems for monitoring and using data in an electric power grid. For example, one disclosed embodiment comprises a sensor for measuring an electrical characteristic of a power line, electrical generator, or electrical device; a network interface; a processor; and one or more computer-readable storage media storing computer-executable instructions. In this embodiment, the computer-executable instructions include instructions for implementing an authorization and authentication module for validating a software agent received at the network interface; instructions for implementing one or more agent execution environments for executing agent code that is included with the software agent and that causes data from the sensor to be collected; and instructions for implementing an agent packaging and instantiation module for storing the collected data in a data container of the software agent and for transmitting the software agent, along with the stored data, to a next destination.

Intelligent sensor and controller framework for the power grid

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akyol, Bora A.; Haack, Jereme Nathan; Craig, Jr., Philip Allen

Disclosed below are representative embodiments of methods, apparatus, and systems for monitoring and using data in an electric power grid. For example, one disclosed embodiment comprises a sensor for measuring an electrical characteristic of a power line, electrical generator, or electrical device; a network interface; a processor; and one or more computer-readable storage media storing computer-executable instructions. In this embodiment, the computer-executable instructions include instructions for implementing an authorization and authentication module for validating a software agent received at the network interface; instructions for implementing one or more agent execution environments for executing agent code that is included with themore » software agent and that causes data from the sensor to be collected; and instructions for implementing an agent packaging and instantiation module for storing the collected data in a data container of the software agent and for transmitting the software agent, along with the stored data, to a next destination.« less

LHCb experience with LFC replication

NASA Astrophysics Data System (ADS)

Bonifazi, F.; Carbone, A.; Perez, E. D.; D'Apice, A.; dell'Agnello, L.; Duellmann, D.; Girone, M.; Re, G. L.; Martelli, B.; Peco, G.; Ricci, P. P.; Sapunenko, V.; Vagnoni, V.; Vitlacil, D.

2008-07-01

Database replication is a key topic in the framework of the LHC Computing Grid to allow processing of data in a distributed environment. In particular, the LHCb computing model relies on the LHC File Catalog, i.e. a database which stores information about files spread across the GRID, their logical names and the physical locations of all the replicas. The LHCb computing model requires the LFC to be replicated at Tier-1s. The LCG 3D project deals with the database replication issue and provides a replication service based on Oracle Streams technology. This paper describes the deployment of the LHC File Catalog replication to the INFN National Center for Telematics and Informatics (CNAF) and to other LHCb Tier-1 sites. We performed stress tests designed to evaluate any delay in the propagation of the streams and the scalability of the system. The tests show the robustness of the replica implementation with performance going much beyond the LHCb requirements.

Towards Integrating Distributed Energy Resources and Storage Devices in Smart Grid.

PubMed

Xu, Guobin; Yu, Wei; Griffith, David; Golmie, Nada; Moulema, Paul

2017-02-01

Internet of Things (IoT) provides a generic infrastructure for different applications to integrate information communication techniques with physical components to achieve automatic data collection, transmission, exchange, and computation. The smart grid, as one of typical applications supported by IoT, denoted as a re-engineering and a modernization of the traditional power grid, aims to provide reliable, secure, and efficient energy transmission and distribution to consumers. How to effectively integrate distributed (renewable) energy resources and storage devices to satisfy the energy service requirements of users, while minimizing the power generation and transmission cost, remains a highly pressing challenge in the smart grid. To address this challenge and assess the effectiveness of integrating distributed energy resources and storage devices, in this paper we develop a theoretical framework to model and analyze three types of power grid systems: the power grid with only bulk energy generators, the power grid with distributed energy resources, and the power grid with both distributed energy resources and storage devices. Based on the metrics of the power cumulative cost and the service reliability to users, we formally model and analyze the impact of integrating distributed energy resources and storage devices in the power grid. We also use the concept of network calculus, which has been traditionally used for carrying out traffic engineering in computer networks, to derive the bounds of both power supply and user demand to achieve a high service reliability to users. Through an extensive performance evaluation, our data shows that integrating distributed energy resources conjointly with energy storage devices can reduce generation costs, smooth the curve of bulk power generation over time, reduce bulk power generation and power distribution losses, and provide a sustainable service reliability to users in the power grid.

Towards Integrating Distributed Energy Resources and Storage Devices in Smart Grid

PubMed Central

Xu, Guobin; Yu, Wei; Griffith, David; Golmie, Nada; Moulema, Paul

2017-01-01

Internet of Things (IoT) provides a generic infrastructure for different applications to integrate information communication techniques with physical components to achieve automatic data collection, transmission, exchange, and computation. The smart grid, as one of typical applications supported by IoT, denoted as a re-engineering and a modernization of the traditional power grid, aims to provide reliable, secure, and efficient energy transmission and distribution to consumers. How to effectively integrate distributed (renewable) energy resources and storage devices to satisfy the energy service requirements of users, while minimizing the power generation and transmission cost, remains a highly pressing challenge in the smart grid. To address this challenge and assess the effectiveness of integrating distributed energy resources and storage devices, in this paper we develop a theoretical framework to model and analyze three types of power grid systems: the power grid with only bulk energy generators, the power grid with distributed energy resources, and the power grid with both distributed energy resources and storage devices. Based on the metrics of the power cumulative cost and the service reliability to users, we formally model and analyze the impact of integrating distributed energy resources and storage devices in the power grid. We also use the concept of network calculus, which has been traditionally used for carrying out traffic engineering in computer networks, to derive the bounds of both power supply and user demand to achieve a high service reliability to users. Through an extensive performance evaluation, our data shows that integrating distributed energy resources conjointly with energy storage devices can reduce generation costs, smooth the curve of bulk power generation over time, reduce bulk power generation and power distribution losses, and provide a sustainable service reliability to users in the power grid1. PMID:29354654

Adaptive Grid Based Localized Learning for Multidimensional Data

ERIC Educational Resources Information Center

Saini, Sheetal

2012-01-01

Rapid advances in data-rich domains of science, technology, and business has amplified the computational challenges of "Big Data" synthesis necessary to slow the widening gap between the rate at which the data is being collected and analyzed for knowledge. This has led to the renewed need for efficient and accurate algorithms, framework,…

Production of single-walled carbon nanotube grids

DOEpatents

Hauge, Robert H; Xu, Ya-Qiong; Pheasant, Sean

2013-12-03

A method of forming a nanotube grid includes placing a plurality of catalyst nanoparticles on a grid framework, contacting the catalyst nanoparticles with a gas mixture that includes hydrogen and a carbon source in a reaction chamber, forming an activated gas from the gas mixture, heating the grid framework and activated gas, and controlling a growth time to generate a single-wall carbon nanotube array radially about the grid framework. A filter membrane may be produced by this method.

A mass and momentum conserving unsplit semi-Lagrangian framework for simulating multiphase flows

DOE Office of Scientific and Technical Information (OSTI.GOV)

Owkes, Mark, E-mail: mark.owkes@montana.edu; Desjardins, Olivier

In this work, we present a computational methodology for convection and advection that handles discontinuities with second order accuracy and maintains conservation to machine precision. This method can transport a variety of discontinuous quantities and is used in the context of an incompressible gas–liquid flow to transport the phase interface, momentum, and scalars. The proposed method provides a modification to the three-dimensional, unsplit, second-order semi-Lagrangian flux method of Owkes & Desjardins (JCP, 2014). The modification adds a refined grid that provides consistent fluxes of mass and momentum defined on a staggered grid and discrete conservation of mass and momentum, evenmore » for flows with large density ratios. Additionally, the refined grid doubles the resolution of the interface without significantly increasing the computational cost over previous non-conservative schemes. This is possible due to a novel partitioning of the semi-Lagrangian fluxes into a small number of simplices. The proposed scheme is tested using canonical verification tests, rising bubbles, and an atomizing liquid jet.« less

The SCEC Unified Community Velocity Model (UCVM) Software Framework for Distributing and Querying Seismic Velocity Models

NASA Astrophysics Data System (ADS)

Maechling, P. J.; Taborda, R.; Callaghan, S.; Shaw, J. H.; Plesch, A.; Olsen, K. B.; Jordan, T. H.; Goulet, C. A.

2017-12-01

Crustal seismic velocity models and datasets play a key role in regional three-dimensional numerical earthquake ground-motion simulation, full waveform tomography, modern physics-based probabilistic earthquake hazard analysis, as well as in other related fields including geophysics, seismology, and earthquake engineering. The standard material properties provided by a seismic velocity model are P- and S-wave velocities and density for any arbitrary point within the geographic volume for which the model is defined. Many seismic velocity models and datasets are constructed by synthesizing information from multiple sources and the resulting models are delivered to users in multiple file formats, such as text files, binary files, HDF-5 files, structured and unstructured grids, and through computer applications that allow for interactive querying of material properties. The Southern California Earthquake Center (SCEC) has developed the Unified Community Velocity Model (UCVM) software framework to facilitate the registration and distribution of existing and future seismic velocity models to the SCEC community. The UCVM software framework is designed to provide a standard query interface to multiple, alternative velocity models, even if the underlying velocity models are defined in different formats or use different geographic projections. The UCVM framework provides a comprehensive set of open-source tools for querying seismic velocity model properties, combining regional 3D models and 1D background models, visualizing 3D models, and generating computational models in the form of regular grids or unstructured meshes that can be used as inputs for ground-motion simulations. The UCVM framework helps researchers compare seismic velocity models and build equivalent simulation meshes from alternative velocity models. These capabilities enable researchers to evaluate the impact of alternative velocity models in ground-motion simulations and seismic hazard analysis applications. In this poster, we summarize the key components of the UCVM framework and describe the impact it has had in various computational geoscientific applications.

Loci-STREAM Version 0.9

NASA Technical Reports Server (NTRS)

Wright, Jeffrey; Thakur, Siddharth

2006-01-01

Loci-STREAM is an evolving computational fluid dynamics (CFD) software tool for simulating possibly chemically reacting, possibly unsteady flows in diverse settings, including rocket engines, turbomachines, oil refineries, etc. Loci-STREAM implements a pressure- based flow-solving algorithm that utilizes unstructured grids. (The benefit of low memory usage by pressure-based algorithms is well recognized by experts in the field.) The algorithm is robust for flows at all speeds from zero to hypersonic. The flexibility of arbitrary polyhedral grids enables accurate, efficient simulation of flows in complex geometries, including those of plume-impingement problems. The present version - Loci-STREAM version 0.9 - includes an interface with the Portable, Extensible Toolkit for Scientific Computation (PETSc) library for access to enhanced linear-equation-solving programs therein that accelerate convergence toward a solution. The name "Loci" reflects the creation of this software within the Loci computational framework, which was developed at Mississippi State University for the primary purpose of simplifying the writing of complex multidisciplinary application programs to run in distributed-memory computing environments including clusters of personal computers. Loci has been designed to relieve application programmers of the details of programming for distributed-memory computers.

gLExec: gluing grid computing to the Unix world

NASA Astrophysics Data System (ADS)

Groep, D.; Koeroo, O.; Venekamp, G.

2008-07-01

The majority of compute resources in todays scientific grids are based on Unix and Unix-like operating systems. In this world, user and user-group management are based around the concepts of a numeric 'user ID' and 'group ID' that are local to the resource. In contrast, grid concepts of user and group management are centered around globally assigned identifiers and VO membership, structures that are independent of any specific resource. At the fabric boundary, these 'grid identities' have to be translated to Unix user IDs. New job submission methodologies, such as job-execution web services, community-deployed local schedulers, and the late binding of user jobs in a grid-wide overlay network of 'pilot jobs', push this fabric boundary ever further down into the resource. gLExec, a light-weight (and thereby auditable) credential mapping and authorization system, addresses these issues. It can be run both on fabric boundary, as part of an execution web service, and on the worker node in a late-binding scenario. In this contribution we describe the rationale for gLExec, how it interacts with the site authorization and credential mapping frameworks such as LCAS, LCMAPS and GUMS, and how it can be used to improve site control and traceability in a pilot-job system.

The Parallel System for Integrating Impact Models and Sectors (pSIMS)

NASA Technical Reports Server (NTRS)

Elliott, Joshua; Kelly, David; Chryssanthacopoulos, James; Glotter, Michael; Jhunjhnuwala, Kanika; Best, Neil; Wilde, Michael; Foster, Ian

2014-01-01

We present a framework for massively parallel climate impact simulations: the parallel System for Integrating Impact Models and Sectors (pSIMS). This framework comprises a) tools for ingesting and converting large amounts of data to a versatile datatype based on a common geospatial grid; b) tools for translating this datatype into custom formats for site-based models; c) a scalable parallel framework for performing large ensemble simulations, using any one of a number of different impacts models, on clusters, supercomputers, distributed grids, or clouds; d) tools and data standards for reformatting outputs to common datatypes for analysis and visualization; and e) methodologies for aggregating these datatypes to arbitrary spatial scales such as administrative and environmental demarcations. By automating many time-consuming and error-prone aspects of large-scale climate impacts studies, pSIMS accelerates computational research, encourages model intercomparison, and enhances reproducibility of simulation results. We present the pSIMS design and use example assessments to demonstrate its multi-model, multi-scale, and multi-sector versatility.

Changing from computing grid to knowledge grid in life-science grid.

PubMed

Talukdar, Veera; Konar, Amit; Datta, Ayan; Choudhury, Anamika Roy

2009-09-01

Grid computing has a great potential to become a standard cyber infrastructure for life sciences that often require high-performance computing and large data handling, which exceeds the computing capacity of a single institution. Grid computer applies the resources of many computers in a network to a single problem at the same time. It is useful to scientific problems that require a great number of computer processing cycles or access to a large amount of data.As biologists,we are constantly discovering millions of genes and genome features, which are assembled in a library and distributed on computers around the world.This means that new, innovative methods must be developed that exploit the re-sources available for extensive calculations - for example grid computing.This survey reviews the latest grid technologies from the viewpoints of computing grid, data grid and knowledge grid. Computing grid technologies have been matured enough to solve high-throughput real-world life scientific problems. Data grid technologies are strong candidates for realizing a "resourceome" for bioinformatics. Knowledge grids should be designed not only from sharing explicit knowledge on computers but also from community formulation for sharing tacit knowledge among a community. By extending the concept of grid from computing grid to knowledge grid, it is possible to make use of a grid as not only sharable computing resources, but also as time and place in which people work together, create knowledge, and share knowledge and experiences in a community.

An adaptive grid to improve the efficiency and accuracy of modelling underwater noise from shipping

NASA Astrophysics Data System (ADS)

Trigg, Leah; Chen, Feng; Shapiro, Georgy; Ingram, Simon; Embling, Clare

2017-04-01

Underwater noise from shipping is becoming a significant concern and has been listed as a pollutant under Descriptor 11 of the Marine Strategy Framework Directive. Underwater noise models are an essential tool to assess and predict noise levels for regulatory procedures such as environmental impact assessments and ship noise monitoring. There are generally two approaches to noise modelling. The first is based on simplified energy flux models, assuming either spherical or cylindrical propagation of sound energy. These models are very quick but they ignore important water column and seabed properties, and produce significant errors in the areas subject to temperature stratification (Shapiro et al., 2014). The second type of model (e.g. ray-tracing and parabolic equation) is based on an advanced physical representation of sound propagation. However, these acoustic propagation models are computationally expensive to execute. Shipping noise modelling requires spatial discretization in order to group noise sources together using a grid. A uniform grid size is often selected to achieve either the greatest efficiency (i.e. speed of computations) or the greatest accuracy. In contrast, this work aims to produce efficient and accurate noise level predictions by presenting an adaptive grid where cell size varies with distance from the receiver. The spatial range over which a certain cell size is suitable was determined by calculating the distance from the receiver at which propagation loss becomes uniform across a grid cell. The computational efficiency and accuracy of the resulting adaptive grid was tested by comparing it to uniform 1 km and 5 km grids. These represent an accurate and computationally efficient grid respectively. For a case study of the Celtic Sea, an application of the adaptive grid over an area of 160×160 km reduced the number of model executions required from 25600 for a 1 km grid to 5356 in December and to between 5056 and 13132 in August, which represents a 2 to 5-fold increase in efficiency. The 5 km grid reduces the number of model executions further to 1024. However, over the first 25 km the 5 km grid produces errors of up to 13.8 dB when compared to the highly accurate but inefficient 1 km grid. The newly developed adaptive grid generates much smaller errors of less than 0.5 dB while demonstrating high computational efficiency. Our results show that the adaptive grid provides the ability to retain the accuracy of noise level predictions and improve the efficiency of the modelling process. This can help safeguard sensitive marine ecosystems from noise pollution by improving the underwater noise predictions that inform management activities. References Shapiro, G., Chen, F., Thain, R., 2014. The Effect of Ocean Fronts on Acoustic Wave Propagation in a Shallow Sea, Journal of Marine System, 139: 217 - 226. http://dx.doi.org/10.1016/j.jmarsys.2014.06.007.

Landlab: A numerical modeling framework for evolving Earth surfaces from mountains to the coast

NASA Astrophysics Data System (ADS)

Gasparini, N. M.; Adams, J. M.; Tucker, G. E.; Hobley, D. E. J.; Hutton, E.; Istanbulluoglu, E.; Nudurupati, S. S.

2016-02-01

Landlab is an open-source, user-friendly, component-based modeling framework for exploring the evolution of Earth's surface. Landlab itself is not a model. Instead, it is a computational framework that facilitates the development of numerical models of coupled earth surface processes. The Landlab Python library includes a gridding engine and process components, along with support functions for tasks such as reading in DEM data and input variables, setting boundary conditions, and plotting and outputting data. Each user of Landlab builds his or her own unique model. The first step in building a Landlab model is generally initializing a grid, either regular (raster) or irregular (e.g. delaunay or radial), and process components. This initialization process involves reading in relevant parameter values and data. The process components act on the grid to alter grid properties over time. For example, a component exists that can track the growth, death, and succession of vegetation over time. There are also several components that evolve surface elevation, through processes such as fluvial sediment transport and linear diffusion, among others. Users can also build their own process components, taking advantage of existing functions in Landlab such as those that identify grid connectivity and calculate gradients and flux divergence. The general nature of the framework makes it applicable to diverse environments - from bedrock rivers to a pile of sand - and processes acting over a range of spatial and temporal scales. In this poster we illustrate how a user builds a model using Landlab and propose a number of ways in which Landlab can be applied in coastal environments - from dune migration to channelization of barrier islands. We seek input from the coastal community as to how the process component library can be expanded to explore the diverse phenomena that act to shape coastal environments.

Porting plasma physics simulation codes to modern computing architectures using the libmrc framework

NASA Astrophysics Data System (ADS)

Germaschewski, Kai; Abbott, Stephen

2015-11-01

Available computing power has continued to grow exponentially even after single-core performance satured in the last decade. The increase has since been driven by more parallelism, both using more cores and having more parallelism in each core, e.g. in GPUs and Intel Xeon Phi. Adapting existing plasma physics codes is challenging, in particular as there is no single programming model that covers current and future architectures. We will introduce the open-source libmrc framework that has been used to modularize and port three plasma physics codes: The extended MHD code MRCv3 with implicit time integration and curvilinear grids; the OpenGGCM global magnetosphere model; and the particle-in-cell code PSC. libmrc consolidates basic functionality needed for simulations based on structured grids (I/O, load balancing, time integrators), and also introduces a parallel object model that makes it possible to maintain multiple implementations of computational kernels, on e.g. conventional processors and GPUs. It handles data layout conversions and enables us to port performance-critical parts of a code to a new architecture step-by-step, while the rest of the code can remain unchanged. We will show examples of the performance gains and some physics applications.

Using CREAM and CEMonitor for job submission and management in the gLite middleware

NASA Astrophysics Data System (ADS)

Aiftimiei, C.; Andreetto, P.; Bertocco, S.; Dalla Fina, S.; Dorigo, A.; Frizziero, E.; Gianelle, A.; Marzolla, M.; Mazzucato, M.; Mendez Lorenzo, P.; Miccio, V.; Sgaravatto, M.; Traldi, S.; Zangrando, L.

2010-04-01

In this paper we describe the use of CREAM and CEMonitor services for job submission and management within the gLite Grid middleware. Both CREAM and CEMonitor address one of the most fundamental operations of a Grid middleware, that is job submission and management. Specifically, CREAM is a job management service used for submitting, managing and monitoring computational jobs. CEMonitor is an event notification framework, which can be coupled with CREAM to provide the users with asynchronous job status change notifications. Both components have been integrated in the gLite Workload Management System by means of ICE (Interface to CREAM Environment). These software components have been released for production in the EGEE Grid infrastructure and, for what concerns the CEMonitor service, also in the OSG Grid. In this paper we report the current status of these services, the achieved results, and the issues that still have to be addressed.

ESMPy and OpenClimateGIS: Python Interfaces for High Performance Grid Remapping and Geospatial Dataset Manipulation

NASA Astrophysics Data System (ADS)

O'Kuinghttons, Ryan; Koziol, Benjamin; Oehmke, Robert; DeLuca, Cecelia; Theurich, Gerhard; Li, Peggy; Jacob, Joseph

2016-04-01

The Earth System Modeling Framework (ESMF) Python interface (ESMPy) supports analysis and visualization in Earth system modeling codes by providing access to a variety of tools for data manipulation. ESMPy started as a Python interface to the ESMF grid remapping package, which provides mature and robust high-performance and scalable grid remapping between 2D and 3D logically rectangular and unstructured grids and sets of unconnected data. ESMPy now also interfaces with OpenClimateGIS (OCGIS), a package that performs subsetting, reformatting, and computational operations on climate datasets. ESMPy exposes a subset of ESMF grid remapping utilities. This includes bilinear, finite element patch recovery, first-order conservative, and nearest neighbor grid remapping methods. There are also options to ignore unmapped destination points, mask points on source and destination grids, and provide grid structure in the polar regions. Grid remapping on the sphere takes place in 3D Cartesian space, so the pole problem is not an issue as it can be with other grid remapping software. Remapping can be done between any combination of 2D and 3D logically rectangular and unstructured grids with overlapping domains. Grid pairs where one side of the regridding is represented by an appropriate set of unconnected data points, as is commonly found with observational data streams, is also supported. There is a developing interoperability layer between ESMPy and OpenClimateGIS (OCGIS). OCGIS is a pure Python, open source package designed for geospatial manipulation, subsetting, and computation on climate datasets stored in local NetCDF files or accessible remotely via the OPeNDAP protocol. Interfacing with OCGIS has brought GIS-like functionality to ESMPy (i.e. subsetting, coordinate transformations) as well as additional file output formats (i.e. CSV, ESRI Shapefile). ESMPy is distinguished by its strong emphasis on open source, community governance, and distributed development. The user base has grown quickly, and the package is integrating with several other software tools and frameworks. These include the Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT), Iris, PyFerret, cfpython, and the Community Surface Dynamics Modeling System (CSDMS). ESMPy minimum requirements include Python 2.6, Numpy 1.6.1 and an ESMF installation. Optional dependencies include NetCDF and OCGIS-related dependencies: GDAL, Shapely, and Fiona. ESMPy is regression tested nightly, and supported on Darwin, Linux and Cray systems with the GNU compiler suite and MPI communications. OCGIS is supported on Linux, and also undergoes nightly regression testing. Both packages are installable from Anaconda channels. Upcoming development plans for ESMPy involve development of a higher order conservative grid remapping method. Future OCGIS development will focus on mesh and location stream interoperability and streamlined access to ESMPy's MPI implementation.

MeDICi Software Superglue for Data Analysis Pipelines

ScienceCinema

Ian Gorton

2017-12-09

The Middleware for Data-Intensive Computing (MeDICi) Integration Framework is an integrated middleware platform developed to solve data analysis and processing needs of scientists across many domains. MeDICi is scalable, easily modified, and robust to multiple languages, protocols, and hardware platforms, and in use today by PNNL scientists for bioinformatics, power grid failure analysis, and text analysis.

Methods for Computationally Efficient Structured CFD Simulations of Complex Turbomachinery Flows

NASA Technical Reports Server (NTRS)

Herrick, Gregory P.; Chen, Jen-Ping

2012-01-01

This research presents more efficient computational methods by which to perform multi-block structured Computational Fluid Dynamics (CFD) simulations of turbomachinery, thus facilitating higher-fidelity solutions of complicated geometries and their associated flows. This computational framework offers flexibility in allocating resources to balance process count and wall-clock computation time, while facilitating research interests of simulating axial compressor stall inception with more complete gridding of the flow passages and rotor tip clearance regions than is typically practiced with structured codes. The paradigm presented herein facilitates CFD simulation of previously impractical geometries and flows. These methods are validated and demonstrate improved computational efficiency when applied to complicated geometries and flows.

High-Order Methods for Computational Fluid Dynamics: A Brief Review of Compact Differential Formulations on Unstructured Grids

NASA Technical Reports Server (NTRS)

Huynh, H. T.; Wang, Z. J.; Vincent, P. E.

2013-01-01

Popular high-order schemes with compact stencils for Computational Fluid Dynamics (CFD) include Discontinuous Galerkin (DG), Spectral Difference (SD), and Spectral Volume (SV) methods. The recently proposed Flux Reconstruction (FR) approach or Correction Procedure using Reconstruction (CPR) is based on a differential formulation and provides a unifying framework for these high-order schemes. Here we present a brief review of recent developments for the FR/CPR schemes as well as some pacing items.

IceProd 2: A Next Generation Data Analysis Framework for the IceCube Neutrino Observatory

NASA Astrophysics Data System (ADS)

Schultz, D.

2015-12-01

We describe the overall structure and new features of the second generation of IceProd, a data processing and management framework. IceProd was developed by the IceCube Neutrino Observatory for processing of Monte Carlo simulations, detector data, and analysis levels. It runs as a separate layer on top of grid and batch systems. This is accomplished by a set of daemons which process job workflow, maintaining configuration and status information on the job before, during, and after processing. IceProd can also manage complex workflow DAGs across distributed computing grids in order to optimize usage of resources. IceProd is designed to be very light-weight; it runs as a python application fully in user space and can be set up easily. For the initial completion of this second version of IceProd, improvements have been made to increase security, reliability, scalability, and ease of use.

Distributed Accounting on the Grid

NASA Technical Reports Server (NTRS)

Thigpen, William; Hacker, Thomas J.; McGinnis, Laura F.; Athey, Brian D.

2001-01-01

By the late 1990s, the Internet was adequately equipped to move vast amounts of data between HPC (High Performance Computing) systems, and efforts were initiated to link together the national infrastructure of high performance computational and data storage resources together into a general computational utility 'grid', analogous to the national electrical power grid infrastructure. The purpose of the Computational grid is to provide dependable, consistent, pervasive, and inexpensive access to computational resources for the computing community in the form of a computing utility. This paper presents a fully distributed view of Grid usage accounting and a methodology for allocating Grid computational resources for use on a Grid computing system.

Dynamic partitioning as a way to exploit new computing paradigms: the cloud use case.

NASA Astrophysics Data System (ADS)

Ciaschini, Vincenzo; Dal Pra, Stefano; dell'Agnello, Luca

2015-12-01

The WLCG community and many groups in the HEP community have based their computing strategy on the Grid paradigm, which proved successful and still ensures its goals. However, Grid technology has not spread much over other communities; in the commercial world, the cloud paradigm is the emerging way to provide computing services. WLCG experiments aim to achieve integration of their existing current computing model with cloud deployments and take advantage of the so-called opportunistic resources (including HPC facilities) which are usually not Grid compliant. One missing feature in the most common cloud frameworks, is the concept of job scheduler, which plays a key role in a traditional computing centre, by enabling a fairshare based access at the resources to the experiments in a scenario where demand greatly outstrips availability. At CNAF we are investigating the possibility to access the Tier-1 computing resources as an OpenStack based cloud service. The system, exploiting the dynamic partitioning mechanism already being used to enable Multicore computing, allowed us to avoid a static splitting of the computing resources in the Tier-1 farm, while permitting a share friendly approach. The hosts in a dynamically partitioned farm may be moved to or from the partition, according to suitable policies for request and release of computing resources. Nodes being requested in the partition switch their role and become available to play a different one. In the cloud use case hosts may switch from acting as Worker Node in the Batch system farm to cloud compute node member, made available to tenants. In this paper we describe the dynamic partitioning concept, its implementation and integration with our current batch system, LSF.

Semantics-enabled service discovery framework in the SIMDAT pharma grid.

PubMed

Qu, Cangtao; Zimmermann, Falk; Kumpf, Kai; Kamuzinzi, Richard; Ledent, Valérie; Herzog, Robert

2008-03-01

We present the design and implementation of a semantics-enabled service discovery framework in the data Grids for process and product development using numerical simulation and knowledge discovery (SIMDAT) Pharma Grid, an industry-oriented Grid environment for integrating thousands of Grid-enabled biological data services and analysis services. The framework consists of three major components: the Web ontology language (OWL)-description logic (DL)-based biological domain ontology, OWL Web service ontology (OWL-S)-based service annotation, and semantic matchmaker based on the ontology reasoning. Built upon the framework, workflow technologies are extensively exploited in the SIMDAT to assist biologists in (semi)automatically performing in silico experiments. We present a typical usage scenario through the case study of a biological workflow: IXodus.

Facilitating higher-fidelity simulations of axial compressor instability and other turbomachinery flow conditions

NASA Astrophysics Data System (ADS)

Herrick, Gregory Paul

The quest to accurately capture flow phenomena with length-scales both short and long and to accurately represent complex flow phenomena within disparately sized geometry inspires a need for an efficient, high-fidelity, multi-block structured computational fluid dynamics (CFD) parallel computational scheme. This research presents and demonstrates a more efficient computational method by which to perform multi-block structured CFD parallel computational simulations, thus facilitating higher-fidelity solutions of complicated geometries (due to the inclusion of grids for "small'' flow areas which are often merely modeled) and their associated flows. This computational framework offers greater flexibility and user-control in allocating the resource balance between process count and wall-clock computation time. The principal modifications implemented in this revision consist of a "multiple grid block per processing core'' software infrastructure and an analytic computation of viscous flux Jacobians. The development of this scheme is largely motivated by the desire to simulate axial compressor stall inception with more complete gridding of the flow passages (including rotor tip clearance regions) than has been previously done while maintaining high computational efficiency (i.e., minimal consumption of computational resources), and thus this paradigm shall be demonstrated with an examination of instability in a transonic axial compressor. However, the paradigm presented herein facilitates CFD simulation of myriad previously impractical geometries and flows and is not limited to detailed analyses of axial compressor flows. While the simulations presented herein were technically possible under the previous structure of the subject software, they were much less computationally efficient and thus not pragmatically feasible; the previous research using this software to perform three-dimensional, full-annulus, time-accurate, unsteady, full-stage (with sliding-interface) simulations of rotating stall inception in axial compressors utilized tip clearance periodic models, while the scheme here is demonstrated by a simulation of axial compressor stall inception utilizing gridded rotor tip clearance regions. As will be discussed, much previous research---experimental, theoretical, and computational---has suggested that understanding clearance flow behavior is critical to understanding stall inception, and previous computational research efforts which have used tip clearance models have begged the question, "What about the clearance flows?''. This research begins to address that question.

A comparative analysis of dynamic grids vs. virtual grids using the A3pviGrid framework.

PubMed

Shankaranarayanan, Avinas; Amaldas, Christine

2010-11-01

With the proliferation of Quad/Multi-core micro-processors in mainstream platforms such as desktops and workstations; a large number of unused CPU cycles can be utilized for running virtual machines (VMs) as dynamic nodes in distributed environments. Grid services and its service oriented business broker now termed cloud computing could deploy image based virtualization platforms enabling agent based resource management and dynamic fault management. In this paper we present an efficient way of utilizing heterogeneous virtual machines on idle desktops as an environment for consumption of high performance grid services. Spurious and exponential increases in the size of the datasets are constant concerns in medical and pharmaceutical industries due to the constant discovery and publication of large sequence databases. Traditional algorithms are not modeled at handing large data sizes under sudden and dynamic changes in the execution environment as previously discussed. This research was undertaken to compare our previous results with running the same test dataset with that of a virtual Grid platform using virtual machines (Virtualization). The implemented architecture, A3pviGrid utilizes game theoretic optimization and agent based team formation (Coalition) algorithms to improve upon scalability with respect to team formation. Due to the dynamic nature of distributed systems (as discussed in our previous work) all interactions were made local within a team transparently. This paper is a proof of concept of an experimental mini-Grid test-bed compared to running the platform on local virtual machines on a local test cluster. This was done to give every agent its own execution platform enabling anonymity and better control of the dynamic environmental parameters. We also analyze performance and scalability of Blast in a multiple virtual node setup and present our findings. This paper is an extension of our previous research on improving the BLAST application framework using dynamic Grids on virtualization platforms such as the virtual box.

An Open Framework for Low-Latency Communications across the Smart Grid Network

ERIC Educational Resources Information Center

Sturm, John Andrew

2011-01-01

The recent White House (2011) policy paper for the Smart Grid that was released on June 13, 2011, "A Policy Framework for the 21st Century Grid: Enabling Our Secure Energy Future," defines four major problems to be solved and the one that is addressed in this dissertation is Securing the Grid. Securing the Grid is referred to as one of…

Intelligent and robust optimization frameworks for smart grids

NASA Astrophysics Data System (ADS)

Dhansri, Naren Reddy

A smart grid implies a cyberspace real-time distributed power control system to optimally deliver electricity based on varying consumer characteristics. Although smart grids solve many of the contemporary problems, they give rise to new control and optimization problems with the growing role of renewable energy sources such as wind or solar energy. Under highly dynamic nature of distributed power generation and the varying consumer demand and cost requirements, the total power output of the grid should be controlled such that the load demand is met by giving a higher priority to renewable energy sources. Hence, the power generated from renewable energy sources should be optimized while minimizing the generation from non renewable energy sources. This research develops a demand-based automatic generation control and optimization framework for real-time smart grid operations by integrating conventional and renewable energy sources under varying consumer demand and cost requirements. Focusing on the renewable energy sources, the intelligent and robust control frameworks optimize the power generation by tracking the consumer demand in a closed-loop control framework, yielding superior economic and ecological benefits and circumvent nonlinear model complexities and handles uncertainties for superior real-time operations. The proposed intelligent system framework optimizes the smart grid power generation for maximum economical and ecological benefits under an uncertain renewable wind energy source. The numerical results demonstrate that the proposed framework is a viable approach to integrate various energy sources for real-time smart grid implementations. The robust optimization framework results demonstrate the effectiveness of the robust controllers under bounded power plant model uncertainties and exogenous wind input excitation while maximizing economical and ecological performance objectives. Therefore, the proposed framework offers a new worst-case deterministic optimization algorithm for smart grid automatic generation control.

Quality Assurance Framework for Mini-Grids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Esterly, Sean; Baring-Gould, Ian; Booth, Samuel

To address the root challenges of providing quality power to remote consumers through financially viable mini-grids, the Global Lighting and Energy Access Partnership (Global LEAP) initiative of the Clean Energy Ministerial and the U.S. Department of Energy teamed with the National Renewable Energy Laboratory (NREL) and Power Africa to develop a Quality Assurance Framework (QAF) for isolated mini-grids. The framework addresses both alternating current (AC) and direct current (DC) mini-grids, and is applicable to renewable, fossil-fuel, and hybrid systems.

A general gridding, discretization, and coarsening methodology for modeling flow in porous formations with discrete geological features

NASA Astrophysics Data System (ADS)

Karimi-Fard, M.; Durlofsky, L. J.

2016-10-01

A comprehensive framework for modeling flow in porous media containing thin, discrete features, which could be high-permeability fractures or low-permeability deformation bands, is presented. The key steps of the methodology are mesh generation, fine-grid discretization, upscaling, and coarse-grid discretization. Our specialized gridding technique combines a set of intersecting triangulated surfaces by constructing approximate intersections using existing edges. This procedure creates a conforming mesh of all surfaces, which defines the internal boundaries for the volumetric mesh. The flow equations are discretized on this conforming fine mesh using an optimized two-point flux finite-volume approximation. The resulting discrete model is represented by a list of control-volumes with associated positions and pore-volumes, and a list of cell-to-cell connections with associated transmissibilities. Coarse models are then constructed by the aggregation of fine-grid cells, and the transmissibilities between adjacent coarse cells are obtained using flow-based upscaling procedures. Through appropriate computation of fracture-matrix transmissibilities, a dual-continuum representation is obtained on the coarse scale in regions with connected fracture networks. The fine and coarse discrete models generated within the framework are compatible with any connectivity-based simulator. The applicability of the methodology is illustrated for several two- and three-dimensional examples. In particular, we consider gas production from naturally fractured low-permeability formations, and transport through complex fracture networks. In all cases, highly accurate solutions are obtained with significant model reduction.

A Security Monitoring Framework For Virtualization Based HEP Infrastructures

NASA Astrophysics Data System (ADS)

Gomez Ramirez, A.; Martinez Pedreira, M.; Grigoras, C.; Betev, L.; Lara, C.; Kebschull, U.; ALICE Collaboration

2017-10-01

High Energy Physics (HEP) distributed computing infrastructures require automatic tools to monitor, analyze and react to potential security incidents. These tools should collect and inspect data such as resource consumption, logs and sequence of system calls for detecting anomalies that indicate the presence of a malicious agent. They should also be able to perform automated reactions to attacks without administrator intervention. We describe a novel framework that accomplishes these requirements, with a proof of concept implementation for the ALICE experiment at CERN. We show how we achieve a fully virtualized environment that improves the security by isolating services and Jobs without a significant performance impact. We also describe a collected dataset for Machine Learning based Intrusion Prevention and Detection Systems on Grid computing. This dataset is composed of resource consumption measurements (such as CPU, RAM and network traffic), logfiles from operating system services, and system call data collected from production Jobs running in an ALICE Grid test site and a big set of malware samples. This malware set was collected from security research sites. Based on this dataset, we will proceed to develop Machine Learning algorithms able to detect malicious Jobs.

Improving ATLAS grid site reliability with functional tests using HammerCloud

NASA Astrophysics Data System (ADS)

Elmsheuser, Johannes; Legger, Federica; Medrano Llamas, Ramon; Sciacca, Gianfranco; van der Ster, Dan

2012-12-01

With the exponential growth of LHC (Large Hadron Collider) data in 2011, and more coming in 2012, distributed computing has become the established way to analyse collider data. The ATLAS grid infrastructure includes almost 100 sites worldwide, ranging from large national computing centers to smaller university clusters. These facilities are used for data reconstruction and simulation, which are centrally managed by the ATLAS production system, and for distributed user analysis. To ensure the smooth operation of such a complex system, regular tests of all sites are necessary to validate the site capability of successfully executing user and production jobs. We report on the development, optimization and results of an automated functional testing suite using the HammerCloud framework. Functional tests are short lightweight applications covering typical user analysis and production schemes, which are periodically submitted to all ATLAS grid sites. Results from those tests are collected and used to evaluate site performances. Sites that fail or are unable to run the tests are automatically excluded from the PanDA brokerage system, therefore avoiding user or production jobs to be sent to problematic sites.

Grid Task Execution

NASA Technical Reports Server (NTRS)

Hu, Chaumin

2007-01-01

IPG Execution Service is a framework that reliably executes complex jobs on a computational grid, and is part of the IPG service architecture designed to support location-independent computing. The new grid service enables users to describe the platform on which they need a job to run, which allows the service to locate the desired platform, configure it for the required application, and execute the job. After a job is submitted, users can monitor it through periodic notifications, or through queries. Each job consists of a set of tasks that performs actions such as executing applications and managing data. Each task is executed based on a starting condition that is an expression of the states of other tasks. This formulation allows tasks to be executed in parallel, and also allows a user to specify tasks to execute when other tasks succeed, fail, or are canceled. The two core components of the Execution Service are the Task Database, which stores tasks that have been submitted for execution, and the Task Manager, which executes tasks in the proper order, based on the user-specified starting conditions, and avoids overloading local and remote resources while executing tasks.

Autonomic Management of Application Workflows on Hybrid Computing Infrastructure

DOE PAGES

Kim, Hyunjoo; el-Khamra, Yaakoub; Rodero, Ivan; ...

2011-01-01

In this paper, we present a programming and runtime framework that enables the autonomic management of complex application workflows on hybrid computing infrastructures. The framework is designed to address system and application heterogeneity and dynamics to ensure that application objectives and constraints are satisfied. The need for such autonomic system and application management is becoming critical as computing infrastructures become increasingly heterogeneous, integrating different classes of resources from high-end HPC systems to commodity clusters and clouds. For example, the framework presented in this paper can be used to provision the appropriate mix of resources based on application requirements and constraints.more » The framework also monitors the system/application state and adapts the application and/or resources to respond to changing requirements or environment. To demonstrate the operation of the framework and to evaluate its ability, we employ a workflow used to characterize an oil reservoir executing on a hybrid infrastructure composed of TeraGrid nodes and Amazon EC2 instances of various types. Specifically, we show how different applications objectives such as acceleration, conservation and resilience can be effectively achieved while satisfying deadline and budget constraints, using an appropriate mix of dynamically provisioned resources. Our evaluations also demonstrate that public clouds can be used to complement and reinforce the scheduling and usage of traditional high performance computing infrastructure.« less

Considering the Spatial Layout Information of Bag of Features (BoF) Framework for Image Classification.

PubMed

Mu, Guangyu; Liu, Ying; Wang, Limin

2015-01-01

The spatial pooling method such as spatial pyramid matching (SPM) is very crucial in the bag of features model used in image classification. SPM partitions the image into a set of regular grids and assumes that the spatial layout of all visual words obey the uniform distribution over these regular grids. However, in practice, we consider that different visual words should obey different spatial layout distributions. To improve SPM, we develop a novel spatial pooling method, namely spatial distribution pooling (SDP). The proposed SDP method uses an extension model of Gauss mixture model to estimate the spatial layout distributions of the visual vocabulary. For each visual word type, SDP can generate a set of flexible grids rather than the regular grids from the traditional SPM. Furthermore, we can compute the grid weights for visual word tokens according to their spatial coordinates. The experimental results demonstrate that SDP outperforms the traditional spatial pooling methods, and is competitive with the state-of-the-art classification accuracy on several challenging image datasets.

Mapped grid methods for long-range molecules and cold collisions

NASA Astrophysics Data System (ADS)

Willner, K.; Dulieu, O.; Masnou-Seeuws, F.

2004-01-01

The paper discusses ways of improving the accuracy of numerical calculations for vibrational levels of diatomic molecules close to the dissociation limit or for ultracold collisions, in the framework of a grid representation. In order to avoid the implementation of very large grids, Kokoouline et al. [J. Chem. Phys. 110, 9865 (1999)] have proposed a mapping procedure through introduction of an adaptive coordinate x subjected to the variation of the local de Broglie wavelength as a function of the internuclear distance R. Some unphysical levels ("ghosts") then appear in the vibrational series computed via a mapped Fourier grid representation. In the present work the choice of the basis set is reexamined, and two alternative expansions are discussed: Sine functions and Hardy functions. It is shown that use of a basis set with fixed nodes at both grid ends is efficient to eliminate "ghost" solutions. It is further shown that the Hamiltonian matrix in the sine basis can be calculated very accurately by using an auxiliary basis of cosine functions, overcoming the problems arising from numerical calculation of the Jacobian J(x) of the R→x coordinate transformation.

SOMAR-LES: A framework for multi-scale modeling of turbulent stratified oceanic flows

NASA Astrophysics Data System (ADS)

Chalamalla, Vamsi K.; Santilli, Edward; Scotti, Alberto; Jalali, Masoud; Sarkar, Sutanu

2017-12-01

A new multi-scale modeling technique, SOMAR-LES, is presented in this paper. Localized grid refinement gives SOMAR (the Stratified Ocean Model with Adaptive Resolution) access to small scales of the flow which are normally inaccessible to general circulation models (GCMs). SOMAR-LES drives a LES (Large Eddy Simulation) on SOMAR's finest grids, forced with large scale forcing from the coarser grids. Three-dimensional simulations of internal tide generation, propagation and scattering are performed to demonstrate this multi-scale modeling technique. In the case of internal tide generation at a two-dimensional bathymetry, SOMAR-LES is able to balance the baroclinic energy budget and accurately model turbulence losses at only 10% of the computational cost required by a non-adaptive solver running at SOMAR-LES's fine grid resolution. This relative cost is significantly reduced in situations with intermittent turbulence or where the location of the turbulence is not known a priori because SOMAR-LES does not require persistent, global, high resolution. To illustrate this point, we consider a three-dimensional bathymetry with grids adaptively refined along the tidally generated internal waves to capture remote mixing in regions of wave focusing. The computational cost in this case is found to be nearly 25 times smaller than that of a non-adaptive solver at comparable resolution. In the final test case, we consider the scattering of a mode-1 internal wave at an isolated two-dimensional and three-dimensional topography, and we compare the results with Legg (2014) numerical experiments. We find good agreement with theoretical estimates. SOMAR-LES is less dissipative than the closure scheme employed by Legg (2014) near the bathymetry. Depending on the flow configuration and resolution employed, a reduction of more than an order of magnitude in computational costs is expected, relative to traditional existing solvers.

Unstructured Adaptive Grid Computations on an Array of SMPs

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Pramanick, Ira; Sohn, Andrew; Simon, Horst D.

1996-01-01

Dynamic load balancing is necessary for parallel adaptive methods to solve unsteady CFD problems on unstructured grids. We have presented such a dynamic load balancing framework called JOVE, in this paper. Results on a four-POWERnode POWER CHALLENGEarray demonstrated that load balancing gives significant performance improvements over no load balancing for such adaptive computations. The parallel speedup of JOVE, implemented using MPI on the POWER CHALLENCEarray, was significant, being as high as 31 for 32 processors. An implementation of JOVE that exploits 'an array of SMPS' architecture was also studied; this hybrid JOVE outperformed flat JOVE by up to 28% on the meshes and adaption models tested. With large, realistic meshes and actual flow-solver and adaption phases incorporated into JOVE, hybrid JOVE can be expected to yield significant advantage over flat JOVE, especially as the number of processors is increased, thus demonstrating the scalability of an array of SMPs architecture.

Design and Analysis Tool for External-Compression Supersonic Inlets

NASA Technical Reports Server (NTRS)

Slater, John W.

2012-01-01

A computational tool named SUPIN has been developed to design and analyze external-compression supersonic inlets for aircraft at cruise speeds from Mach 1.6 to 2.0. The inlet types available include the axisymmetric outward-turning, two-dimensional single-duct, two-dimensional bifurcated-duct, and streamline-traced Busemann inlets. The aerodynamic performance is characterized by the flow rates, total pressure recovery, and drag. The inlet flowfield is divided into parts to provide a framework for the geometry and aerodynamic modeling and the parts are defined in terms of geometric factors. The low-fidelity aerodynamic analysis and design methods are based on analytic, empirical, and numerical methods which provide for quick analysis. SUPIN provides inlet geometry in the form of coordinates and surface grids useable by grid generation methods for higher-fidelity computational fluid dynamics (CFD) analysis. SUPIN is demonstrated through a series of design studies and CFD analyses were performed to verify some of the analysis results.

Grid cell hexagonal patterns formed by fast self-organized learning within entorhinal cortex.

PubMed

Mhatre, Himanshu; Gorchetchnikov, Anatoli; Grossberg, Stephen

2012-02-01

Grid cells in the dorsal segment of the medial entorhinal cortex (dMEC) show remarkable hexagonal activity patterns, at multiple spatial scales, during spatial navigation. It has previously been shown how a self-organizing map can convert firing patterns across entorhinal grid cells into hippocampal place cells that are capable of representing much larger spatial scales. Can grid cell firing fields also arise during navigation through learning within a self-organizing map? This article describes a simple and general mathematical property of the trigonometry of spatial navigation which favors hexagonal patterns. The article also develops a neural model that can learn to exploit this trigonometric relationship. This GRIDSmap self-organizing map model converts path integration signals into hexagonal grid cell patterns of multiple scales. GRIDSmap creates only grid cell firing patterns with the observed hexagonal structure, predicts how these hexagonal patterns can be learned from experience, and can process biologically plausible neural input and output signals during navigation. These results support an emerging unified computational framework based on a hierarchy of self-organizing maps for explaining how entorhinal-hippocampal interactions support spatial navigation. Copyright © 2010 Wiley Periodicals, Inc.

Knowledge Discovery for Smart Grid Operation, Control, and Situation Awareness -- A Big Data Visualization Platform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gu, Yi; Jiang, Huaiguang; Zhang, Yingchen

In this paper, a big data visualization platform is designed to discover the hidden useful knowledge for smart grid (SG) operation, control and situation awareness. The spawn of smart sensors at both grid side and customer side can provide large volume of heterogeneous data that collect information in all time spectrums. Extracting useful knowledge from this big-data poll is still challenging. In this paper, the Apache Spark, an open source cluster computing framework, is used to process the big-data to effectively discover the hidden knowledge. A high-speed communication architecture utilizing the Open System Interconnection (OSI) model is designed to transmitmore » the data to a visualization platform. This visualization platform uses Google Earth, a global geographic information system (GIS) to link the geological information with the SG knowledge and visualize the information in user defined fashion. The University of Denver's campus grid is used as a SG test bench and several demonstrations are presented for the proposed platform.« less

An Approach for Dynamic Grids

NASA Technical Reports Server (NTRS)

Slater, John W.; Liou, Meng-Sing; Hindman, Richard G.

1994-01-01

An approach is presented for the generation of two-dimensional, structured, dynamic grids. The grid motion may be due to the motion of the boundaries of the computational domain or to the adaptation of the grid to the transient, physical solution. A time-dependent grid is computed through the time integration of the grid speeds which are computed from a system of grid speed equations. The grid speed equations are derived from the time-differentiation of the grid equations so as to ensure that the dynamic grid maintains the desired qualities of the static grid. The grid equations are the Euler-Lagrange equations derived from a variational statement for the grid. The dynamic grid method is demonstrated for a model problem involving boundary motion, an inviscid flow in a converging-diverging nozzle during startup, and a viscous flow over a flat plate with an impinging shock wave. It is shown that the approach is more accurate for transient flows than an approach in which the grid speeds are computed using a finite difference with respect to time of the grid. However, the approach requires significantly more computational effort.

Additional Security Considerations for Grid Management

NASA Technical Reports Server (NTRS)

Eidson, Thomas M.

2003-01-01

The use of Grid computing environments is growing in popularity. A Grid computing environment is primarily a wide area network that encompasses multiple local area networks, where some of the local area networks are managed by different organizations. A Grid computing environment also includes common interfaces for distributed computing software so that the heterogeneous set of machines that make up the Grid can be used more easily. The other key feature of a Grid is that the distributed computing software includes appropriate security technology. The focus of most Grid software is on the security involved with application execution, file transfers, and other remote computing procedures. However, there are other important security issues related to the management of a Grid and the users who use that Grid. This note discusses these additional security issues and makes several suggestions as how they can be managed.

Cloud Computing for the Grid: GridControl: A Software Platform to Support the Smart Grid

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

GENI Project: Cornell University is creating a new software platform for grid operators called GridControl that will utilize cloud computing to more efficiently control the grid. In a cloud computing system, there are minimal hardware and software demands on users. The user can tap into a network of computers that is housed elsewhere (the cloud) and the network runs computer applications for the user. The user only needs interface software to access all of the cloud’s data resources, which can be as simple as a web browser. Cloud computing can reduce costs, facilitate innovation through sharing, empower users, and improvemore » the overall reliability of a dispersed system. Cornell’s GridControl will focus on 4 elements: delivering the state of the grid to users quickly and reliably; building networked, scalable grid-control software; tailoring services to emerging smart grid uses; and simulating smart grid behavior under various conditions.« less

A grid-embedding transonic flow analysis computer program for wing/nacelle configurations

NASA Technical Reports Server (NTRS)

Atta, E. H.; Vadyak, J.

1983-01-01

An efficient grid-interfacing zonal algorithm was developed for computing the three-dimensional transonic flow field about wing/nacelle configurations. the algorithm uses the full-potential formulation and the AF2 approximate factorization scheme. The flow field solution is computed using a component-adaptive grid approach in which separate grids are employed for the individual components in the multi-component configuration, where each component grid is optimized for a particular geometry such as the wing or nacelle. The wing and nacelle component grids are allowed to overlap, and flow field information is transmitted from one grid to another through the overlap region using trivariate interpolation. This report represents a discussion of the computational methods used to generate both the wing and nacelle component grids, the technique used to interface the component grids, and the method used to obtain the inviscid flow solution. Computed results and correlations with experiment are presented. also presented are discussions on the organization of the wing grid generation (GRGEN3) and nacelle grid generation (NGRIDA) computer programs, the grid interface (LK) computer program, and the wing/nacelle flow solution (TWN) computer program. Descriptions of the respective subroutines, definitions of the required input parameters, a discussion on interpretation of the output, and the sample cases illustrating application of the analysis are provided for each of the four computer programs.

A parallel overset-curvilinear-immersed boundary framework for simulating complex 3D incompressible flows

PubMed Central

Borazjani, Iman; Ge, Liang; Le, Trung; Sotiropoulos, Fotis

2013-01-01

We develop an overset-curvilinear immersed boundary (overset-CURVIB) method in a general non-inertial frame of reference to simulate a wide range of challenging biological flow problems. The method incorporates overset-curvilinear grids to efficiently handle multi-connected geometries and increase the resolution locally near immersed boundaries. Complex bodies undergoing arbitrarily large deformations may be embedded within the overset-curvilinear background grid and treated as sharp interfaces using the curvilinear immersed boundary (CURVIB) method (Ge and Sotiropoulos, Journal of Computational Physics, 2007). The incompressible flow equations are formulated in a general non-inertial frame of reference to enhance the overall versatility and efficiency of the numerical approach. Efficient search algorithms to identify areas requiring blanking, donor cells, and interpolation coefficients for constructing the boundary conditions at grid interfaces of the overset grid are developed and implemented using efficient parallel computing communication strategies to transfer information among sub-domains. The governing equations are discretized using a second-order accurate finite-volume approach and integrated in time via an efficient fractional-step method. Various strategies for ensuring globally conservative interpolation at grid interfaces suitable for incompressible flow fractional step methods are implemented and evaluated. The method is verified and validated against experimental data, and its capabilities are demonstrated by simulating the flow past multiple aquatic swimmers and the systolic flow in an anatomic left ventricle with a mechanical heart valve implanted in the aortic position. PMID:23833331

Improving Barotropic Tides by Two-way Nesting High and Low Resolution Domains

NASA Astrophysics Data System (ADS)

Jeon, C. H.; Buijsman, M. C.; Wallcraft, A. J.; Shriver, J. F.; Hogan, P. J.; Arbic, B. K.; Richman, J. G.

2017-12-01

In a realistically forced global ocean model, relatively large sea-surface-height root-mean-square (RMS) errors are observed in the North Atlantic near the Hudson Strait. These may be associated with large tidal resonances interacting with coastal bathymetry that are not correctly represented with a low resolution grid. This issue can be overcome by using high resolution grids, but at a high computational cost. In this paper we apply two-way nesting as an alternative solution. This approach applies high resolution to the area with large RMS errors and a lower resolution to the rest. It is expected to improve the tidal solution as well as reduce the computational cost. To minimize modification of the original source codes of the ocean circulation model (HYCOM), we apply the coupler OASIS3-MCT. This coupler is used to exchange barotropic pressures and velocity fields through its APIs (Application Programming Interface) between the parent and the child components. The developed two-way nesting framework has been validated with an idealized test case where the parent and the child domains have identical grid resolutions. The result of the idealized case shows very small RMS errors between the child and parent solutions. We plan to show results for a case with realistic tidal forcing in which the resolution of the child grid is three times that of the parent grid. The numerical results of this realistic case are compared to TPXO data.

Decomposed multidimensional control grid interpolation for common consumer electronic image processing applications

NASA Astrophysics Data System (ADS)

Zwart, Christine M.; Venkatesan, Ragav; Frakes, David H.

2012-10-01

Interpolation is an essential and broadly employed function of signal processing. Accordingly, considerable development has focused on advancing interpolation algorithms toward optimal accuracy. Such development has motivated a clear shift in the state-of-the art from classical interpolation to more intelligent and resourceful approaches, registration-based interpolation for example. As a natural result, many of the most accurate current algorithms are highly complex, specific, and computationally demanding. However, the diverse hardware destinations for interpolation algorithms present unique constraints that often preclude use of the most accurate available options. For example, while computationally demanding interpolators may be suitable for highly equipped image processing platforms (e.g., computer workstations and clusters), only more efficient interpolators may be practical for less well equipped platforms (e.g., smartphones and tablet computers). The latter examples of consumer electronics present a design tradeoff in this regard: high accuracy interpolation benefits the consumer experience but computing capabilities are limited. It follows that interpolators with favorable combinations of accuracy and efficiency are of great practical value to the consumer electronics industry. We address multidimensional interpolation-based image processing problems that are common to consumer electronic devices through a decomposition approach. The multidimensional problems are first broken down into multiple, independent, one-dimensional (1-D) interpolation steps that are then executed with a newly modified registration-based one-dimensional control grid interpolator. The proposed approach, decomposed multidimensional control grid interpolation (DMCGI), combines the accuracy of registration-based interpolation with the simplicity, flexibility, and computational efficiency of a 1-D interpolation framework. Results demonstrate that DMCGI provides improved interpolation accuracy (and other benefits) in image resizing, color sample demosaicing, and video deinterlacing applications, at a computational cost that is manageable or reduced in comparison to popular alternatives.

A new vertical grid nesting capability in the Weather Research and Forecasting (WRF) Model

DOE PAGES

Daniels, Megan H.; Lundquist, Katherine A.; Mirocha, Jeffrey D.; ...

2016-09-16

Mesoscale atmospheric models are increasingly used for high-resolution (<3 km) simulations to better resolve smaller-scale flow details. Increased resolution is achieved using mesh refinement via grid nesting, a procedure where multiple computational domains are integrated either concurrently or in series. A constraint in the concurrent nesting framework offered by the Weather Research and Forecasting (WRF) Model is that mesh refinement is restricted to the horizontal dimensions. This limitation prevents control of the grid aspect ratio, leading to numerical errors due to poor grid quality and preventing grid optimization. Here, a procedure permitting vertical nesting for one-way concurrent simulation is developedmore » and validated through idealized cases. The benefits of vertical nesting are demonstrated using both mesoscale and large-eddy simulations (LES). Mesoscale simulations of the Terrain-Induced Rotor Experiment (T-REX) show that vertical grid nesting can alleviate numerical errors due to large aspect ratios on coarse grids, while allowing for higher vertical resolution on fine grids. Furthermore, the coarsening of the parent domain does not result in a significant loss of accuracy on the nested domain. LES of neutral boundary layer flow shows that, by permitting optimal grid aspect ratios on both parent and nested domains, use of vertical nesting yields improved agreement with the theoretical logarithmic velocity profile on both domains. Lastly, vertical grid nesting in WRF opens the path forward for multiscale simulations, allowing more accurate simulations spanning a wider range of scales than previously possible.« less

A new vertical grid nesting capability in the Weather Research and Forecasting (WRF) Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daniels, Megan H.; Lundquist, Katherine A.; Mirocha, Jeffrey D.

Mesoscale atmospheric models are increasingly used for high-resolution (<3 km) simulations to better resolve smaller-scale flow details. Increased resolution is achieved using mesh refinement via grid nesting, a procedure where multiple computational domains are integrated either concurrently or in series. A constraint in the concurrent nesting framework offered by the Weather Research and Forecasting (WRF) Model is that mesh refinement is restricted to the horizontal dimensions. This limitation prevents control of the grid aspect ratio, leading to numerical errors due to poor grid quality and preventing grid optimization. Here, a procedure permitting vertical nesting for one-way concurrent simulation is developedmore » and validated through idealized cases. The benefits of vertical nesting are demonstrated using both mesoscale and large-eddy simulations (LES). Mesoscale simulations of the Terrain-Induced Rotor Experiment (T-REX) show that vertical grid nesting can alleviate numerical errors due to large aspect ratios on coarse grids, while allowing for higher vertical resolution on fine grids. Furthermore, the coarsening of the parent domain does not result in a significant loss of accuracy on the nested domain. LES of neutral boundary layer flow shows that, by permitting optimal grid aspect ratios on both parent and nested domains, use of vertical nesting yields improved agreement with the theoretical logarithmic velocity profile on both domains. Lastly, vertical grid nesting in WRF opens the path forward for multiscale simulations, allowing more accurate simulations spanning a wider range of scales than previously possible.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Babun, Leonardo; Aksu, Hidayet; Uluagac, A. Selcuk

The core vision of the smart grid concept is the realization of reliable two-­way communications between smart devices (e.g., IEDs, PLCs, PMUs). The benefits of the smart grid also come with tremendous security risks and new challenges in protecting the smart grid systems from cyber threats. Particularly, the use of untrusted counterfeit smart grid devices represents a real problem. Consequences of propagating false or malicious data, as well as stealing valuable user or smart grid state information from counterfeit devices are costly. Hence, early detection of counterfeit devices is critical for protecting smart grid’s components and users. To address thesemore » concerns, in this poster, we introduce our initial design of a configurable framework that utilize system call tracing, library interposition, and statistical techniques for monitoring and detection of counterfeit smart grid devices. In our framework, we consider six different counterfeit device scenarios with different smart grid devices and adversarial seZings. Our initial results on a realistic testbed utilizing actual smart-­grid GOOSE messages with IEC-­61850 communication protocol are very promising. Our framework is showing excellent rates on detection of smart grid counterfeit devices from impostors.« less

Trial Implementation of a Multihazard Risk Assessment Framework for High-Impact Low-Frequency Power Grid Events

DOE Office of Scientific and Technical Information (OSTI.GOV)

Veeramany, Arun; Coles, Garill A.; Unwin, Stephen D.

The Pacific Northwest National Laboratory developed a risk framework for modeling high-impact, low-frequency power grid events to support risk-informed decisions. In this paper, we briefly recap the framework and demonstrate its implementation for seismic and geomagnetic hazards using a benchmark reliability test system. We describe integration of a collection of models implemented to perform hazard analysis, fragility evaluation, consequence estimation, and postevent restoration. We demonstrate the value of the framework as a multihazard power grid risk assessment and management tool. As a result, the research will benefit transmission planners and emergency planners by improving their ability to maintain a resilientmore » grid infrastructure against impacts from major events.« less

Trial Implementation of a Multihazard Risk Assessment Framework for High-Impact Low-Frequency Power Grid Events

DOE PAGES

Veeramany, Arun; Coles, Garill A.; Unwin, Stephen D.; ...

2017-08-25

The Pacific Northwest National Laboratory developed a risk framework for modeling high-impact, low-frequency power grid events to support risk-informed decisions. In this paper, we briefly recap the framework and demonstrate its implementation for seismic and geomagnetic hazards using a benchmark reliability test system. We describe integration of a collection of models implemented to perform hazard analysis, fragility evaluation, consequence estimation, and postevent restoration. We demonstrate the value of the framework as a multihazard power grid risk assessment and management tool. As a result, the research will benefit transmission planners and emergency planners by improving their ability to maintain a resilientmore » grid infrastructure against impacts from major events.« less

Distributed intrusion detection system based on grid security model

NASA Astrophysics Data System (ADS)

Su, Jie; Liu, Yahui

2008-03-01

Grid computing has developed rapidly with the development of network technology and it can solve the problem of large-scale complex computing by sharing large-scale computing resource. In grid environment, we can realize a distributed and load balance intrusion detection system. This paper first discusses the security mechanism in grid computing and the function of PKI/CA in the grid security system, then gives the application of grid computing character in the distributed intrusion detection system (IDS) based on Artificial Immune System. Finally, it gives a distributed intrusion detection system based on grid security system that can reduce the processing delay and assure the detection rates.

Evolution of the ATLAS distributed computing system during the LHC long shutdown

NASA Astrophysics Data System (ADS)

Campana, S.; Atlas Collaboration

2014-06-01

The ATLAS Distributed Computing project (ADC) was established in 2007 to develop and operate a framework, following the ATLAS computing model, to enable data storage, processing and bookkeeping on top of the Worldwide LHC Computing Grid (WLCG) distributed infrastructure. ADC development has always been driven by operations and this contributed to its success. The system has fulfilled the demanding requirements of ATLAS, daily consolidating worldwide up to 1 PB of data and running more than 1.5 million payloads distributed globally, supporting almost one thousand concurrent distributed analysis users. Comprehensive automation and monitoring minimized the operational manpower required. The flexibility of the system to adjust to operational needs has been important to the success of the ATLAS physics program. The LHC shutdown in 2013-2015 affords an opportunity to improve the system in light of operational experience and scale it to cope with the demanding requirements of 2015 and beyond, most notably a much higher trigger rate and event pileup. We will describe the evolution of the ADC software foreseen during this period. This includes consolidating the existing Production and Distributed Analysis framework (PanDA) and ATLAS Grid Information System (AGIS), together with the development and commissioning of next generation systems for distributed data management (DDM/Rucio) and production (Prodsys-2). We will explain how new technologies such as Cloud Computing and NoSQL databases, which ATLAS investigated as R&D projects in past years, will be integrated in production. Finally, we will describe more fundamental developments such as breaking job-to-data locality by exploiting storage federations and caches, and event level (rather than file or dataset level) workload engines.

Discrete Adjoint-Based Design for Unsteady Turbulent Flows On Dynamic Overset Unstructured Grids

NASA Technical Reports Server (NTRS)

Nielsen, Eric J.; Diskin, Boris

2012-01-01

A discrete adjoint-based design methodology for unsteady turbulent flows on three-dimensional dynamic overset unstructured grids is formulated, implemented, and verified. The methodology supports both compressible and incompressible flows and is amenable to massively parallel computing environments. The approach provides a general framework for performing highly efficient and discretely consistent sensitivity analysis for problems involving arbitrary combinations of overset unstructured grids which may be static, undergoing rigid or deforming motions, or any combination thereof. General parent-child motions are also accommodated, and the accuracy of the implementation is established using an independent verification based on a complex-variable approach. The methodology is used to demonstrate aerodynamic optimizations of a wind turbine geometry, a biologically-inspired flapping wing, and a complex helicopter configuration subject to trimming constraints. The objective function for each problem is successfully reduced and all specified constraints are satisfied.

A Cartesian grid approach with hierarchical refinement for compressible flows

NASA Technical Reports Server (NTRS)

Quirk, James J.

1994-01-01

Many numerical studies of flows that involve complex geometries are limited by the difficulties in generating suitable grids. We present a Cartesian boundary scheme for two-dimensional, compressible flows that is unfettered by the need to generate a computational grid and so it may be used, routinely, even for the most awkward of geometries. In essence, an arbitrary-shaped body is allowed to blank out some region of a background Cartesian mesh and the resultant cut-cells are singled out for special treatment. This is done within a finite-volume framework and so, in principle, any explicit flux-based integration scheme can take advantage of this method for enforcing solid boundary conditions. For best effect, the present Cartesian boundary scheme has been combined with a sophisticated, local mesh refinement scheme, and a number of examples are shown in order to demonstrate the efficacy of the combined algorithm for simulations of shock interaction phenomena.

PyMT: A Python package for model-coupling in the Earth sciences

NASA Astrophysics Data System (ADS)

Hutton, E.

2016-12-01

The current landscape of Earth-system models is not only broad in scientific scope, but also broad in type. On the one hand, the large variety of models is exciting, as it provides fertile ground for extending or linking models together in novel ways to answer new scientific questions. However, the heterogeneity in model type acts to inhibit model coupling, model development, or even model use. Existing models are written in a variety of programming languages, operate on different grids, use their own file formats (both for input and output), have different user interfaces, have their own time steps, etc. Each of these factors become obstructions to scientists wanting to couple, extend - or simply run - existing models. For scientists whose main focus may not be computer science these barriers become even larger and become significant logistical hurdles. And this is all before the scientific difficulties of coupling or running models are addressed. The CSDMS Python Modeling Toolkit (PyMT) was developed to help non-computer scientists deal with these sorts of modeling logistics. PyMT is the fundamental package the Community Surface Dynamics Modeling System uses for the coupling of models that expose the Basic Modeling Interface (BMI). It contains: Tools necessary for coupling models of disparate time and space scales (including grid mappers) Time-steppers that coordinate the sequencing of coupled models Exchange of data between BMI-enabled models Wrappers that automatically load BMI-enabled models into the PyMT framework Utilities that support open-source interfaces (UGRID, SGRID,CSDMS Standard Names, etc.) A collection of community-submitted models, written in a variety of programminglanguages, from a variety of process domains - but all usable from within the Python programming language A plug-in framework for adding additional BMI-enabled models to the framework In this presentation we intoduce the basics of the PyMT as well as provide an example of coupling models of different domains and grid types.

Statistical Analysis of CFD Solutions from the Fourth AIAA Drag Prediction Workshop

NASA Technical Reports Server (NTRS)

Morrison, Joseph H.

2010-01-01

A graphical framework is used for statistical analysis of the results from an extensive N-version test of a collection of Reynolds-averaged Navier-Stokes computational fluid dynamics codes. The solutions were obtained by code developers and users from the U.S., Europe, Asia, and Russia using a variety of grid systems and turbulence models for the June 2009 4th Drag Prediction Workshop sponsored by the AIAA Applied Aerodynamics Technical Committee. The aerodynamic configuration for this workshop was a new subsonic transport model, the Common Research Model, designed using a modern approach for the wing and included a horizontal tail. The fourth workshop focused on the prediction of both absolute and incremental drag levels for wing-body and wing-body-horizontal tail configurations. This work continues the statistical analysis begun in the earlier workshops and compares the results from the grid convergence study of the most recent workshop with earlier workshops using the statistical framework.

High-Throughput Characterization of Porous Materials Using Graphics Processing Units

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Jihan; Martin, Richard L.; Rübel, Oliver

We have developed a high-throughput graphics processing units (GPU) code that can characterize a large database of crystalline porous materials. In our algorithm, the GPU is utilized to accelerate energy grid calculations where the grid values represent interactions (i.e., Lennard-Jones + Coulomb potentials) between gas molecules (i.e., CHmore » $$_{4}$$ and CO$$_{2}$$) and material's framework atoms. Using a parallel flood fill CPU algorithm, inaccessible regions inside the framework structures are identified and blocked based on their energy profiles. Finally, we compute the Henry coefficients and heats of adsorption through statistical Widom insertion Monte Carlo moves in the domain restricted to the accessible space. The code offers significant speedup over a single core CPU code and allows us to characterize a set of porous materials at least an order of magnitude larger than ones considered in earlier studies. For structures selected from such a prescreening algorithm, full adsorption isotherms can be calculated by conducting multiple grand canonical Monte Carlo simulations concurrently within the GPU.« less

A nominally second-order cell-centered Lagrangian scheme for simulating elastic-plastic flows on two-dimensional unstructured grids

NASA Astrophysics Data System (ADS)

Maire, Pierre-Henri; Abgrall, Rémi; Breil, Jérôme; Loubère, Raphaël; Rebourcet, Bernard

2013-02-01

In this paper, we describe a cell-centered Lagrangian scheme devoted to the numerical simulation of solid dynamics on two-dimensional unstructured grids in planar geometry. This numerical method, utilizes the classical elastic-perfectly plastic material model initially proposed by Wilkins [M.L. Wilkins, Calculation of elastic-plastic flow, Meth. Comput. Phys. (1964)]. In this model, the Cauchy stress tensor is decomposed into the sum of its deviatoric part and the thermodynamic pressure which is defined by means of an equation of state. Regarding the deviatoric stress, its time evolution is governed by a classical constitutive law for isotropic material. The plasticity model employs the von Mises yield criterion and is implemented by means of the radial return algorithm. The numerical scheme relies on a finite volume cell-centered method wherein numerical fluxes are expressed in terms of sub-cell force. The generic form of the sub-cell force is obtained by requiring the scheme to satisfy a semi-discrete dissipation inequality. Sub-cell force and nodal velocity to move the grid are computed consistently with cell volume variation by means of a node-centered solver, which results from total energy conservation. The nominally second-order extension is achieved by developing a two-dimensional extension in the Lagrangian framework of the Generalized Riemann Problem methodology, introduced by Ben-Artzi and Falcovitz [M. Ben-Artzi, J. Falcovitz, Generalized Riemann Problems in Computational Fluid Dynamics, Cambridge Monogr. Appl. Comput. Math. (2003)]. Finally, the robustness and the accuracy of the numerical scheme are assessed through the computation of several test cases.

Setting Up a Grid-CERT: Experiences of an Academic CSIRT

ERIC Educational Resources Information Center

Moller, Klaus

2007-01-01

Purpose: Grid computing has often been heralded as the next logical step after the worldwide web. Users of grids can access dynamic resources such as computer storage and use the computing resources of computers under the umbrella of a virtual organisation. Although grid computing is often compared to the worldwide web, it is vastly more complex…

Validation of a Pressure-Based Combustion Simulation Tool Using a Single Element Injector Test Problem

NASA Technical Reports Server (NTRS)

Thakur, Siddarth; Wright, Jeffrey

2006-01-01

The traditional design and analysis practice for advanced propulsion systems, particularly chemical rocket engines, relies heavily on expensive full-scale prototype development and testing. Over the past decade, use of high-fidelity analysis and design tools such as CFD early in the product development cycle has been identified as one way to alleviate testing costs and to develop these devices better, faster and cheaper. Increased emphasis is being placed on developing and applying CFD models to simulate the flow field environments and performance of advanced propulsion systems. This necessitates the development of next generation computational tools which can be used effectively and reliably in a design environment by non-CFD specialists. A computational tool, called Loci-STREAM is being developed for this purpose. It is a pressure-based, Reynolds-averaged Navier-Stokes (RANS) solver for generalized unstructured grids, which is designed to handle all-speed flows (incompressible to hypersonic) and is particularly suitable for solving multi-species flow in fixed-frame combustion devices. Loci-STREAM integrates proven numerical methods for generalized grids and state-of-the-art physical models in a novel rule-based programming framework called Loci which allows: (a) seamless integration of multidisciplinary physics in a unified manner, and (b) automatic handling of massively parallel computing. The objective of the ongoing work is to develop a robust simulation capability for combustion problems in rocket engines. As an initial step towards validating this capability, a model problem is investigated in the present study which involves a gaseous oxygen/gaseous hydrogen (GO2/GH2) shear coaxial single element injector, for which experimental data are available. The sensitivity of the computed solutions to grid density, grid distribution, different turbulence models, and different near-wall treatments is investigated. A refined grid, which is clustered in the vicinity of the solid walls as well as the flame, is used to obtain a steady state solution which may be considered as the best solution attainable with the steady-state RANS methodology. From a design point of view, quick turnaround times are desirable; with this in mind, coarser grids are also employed and the resulting solutions are evaluated with respect to the fine grid solution.

A Three-Dimensional Parallel Time-Accurate Turbopump Simulation Procedure Using Overset Grid System

NASA Technical Reports Server (NTRS)

Kiris, Cetin; Chan, William; Kwak, Dochan

2002-01-01

The objective of the current effort is to provide a computational framework for design and analysis of the entire fuel supply system of a liquid rocket engine, including high-fidelity unsteady turbopump flow analysis. This capability is needed to support the design of pump sub-systems for advanced space transportation vehicles that are likely to involve liquid propulsion systems. To date, computational tools for design/analysis of turbopump flows are based on relatively lower fidelity methods. An unsteady, three-dimensional viscous flow analysis tool involving stationary and rotational components for the entire turbopump assembly has not been available for real-world engineering applications. The present effort provides developers with information such as transient flow phenomena at start up, and nonuniform inflows, and will eventually impact on system vibration and structures. In the proposed paper, the progress toward the capability of complete simulation of the turbo-pump for a liquid rocket engine is reported. The Space Shuttle Main Engine (SSME) turbo-pump is used as a test case for evaluation of the hybrid MPI/Open-MP and MLP versions of the INS3D code. CAD to solution auto-scripting capability is being developed for turbopump applications. The relative motion of the grid systems for the rotor-stator interaction was obtained using overset grid techniques. Unsteady computations for the SSME turbo-pump, which contains 114 zones with 34.5 million grid points, are carried out on Origin 3000 systems at NASA Ames Research Center. Results from these time-accurate simulations with moving boundary capability are presented along with the performance of parallel versions of the code.

Integration of Grid and Sensor Web for Flood Monitoring and Risk Assessment from Heterogeneous Data

NASA Astrophysics Data System (ADS)

Kussul, Nataliia; Skakun, Sergii; Shelestov, Andrii

2013-04-01

Over last decades we have witnessed the upward global trend in natural disaster occurrence. Hydrological and meteorological disasters such as floods are the main contributors to this pattern. In recent years flood management has shifted from protection against floods to managing the risks of floods (the European Flood risk directive). In order to enable operational flood monitoring and assessment of flood risk, it is required to provide an infrastructure with standardized interfaces and services. Grid and Sensor Web can meet these requirements. In this paper we present a general approach to flood monitoring and risk assessment based on heterogeneous geospatial data acquired from multiple sources. To enable operational flood risk assessment integration of Grid and Sensor Web approaches is proposed [1]. Grid represents a distributed environment that integrates heterogeneous computing and storage resources administrated by multiple organizations. SensorWeb is an emerging paradigm for integrating heterogeneous satellite and in situ sensors and data systems into a common informational infrastructure that produces products on demand. The basic Sensor Web functionality includes sensor discovery, triggering events by observed or predicted conditions, remote data access and processing capabilities to generate and deliver data products. Sensor Web is governed by the set of standards, called Sensor Web Enablement (SWE), developed by the Open Geospatial Consortium (OGC). Different practical issues regarding integration of Sensor Web with Grids are discussed in the study. We show how the Sensor Web can benefit from using Grids and vice versa. For example, Sensor Web services such as SOS, SPS and SAS can benefit from the integration with the Grid platform like Globus Toolkit. The proposed approach is implemented within the Sensor Web framework for flood monitoring and risk assessment, and a case-study of exploiting this framework, namely the Namibia SensorWeb Pilot Project, is described. The project was created as a testbed for evaluating and prototyping key technologies for rapid acquisition and distribution of data products for decision support systems to monitor floods and enable flood risk assessment. The system provides access to real-time products on rainfall estimates and flood potential forecast derived from the Tropical Rainfall Measuring Mission (TRMM) mission with lag time of 6 h, alerts from the Global Disaster Alert and Coordination System (GDACS) with lag time of 4 h, and the Coupled Routing and Excess STorage (CREST) model to generate alerts. These are alerts are used to trigger satellite observations. With deployed SPS service for NASA's EO-1 satellite it is possible to automatically task sensor with re-image capability of less 8 h. Therefore, with enabled computational and storage services provided by Grid and cloud infrastructure it was possible to generate flood maps within 24-48 h after trigger was alerted. To enable interoperability between system components and services OGC-compliant standards are utilized. [1] Hluchy L., Kussul N., Shelestov A., Skakun S., Kravchenko O., Gripich Y., Kopp P., Lupian E., "The Data Fusion Grid Infrastructure: Project Objectives and Achievements," Computing and Informatics, 2010, vol. 29, no. 2, pp. 319-334.

Kwf-Grid workflow management system for Earth science applications

NASA Astrophysics Data System (ADS)

Tran, V.; Hluchy, L.

2009-04-01

In this paper, we present workflow management tool for Earth science applications in EGEE. The workflow management tool was originally developed within K-wf Grid project for GT4 middleware and has many advanced features like semi-automatic workflow composition, user-friendly GUI for managing workflows, knowledge management. In EGEE, we are porting the workflow management tool to gLite middleware for Earth science applications K-wf Grid workflow management system was developed within "Knowledge-based Workflow System for Grid Applications" under the 6th Framework Programme. The workflow mangement system intended to - semi-automatically compose a workflow of Grid services, - execute the composed workflow application in a Grid computing environment, - monitor the performance of the Grid infrastructure and the Grid applications, - analyze the resulting monitoring information, - capture the knowledge that is contained in the information by means of intelligent agents, - and finally to reuse the joined knowledge gathered from all participating users in a collaborative way in order to efficiently construct workflows for new Grid applications. Kwf Grid workflow engines can support different types of jobs (e.g. GRAM job, web services) in a workflow. New class of gLite job has been added to the system, allows system to manage and execute gLite jobs in EGEE infrastructure. The GUI has been adapted to the requirements of EGEE users, new credential management servlet is added to portal. Porting K-wf Grid workflow management system to gLite would allow EGEE users to use the system and benefit from its avanced features. The system is primarly tested and evaluated with applications from ES clusters.

Proposal for grid computing for nuclear applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Idris, Faridah Mohamad; Ismail, Saaidi; Haris, Mohd Fauzi B.

2014-02-12

The use of computer clusters for computational sciences including computational physics is vital as it provides computing power to crunch big numbers at a faster rate. In compute intensive applications that requires high resolution such as Monte Carlo simulation, the use of computer clusters in a grid form that supplies computational power to any nodes within the grid that needs computing power, has now become a necessity. In this paper, we described how the clusters running on a specific application could use resources within the grid, to run the applications to speed up the computing process.

Assessment of Preconditioner for a USM3D Hierarchical Adaptive Nonlinear Method (HANIM) (Invited)

NASA Technical Reports Server (NTRS)

Pandya, Mohagna J.; Diskin, Boris; Thomas, James L.; Frink, Neal T.

2016-01-01

Enhancements to the previously reported mixed-element USM3D Hierarchical Adaptive Nonlinear Iteration Method (HANIM) framework have been made to further improve robustness, efficiency, and accuracy of computational fluid dynamic simulations. The key enhancements include a multi-color line-implicit preconditioner, a discretely consistent symmetry boundary condition, and a line-mapping method for the turbulence source term discretization. The USM3D iterative convergence for the turbulent flows is assessed on four configurations. The configurations include a two-dimensional (2D) bump-in-channel, the 2D NACA 0012 airfoil, a three-dimensional (3D) bump-in-channel, and a 3D hemisphere cylinder. The Reynolds Averaged Navier Stokes (RANS) solutions have been obtained using a Spalart-Allmaras turbulence model and families of uniformly refined nested grids. Two types of HANIM solutions using line- and point-implicit preconditioners have been computed. Additional solutions using the point-implicit preconditioner alone (PA) method that broadly represents the baseline solver technology have also been computed. The line-implicit HANIM shows superior iterative convergence in most cases with progressively increasing benefits on finer grids.

SUPIN: A Computational Tool for Supersonic Inlet Design

NASA Technical Reports Server (NTRS)

Slater, John W.

2016-01-01

A computational tool named SUPIN is being developed to design and analyze the aerodynamic performance of supersonic inlets. The inlet types available include the axisymmetric pitot, three-dimensional pitot, axisymmetric outward-turning, two-dimensional single-duct, two-dimensional bifurcated-duct, and streamline-traced inlets. The aerodynamic performance is characterized by the flow rates, total pressure recovery, and drag. The inlet flow-field is divided into parts to provide a framework for the geometry and aerodynamic modeling. Each part of the inlet is defined in terms of geometric factors. The low-fidelity aerodynamic analysis and design methods are based on analytic, empirical, and numerical methods which provide for quick design and analysis. SUPIN provides inlet geometry in the form of coordinates, surface angles, and cross-sectional areas. SUPIN can generate inlet surface grids and three-dimensional, structured volume grids for use with higher-fidelity computational fluid dynamics (CFD) analysis. Capabilities highlighted in this paper include the design and analysis of streamline-traced external-compression inlets, modeling of porous bleed, and the design and analysis of mixed-compression inlets. CFD analyses are used to verify the SUPIN results.

Numerical investigation of interactions between marine atmospheric boundary layer and offshore wind farm

NASA Astrophysics Data System (ADS)

Lyu, Pin; Chen, Wenli; Li, Hui; Shen, Lian

2017-11-01

In recent studies, Yang, Meneveau & Shen (Physics of Fluids, 2014; Renewable Energy, 2014) developed a hybrid numerical framework for simulation of offshore wind farm. The framework consists of simulation of nonlinear surface waves using a high-order spectral method, large-eddy simulation of wind turbulence on a wave-surface-fitted curvilinear grid, and an actuator disk model for wind turbines. In the present study, several more precise wind turbine models, including the actuator line model, actuator disk model with rotation, and nacelle model, are introduced into the computation. Besides offshore wind turbines on fixed piles, the new computational framework has the capability to investigate the interaction among wind, waves, and floating wind turbines. In this study, onshore, offshore fixed pile, and offshore floating wind farms are compared in terms of flow field statistics and wind turbine power extraction rate. The authors gratefully acknowledge financial support from China Scholarship Council (No. 201606120186) and the Institute on the Environment of University of Minnesota.

eScience for molecular-scale simulations and the eMinerals project.

PubMed

Salje, E K H; Artacho, E; Austen, K F; Bruin, R P; Calleja, M; Chappell, H F; Chiang, G-T; Dove, M T; Frame, I; Goodwin, A L; Kleese van Dam, K; Marmier, A; Parker, S C; Pruneda, J M; Todorov, I T; Trachenko, K; Tyer, R P; Walker, A M; White, T O H

2009-03-13

We review the work carried out within the eMinerals project to develop eScience solutions that facilitate a new generation of molecular-scale simulation work. Technological developments include integration of compute and data systems, developing of collaborative frameworks and new researcher-friendly tools for grid job submission, XML data representation, information delivery, metadata harvesting and metadata management. A number of diverse science applications will illustrate how these tools are being used for large parameter-sweep studies, an emerging type of study for which the integration of computing, data and collaboration is essential.

Dose calculation algorithm of fast fine-heterogeneity correction for heavy charged particle radiotherapy.

PubMed

Kanematsu, Nobuyuki

2011-04-01

This work addresses computing techniques for dose calculations in treatment planning with proton and ion beams, based on an efficient kernel-convolution method referred to as grid-dose spreading (GDS) and accurate heterogeneity-correction method referred to as Gaussian beam splitting. The original GDS algorithm suffered from distortion of dose distribution for beams tilted with respect to the dose-grid axes. Use of intermediate grids normal to the beam field has solved the beam-tilting distortion. Interplay of arrangement between beams and grids was found as another intrinsic source of artifact. Inclusion of rectangular-kernel convolution in beam transport, to share the beam contribution among the nearest grids in a regulatory manner, has solved the interplay problem. This algorithmic framework was applied to a tilted proton pencil beam and a broad carbon-ion beam. In these cases, while the elementary pencil beams individually split into several tens, the calculation time increased only by several times with the GDS algorithm. The GDS and beam-splitting methods will complementarily enable accurate and efficient dose calculations for radiotherapy with protons and ions. Copyright © 2010 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Vanderbilt University Institute of Imaging Science Center for Computational Imaging XNAT: A multimodal data archive and processing environment.

PubMed

Harrigan, Robert L; Yvernault, Benjamin C; Boyd, Brian D; Damon, Stephen M; Gibney, Kyla David; Conrad, Benjamin N; Phillips, Nicholas S; Rogers, Baxter P; Gao, Yurui; Landman, Bennett A

2016-01-01

The Vanderbilt University Institute for Imaging Science (VUIIS) Center for Computational Imaging (CCI) has developed a database built on XNAT housing over a quarter of a million scans. The database provides framework for (1) rapid prototyping, (2) large scale batch processing of images and (3) scalable project management. The system uses the web-based interfaces of XNAT and REDCap to allow for graphical interaction. A python middleware layer, the Distributed Automation for XNAT (DAX) package, distributes computation across the Vanderbilt Advanced Computing Center for Research and Education high performance computing center. All software are made available in open source for use in combining portable batch scripting (PBS) grids and XNAT servers. Copyright © 2015 Elsevier Inc. All rights reserved.

Refinement Of Hexahedral Cells In Euler Flow Computations

NASA Technical Reports Server (NTRS)

Melton, John E.; Cappuccio, Gelsomina; Thomas, Scott D.

1996-01-01

Topologically Independent Grid, Euler Refinement (TIGER) computer program solves Euler equations of three-dimensional, unsteady flow of inviscid, compressible fluid by numerical integration on unstructured hexahedral coordinate grid refined where necessary to resolve shocks and other details. Hexahedral cells subdivided, each into eight smaller cells, as needed to refine computational grid in regions of high flow gradients. Grid Interactive Refinement and Flow-Field Examination (GIRAFFE) computer program written in conjunction with TIGER program to display computed flow-field data and to assist researcher in verifying specified boundary conditions and refining grid.

Tempest: Tools for Addressing the Needs of Next-Generation Climate Models

NASA Astrophysics Data System (ADS)

Ullrich, P. A.; Guerra, J. E.; Pinheiro, M. C.; Fong, J.

2015-12-01

Tempest is a comprehensive simulation-to-science infrastructure that tackles the needs of next-generation, high-resolution, data intensive climate modeling activities. This project incorporates three key components: TempestDynamics, a global modeling framework for experimental numerical methods and high-performance computing; TempestRemap, a toolset for arbitrary-order conservative and consistent remapping between unstructured grids; and TempestExtremes, a suite of detection and characterization tools for identifying weather extremes in large climate datasets. In this presentation, the latest advances with the implementation of this framework will be discussed, and a number of projects now utilizing these tools will be featured.

System design and implementation of digital-image processing using computational grids

NASA Astrophysics Data System (ADS)

Shen, Zhanfeng; Luo, Jiancheng; Zhou, Chenghu; Huang, Guangyu; Ma, Weifeng; Ming, Dongping

2005-06-01

As a special type of digital image, remotely sensed images are playing increasingly important roles in our daily lives. Because of the enormous amounts of data involved, and the difficulties of data processing and transfer, an important issue for current computer and geo-science experts is developing internet technology to implement rapid remotely sensed image processing. Computational grids are able to solve this problem effectively. These networks of computer workstations enable the sharing of data and resources, and are used by computer experts to solve imbalances of network resources and lopsided usage. In China, computational grids combined with spatial-information-processing technology have formed a new technology: namely, spatial-information grids. In the field of remotely sensed images, spatial-information grids work more effectively for network computing, data processing, resource sharing, task cooperation and so on. This paper focuses mainly on the application of computational grids to digital-image processing. Firstly, we describe the architecture of digital-image processing on the basis of computational grids, its implementation is then discussed in detail with respect to the technology of middleware. The whole network-based intelligent image-processing system is evaluated on the basis of the experimental analysis of remotely sensed image-processing tasks; the results confirm the feasibility of the application of computational grids to digital-image processing.

Software Surface Modeling and Grid Generation Steering Committee

NASA Technical Reports Server (NTRS)

Smith, Robert E. (Editor)

1992-01-01

It is a NASA objective to promote improvements in the capability and efficiency of computational fluid dynamics. Grid generation, the creation of a discrete representation of the solution domain, is an essential part of computational fluid dynamics. However, grid generation about complex boundaries requires sophisticated surface-model descriptions of the boundaries. The surface modeling and the associated computation of surface grids consume an extremely large percentage of the total time required for volume grid generation. Efficient and user friendly software systems for surface modeling and grid generation are critical for computational fluid dynamics to reach its potential. The papers presented here represent the state-of-the-art in software systems for surface modeling and grid generation. Several papers describe improved techniques for grid generation.

Effect of particle size distribution on the hydrodynamics of dense CFB risers

NASA Astrophysics Data System (ADS)

Bakshi, Akhilesh; Khanna, Samir; Venuturumilli, Raj; Altantzis, Christos; Ghoniem, Ahmed

2015-11-01

Circulating Fluidized Beds (CFB) are favorable in the energy and chemical industries, due to their high efficiency. While accurate hydrodynamic modeling is essential for optimizing performance, most CFB riser simulations are performed assuming equally-sized solid particles, owing to limited computational resources. Even though this approach yields reasonable predictions, it neglects commonly observed experimental findings suggesting the strong effect of particle size distribution (psd) on the hydrodynamics and chemical conversion. Thus, this study is focused on the inclusion of discrete particle sizes to represent the psd and its effect on fluidization via 2D numerical simulations. The particle sizes and corresponding mass fluxes are obtained using experimental data in dense CFB riser while the modeling framework is described in Bakshi et al 2015. Simulations are conducted at two scales: (a) fine grid to resolve heterogeneous structures and (b) coarse grid using EMMS sub-grid modifications. Using suitable metrics which capture bed dynamics, this study provides insights into segregation and mixing of particles as well as highlights need for improved sub-grid models.

Implementing the Victory Access Control Framework in a Military Ground Vehicle

DTIC Science & Technology

2015-08-01

Protocol ( SOAP ) message body, but lacked the ability to encrypt individual XML elements within the SOAP body. Several attempts were made to augment the C...Service and both use SOAP and provide freely available WSDLs with similarly defined operations. TS3 even leverages the same XACML engine that is...Characterizing the Performance of SOAP Toolkits”, Fifth IEEE/ACM International Workshop on Grid Computing, pages 365- 372, November 2004. [8] J.A

Fault tolerance in computational grids: perspectives, challenges, and issues.

PubMed

Haider, Sajjad; Nazir, Babar

2016-01-01

Computational grids are established with the intention of providing shared access to hardware and software based resources with special reference to increased computational capabilities. Fault tolerance is one of the most important issues faced by the computational grids. The main contribution of this survey is the creation of an extended classification of problems that incur in the computational grid environments. The proposed classification will help researchers, developers, and maintainers of grids to understand the types of issues to be anticipated. Moreover, different types of problems, such as omission, interaction, and timing related have been identified that need to be handled on various layers of the computational grid. In this survey, an analysis and examination is also performed pertaining to the fault tolerance and fault detection mechanisms. Our conclusion is that a dependable and reliable grid can only be established when more emphasis is on fault identification. Moreover, our survey reveals that adaptive and intelligent fault identification, and tolerance techniques can improve the dependability of grid working environments.

Chimera grids in the simulation of three-dimensional flowfields in turbine-blade-coolant passages

NASA Technical Reports Server (NTRS)

Stephens, M. A.; Rimlinger, M. J.; Shih, T. I.-P.; Civinskas, K. C.

1993-01-01

When computing flows inside geometrically complex turbine-blade coolant passages, the structure of the grid system used can affect significantly the overall time and cost required to obtain solutions. This paper addresses this issue while evaluating and developing computational tools for the design and analysis of coolant-passages, and is divided into two parts. In the first part, the various types of structured and unstructured grids are compared in relation to their ability to provide solutions in a timely and cost-effective manner. This comparison shows that the overlapping structured grids, known as Chimera grids, can rival and in some instances exceed the cost-effectiveness of unstructured grids in terms of both the man hours needed to generate grids and the amount of computer memory and CPU time needed to obtain solutions. In the second part, a computational tool utilizing Chimera grids was used to compute the flow and heat transfer in two different turbine-blade coolant passages that contain baffles and numerous pin fins. These computations showed the versatility and flexibility offered by Chimera grids.

Cause and Cure - Deterioration in Accuracy of CFD Simulations With Use of High-Aspect-Ratio Triangular Tetrahedral Grids

NASA Technical Reports Server (NTRS)

Chang, Sin-Chung; Chang, Chau-Lyan; Venkatachari, Balaji Shankar

2017-01-01

Traditionally high-aspect ratio triangular/tetrahedral meshes are avoided by CFD re-searchers in the vicinity of a solid wall, as it is known to reduce the accuracy of gradient computations in those regions and also cause numerical instability. Although for certain complex geometries, the use of high-aspect ratio triangular/tetrahedral elements in the vicinity of a solid wall can be replaced by quadrilateral/prismatic elements, ability to use triangular/tetrahedral elements in such regions without any degradation in accuracy can be beneficial from a mesh generation point of view. The benefits also carry over to numerical frameworks such as the space-time conservation element and solution element (CESE), where triangular/tetrahedral elements are the mandatory building blocks. With the requirement of the CESE method in mind, a rigorous mathematical framework that clearly identities the reason behind the difficulties in use of such high-aspect ratio triangular/tetrahedral elements is presented here. As will be shown, it turns out that the degree of accuracy deterioration of gradient computation involving a triangular element is hinged on the value of its shape factor Gamma def = sq sin Alpha1 + sq sin Alpha2 + sq sin Alpha3, where Alpha1; Alpha2 and Alpha3 are the internal angles of the element. In fact, it is shown that the degree of accuracy deterioration increases monotonically as the value of Gamma decreases monotonically from its maximal value 9/4 (attained by an equilateral triangle only) to a value much less than 1 (associated with a highly obtuse triangle). By taking advantage of the fact that a high-aspect ratio triangle is not necessarily highly obtuse, and in fact it can have a shape factor whose value is close to the maximal value 9/4, a potential solution to avoid accuracy deterioration of gradient computation associated with a high-aspect ratio triangular grid is given. Also a brief discussion on the extension of the current mathematical framework to the tetrahedral-grid case along with some of the practical results of this extension is also provided. Furthermore, through the use of numerical simulations of practical viscous problems involving high-Reynolds number flows, the effectiveness of the gradient evaluation procedures within the CESE framework (that have their basis on the analysis presented here) to produce accurate and stable results on such high-aspect ratio meshes is also showcased.

Statistical Analysis of CFD Solutions From the Fifth AIAA Drag Prediction Workshop

NASA Technical Reports Server (NTRS)

Morrison, Joseph H.

2013-01-01

A graphical framework is used for statistical analysis of the results from an extensive N-version test of a collection of Reynolds-averaged Navier-Stokes computational fluid dynamics codes. The solutions were obtained by code developers and users from North America, Europe, Asia, and South America using a common grid sequence and multiple turbulence models for the June 2012 fifth Drag Prediction Workshop sponsored by the AIAA Applied Aerodynamics Technical Committee. The aerodynamic configuration for this workshop was the Common Research Model subsonic transport wing-body previously used for the 4th Drag Prediction Workshop. This work continues the statistical analysis begun in the earlier workshops and compares the results from the grid convergence study of the most recent workshop with previous workshops.

Interoperability of GADU in using heterogeneous Grid resources for bioinformatics applications.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sulakhe, D.; Rodriguez, A.; Wilde, M.

2008-03-01

Bioinformatics tools used for efficient and computationally intensive analysis of genetic sequences require large-scale computational resources to accommodate the growing data. Grid computational resources such as the Open Science Grid and TeraGrid have proved useful for scientific discovery. The genome analysis and database update system (GADU) is a high-throughput computational system developed to automate the steps involved in accessing the Grid resources for running bioinformatics applications. This paper describes the requirements for building an automated scalable system such as GADU that can run jobs on different Grids. The paper describes the resource-independent configuration of GADU using the Pegasus-based virtual datamore » system that makes high-throughput computational tools interoperable on heterogeneous Grid resources. The paper also highlights the features implemented to make GADU a gateway to computationally intensive bioinformatics applications on the Grid. The paper will not go into the details of problems involved or the lessons learned in using individual Grid resources as it has already been published in our paper on genome analysis research environment (GNARE) and will focus primarily on the architecture that makes GADU resource independent and interoperable across heterogeneous Grid resources.« less

Multidimensional Environmental Data Resource Brokering on Computational Grids and Scientific Clouds

NASA Astrophysics Data System (ADS)

Montella, Raffaele; Giunta, Giulio; Laccetti, Giuliano

Grid computing has widely evolved over the past years, and its capabilities have found their way even into business products and are no longer relegated to scientific applications. Today, grid computing technology is not restricted to a set of specific grid open source or industrial products, but rather it is comprised of a set of capabilities virtually within any kind of software to create shared and highly collaborative production environments. These environments are focused on computational (workload) capabilities and the integration of information (data) into those computational capabilities. An active grid computing application field is the fully virtualization of scientific instruments in order to increase their availability and decrease operational and maintaining costs. Computational and information grids allow to manage real-world objects in a service-oriented way using industrial world-spread standards.

Grid Computing in K-12 Schools. Soapbox Digest. Volume 3, Number 2, Fall 2004

ERIC Educational Resources Information Center

AEL, 2004

2004-01-01

Grid computing allows large groups of computers (either in a lab, or remote and connected only by the Internet) to extend extra processing power to each individual computer to work on components of a complex request. Grid middleware, recognizing priorities set by systems administrators, allows the grid to identify and use this power without…

Patch forest: a hybrid framework of random forest and patch-based segmentation

NASA Astrophysics Data System (ADS)

Xie, Zhongliu; Gillies, Duncan

2016-03-01

The development of an accurate, robust and fast segmentation algorithm has long been a research focus in medical computer vision. State-of-the-art practices often involve non-rigidly registering a target image with a set of training atlases for label propagation over the target space to perform segmentation, a.k.a. multi-atlas label propagation (MALP). In recent years, the patch-based segmentation (PBS) framework has gained wide attention due to its advantage of relaxing the strict voxel-to-voxel correspondence to a series of pair-wise patch comparisons for contextual pattern matching. Despite a high accuracy reported in many scenarios, computational efficiency has consistently been a major obstacle for both approaches. Inspired by recent work on random forest, in this paper we propose a patch forest approach, which by equipping the conventional PBS with a fast patch search engine, is able to boost segmentation speed significantly while retaining an equal level of accuracy. In addition, a fast forest training mechanism is also proposed, with the use of a dynamic grid framework to efficiently approximate data compactness computation and a 3D integral image technique for fast box feature retrieval.

Study on Global GIS architecture and its key technologies

NASA Astrophysics Data System (ADS)

Cheng, Chengqi; Guan, Li; Lv, Xuefeng

2009-09-01

Global GIS (G2IS) is a system, which supports the huge data process and the global direct manipulation on global grid based on spheroid or ellipsoid surface. Based on global subdivision grid (GSG), Global GIS architecture is presented in this paper, taking advantage of computer cluster theory, the space-time integration technology and the virtual reality technology. Global GIS system architecture is composed of five layers, including data storage layer, data representation layer, network and cluster layer, data management layer and data application layer. Thereinto, it is designed that functions of four-level protocol framework and three-layer data management pattern of Global GIS based on organization, management and publication of spatial information in this architecture. Three kinds of core supportive technologies, which are computer cluster theory, the space-time integration technology and the virtual reality technology, and its application pattern in the Global GIS are introduced in detail. The primary ideas of Global GIS in this paper will be an important development tendency of GIS.

Study on Global GIS architecture and its key technologies

NASA Astrophysics Data System (ADS)

Cheng, Chengqi; Guan, Li; Lv, Xuefeng

2010-11-01

Global GIS (G2IS) is a system, which supports the huge data process and the global direct manipulation on global grid based on spheroid or ellipsoid surface. Based on global subdivision grid (GSG), Global GIS architecture is presented in this paper, taking advantage of computer cluster theory, the space-time integration technology and the virtual reality technology. Global GIS system architecture is composed of five layers, including data storage layer, data representation layer, network and cluster layer, data management layer and data application layer. Thereinto, it is designed that functions of four-level protocol framework and three-layer data management pattern of Global GIS based on organization, management and publication of spatial information in this architecture. Three kinds of core supportive technologies, which are computer cluster theory, the space-time integration technology and the virtual reality technology, and its application pattern in the Global GIS are introduced in detail. The primary ideas of Global GIS in this paper will be an important development tendency of GIS.

AESOP: A Python Library for Investigating Electrostatics in Protein Interactions.

PubMed

Harrison, Reed E S; Mohan, Rohith R; Gorham, Ronald D; Kieslich, Chris A; Morikis, Dimitrios

2017-05-09

Electric fields often play a role in guiding the association of protein complexes. Such interactions can be further engineered to accelerate complex association, resulting in protein systems with increased productivity. This is especially true for enzymes where reaction rates are typically diffusion limited. To facilitate quantitative comparisons of electrostatics in protein families and to describe electrostatic contributions of individual amino acids, we previously developed a computational framework called AESOP. We now implement this computational tool in Python with increased usability and the capability of performing calculations in parallel. AESOP utilizes PDB2PQR and Adaptive Poisson-Boltzmann Solver to generate grid-based electrostatic potential files for protein structures provided by the end user. There are methods within AESOP for quantitatively comparing sets of grid-based electrostatic potentials in terms of similarity or generating ensembles of electrostatic potential files for a library of mutants to quantify the effects of perturbations in protein structure and protein-protein association. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Nonlinear ship waves and computational fluid dynamics

PubMed Central

MIYATA, Hideaki; ORIHARA, Hideo; SATO, Yohei

2014-01-01

Research works undertaken in the first author’s laboratory at the University of Tokyo over the past 30 years are highlighted. Finding of the occurrence of nonlinear waves (named Free-Surface Shock Waves) in the vicinity of a ship advancing at constant speed provided the start-line for the progress of innovative technologies in the ship hull-form design. Based on these findings, a multitude of the Computational Fluid Dynamic (CFD) techniques have been developed over this period, and are highlighted in this paper. The TUMMAC code has been developed for wave problems, based on a rectangular grid system, while the WISDAM code treats both wave and viscous flow problems in the framework of a boundary-fitted grid system. These two techniques are able to cope with almost all fluid dynamical problems relating to ships, including the resistance, ship’s motion and ride-comfort issues. Consequently, the two codes have contributed significantly to the progress in the technology of ship design, and now form an integral part of the ship-designing process. PMID:25311139

Numerical studies of the fluid and optical fields associated with complex cavity flows

NASA Technical Reports Server (NTRS)

Atwood, Christopher A.

1992-01-01

Numerical solutions for the flowfield about several cavity configurations have been computed using the Reynolds averaged Navier-Stokes equations. Comparisons between numerical and experimental results are made in two dimensions for free shear layers and a rectangular cavity, and in three dimensions for the transonic aero-window problem of the Stratospheric Observatory for Infrared Astronomy (SOFIA). Results show that dominant acoustic frequencies and magnitudes of the self excited resonant cavity flows compare well with the experiment. In addition, solution sensitivity to artificial dissipation and grid resolution levels are determined. Optical path distortion due to the flow field is modelled geometrically and is found to match the experiment. The fluid field was computed using a diagonalized scheme within an overset mesh framework. An existing code, OVERFLOW, was utilized with the additions of characteristic boundary condition and output routines required for reduction of the unsteady data. The newly developed code is directly applicable to a generalized three dimensional structured grid zone. Details are provided in a paper included in Appendix A.

Current Grid Generation Strategies and Future Requirements in Hypersonic Vehicle Design, Analysis and Testing

NASA Technical Reports Server (NTRS)

Papadopoulos, Periklis; Venkatapathy, Ethiraj; Prabhu, Dinesh; Loomis, Mark P.; Olynick, Dave; Arnold, James O. (Technical Monitor)

1998-01-01

Recent advances in computational power enable computational fluid dynamic modeling of increasingly complex configurations. A review of grid generation methodologies implemented in support of the computational work performed for the X-38 and X-33 are presented. In strategizing topological constructs and blocking structures factors considered are the geometric configuration, optimal grid size, numerical algorithms, accuracy requirements, physics of the problem at hand, computational expense, and the available computer hardware. Also addressed are grid refinement strategies, the effects of wall spacing, and convergence. The significance of grid is demonstrated through a comparison of computational and experimental results of the aeroheating environment experienced by the X-38 vehicle. Special topics on grid generation strategies are also addressed to model control surface deflections, and material mapping.

Status of the DIRAC Project

NASA Astrophysics Data System (ADS)

Casajus, A.; Ciba, K.; Fernandez, V.; Graciani, R.; Hamar, V.; Mendez, V.; Poss, S.; Sapunov, M.; Stagni, F.; Tsaregorodtsev, A.; Ubeda, M.

2012-12-01

The DIRAC Project was initiated to provide a data processing system for the LHCb Experiment at CERN. It provides all the necessary functionality and performance to satisfy the current and projected future requirements of the LHCb Computing Model. A considerable restructuring of the DIRAC software was undertaken in order to turn it into a general purpose framework for building distributed computing systems that can be used by various user communities in High Energy Physics and other scientific application domains. The CLIC and ILC-SID detector projects started to use DIRAC for their data production system. The Belle Collaboration at KEK, Japan, has adopted the Computing Model based on the DIRAC system for its second phase starting in 2015. The CTA Collaboration uses DIRAC for the data analysis tasks. A large number of other experiments are starting to use DIRAC or are evaluating this solution for their data processing tasks. DIRAC services are included as part of the production infrastructure of the GISELA Latin America grid. Similar services are provided for the users of the France-Grilles and IBERGrid National Grid Initiatives in France and Spain respectively. The new communities using DIRAC started to provide important contributions to its functionality. Among recent additions can be mentioned the support of the Amazon EC2 computing resources as well as other Cloud management systems; a versatile File Replica Catalog with File Metadata capabilities; support for running MPI jobs in the pilot based Workload Management System. Integration with existing application Web Portals, like WS-PGRADE, is demonstrated. In this paper we will describe the current status of the DIRAC Project, recent developments of its framework and functionality as well as the status of the rapidly evolving community of the DIRAC users.

Distributed computations in a dynamic, heterogeneous Grid environment

NASA Astrophysics Data System (ADS)

Dramlitsch, Thomas

2003-06-01

In order to face the rapidly increasing need for computational resources of various scientific and engineering applications one has to think of new ways to make more efficient use of the worlds current computational resources. In this respect, the growing speed of wide area networks made a new kind of distributed computing possible: Metacomputing or (distributed) Grid computing. This is a rather new and uncharted field in computational science. The rapidly increasing speed of networks even outperforms the average increase of processor speed: Processor speeds double on average each 18 month whereas network bandwidths double every 9 months. Due to this development of local and wide area networks Grid computing will certainly play a key role in the future of parallel computing. This type of distributed computing, however, distinguishes from the traditional parallel computing in many ways since it has to deal with many problems not occurring in classical parallel computing. Those problems are for example heterogeneity, authentication and slow networks to mention only a few. Some of those problems, e.g. the allocation of distributed resources along with the providing of information about these resources to the application have been already attacked by the Globus software. Unfortunately, as far as we know, hardly any application or middle-ware software takes advantage of this information, since most parallelizing algorithms for finite differencing codes are implicitly designed for single supercomputer or cluster execution. We show that although it is possible to apply classical parallelizing algorithms in a Grid environment, in most cases the observed efficiency of the executed code is very poor. In this work we are closing this gap. In our thesis, we will - show that an execution of classical parallel codes in Grid environments is possible but very slow - analyze this situation of bad performance, nail down bottlenecks in communication, remove unnecessary overhead and other reasons for low performance - develop new and advanced algorithms for parallelisation that are aware of a Grid environment in order to generelize the traditional parallelization schemes - implement and test these new methods, replace and compare with the classical ones - introduce dynamic strategies that automatically adapt the running code to the nature of the underlying Grid environment. The higher the performance one can achieve for a single application by manual tuning for a Grid environment, the lower the chance that those changes are widely applicable to other programs. In our analysis as well as in our implementation we tried to keep the balance between high performance and generality. None of our changes directly affect code on the application level which makes our algorithms applicable to a whole class of real world applications. The implementation of our work is done within the Cactus framework using the Globus toolkit, since we think that these are the most reliable and advanced programming frameworks for supporting computations in Grid environments. On the other hand, however, we tried to be as general as possible, i.e. all methods and algorithms discussed in this thesis are independent of Cactus or Globus. Die immer dichtere und schnellere Vernetzung von Rechnern und Rechenzentren über Hochgeschwindigkeitsnetzwerke ermöglicht eine neue Art des wissenschaftlich verteilten Rechnens, bei der geographisch weit auseinanderliegende Rechenkapazitäten zu einer Gesamtheit zusammengefasst werden können. Dieser so entstehende virtuelle Superrechner, der selbst aus mehreren Grossrechnern besteht, kann dazu genutzt werden Probleme zu berechnen, für die die einzelnen Grossrechner zu klein sind. Die Probleme, die numerisch mit heutigen Rechenkapazitäten nicht lösbar sind, erstrecken sich durch sämtliche Gebiete der heutigen Wissenschaft, angefangen von Astrophysik, Molekülphysik, Bioinformatik, Meteorologie, bis hin zur Zahlentheorie und Fluiddynamik um nur einige Gebiete zu nennen. Je nach Art der Problemstellung und des Lösungsverfahrens gestalten sich solche "Meta-Berechnungen" mehr oder weniger schwierig. Allgemein kann man sagen, dass solche Berechnungen um so schwerer und auch um so uneffizienter werden, je mehr Kommunikation zwischen den einzelnen Prozessen (oder Prozessoren) herrscht. Dies ist dadurch begründet, dass die Bandbreiten bzw. Latenzzeiten zwischen zwei Prozessoren auf demselben Grossrechner oder Cluster um zwei bis vier Grössenordnungen höher bzw. niedriger liegen als zwischen Prozessoren, welche hunderte von Kilometern entfernt liegen. Dennoch bricht nunmehr eine Zeit an, in der es möglich ist Berechnungen auf solch virtuellen Supercomputern auch mit kommunikationsintensiven Programmen durchzuführen. Eine grosse Klasse von kommunikations- und berechnungsintensiven Programmen ist diejenige, die die Lösung von Differentialgleichungen mithilfe von finiten Differenzen zum Inhalt hat. Gerade diese Klasse von Programmen und deren Betrieb in einem virtuellen Superrechner wird in dieser vorliegenden Dissertation behandelt. Methoden zur effizienteren Durchführung von solch verteilten Berechnungen werden entwickelt, analysiert und implementiert. Der Schwerpunkt liegt darin vorhandene, klassische Parallelisierungsalgorithmen zu analysieren und so zu erweitern, dass sie vorhandene Informationen (z.B. verfügbar durch das Globus Toolkit) über Maschinen und Netzwerke zur effizienteren Parallelisierung nutzen. Soweit wir wissen werden solche Zusatzinformationen kaum in relevanten Programmen genutzt, da der Grossteil aller Parallelisierungsalgorithmen implizit für die Ausführung auf Grossrechnern oder Clustern entwickelt wurde.

A nominally second-order cell-centered Lagrangian scheme for simulating elastic–plastic flows on two-dimensional unstructured grids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maire, Pierre-Henri, E-mail: maire@celia.u-bordeaux1.fr; Abgrall, Rémi, E-mail: remi.abgrall@math.u-bordeau1.fr; Breil, Jérôme, E-mail: breil@celia.u-bordeaux1.fr

2013-02-15

In this paper, we describe a cell-centered Lagrangian scheme devoted to the numerical simulation of solid dynamics on two-dimensional unstructured grids in planar geometry. This numerical method, utilizes the classical elastic-perfectly plastic material model initially proposed by Wilkins [M.L. Wilkins, Calculation of elastic–plastic flow, Meth. Comput. Phys. (1964)]. In this model, the Cauchy stress tensor is decomposed into the sum of its deviatoric part and the thermodynamic pressure which is defined by means of an equation of state. Regarding the deviatoric stress, its time evolution is governed by a classical constitutive law for isotropic material. The plasticity model employs themore » von Mises yield criterion and is implemented by means of the radial return algorithm. The numerical scheme relies on a finite volume cell-centered method wherein numerical fluxes are expressed in terms of sub-cell force. The generic form of the sub-cell force is obtained by requiring the scheme to satisfy a semi-discrete dissipation inequality. Sub-cell force and nodal velocity to move the grid are computed consistently with cell volume variation by means of a node-centered solver, which results from total energy conservation. The nominally second-order extension is achieved by developing a two-dimensional extension in the Lagrangian framework of the Generalized Riemann Problem methodology, introduced by Ben-Artzi and Falcovitz [M. Ben-Artzi, J. Falcovitz, Generalized Riemann Problems in Computational Fluid Dynamics, Cambridge Monogr. Appl. Comput. Math. (2003)]. Finally, the robustness and the accuracy of the numerical scheme are assessed through the computation of several test cases.« less

Consolidation and development roadmap of the EMI middleware

NASA Astrophysics Data System (ADS)

Kónya, B.; Aiftimiei, C.; Cecchi, M.; Field, L.; Fuhrmann, P.; Nilsen, J. K.; White, J.

2012-12-01

Scientific research communities have benefited recently from the increasing availability of computing and data infrastructures with unprecedented capabilities for large scale distributed initiatives. These infrastructures are largely defined and enabled by the middleware they deploy. One of the major issues in the current usage of research infrastructures is the need to use similar but often incompatible middleware solutions. The European Middleware Initiative (EMI) is a collaboration of the major European middleware providers ARC, dCache, gLite and UNICORE. EMI aims to: deliver a consolidated set of middleware components for deployment in EGI, PRACE and other Distributed Computing Infrastructures; extend the interoperability between grids and other computing infrastructures; strengthen the reliability of the services; establish a sustainable model to maintain and evolve the middleware; fulfil the requirements of the user communities. This paper presents the consolidation and development objectives of the EMI software stack covering the last two years. The EMI development roadmap is introduced along the four technical areas of compute, data, security and infrastructure. The compute area plan focuses on consolidation of standards and agreements through a unified interface for job submission and management, a common format for accounting, the wide adoption of GLUE schema version 2.0 and the provision of a common framework for the execution of parallel jobs. The security area is working towards a unified security model and lowering the barriers to Grid usage by allowing users to gain access with their own credentials. The data area is focusing on implementing standards to ensure interoperability with other grids and industry components and to reuse already existing clients in operating systems and open source distributions. One of the highlights of the infrastructure area is the consolidation of the information system services via the creation of a common information backbone.

An iceberg model implementation in ACME.

NASA Astrophysics Data System (ADS)

Comeau, D.; Turner, A. K.; Hunke, E. C.

2017-12-01

Icebergs represent approximately half of the mass flux from the Antarctic ice sheet, transporting freshwater and nutrients away from the coast to the Southern Ocean. Icebergs impact the surrounding ocean and sea ice environment, and serve as nutrient sources for biogeochemical activity, yet these processes are typically not resolved in current climate models. We have implemented a parameterization for iceberg drift and decay into the Department of Energy's Accelerated Climate Model for Energy (ACME), where the ocean, sea ice, and land ice components are based on the unstructured grid modeling framework Multiple Prediction Across Scales (MPAS), to improve the representation of Antarctic mass flux to the Southern Ocean and its impacts on ocean stratification and circulation, sea ice, and biogeochemical processes in a fully coupled global climate model. The iceberg model is implemented in two frameworks: Lagrangian and Eulerian. The Lagrangian framework embeds individual icebergs into the ocean and sea ice grids, and will be useful in modeling `giant' (>10 nautical miles) iceberg events, which may have highly localized impacts on ocean and sea ice. The Eulerian framework allows us to model a realistic population of Antarctic icebergs without the computational expense of individual particle tracking to simulate the aggregate impact on the Southern Ocean climate system. This capability, together with under ice-shelf ocean cavities and dynamic ice-shelf fronts, will allow for extremely high fidelity simulation of the southern cryosphere within ACME.

A Three Dimensional Parallel Time Accurate Turbopump Simulation Procedure Using Overset Grid Systems

NASA Technical Reports Server (NTRS)

Kiris, Cetin; Chan, William; Kwak, Dochan

2001-01-01

The objective of the current effort is to provide a computational framework for design and analysis of the entire fuel supply system of a liquid rocket engine, including high-fidelity unsteady turbopump flow analysis. This capability is needed to support the design of pump sub-systems for advanced space transportation vehicles that are likely to involve liquid propulsion systems. To date, computational tools for design/analysis of turbopump flows are based on relatively lower fidelity methods. An unsteady, three-dimensional viscous flow analysis tool involving stationary and rotational components for the entire turbopump assembly has not been available for real-world engineering applications. The present effort provides developers with information such as transient flow phenomena at start up, and non-uniform inflows, and will eventually impact on system vibration and structures. In the proposed paper, the progress toward the capability of complete simulation of the turbo-pump for a liquid rocket engine is reported. The Space Shuttle Main Engine (SSME) turbo-pump is used as a test case for evaluation of the hybrid MPI/Open-MP and MLP versions of the INS3D code. CAD to solution auto-scripting capability is being developed for turbopump applications. The relative motion of the grid systems for the rotor-stator interaction was obtained using overset grid techniques. Unsteady computations for the SSME turbo-pump, which contains 114 zones with 34.5 million grid points, are carried out on Origin 3000 systems at NASA Ames Research Center. Results from these time-accurate simulations with moving boundary capability will be presented along with the performance of parallel versions of the code.

Rapid inundation estimates at harbor scale using tsunami wave heights offshore simulation and Green's law approach

NASA Astrophysics Data System (ADS)

Gailler, Audrey; Hébert, Hélène; Loevenbruck, Anne

2013-04-01

Improvements in the availability of sea-level observations and advances in numerical modeling techniques are increasing the potential for tsunami warnings to be based on numerical model forecasts. Numerical tsunami propagation and inundation models are well developed and have now reached an impressive level of accuracy, especially in locations such as harbors where the tsunami waves are mostly amplified. In the framework of tsunami warning under real-time operational conditions, the main obstacle for the routine use of such numerical simulations remains the slowness of the numerical computation, which is strengthened when detailed grids are required for the precise modeling of the coastline response on the scale of an individual harbor. In fact, when facing the problem of the interaction of the tsunami wavefield with a shoreline, any numerical simulation must be performed over an increasingly fine grid, which in turn mandates a reduced time step, and the use of a fully non-linear code. Such calculations become then prohibitively time-consuming, which is clearly unacceptable in the framework of real-time warning. Thus only tsunami offshore propagation modeling tools using a single sparse bathymetric computation grid are presently included within the French Tsunami Warning Center (CENALT), providing rapid estimation of tsunami wave heights in high seas, and tsunami warning maps at western Mediterranean and NE Atlantic basins scale. We present here a preliminary work that performs quick estimates of the inundation at individual harbors from these deep wave heights simulations. The method involves an empirical correction relation derived from Green's law, expressing conservation of wave energy flux to extend the gridded wave field into the harbor with respect to the nearby deep-water grid node. The main limitation of this method is that its application to a given coastal area would require a large database of previous observations, in order to define the empirical parameters of the correction equation. As no such data (i.e., historical tide gage records of significant tsunamis) are available for the western Mediterranean and NE Atlantic basins, a set of synthetic mareograms is calculated for both fake and well-known historical tsunamigenic earthquakes in the area. This synthetic dataset is obtained through accurate numerical tsunami propagation and inundation modeling by using several nested bathymetric grids characterized by a coarse resolution over deep water regions and an increasingly fine resolution close to the shores (down to a grid cell size of 3m in some Mediterranean harbors). This synthetic dataset is then used to approximate the empirical parameters of the correction equation. Results of inundation estimates in several french Mediterranean harbors obtained with the fast "Green's law - derived" method are presented and compared with values given by time-consuming nested grids simulations.

SciSpark's SRDD : A Scientific Resilient Distributed Dataset for Multidimensional Data

NASA Astrophysics Data System (ADS)

Palamuttam, R. S.; Wilson, B. D.; Mogrovejo, R. M.; Whitehall, K. D.; Mattmann, C. A.; McGibbney, L. J.; Ramirez, P.

2015-12-01

Remote sensing data and climate model output are multi-dimensional arrays of massive sizes locked away in heterogeneous file formats (HDF5/4, NetCDF 3/4) and metadata models (HDF-EOS, CF) making it difficult to perform multi-stage, iterative science processing since each stage requires writing and reading data to and from disk. We have developed SciSpark, a robust Big Data framework, that extends ApacheTM Spark for scaling scientific computations. Apache Spark improves the map-reduce implementation in ApacheTM Hadoop for parallel computing on a cluster, by emphasizing in-memory computation, "spilling" to disk only as needed, and relying on lazy evaluation. Central to Spark is the Resilient Distributed Dataset (RDD), an in-memory distributed data structure that extends the functional paradigm provided by the Scala programming language. However, RDDs are ideal for tabular or unstructured data, and not for highly dimensional data. The SciSpark project introduces the Scientific Resilient Distributed Dataset (sRDD), a distributed-computing array structure which supports iterative scientific algorithms for multidimensional data. SciSpark processes data stored in NetCDF and HDF files by partitioning them across time or space and distributing the partitions among a cluster of compute nodes. We show usability and extensibility of SciSpark by implementing distributed algorithms for geospatial operations on large collections of multi-dimensional grids. In particular we address the problem of scaling an automated method for finding Mesoscale Convective Complexes. SciSpark provides a tensor interface to support the pluggability of different matrix libraries. We evaluate performance of the various matrix libraries in distributed pipelines, such as Nd4jTM and BreezeTM. We detail the architecture and design of SciSpark, our efforts to integrate climate science algorithms, parallel ingest and partitioning (sharding) of A-Train satellite observations from model grids. These solutions are encompassed in SciSpark, an open-source software framework for distributed computing on scientific data.

Program Aids Specification Of Multiple-Block Grids

NASA Technical Reports Server (NTRS)

Sorenson, R. L.; Mccann, K. M.

1993-01-01

3DPREP computer program aids specification of multiple-block computational grids. Highly interactive graphical preprocessing program designed for use on powerful graphical scientific computer workstation. Divided into three main parts, each corresponding to principal graphical-and-alphanumerical display. Relieves user of some burden of collecting and formatting many data needed to specify blocks and grids, and prepares input data for NASA's 3DGRAPE grid-generating computer program.

Uncertainty Analysis Based on Sparse Grid Collocation and Quasi-Monte Carlo Sampling with Application in Groundwater Modeling

NASA Astrophysics Data System (ADS)

Zhang, G.; Lu, D.; Ye, M.; Gunzburger, M.

2011-12-01

Markov Chain Monte Carlo (MCMC) methods have been widely used in many fields of uncertainty analysis to estimate the posterior distributions of parameters and credible intervals of predictions in the Bayesian framework. However, in practice, MCMC may be computationally unaffordable due to slow convergence and the excessive number of forward model executions required, especially when the forward model is expensive to compute. Both disadvantages arise from the curse of dimensionality, i.e., the posterior distribution is usually a multivariate function of parameters. Recently, sparse grid method has been demonstrated to be an effective technique for coping with high-dimensional interpolation or integration problems. Thus, in order to accelerate the forward model and avoid the slow convergence of MCMC, we propose a new method for uncertainty analysis based on sparse grid interpolation and quasi-Monte Carlo sampling. First, we construct a polynomial approximation of the forward model in the parameter space by using the sparse grid interpolation. This approximation then defines an accurate surrogate posterior distribution that can be evaluated repeatedly at minimal computational cost. Second, instead of using MCMC, a quasi-Monte Carlo method is applied to draw samples in the parameter space. Then, the desired probability density function of each prediction is approximated by accumulating the posterior density values of all the samples according to the prediction values. Our method has the following advantages: (1) the polynomial approximation of the forward model on the sparse grid provides a very efficient evaluation of the surrogate posterior distribution; (2) the quasi-Monte Carlo method retains the same accuracy in approximating the PDF of predictions but avoids all disadvantages of MCMC. The proposed method is applied to a controlled numerical experiment of groundwater flow modeling. The results show that our method attains the same accuracy much more efficiently than traditional MCMC.

Hydrological Scenario Using Tools and Applications Available in enviroGRIDS Portal

NASA Astrophysics Data System (ADS)

Bacu, V.; Mihon, D.; Stefanut, T.; Rodila, D.; Cau, P.; Manca, S.; Soru, C.; Gorgan, D.

2012-04-01

Nowadays the decision makers but also citizens are concerning with the sustainability and vulnerability of land management practices on various aspects and in particular on water quality and quantity in complex watersheds. The Black Sea Catchment is an important watershed in the Central and East Europe. In the FP7 project enviroGRIDS [1] was developed a Web Portal that incorporates different tools and applications focused on geospatial data management, hydrologic model calibration, execution and visualization and training activities. This presentation highlights, from the end-user point of view, the scenario related with hydrological models using the tools and applications available in the enviroGRIDS Web Portal [2]. The development of SWAT (Soil Water Assessment Tool) hydrological models is a well known procedure for the hydrological specialists [3]. Starting from the primary data (information related to weather, soil properties, topography, vegetation, and land management practices of the particular watershed) that are used to develop SWAT hydrological models, to specific reports, about the water quality in the studied watershed, the hydrological specialist will use different applications available in the enviroGRIDS portal. The tools and applications available through the enviroGRIDS portal are not dealing with the building up of the SWAT hydrological models. They are mainly focused on: calibration procedure (gSWAT [4]) - uses the GRID computational infrastructure to speed-up the calibration process; development of specific scenarios (BASHYT [5]) - starts from an already calibrated SWAT hydrological model and defines new scenarios; execution of scenarios (gSWATSim [6]) - executes the scenarios exported from BASHYT; visualization (BASHYT) - displays charts, tables and maps. Each application is built-up as a stack of functional layers. We combine different layers of applications by vertical interoperability in order to build the desired complex functionality. On the other hand, the applications can collaborate at the same architectural levels, which represent the horizontal interoperability. Both the horizontal and vertical interoperability is accomplished by services and by exchanging data. The calibration procedure requires huge computational resources, which are provided by the Grid infrastructure. On the other hand the scenario development through BASHYT requires a flexible way of interaction with the SWAT model in order to easily change the input model. The large user community of SWAT from the enviroGRIDS consortium or outside may greatly benefit from tools and applications related with the calibration process, scenario development and execution from the enviroGRIDS portal. [1]. enviroGRIDS project, http://envirogrids.net/ [2]. Gorgan D., Abbaspour K., Cau P., Bacu V., Mihon D., Giuliani G., Ray N., Lehmann A., Grid Based Data Processing Tools and Applications for Black Sea Catchment Basin. IDAACS 2011 - The 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications 15-17 September 2011, Prague. IEEE Computer Press, pp. 223 - 228 (2011). [3]. Soil and Water Assessment Tool, http://www.brc.tamus.edu/swat/index.html [4]. Bacu V., Mihon D., Rodila D., Stefanut T., Gorgan D., Grid Based Architectural Components for SWAT Model Calibration. HPCS 2011 - International Conference on High Performance Computing and Simulation, 4-8 July, Istanbul, Turkey, ISBN 978-1-61284-381-0, doi: 10.1109/HPCSim.2011.5999824, pp. 193-198 (2011). [5]. Manca S., Soru C., Cau P., Meloni G., Fiori M., A multi model and multiscale, GIS oriented Web framework based on the SWAT model to face issues of water and soil resource vulnerability. Presentation at the 5th International SWAT Conference, August 3-7, 2009, http://www.brc.tamus.edu/swat/4thswatconf/docs/rooma/session5/Cau-Bashyt.pdf [6]. Bacu V., Mihon D., Stefanut T., Rodila D., Gorgan D., Cau P., Manca S., Grid Based Services and Tools for Hydrological Model Processing and Visualization. SYNASC 2011 - 13 International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (in press).

Multiprocessor computer overset grid method and apparatus

DOEpatents

Barnette, Daniel W.; Ober, Curtis C.

2003-01-01

A multiprocessor computer overset grid method and apparatus comprises associating points in each overset grid with processors and using mapped interpolation transformations to communicate intermediate values between processors assigned base and target points of the interpolation transformations. The method allows a multiprocessor computer to operate with effective load balance on overset grid applications.

ON JOINT DETERMINISTIC GRID MODELING AND SUB-GRID VARIABILITY CONCEPTUAL FRAMEWORK FOR MODEL EVALUATION

EPA Science Inventory

The general situation, (but exemplified in urban areas), where a significant degree of sub-grid variability (SGV) exists in grid models poses problems when comparing gridbased air quality modeling results with observations. Typically, grid models ignore or parameterize processes ...

Modeling Complex Biological Flows in Multi-Scale Systems using the APDEC Framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Trebotich, D

We have developed advanced numerical algorithms to model biological fluids in multiscale flow environments using the software framework developed under the SciDAC APDEC ISIC. The foundation of our computational effort is an approach for modeling DNA-laden fluids as ''bead-rod'' polymers whose dynamics are fully coupled to an incompressible viscous solvent. The method is capable of modeling short range forces and interactions between particles using soft potentials and rigid constraints. Our methods are based on higher-order finite difference methods in complex geometry with adaptivity, leveraging algorithms and solvers in the APDEC Framework. Our Cartesian grid embedded boundary approach to incompressible viscousmore » flow in irregular geometries has also been interfaced to a fast and accurate level-sets method within the APDEC Framework for extracting surfaces from volume renderings of medical image data and used to simulate cardio-vascular and pulmonary flows in critical anatomies.« less

Modeling complex biological flows in multi-scale systems using the APDEC framework

NASA Astrophysics Data System (ADS)

Trebotich, David

2006-09-01

We have developed advanced numerical algorithms to model biological fluids in multiscale flow environments using the software framework developed under the SciDAC APDEC ISIC. The foundation of our computational effort is an approach for modeling DNA laden fluids as ''bead-rod'' polymers whose dynamics are fully coupled to an incompressible viscous solvent. The method is capable of modeling short range forces and interactions between particles using soft potentials and rigid constraints. Our methods are based on higher-order finite difference methods in complex geometry with adaptivity, leveraging algorithms and solvers in the APDEC Framework. Our Cartesian grid embedded boundary approach to incompressible viscous flow in irregular geometries has also been interfaced to a fast and accurate level-sets method within the APDEC Framework for extracting surfaces from volume renderings of medical image data and used to simulate cardio-vascular and pulmonary flows in critical anatomies.

Investigation of Grid Adaptation to Reduce Computational Efforts for a 2-D Hydrogen-Fueled Dual-Mode Scramjet

NASA Astrophysics Data System (ADS)

Foo, Kam Keong

A two-dimensional dual-mode scramjet flowpath is developed and evaluated using the ANSYS Fluent density-based flow solver with various computational grids. Results are obtained for fuel-off, fuel-on non-reacting, and fuel-on reacting cases at different equivalence ratios. A one-step global chemical kinetics hydrogen-air model is used in conjunction with the eddy-dissipation model. Coarse, medium and fine computational grids are used to evaluate grid sensitivity and to investigate a lack of grid independence. Different grid adaptation strategies are performed on the coarse grid in an attempt to emulate the solutions obtained from the finer grids. The goal of this study is to investigate the feasibility of using various mesh adaptation criteria to significantly decrease computational efforts for high-speed reacting flows.

Subgrid Modeling Geomorphological and Ecological Processes in Salt Marsh Evolution

NASA Astrophysics Data System (ADS)

Shi, F.; Kirby, J. T., Jr.; Wu, G.; Abdolali, A.; Deb, M.

2016-12-01

Numerical modeling a long-term evolution of salt marshes is challenging because it requires an extensive use of computational resources. Due to the presence of narrow tidal creeks, variations of salt marsh topography can be significant over spatial length scales on the order of a meter. With growing availability of high-resolution bathymetry measurements, like LiDAR-derived DEM data, it is increasingly desirable to run a high-resolution model in a large domain and for a long period of time to get trends of sedimentation patterns, morphological change and marsh evolution. However, high spatial-resolution poses a big challenge in both computational time and memory storage, when simulating a salt marsh with dimensions of up to O(100 km^2) with a small time step. In this study, we have developed a so-called Pre-storage, Sub-grid Model (PSM, Wu et al., 2015) for simulating flooding and draining processes in salt marshes. The simulation of Brokenbridge salt marsh, Delaware, shows that, with the combination of the sub-grid model and the pre-storage method, over 2 orders of magnitude computational speed-up can be achieved with minimal loss of model accuracy. We recently extended PSM to include a sediment transport component and models for biomass growth and sedimentation in the sub-grid model framework. The sediment transport model is formulated based on a newly derived sub-grid sediment concentration equation following Defina's (2000) area-averaging procedure. Suspended sediment transport is modeled by the advection-diffusion equation in the coarse grid level, but the local erosion and sedimentation rates are integrated over the sub-grid level. The morphological model is based on the existing morphological model in NearCoM (Shi et al., 2013), extended to include organic production from the biomass model. The vegetation biomass is predicted by a simple logistic equation model proposed by Marani et al. (2010). The biomass component is loosely coupled with hydrodynamic and sedimentation models owing to the different time scales of the physical and ecological processes. The coupled model is being applied to Delaware marsh evolution in response to rising sea level and changing sediment supplies.

Divide-and-conquer density functional theory on hierarchical real-space grids: Parallel implementation and applications

NASA Astrophysics Data System (ADS)

Shimojo, Fuyuki; Kalia, Rajiv K.; Nakano, Aiichiro; Vashishta, Priya

2008-02-01

A linear-scaling algorithm based on a divide-and-conquer (DC) scheme has been designed to perform large-scale molecular-dynamics (MD) simulations, in which interatomic forces are computed quantum mechanically in the framework of the density functional theory (DFT). Electronic wave functions are represented on a real-space grid, which is augmented with a coarse multigrid to accelerate the convergence of iterative solutions and with adaptive fine grids around atoms to accurately calculate ionic pseudopotentials. Spatial decomposition is employed to implement the hierarchical-grid DC-DFT algorithm on massively parallel computers. The largest benchmark tests include 11.8×106 -atom ( 1.04×1012 electronic degrees of freedom) calculation on 131 072 IBM BlueGene/L processors. The DC-DFT algorithm has well-defined parameters to control the data locality, with which the solutions converge rapidly. Also, the total energy is well conserved during the MD simulation. We perform first-principles MD simulations based on the DC-DFT algorithm, in which large system sizes bring in excellent agreement with x-ray scattering measurements for the pair-distribution function of liquid Rb and allow the description of low-frequency vibrational modes of graphene. The band gap of a CdSe nanorod calculated by the DC-DFT algorithm agrees well with the available conventional DFT results. With the DC-DFT algorithm, the band gap is calculated for larger system sizes until the result reaches the asymptotic value.

Chimera Grid Tools

NASA Technical Reports Server (NTRS)

Chan, William M.; Rogers, Stuart E.; Nash, Steven M.; Buning, Pieter G.; Meakin, Robert

2005-01-01

Chimera Grid Tools (CGT) is a software package for performing computational fluid dynamics (CFD) analysis utilizing the Chimera-overset-grid method. For modeling flows with viscosity about geometrically complex bodies in relative motion, the Chimera-overset-grid method is among the most computationally cost-effective methods for obtaining accurate aerodynamic results. CGT contains a large collection of tools for generating overset grids, preparing inputs for computer programs that solve equations of flow on the grids, and post-processing of flow-solution data. The tools in CGT include grid editing tools, surface-grid-generation tools, volume-grid-generation tools, utility scripts, configuration scripts, and tools for post-processing (including generation of animated images of flows and calculating forces and moments exerted on affected bodies). One of the tools, denoted OVERGRID, is a graphical user interface (GUI) that serves to visualize the grids and flow solutions and provides central access to many other tools. The GUI facilitates the generation of grids for a new flow-field configuration. Scripts that follow the grid generation process can then be constructed to mostly automate grid generation for similar configurations. CGT is designed for use in conjunction with a computer-aided-design program that provides the geometry description of the bodies, and a flow-solver program.

Surface Modeling and Grid Generation of Orbital Sciences X34 Vehicle. Phase 1

NASA Technical Reports Server (NTRS)

Alter, Stephen J.

1997-01-01

The surface modeling and grid generation requirements, motivations, and methods used to develop Computational Fluid Dynamic volume grids for the X34-Phase 1 are presented. The requirements set forth by the Aerothermodynamics Branch at the NASA Langley Research Center serve as the basis for the final techniques used in the construction of all volume grids, including grids for parametric studies of the X34. The Integrated Computer Engineering and Manufacturing code for Computational Fluid Dynamics (ICEM/CFD), the Grid Generation code (GRIDGEN), the Three-Dimensional Multi-block Advanced Grid Generation System (3DMAGGS) code, and Volume Grid Manipulator (VGM) code are used to enable the necessary surface modeling, surface grid generation, volume grid generation, and grid alterations, respectively. All volume grids generated for the X34, as outlined in this paper, were used for CFD simulations within the Aerothermodynamics Branch.

A simple grid implementation with Berkeley Open Infrastructure for Network Computing using BLAST as a model

PubMed Central

Pinthong, Watthanai; Muangruen, Panya

2016-01-01

Development of high-throughput technologies, such as Next-generation sequencing, allows thousands of experiments to be performed simultaneously while reducing resource requirement. Consequently, a massive amount of experiment data is now rapidly generated. Nevertheless, the data are not readily usable or meaningful until they are further analysed and interpreted. Due to the size of the data, a high performance computer (HPC) is required for the analysis and interpretation. However, the HPC is expensive and difficult to access. Other means were developed to allow researchers to acquire the power of HPC without a need to purchase and maintain one such as cloud computing services and grid computing system. In this study, we implemented grid computing in a computer training center environment using Berkeley Open Infrastructure for Network Computing (BOINC) as a job distributor and data manager combining all desktop computers to virtualize the HPC. Fifty desktop computers were used for setting up a grid system during the off-hours. In order to test the performance of the grid system, we adapted the Basic Local Alignment Search Tools (BLAST) to the BOINC system. Sequencing results from Illumina platform were aligned to the human genome database by BLAST on the grid system. The result and processing time were compared to those from a single desktop computer and HPC. The estimated durations of BLAST analysis for 4 million sequence reads on a desktop PC, HPC and the grid system were 568, 24 and 5 days, respectively. Thus, the grid implementation of BLAST by BOINC is an efficient alternative to the HPC for sequence alignment. The grid implementation by BOINC also helped tap unused computing resources during the off-hours and could be easily modified for other available bioinformatics software. PMID:27547555

Framework for computing the spatial coherence effects of polycapillary x-ray optics

PubMed Central

Zysk, Adam M.; Schoonover, Robert W.; Xu, Qiaofeng; Anastasio, Mark A.

2012-01-01

Despite the extensive use of polycapillary x-ray optics for focusing and collimating applications, there remains a significant need for characterization of the coherence properties of the output wavefield. In this work, we present the first quantitative computational method for calculation of the spatial coherence effects of polycapillary x-ray optical devices. This method employs the coherent mode decomposition of an extended x-ray source, geometric optical propagation of individual wavefield modes through a polycapillary device, output wavefield calculation by ray data resampling onto a uniform grid, and the calculation of spatial coherence properties by way of the spectral degree of coherence. PMID:22418154

Introducing FNCS: Framework for Network Co-Simulation

ScienceCinema

None

2018-06-07

This video provides a basic overview of the PNNL Future Power Grid Initiative-developed Framework for Network Co-Simulation (FNCS). It discusses the increasing amounts of data coming from the power grid, and the need for a tool like FNCS that brings together data, transmission and distribution simulators. Included is a description of the FNCS architecture, and the advantages this new open source tool can bring to grid research and development efforts.

Introducing FNCS: Framework for Network Co-Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

2014-10-23

This video provides a basic overview of the PNNL Future Power Grid Initiative-developed Framework for Network Co-Simulation (FNCS). It discusses the increasing amounts of data coming from the power grid, and the need for a tool like FNCS that brings together data, transmission and distribution simulators. Included is a description of the FNCS architecture, and the advantages this new open source tool can bring to grid research and development efforts.

GRID3O- FAST GENERATION OF MULTILEVEL, THREE-DIMENSIONAL BOUNDARY-CONFORMING O-TYPE COMPUTATIONAL GRIDS

NASA Technical Reports Server (NTRS)

Dulikravich, D. S.

1994-01-01

A fast algorithm has been developed for accurately generating boundary-conforming, three-dimensional consecutively refined computational grids applicable to arbitrary wing-body and axial turbomachinery geometries. This algorithm has been incorporated into the GRID3O computer program. The method employed in GRID3O is based on using an analytic function to generate two-dimensional grids on a number of coaxial axisymmetric surfaces positioned between the centerbody and the outer radial boundary. These grids are of the O-type and are characterized by quasi-orthogonality, geometric periodicity, and an adequate resolution throughout the flow field. Because the built-in nonorthogonal coordinate stretching and shearing cause the grid lines leaving the blade or wing trailing-edge to end at downstream infinity, use of the generated grid simplifies the numerical treatment of three-dimensional trailing vortex sheets. The GRID3O program is written in FORTRAN IV for batch execution and has been implemented on an IBM 370 series computer with a central memory requirement of approximately 450K of 8 bit bytes. The GRID3O program was developed in 1981.

An Object-Oriented Serial DSMC Simulation Package

NASA Astrophysics Data System (ADS)

Liu, Hongli; Cai, Chunpei

2011-05-01

A newly developed three-dimensional direct simulation Monte Carlo (DSMC) simulation package, named GRASP ("Generalized Rarefied gAs Simulation Package"), is reported in this paper. This package utilizes the concept of simulation engine, many C++ features and software design patterns. The package has an open architecture which can benefit further development and maintenance of the code. In order to reduce the engineering time for three-dimensional models, a hybrid grid scheme, combined with a flexible data structure compiled by C++ language, are implemented in this package. This scheme utilizes a local data structure based on the computational cell to achieve high performance on workstation processors. This data structure allows the DSMC algorithm to be very efficiently parallelized with domain decomposition and it provides much flexibility in terms of grid types. This package can utilize traditional structured, unstructured or hybrid grids within the framework of a single code to model arbitrarily complex geometries and to simulate rarefied gas flows. Benchmark test cases indicate that this package has satisfactory accuracy for complex rarefied gas flows.

Towards a centralized Grid Speedometer

NASA Astrophysics Data System (ADS)

Dzhunov, I.; Andreeva, J.; Fajardo, E.; Gutsche, O.; Luyckx, S.; Saiz, P.

2014-06-01

Given the distributed nature of the Worldwide LHC Computing Grid and the way CPU resources are pledged and shared around the globe, Virtual Organizations (VOs) face the challenge of monitoring the use of these resources. For CMS and the operation of centralized workflows, the monitoring of how many production jobs are running and pending in the Glidein WMS production pools is very important. The Dashboard Site Status Board (SSB) provides a very flexible framework to collect, aggregate and visualize data. The CMS production monitoring team uses the SSB to define the metrics that have to be monitored and the alarms that have to be raised. During the integration of CMS production monitoring into the SSB, several enhancements to the core functionality of the SSB were required; They were implemented in a generic way, so that other VOs using the SSB can exploit them. Alongside these enhancements, there were a number of changes to the core of the SSB framework. This paper presents the details of the implementation and the advantages for current and future usage of the new features in SSB.

Spatial services grid

NASA Astrophysics Data System (ADS)

Cao, Jian; Li, Qi; Cheng, Jicheng

2005-10-01

This paper discusses the concept, key technologies and main application of Spatial Services Grid. The technologies of Grid computing and Webservice is playing a revolutionary role in studying the spatial information services. The concept of the SSG (Spatial Services Grid) is put forward based on the SIG (Spatial Information Grid) and OGSA (open grid service architecture). Firstly, the grid computing is reviewed and the key technologies of SIG and their main applications are reviewed. Secondly, the grid computing and three kinds of SIG (in broad sense)--SDG (spatial data grid), SIG (spatial information grid) and SSG (spatial services grid) and their relationships are proposed. Thirdly, the key technologies of the SSG (spatial services grid) is put forward. Finally, three representative applications of SSG (spatial services grid) are discussed. The first application is urban location based services gird, which is a typical spatial services grid and can be constructed on OGSA (Open Grid Services Architecture) and digital city platform. The second application is region sustainable development grid which is the key to the urban development. The third application is Region disaster and emergency management services grid.

Wide-area, real-time monitoring and visualization system

DOEpatents

Budhraja, Vikram S.; Dyer, James D.; Martinez Morales, Carlos A.

2013-03-19

A real-time performance monitoring system for monitoring an electric power grid. The electric power grid has a plurality of grid portions, each grid portion corresponding to one of a plurality of control areas. The real-time performance monitoring system includes a monitor computer for monitoring at least one of reliability metrics, generation metrics, transmission metrics, suppliers metrics, grid infrastructure security metrics, and markets metrics for the electric power grid. The data for metrics being monitored by the monitor computer are stored in a data base, and a visualization of the metrics is displayed on at least one display computer having a monitor. The at least one display computer in one said control area enables an operator to monitor the grid portion corresponding to a different said control area.

Wide-area, real-time monitoring and visualization system

DOEpatents

Budhraja, Vikram S [Los Angeles, CA; Dyer, James D [La Mirada, CA; Martinez Morales, Carlos A [Upland, CA

2011-11-15

A real-time performance monitoring system for monitoring an electric power grid. The electric power grid has a plurality of grid portions, each grid portion corresponding to one of a plurality of control areas. The real-time performance monitoring system includes a monitor computer for monitoring at least one of reliability metrics, generation metrics, transmission metrics, suppliers metrics, grid infrastructure security metrics, and markets metrics for the electric power grid. The data for metrics being monitored by the monitor computer are stored in a data base, and a visualization of the metrics is displayed on at least one display computer having a monitor. The at least one display computer in one said control area enables an operator to monitor the grid portion corresponding to a different said control area.

Real-time performance monitoring and management system

DOEpatents

Budhraja, Vikram S [Los Angeles, CA; Dyer, James D [La Mirada, CA; Martinez Morales, Carlos A [Upland, CA

2007-06-19

A real-time performance monitoring system for monitoring an electric power grid. The electric power grid has a plurality of grid portions, each grid portion corresponding to one of a plurality of control areas. The real-time performance monitoring system includes a monitor computer for monitoring at least one of reliability metrics, generation metrics, transmission metrics, suppliers metrics, grid infrastructure security metrics, and markets metrics for the electric power grid. The data for metrics being monitored by the monitor computer are stored in a data base, and a visualization of the metrics is displayed on at least one display computer having a monitor. The at least one display computer in one said control area enables an operator to monitor the grid portion corresponding to a different said control area.

Grid infrastructure for automatic processing of SAR data for flood applications

NASA Astrophysics Data System (ADS)

Kussul, Natalia; Skakun, Serhiy; Shelestov, Andrii

2010-05-01

More and more geosciences applications are being put on to the Grids. Due to the complexity of geosciences applications that is caused by complex workflow, the use of computationally intensive environmental models, the need of management and integration of heterogeneous data sets, Grid offers solutions to tackle these problems. Many geosciences applications, especially those related to the disaster management and mitigations require the geospatial services to be delivered in proper time. For example, information on flooded areas should be provided to corresponding organizations (local authorities, civil protection agencies, UN agencies etc.) no more than in 24 h to be able to effectively allocate resources required to mitigate the disaster. Therefore, providing infrastructure and services that will enable automatic generation of products based on the integration of heterogeneous data represents the tasks of great importance. In this paper we present Grid infrastructure for automatic processing of synthetic-aperture radar (SAR) satellite images to derive flood products. In particular, we use SAR data acquired by ESA's ENVSAT satellite, and neural networks to derive flood extent. The data are provided in operational mode from ESA rolling archive (within ESA Category-1 grant). We developed a portal that is based on OpenLayers frameworks and provides access point to the developed services. Through the portal the user can define geographical region and search for the required data. Upon selection of data sets a workflow is automatically generated and executed on the resources of Grid infrastructure. For workflow execution and management we use Karajan language. The workflow of SAR data processing consists of the following steps: image calibration, image orthorectification, image processing with neural networks, topographic effects removal, geocoding and transformation to lat/long projection, and visualisation. These steps are executed by different software, and can be executed by different resources of the Grid system. The resulting geospatial services are available in various OGC standards such as KML and WMS. Currently, the Grid infrastructure integrates the resources of several geographically distributed organizations, in particular: Space Research Institute NASU-NSAU (Ukraine) with deployed computational and storage nodes based on Globus Toolkit 4 (htpp://www.globus.org) and gLite 3 (http://glite.web.cern.ch) middleware, access to geospatial data and a Grid portal; Institute of Cybernetics of NASU (Ukraine) with deployed computational and storage nodes (SCIT-1/2/3 clusters) based on Globus Toolkit 4 middleware and access to computational resources (approximately 500 processors); Center of Earth Observation and Digital Earth Chinese Academy of Sciences (CEODE-CAS, China) with deployed computational nodes based on Globus Toolkit 4 middleware and access to geospatial data (approximately 16 processors). We are currently adding new geospatial services based on optical satellite data, namely MODIS. This work is carried out jointly with the CEODE-CAS. Using workflow patterns that were developed for SAR data processing we are building new workflows for optical data processing.

A policy system for Grid Management and Monitoring

NASA Astrophysics Data System (ADS)

Stagni, Federico; Santinelli, Roberto; LHCb Collaboration

2011-12-01

Organizations using a Grid computing model are faced with non-traditional administrative challenges: the heterogeneous nature of the underlying resources requires professionals acting as Grid Administrators. Members of a Virtual Organization (VO) can use a subset of available resources and services in the grid infrastructure and in an ideal world, the more resoures are exploited the better. In the real world, the less faulty services, the better: experienced Grid administrators apply procedures for adding and removing services, based on their status, as it is reported by an ever-growing set of monitoring tools. When a procedure is agreed and well-exercised, a formal policy could be derived. For this reason, using the DIRAC framework in the LHCb collaboration, we developed a policy system that can enforce management and operational policies, in a VO-specific fashion. A single policy makes an assessment on the status of a subject, relative to one or more monitoring information. Subjects of the policies are monitored entities of an established Grid ontology. The status of a same entity is evaluated against a number of policies, whose results are then combined by a Policy Decision Point. Such results are enforced in a Policy Enforcing Point, which provides plug-ins for actions, like raising alarms, sending notifications, automatic addition and removal of services and resources from the Grid mask. Policy results are shown in the web portal, and site-specific views are provided also. This innovative system provides advantages in terms of procedures automation, information aggregation and problem solving.

75 FR 63462 - Smart Grid Interoperability Standards; Notice of Docket Designation for Smart Grid...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-15

... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Docket No. RM11-2-000] Smart Grid Interoperability Standards; Notice of Docket Designation for Smart Grid Interoperability Standards October 7, 2010... directs the development of a framework to achieve interoperability of smart grid devices and systems...

System and method for design and optimization of grid connected photovoltaic power plant with multiple photovoltaic module technologies

DOEpatents

Thomas, Bex George; Elasser, Ahmed; Bollapragada, Srinivas; Galbraith, Anthony William; Agamy, Mohammed; Garifullin, Maxim Valeryevich

2016-03-29

A system and method of using one or more DC-DC/DC-AC converters and/or alternative devices allows strings of multiple module technologies to coexist within the same PV power plant. A computing (optimization) framework estimates the percentage allocation of PV power plant capacity to selected PV module technologies. The framework and its supporting components considers irradiation, temperature, spectral profiles, cost and other practical constraints to achieve the lowest levelized cost of electricity, maximum output and minimum system cost. The system and method can function using any device enabling distributed maximum power point tracking at the module, string or combiner level.

Geometry definition and grid generation for a complete fighter aircraft

NASA Technical Reports Server (NTRS)

Edwards, T. A.

1986-01-01

Recent advances in computing power and numerical solution procedures have enabled computational fluid dynamicists to attempt increasingly difficult problems. In particular, efforts are focusing on computations of complex three-dimensional flow fields about realistic aerodynamic bodies. To perform such computations, a very accurate and detailed description of the surface geometry must be provided, and a three-dimensional grid must be generated in the space around the body. The geometry must be supplied in a format compatible with the grid generation requirements, and must be verified to be free of inconsistencies. This paper presents a procedure for performing the geometry definition of a fighter aircraft that makes use of a commercial computer-aided design/computer-aided manufacturing system. Furthermore, visual representations of the geometry are generated using a computer graphics system for verification of the body definition. Finally, the three-dimensional grids for fighter-like aircraft are generated by means of an efficient new parabolic grid generation method. This method exhibits good control of grid quality.

Geometry definition and grid generation for a complete fighter aircraft

NASA Technical Reports Server (NTRS)

Edwards, Thomas A.

1986-01-01

Recent advances in computing power and numerical solution procedures have enabled computational fluid dynamicists to attempt increasingly difficult problems. In particular, efforts are focusing on computations of complex three-dimensional flow fields about realistic aerodynamic bodies. To perform such computations, a very accurate and detailed description of the surface geometry must be provided, and a three-dimensional grid must be generated in the space around the body. The geometry must be supplied in a format compatible with the grid generation requirements, and must be verified to be free of inconsistencies. A procedure for performing the geometry definition of a fighter aircraft that makes use of a commercial computer-aided design/computer-aided manufacturing system is presented. Furthermore, visual representations of the geometry are generated using a computer graphics system for verification of the body definition. Finally, the three-dimensional grids for fighter-like aircraft are generated by means of an efficient new parabolic grid generation method. This method exhibits good control of grid quality.

The LHCb Grid Simulation: Proof of Concept

NASA Astrophysics Data System (ADS)

Hushchyn, M.; Ustyuzhanin, A.; Arzymatov, K.; Roiser, S.; Baranov, A.

2017-10-01

The Worldwide LHC Computing Grid provides access to data and computational resources to analyze it for researchers with different geographical locations. The grid has a hierarchical topology with multiple sites distributed over the world with varying number of CPUs, amount of disk storage and connection bandwidth. Job scheduling and data distribution strategy are key elements of grid performance. Optimization of algorithms for those tasks requires their testing on real grid which is hard to achieve. Having a grid simulator might simplify this task and therefore lead to more optimal scheduling and data placement algorithms. In this paper we demonstrate a grid simulator for the LHCb distributed computing software.

Cloud computing for energy management in smart grid - an application survey

NASA Astrophysics Data System (ADS)

Naveen, P.; Kiing Ing, Wong; Kobina Danquah, Michael; Sidhu, Amandeep S.; Abu-Siada, Ahmed

2016-03-01

The smart grid is the emerging energy system wherein the application of information technology, tools and techniques that make the grid run more efficiently. It possesses demand response capacity to help balance electrical consumption with supply. The challenges and opportunities of emerging and future smart grids can be addressed by cloud computing. To focus on these requirements, we provide an in-depth survey on different cloud computing applications for energy management in the smart grid architecture. In this survey, we present an outline of the current state of research on smart grid development. We also propose a model of cloud based economic power dispatch for smart grid.

Integrated geometry and grid generation system for complex configurations

NASA Technical Reports Server (NTRS)

Akdag, Vedat; Wulf, Armin

1992-01-01

A grid generation system was developed that enables grid generation for complex configurations. The system called ICEM/CFD is described and its role in computational fluid dynamics (CFD) applications is presented. The capabilities of the system include full computer aided design (CAD), grid generation on the actual CAD geometry definition using robust surface projection algorithms, interfacing easily with known CAD packages through common file formats for geometry transfer, grid quality evaluation of the volume grid, coupling boundary condition set-up for block faces with grid topology generation, multi-block grid generation with or without point continuity and block to block interface requirement, and generating grid files directly compatible with known flow solvers. The interactive and integrated approach to the problem of computational grid generation not only substantially reduces manpower time but also increases the flexibility of later grid modifications and enhancements which is required in an environment where CFD is integrated into a product design cycle.

Enabling campus grids with open science grid technology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weitzel, Derek; Bockelman, Brian; Swanson, David

2011-01-01

The Open Science Grid is a recognized key component of the US national cyber-infrastructure enabling scientific discovery through advanced high throughput computing. The principles and techniques that underlie the Open Science Grid can also be applied to Campus Grids since many of the requirements are the same, even if the implementation technologies differ. We find five requirements for a campus grid: trust relationships, job submission, resource independence, accounting, and data management. The Holland Computing Center's campus grid at the University of Nebraska-Lincoln was designed to fulfill the requirements of a campus grid. A bridging daemon was designed to bring non-Condormore » clusters into a grid managed by Condor. Condor features which make it possible to bridge Condor sites into a multi-campus grid have been exploited at the Holland Computing Center as well.« less

Anisotropic three-dimensional inversion of CSEM data using finite-element techniques on unstructured grids

NASA Astrophysics Data System (ADS)

Wang, Feiyan; Morten, Jan Petter; Spitzer, Klaus

2018-05-01

In this paper, we present a recently developed anisotropic 3-D inversion framework for interpreting controlled-source electromagnetic (CSEM) data in the frequency domain. The framework integrates a high-order finite-element forward operator and a Gauss-Newton inversion algorithm. Conductivity constraints are applied using a parameter transformation. We discretize the continuous forward and inverse problems on unstructured grids for a flexible treatment of arbitrarily complex geometries. Moreover, an unstructured mesh is more desirable in comparison to a single rectilinear mesh for multisource problems because local grid refinement will not significantly influence the mesh density outside the region of interest. The non-uniform spatial discretization facilitates parametrization of the inversion domain at a suitable scale. For a rapid simulation of multisource EM data, we opt to use a parallel direct solver. We further accelerate the inversion process by decomposing the entire data set into subsets with respect to frequencies (and transmitters if memory requirement is affordable). The computational tasks associated with each data subset are distributed to different processes and run in parallel. We validate the scheme using a synthetic marine CSEM model with rough bathymetry, and finally, apply it to an industrial-size 3-D data set from the Troll field oil province in the North Sea acquired in 2008 to examine its robustness and practical applicability.

Theoretical Framework for Integrating Distributed Energy Resources into Distribution Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lian, Jianming; Wu, Di; Kalsi, Karanjit

This paper focuses on developing a novel theoretical framework for effective coordination and control of a large number of distributed energy resources in distribution systems in order to more reliably manage the future U.S. electric power grid under the high penetration of renewable generation. The proposed framework provides a systematic view of the overall structure of the future distribution systems along with the underlying information flow, functional organization, and operational procedures. It is characterized by the features of being open, flexible and interoperable with the potential to support dynamic system configuration. Under the proposed framework, the energy consumption of variousmore » DERs is coordinated and controlled in a hierarchical way by using market-based approaches. The real-time voltage control is simultaneously considered to complement the real power control in order to keep nodal voltages stable within acceptable ranges during real time. In addition, computational challenges associated with the proposed framework are also discussed with recommended practices.« less

Open-source framework for power system transmission and distribution dynamics co-simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Renke; Fan, Rui; Daily, Jeff

The promise of the smart grid entails more interactions between the transmission and distribution networks, and there is an immediate need for tools to provide the comprehensive modelling and simulation required to integrate operations at both transmission and distribution levels. Existing electromagnetic transient simulators can perform simulations with integration of transmission and distribution systems, but the computational burden is high for large-scale system analysis. For transient stability analysis, currently there are only separate tools for simulating transient dynamics of the transmission and distribution systems. In this paper, we introduce an open source co-simulation framework “Framework for Network Co-Simulation” (FNCS), togethermore » with the decoupled simulation approach that links existing transmission and distribution dynamic simulators through FNCS. FNCS is a middleware interface and framework that manages the interaction and synchronization of the transmission and distribution simulators. Preliminary testing results show the validity and capability of the proposed open-source co-simulation framework and the decoupled co-simulation methodology.« less

Parametric Geometry, Structured Grid Generation, and Initial Design Study for REST-Class Hypersonic Inlets

NASA Technical Reports Server (NTRS)

Ferlemann, Paul G.; Gollan, Rowan J.

2010-01-01

Computational design and analysis of three-dimensional hypersonic inlets with shape transition has been a significant challenge due to the complex geometry and grid required for three-dimensional viscous flow calculations. Currently, the design process utilizes an inviscid design tool to produce initial inlet shapes by streamline tracing through an axisymmetric compression field. However, the shape is defined by a large number of points rather than a continuous surface and lacks important features such as blunt leading edges. Therefore, a design system has been developed to parametrically construct true CAD geometry and link the topology of a structured grid to the geometry. The Adaptive Modeling Language (AML) constitutes the underlying framework that is used to build the geometry and grid topology. Parameterization of the CAD geometry allows the inlet shapes produced by the inviscid design tool to be generated, but also allows a great deal of flexibility to modify the shape to account for three-dimensional viscous effects. By linking the grid topology to the parametric geometry, the GridPro grid generation software can be used efficiently to produce a smooth hexahedral multiblock grid. To demonstrate the new capability, a matrix of inlets were designed by varying four geometry parameters in the inviscid design tool. The goals of the initial design study were to explore inviscid design tool geometry variations with a three-dimensional analysis approach, demonstrate a solution rate which would enable the use of high-fidelity viscous three-dimensional CFD in future design efforts, process the results for important performance parameters, and perform a sample optimization.

HOMAR: A computer code for generating homotopic grids using algebraic relations: User's manual

NASA Technical Reports Server (NTRS)

Moitra, Anutosh

1989-01-01

A computer code for fast automatic generation of quasi-three-dimensional grid systems for aerospace configurations is described. The code employs a homotopic method to algebraically generate two-dimensional grids in cross-sectional planes, which are stacked to produce a three-dimensional grid system. Implementation of the algebraic equivalents of the homotopic relations for generating body geometries and grids are explained. Procedures for controlling grid orthogonality and distortion are described. Test cases with description and specification of inputs are presented in detail. The FORTRAN computer program and notes on implementation and use are included.

[Research on tumor information grid framework].

PubMed

Zhang, Haowei; Qin, Zhu; Liu, Ying; Tan, Jianghao; Cao, Haitao; Chen, Youping; Zhang, Ke; Ding, Yuqing

2013-10-01

In order to realize tumor disease information sharing and unified management, we utilized grid technology to make the data and software resources which distributed in various medical institutions for effective integration so that we could make the heterogeneous resources consistent and interoperable in both semantics and syntax aspects. This article describes the tumor grid framework, the type of the service being packaged in Web Service Description Language (WSDL) and extensible markup language schemas definition (XSD), the client use the serialized document to operate the distributed resources. The service objects could be built by Unified Modeling Language (UML) as middle ware to create application programming interface. All of the grid resources are registered in the index and released in the form of Web Services based on Web Services Resource Framework (WSRF). Using the system we can build a multi-center, large sample and networking tumor disease resource sharing framework to improve the level of development in medical scientific research institutions and the patient's quality of life.

Numerical Nuclear Second Derivatives on a Computing Grid: Enabling and Accelerating Frequency Calculations on Complex Molecular Systems.

PubMed

Yang, Tzuhsiung; Berry, John F

2018-06-04

The computation of nuclear second derivatives of energy, or the nuclear Hessian, is an essential routine in quantum chemical investigations of ground and transition states, thermodynamic calculations, and molecular vibrations. Analytic nuclear Hessian computations require the resolution of costly coupled-perturbed self-consistent field (CP-SCF) equations, while numerical differentiation of analytic first derivatives has an unfavorable 6 N ( N = number of atoms) prefactor. Herein, we present a new method in which grid computing is used to accelerate and/or enable the evaluation of the nuclear Hessian via numerical differentiation: NUMFREQ@Grid. Nuclear Hessians were successfully evaluated by NUMFREQ@Grid at the DFT level as well as using RIJCOSX-ZORA-MP2 or RIJCOSX-ZORA-B2PLYP for a set of linear polyacenes with systematically increasing size. For the larger members of this group, NUMFREQ@Grid was found to outperform the wall clock time of analytic Hessian evaluation; at the MP2 or B2LYP levels, these Hessians cannot even be evaluated analytically. We also evaluated a 156-atom catalytically relevant open-shell transition metal complex and found that NUMFREQ@Grid is faster (7.7 times shorter wall clock time) and less demanding (4.4 times less memory requirement) than an analytic Hessian. Capitalizing on the capabilities of parallel grid computing, NUMFREQ@Grid can outperform analytic methods in terms of wall time, memory requirements, and treatable system size. The NUMFREQ@Grid method presented herein demonstrates how grid computing can be used to facilitate embarrassingly parallel computational procedures and is a pioneer for future implementations.

ooi: OpenStack OCCI interface

NASA Astrophysics Data System (ADS)

López García, Álvaro; Fernández del Castillo, Enol; Orviz Fernández, Pablo

In this document we present an implementation of the Open Grid Forum's Open Cloud Computing Interface (OCCI) for OpenStack, namely ooi (Openstack occi interface, 2015) [1]. OCCI is an open standard for management tasks over cloud resources, focused on interoperability, portability and integration. ooi aims to implement this open interface for the OpenStack cloud middleware, promoting interoperability with other OCCI-enabled cloud management frameworks and infrastructures. ooi focuses on being non-invasive with a vanilla OpenStack installation, not tied to a particular OpenStack release version.

Monitoring of services with non-relational databases and map-reduce framework

NASA Astrophysics Data System (ADS)

Babik, M.; Souto, F.

2012-12-01

Service Availability Monitoring (SAM) is a well-established monitoring framework that performs regular measurements of the core site services and reports the corresponding availability and reliability of the Worldwide LHC Computing Grid (WLCG) infrastructure. One of the existing extensions of SAM is Site Wide Area Testing (SWAT), which gathers monitoring information from the worker nodes via instrumented jobs. This generates quite a lot of monitoring data to process, as there are several data points for every job and several million jobs are executed every day. The recent uptake of non-relational databases opens a new paradigm in the large-scale storage and distributed processing of systems with heavy read-write workloads. For SAM this brings new possibilities to improve its model, from performing aggregation of measurements to storing raw data and subsequent re-processing. Both SAM and SWAT are currently tuned to run at top performance, reaching some of the limits in storage and processing power of their existing Oracle relational database. We investigated the usability and performance of non-relational storage together with its distributed data processing capabilities. For this, several popular systems have been compared. In this contribution we describe our investigation of the existing non-relational databases suited for monitoring systems covering Cassandra, HBase and MongoDB. Further, we present our experiences in data modeling and prototyping map-reduce algorithms focusing on the extension of the already existing availability and reliability computations. Finally, possible future directions in this area are discussed, analyzing the current deficiencies of the existing Grid monitoring systems and proposing solutions to leverage the benefits of the non-relational databases to get more scalable and flexible frameworks.

Synchrotron Imaging Computations on the Grid without the Computing Element

NASA Astrophysics Data System (ADS)

Curri, A.; Pugliese, R.; Borghes, R.; Kourousias, G.

2011-12-01

Besides the heavy use of the Grid in the Synchrotron Radiation Facility (SRF) Elettra, additional special requirements from the beamlines had to be satisfied through a novel solution that we present in this work. In the traditional Grid Computing paradigm the computations are performed on the Worker Nodes of the grid element known as the Computing Element. A Grid middleware extension that our team has been working on, is that of the Instrument Element. In general it is used to Grid-enable instrumentation; and it can be seen as a neighbouring concept to that of the traditional Control Systems. As a further extension we demonstrate the Instrument Element as the steering mechanism for a series of computations. In our deployment it interfaces a Control System that manages a series of computational demanding Scientific Imaging tasks in an online manner. The instrument control in Elettra is done through a suitable Distributed Control System, a common approach in the SRF community. The applications that we present are for a beamline working in medical imaging. The solution resulted to a substantial improvement of a Computed Tomography workflow. The near-real-time requirements could not have been easily satisfied from our Grid's middleware (gLite) due to the various latencies often occurred during the job submission and queuing phases. Moreover the required deployment of a set of TANGO devices could not have been done in a standard gLite WN. Besides the avoidance of certain core Grid components, the Grid Security infrastructure has been utilised in the final solution.

Semantic Interoperability for Computational Mineralogy: Experiences of the eMinerals Consortium

NASA Astrophysics Data System (ADS)

Walker, A. M.; White, T. O.; Dove, M. T.; Bruin, R. P.; Couch, P. A.; Tyer, R. P.

2006-12-01

The use of atomic scale computer simulation of minerals to obtain information for geophysics and environmental science has grown enormously over the past couple of decades. It is now routine to probe mineral behavior in the Earth's deep interior and in the surface environment by borrowing methods and simulation codes from computational chemistry and physics. It is becoming increasingly important to use methods embodied in more than one of these codes to solve any single scientific problem. However, scientific codes are rarely designed for easy interoperability and data exchange; data formats are often code-specific, poorly documented and fragile, liable to frequent change between software versions, and even compiler versions. This means that the scientist's simple desire to use the methodological approaches offered by multiple codes is frustrated, and even the sharing of data between collaborators becomes fraught with difficulties. The eMinerals consortium was formed in the early stages of the UK eScience program with the aim of developing the tools needed to apply atomic scale simulation to environmental problems in a grid-enabled world, and to harness the computational power offered by grid technologies to address some outstanding mineralogical problems. One example of the kind of problem we can tackle is the origin of the compressibility anomaly in silica glass. By passing data directly between simulation and analysis tools we were able to probe this effect in more detail than has previously been possible and have shown how the anomaly is related to the details of the amorphous structure. In order to approach this kind of problem we have constructed a mini-grid, a small scale and extensible combined compute- and data-grid that allows the execution of many calculations in parallel, and the transparent storage of semantically-rich marked-up result data. Importantly, we automatically capture multiple kinds of metadata and key results from each calculation. We believe that the lessons learned and tools developed will be useful in many areas of science beyond the computational mineralogy. Key tools that will be described include: a pure Fortran XML library (FoX) that presents XPath, SAX and DOM interfaces as well as permitting the easy production of valid XML from legacy Fortran programs; a job submission framework that automatically schedules calculations to remote grid resources, handles data staging and metadata capture; and a tool (AgentX) that map concepts from an ontology onto locations in documents of various formats that we use to enable data exchange.

A sparse grid based method for generative dimensionality reduction of high-dimensional data

NASA Astrophysics Data System (ADS)

Bohn, Bastian; Garcke, Jochen; Griebel, Michael

2016-03-01

Generative dimensionality reduction methods play an important role in machine learning applications because they construct an explicit mapping from a low-dimensional space to the high-dimensional data space. We discuss a general framework to describe generative dimensionality reduction methods, where the main focus lies on a regularized principal manifold learning variant. Since most generative dimensionality reduction algorithms exploit the representer theorem for reproducing kernel Hilbert spaces, their computational costs grow at least quadratically in the number n of data. Instead, we introduce a grid-based discretization approach which automatically scales just linearly in n. To circumvent the curse of dimensionality of full tensor product grids, we use the concept of sparse grids. Furthermore, in real-world applications, some embedding directions are usually more important than others and it is reasonable to refine the underlying discretization space only in these directions. To this end, we employ a dimension-adaptive algorithm which is based on the ANOVA (analysis of variance) decomposition of a function. In particular, the reconstruction error is used to measure the quality of an embedding. As an application, the study of large simulation data from an engineering application in the automotive industry (car crash simulation) is performed.

Network gateway security method for enterprise Grid: a literature review

NASA Astrophysics Data System (ADS)

Sujarwo, A.; Tan, J.

2017-03-01

The computational Grid has brought big computational resources closer to scientists. It enables people to do a large computational job anytime and anywhere without any physical border anymore. However, the massive and spread of computer participants either as user or computational provider arise problems in security. The challenge is on how the security system, especially the one which filters data in the gateway could works in flexibility depends on the registered Grid participants. This paper surveys what people have done to approach this challenge, in order to find the better and new method for enterprise Grid. The findings of this paper is the dynamically controlled enterprise firewall to secure the Grid resources from unwanted connections with a new firewall controlling method and components.

Processing of the WLCG monitoring data using NoSQL

NASA Astrophysics Data System (ADS)

Andreeva, J.; Beche, A.; Belov, S.; Dzhunov, I.; Kadochnikov, I.; Karavakis, E.; Saiz, P.; Schovancova, J.; Tuckett, D.

2014-06-01

The Worldwide LHC Computing Grid (WLCG) today includes more than 150 computing centres where more than 2 million jobs are being executed daily and petabytes of data are transferred between sites. Monitoring the computing activities of the LHC experiments, over such a huge heterogeneous infrastructure, is extremely demanding in terms of computation, performance and reliability. Furthermore, the generated monitoring flow is constantly increasing, which represents another challenge for the monitoring systems. While existing solutions are traditionally based on Oracle for data storage and processing, recent developments evaluate NoSQL for processing large-scale monitoring datasets. NoSQL databases are getting increasingly popular for processing datasets at the terabyte and petabyte scale using commodity hardware. In this contribution, the integration of NoSQL data processing in the Experiment Dashboard framework is described along with first experiences of using this technology for monitoring the LHC computing activities.

Using an Adjoint Approach to Eliminate Mesh Sensitivities in Computational Design

NASA Technical Reports Server (NTRS)

Nielsen, Eric J.; Park, Michael A.

2006-01-01

An algorithm for efficiently incorporating the effects of mesh sensitivities in a computational design framework is introduced. The method is based on an adjoint approach and eliminates the need for explicit linearizations of the mesh movement scheme with respect to the geometric parameterization variables, an expense that has hindered practical large-scale design optimization using discrete adjoint methods. The effects of the mesh sensitivities can be accounted for through the solution of an adjoint problem equivalent in cost to a single mesh movement computation, followed by an explicit matrix-vector product scaling with the number of design variables and the resolution of the parameterized surface grid. The accuracy of the implementation is established and dramatic computational savings obtained using the new approach are demonstrated using several test cases. Sample design optimizations are also shown.

Using an Adjoint Approach to Eliminate Mesh Sensitivities in Computational Design

NASA Technical Reports Server (NTRS)

Nielsen, Eric J.; Park, Michael A.

2005-01-01

An algorithm for efficiently incorporating the effects of mesh sensitivities in a computational design framework is introduced. The method is based on an adjoint approach and eliminates the need for explicit linearizations of the mesh movement scheme with respect to the geometric parameterization variables, an expense that has hindered practical large-scale design optimization using discrete adjoint methods. The effects of the mesh sensitivities can be accounted for through the solution of an adjoint problem equivalent in cost to a single mesh movement computation, followed by an explicit matrix-vector product scaling with the number of design variables and the resolution of the parameterized surface grid. The accuracy of the implementation is established and dramatic computational savings obtained using the new approach are demonstrated using several test cases. Sample design optimizations are also shown.

The Adoption of Grid Computing Technology by Organizations: A Quantitative Study Using Technology Acceptance Model

ERIC Educational Resources Information Center

Udoh, Emmanuel E.

2010-01-01

Advances in grid technology have enabled some organizations to harness enormous computational power on demand. However, the prediction of widespread adoption of the grid technology has not materialized despite the obvious grid advantages. This situation has encouraged intense efforts to close the research gap in the grid adoption process. In this…

A Debugger for Computational Grid Applications

NASA Technical Reports Server (NTRS)

Hood, Robert; Jost, Gabriele; Biegel, Bryan (Technical Monitor)

2001-01-01

This viewgraph presentation gives an overview of a debugger for computational grid applications. Details are given on NAS parallel tools groups (including parallelization support tools, evaluation of various parallelization strategies, and distributed and aggregated computing), debugger dependencies, scalability, initial implementation, the process grid, and information on Globus.

A Development of Lightweight Grid Interface

NASA Astrophysics Data System (ADS)

Iwai, G.; Kawai, Y.; Sasaki, T.; Watase, Y.

2011-12-01

In order to help a rapid development of Grid/Cloud aware applications, we have developed API to abstract the distributed computing infrastructures based on SAGA (A Simple API for Grid Applications). SAGA, which is standardized in the OGF (Open Grid Forum), defines API specifications to access distributed computing infrastructures, such as Grid, Cloud and local computing resources. The Universal Grid API (UGAPI), which is a set of command line interfaces (CLI) and APIs, aims to offer simpler API to combine several SAGA interfaces with richer functionalities. These CLIs of the UGAPI offer typical functionalities required by end users for job management and file access to the different distributed computing infrastructures as well as local computing resources. We have also built a web interface for the particle therapy simulation and demonstrated the large scale calculation using the different infrastructures at the same time. In this paper, we would like to present how the web interface based on UGAPI and SAGA achieve more efficient utilization of computing resources over the different infrastructures with technical details and practical experiences.

Fast Geostatistical Inversion using Randomized Matrix Decompositions and Sketchings for Heterogeneous Aquifer Characterization

NASA Astrophysics Data System (ADS)

O'Malley, D.; Le, E. B.; Vesselinov, V. V.

2015-12-01

We present a fast, scalable, and highly-implementable stochastic inverse method for characterization of aquifer heterogeneity. The method utilizes recent advances in randomized matrix algebra and exploits the structure of the Quasi-Linear Geostatistical Approach (QLGA), without requiring a structured grid like Fast-Fourier Transform (FFT) methods. The QLGA framework is a more stable version of Gauss-Newton iterates for a large number of unknown model parameters, but provides unbiased estimates. The methods are matrix-free and do not require derivatives or adjoints, and are thus ideal for complex models and black-box implementation. We also incorporate randomized least-square solvers and data-reduction methods, which speed up computation and simulate missing data points. The new inverse methodology is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). Julia is an advanced high-level scientific programing language that allows for efficient memory management and utilization of high-performance computational resources. Inversion results based on series of synthetic problems with steady-state and transient calibration data are presented.

Running ATLAS workloads within massively parallel distributed applications using Athena Multi-Process framework (AthenaMP)

NASA Astrophysics Data System (ADS)

Calafiura, Paolo; Leggett, Charles; Seuster, Rolf; Tsulaia, Vakhtang; Van Gemmeren, Peter

2015-12-01

AthenaMP is a multi-process version of the ATLAS reconstruction, simulation and data analysis framework Athena. By leveraging Linux fork and copy-on-write mechanisms, it allows for sharing of memory pages between event processors running on the same compute node with little to no change in the application code. Originally targeted to optimize the memory footprint of reconstruction jobs, AthenaMP has demonstrated that it can reduce the memory usage of certain configurations of ATLAS production jobs by a factor of 2. AthenaMP has also evolved to become the parallel event-processing core of the recently developed ATLAS infrastructure for fine-grained event processing (Event Service) which allows the running of AthenaMP inside massively parallel distributed applications on hundreds of compute nodes simultaneously. We present the architecture of AthenaMP, various strategies implemented by AthenaMP for scheduling workload to worker processes (for example: Shared Event Queue and Shared Distributor of Event Tokens) and the usage of AthenaMP in the diversity of ATLAS event processing workloads on various computing resources: Grid, opportunistic resources and HPC.

Data Management System for the National Energy-Water System (NEWS) Assessment Framework

NASA Astrophysics Data System (ADS)

Corsi, F.; Prousevitch, A.; Glidden, S.; Piasecki, M.; Celicourt, P.; Miara, A.; Fekete, B. M.; Vorosmarty, C. J.; Macknick, J.; Cohen, S. M.

2015-12-01

Aiming at providing a comprehensive assessment of the water-energy nexus, the National Energy-Water System (NEWS) project requires the integration of data to support a modeling framework that links climate, hydrological, power production, transmission, and economical models. Large amounts of Georeferenced data has to be streamed to the components of the inter-disciplinary model to explore future challenges and tradeoffs in the US power production, based on climate scenarios, power plant locations and technologies, available water resources, ecosystem sustainability, and economic demand. We used open source and in-house build software components to build a system that addresses two major data challenges: On-the-fly re-projection, re-gridding, interpolation, extrapolation, nodata patching, merging, temporal and spatial aggregation, of static and time series datasets in virtually any file formats and file structures, and any geographic extent for the models I/O, directly at run time; Comprehensive data management based on metadata cataloguing and discovery in repositories utilizing the MAGIC Table (Manipulation and Geographic Inquiry Control database). This innovative concept allows models to access data on-the-fly by data ID, irrespective of file path, file structure, file format and regardless its GIS specifications. In addition, a web-based information and computational system is being developed to control the I/O of spatially distributed Earth system, climate, and hydrological, power grid, and economical data flow within the NEWS framework. The system allows scenario building, data exploration, visualization, querying, and manipulation any loaded gridded, point, and vector polygon dataset. The system has demonstrated its potential for applications in other fields of Earth science modeling, education, and outreach. Over time, this implementation of the system will provide near real-time assessment of various current and future scenarios of the water-energy nexus.

GLAD: a system for developing and deploying large-scale bioinformatics grid.

PubMed

Teo, Yong-Meng; Wang, Xianbing; Ng, Yew-Kwong

2005-03-01

Grid computing is used to solve large-scale bioinformatics problems with gigabytes database by distributing the computation across multiple platforms. Until now in developing bioinformatics grid applications, it is extremely tedious to design and implement the component algorithms and parallelization techniques for different classes of problems, and to access remotely located sequence database files of varying formats across the grid. In this study, we propose a grid programming toolkit, GLAD (Grid Life sciences Applications Developer), which facilitates the development and deployment of bioinformatics applications on a grid. GLAD has been developed using ALiCE (Adaptive scaLable Internet-based Computing Engine), a Java-based grid middleware, which exploits the task-based parallelism. Two bioinformatics benchmark applications, such as distributed sequence comparison and distributed progressive multiple sequence alignment, have been developed using GLAD.

Automated Euler and Navier-Stokes Database Generation for a Glide-Back Booster

NASA Technical Reports Server (NTRS)

Chaderjian, Neal M.; Rogers, Stuart E.; Aftosmis, Mike J.; Pandya, Shishir A.; Ahmad, Jasim U.; Tejnil, Edward

2004-01-01

The past two decades have seen a sustained increase in the use of high fidelity Computational Fluid Dynamics (CFD) in basic research, aircraft design, and the analysis of post-design issues. As the fidelity of a CFD method increases, the number of cases that can be readily and affordably computed greatly diminishes. However, computer speeds now exceed 2 GHz, hundreds of processors are currently available and more affordable, and advances in parallel CFD algorithms scale more readily with large numbers of processors. All of these factors make it feasible to compute thousands of high fidelity cases. However, there still remains the overwhelming task of monitoring the solution process. This paper presents an approach to automate the CFD solution process. A new software tool, AeroDB, is used to compute thousands of Euler and Navier-Stokes solutions for a 2nd generation glide-back booster in one week. The solution process exploits a common job-submission grid environment, the NASA Information Power Grid (IPG), using 13 computers located at 4 different geographical sites. Process automation and web-based access to a MySql database greatly reduces the user workload, removing much of the tedium and tendency for user input errors. The AeroDB framework is shown. The user submits/deletes jobs, monitors AeroDB's progress, and retrieves data and plots via a web portal. Once a job is in the database, a job launcher uses an IPG resource broker to decide which computers are best suited to run the job. Job/code requirements, the number of CPUs free on a remote system, and queue lengths are some of the parameters the broker takes into account. The Globus software provides secure services for user authentication, remote shell execution, and secure file transfers over an open network. AeroDB automatically decides when a job is completed. Currently, the Cart3D unstructured flow solver is used for the Euler equations, and the Overflow structured overset flow solver is used for the Navier-Stokes equations. Other codes can be readily included into the AeroDB framework.

CAGI: Computer Aided Grid Interface. A work in progress

NASA Technical Reports Server (NTRS)

Soni, Bharat K.; Yu, Tzu-Yi; Vaughn, David

1992-01-01

Progress realized in the development of a Computer Aided Grid Interface (CAGI) software system in integrating CAD/CAM geometric system output and/or Interactive Graphics Exchange Standard (IGES) files, geometry manipulations associated with grid generation, and robust grid generation methodologies is presented. CAGI is being developed in a modular fashion and will offer fast, efficient and economical response to geometry/grid preparation, allowing the ability to upgrade basic geometry in a step-by-step fashion interactively and under permanent visual control along with minimizing the differences between the actual hardware surface descriptions and corresponding numerical analog. The computer code GENIE is used as a basis. The Non-Uniform Rational B-Splines (NURBS) representation of sculptured surfaces is utilized for surface grid redistribution. The computer aided analysis system, PATRAN, is adapted as a CAD/CAM system. The progress realized in NURBS surface grid generation, the development of IGES transformer, and geometry adaption using PATRAN will be presented along with their applicability to grid generation associated with rocket propulsion applications.

Error Estimates of the Ares I Computed Turbulent Ascent Longitudinal Aerodynamic Analysis

NASA Technical Reports Server (NTRS)

Abdol-Hamid, Khaled S.; Ghaffari, Farhad

2012-01-01

Numerical predictions of the longitudinal aerodynamic characteristics for the Ares I class of vehicles, along with the associated error estimate derived from an iterative convergence grid refinement, are presented. Computational results are based on an unstructured grid, Reynolds-averaged Navier-Stokes analysis. The validity of the approach to compute the associated error estimates, derived from a base grid to an extrapolated infinite-size grid, was first demonstrated on a sub-scaled wind tunnel model at representative ascent flow conditions for which the experimental data existed. Such analysis at the transonic flow conditions revealed a maximum deviation of about 23% between the computed longitudinal aerodynamic coefficients with the base grid and the measured data across the entire roll angles. This maximum deviation from the wind tunnel data was associated with the computed normal force coefficient at the transonic flow condition and was reduced to approximately 16% based on the infinite-size grid. However, all the computed aerodynamic coefficients with the base grid at the supersonic flow conditions showed a maximum deviation of only about 8% with that level being improved to approximately 5% for the infinite-size grid. The results and the error estimates based on the established procedure are also presented for the flight flow conditions.

A Public Health Grid (PHGrid): Architecture and value proposition for 21st century public health.

PubMed

Savel, T; Hall, K; Lee, B; McMullin, V; Miles, M; Stinn, J; White, P; Washington, D; Boyd, T; Lenert, L

2010-07-01

This manuscript describes the value of and proposal for a high-level architectural framework for a Public Health Grid (PHGrid), which the authors feel has the capability to afford the public health community a robust technology infrastructure for secure and timely data, information, and knowledge exchange, not only within the public health domain, but between public health and the overall health care system. The CDC facilitated multiple Proof-of-Concept (PoC) projects, leveraging an open-source-based software development methodology, to test four hypotheses with regard to this high-level framework. The outcomes of the four PoCs in combination with the use of the Federal Enterprise Architecture Framework (FEAF) and the newly emerging Federal Segment Architecture Methodology (FSAM) was used to develop and refine a high-level architectural framework for a Public Health Grid infrastructure. The authors were successful in documenting a robust high-level architectural framework for a PHGrid. The documentation generated provided a level of granularity needed to validate the proposal, and included examples of both information standards and services to be implemented. Both the results of the PoCs as well as feedback from selected public health partners were used to develop the granular documentation. A robust high-level cohesive architectural framework for a Public Health Grid (PHGrid) has been successfully articulated, with its feasibility demonstrated via multiple PoCs. In order to successfully implement this framework for a Public Health Grid, the authors recommend moving forward with a three-pronged approach focusing on interoperability and standards, streamlining the PHGrid infrastructure, and developing robust and high-impact public health services. Published by Elsevier Ireland Ltd.

Simulation of an Isolated Tiltrotor in Hover with an Unstructured Overset-Grid RANS Solver

NASA Technical Reports Server (NTRS)

Lee-Rausch, Elizabeth M.; Biedron, Robert T.

2009-01-01

An unstructured overset-grid Reynolds Averaged Navier-Stokes (RANS) solver, FUN3D, is used to simulate an isolated tiltrotor in hover. An overview of the computational method is presented as well as the details of the overset-grid systems. Steady-state computations within a noninertial reference frame define the performance trends of the rotor across a range of the experimental collective settings. Results are presented to show the effects of off-body grid refinement and blade grid refinement. The computed performance and blade loading trends show good agreement with experimental results and previously published structured overset-grid computations. Off-body flow features indicate a significant improvement in the resolution of the first perpendicular blade vortex interaction with background grid refinement across the collective range. Considering experimental data uncertainty and effects of transition, the prediction of figure of merit on the baseline and refined grid is reasonable at the higher collective range- within 3 percent of the measured values. At the lower collective settings, the computed figure of merit is approximately 6 percent lower than the experimental data. A comparison of steady and unsteady results show that with temporal refinement, the dynamic results closely match the steady-state noninertial results which gives confidence in the accuracy of the dynamic overset-grid approach.

Final Report for''Numerical Methods and Studies of High-Speed Reactive and Non-Reactive Flows''

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schwendeman, D W

2002-11-20

The work carried out under this subcontract involved the development and use of an adaptive numerical method for the accurate calculation of high-speed reactive flows on overlapping grids. The flow is modeled by the reactive Euler equations with an assumed equation of state and with various reaction rate models. A numerical method has been developed to solve the nonlinear hyperbolic partial differential equations in the model. The method uses an unsplit, shock-capturing scheme, and uses a Godunov-type scheme to compute fluxes and a Runge-Kutta error control scheme to compute the source term modeling the chemical reactions. An adaptive mesh refinementmore » (AMR) scheme has been implemented in order to locally increase grid resolution. The numerical method uses composite overlapping grids to handle complex flow geometries. The code is part of the ''Overture-OverBlown'' framework of object-oriented codes [1, 2], and the development has occurred in close collaboration with Bill Henshaw and David Brown, and other members of the Overture team within CASC. During the period of this subcontract, a number of tasks were accomplished, including: (1) an extension of the numerical method to handle ''ignition and grow'' reaction models and a JWL equations of state; (2) an improvement in the efficiency of the AMR scheme and the error estimator; (3) an addition of a scheme of numerical dissipation designed to suppress numerical oscillations/instabilities near expanding detonations and along grid overlaps; and (4) an exploration of the evolution to detonation in an annulus and of detonation failure in an expanding channel.« less

Using Multiple Grids To Compute Flows

NASA Technical Reports Server (NTRS)

Rai, Man Mohan

1991-01-01

Paper discusses decomposition of global grids into multiple patched and/or overlaid local grids in computations of fluid flow. Such "domain decomposition" particularly useful in computation of flows about complicated bodies moving relative to each other; for example, flows associated with rotors and stators in turbomachinery and rotors and fuselages in helicopters.

Applications of the MapReduce programming framework to clinical big data analysis: current landscape and future trends

PubMed Central

2014-01-01

The emergence of massive datasets in a clinical setting presents both challenges and opportunities in data storage and analysis. This so called “big data” challenges traditional analytic tools and will increasingly require novel solutions adapted from other fields. Advances in information and communication technology present the most viable solutions to big data analysis in terms of efficiency and scalability. It is vital those big data solutions are multithreaded and that data access approaches be precisely tailored to large volumes of semi-structured/unstructured data. The MapReduce programming framework uses two tasks common in functional programming: Map and Reduce. MapReduce is a new parallel processing framework and Hadoop is its open-source implementation on a single computing node or on clusters. Compared with existing parallel processing paradigms (e.g. grid computing and graphical processing unit (GPU)), MapReduce and Hadoop have two advantages: 1) fault-tolerant storage resulting in reliable data processing by replicating the computing tasks, and cloning the data chunks on different computing nodes across the computing cluster; 2) high-throughput data processing via a batch processing framework and the Hadoop distributed file system (HDFS). Data are stored in the HDFS and made available to the slave nodes for computation. In this paper, we review the existing applications of the MapReduce programming framework and its implementation platform Hadoop in clinical big data and related medical health informatics fields. The usage of MapReduce and Hadoop on a distributed system represents a significant advance in clinical big data processing and utilization, and opens up new opportunities in the emerging era of big data analytics. The objective of this paper is to summarize the state-of-the-art efforts in clinical big data analytics and highlight what might be needed to enhance the outcomes of clinical big data analytics tools. This paper is concluded by summarizing the potential usage of the MapReduce programming framework and Hadoop platform to process huge volumes of clinical data in medical health informatics related fields. PMID:25383096

Applications of the MapReduce programming framework to clinical big data analysis: current landscape and future trends.

PubMed

Mohammed, Emad A; Far, Behrouz H; Naugler, Christopher

2014-01-01

The emergence of massive datasets in a clinical setting presents both challenges and opportunities in data storage and analysis. This so called "big data" challenges traditional analytic tools and will increasingly require novel solutions adapted from other fields. Advances in information and communication technology present the most viable solutions to big data analysis in terms of efficiency and scalability. It is vital those big data solutions are multithreaded and that data access approaches be precisely tailored to large volumes of semi-structured/unstructured data. THE MAPREDUCE PROGRAMMING FRAMEWORK USES TWO TASKS COMMON IN FUNCTIONAL PROGRAMMING: Map and Reduce. MapReduce is a new parallel processing framework and Hadoop is its open-source implementation on a single computing node or on clusters. Compared with existing parallel processing paradigms (e.g. grid computing and graphical processing unit (GPU)), MapReduce and Hadoop have two advantages: 1) fault-tolerant storage resulting in reliable data processing by replicating the computing tasks, and cloning the data chunks on different computing nodes across the computing cluster; 2) high-throughput data processing via a batch processing framework and the Hadoop distributed file system (HDFS). Data are stored in the HDFS and made available to the slave nodes for computation. In this paper, we review the existing applications of the MapReduce programming framework and its implementation platform Hadoop in clinical big data and related medical health informatics fields. The usage of MapReduce and Hadoop on a distributed system represents a significant advance in clinical big data processing and utilization, and opens up new opportunities in the emerging era of big data analytics. The objective of this paper is to summarize the state-of-the-art efforts in clinical big data analytics and highlight what might be needed to enhance the outcomes of clinical big data analytics tools. This paper is concluded by summarizing the potential usage of the MapReduce programming framework and Hadoop platform to process huge volumes of clinical data in medical health informatics related fields.

LES-based filter-matrix lattice Boltzmann model for simulating fully developed turbulent channel flow

NASA Astrophysics Data System (ADS)

Zhuo, Congshan; Zhong, Chengwen

2016-11-01

In this paper, a three-dimensional filter-matrix lattice Boltzmann (FMLB) model based on large eddy simulation (LES) was verified for simulating wall-bounded turbulent flows. The Vreman subgrid-scale model was employed in the present FMLB-LES framework, which had been proved to be capable of predicting turbulent near-wall region accurately. The fully developed turbulent channel flows were performed at a friction Reynolds number Reτ of 180. The turbulence statistics computed from the present FMLB-LES simulations, including mean stream velocity profile, Reynolds stress profile and root-mean-square velocity fluctuations greed well with the LES results of multiple-relaxation-time (MRT) LB model, and some discrepancies in comparison with those direct numerical simulation (DNS) data of Kim et al. was also observed due to the relatively low grid resolution. Moreover, to investigate the influence of grid resolution on the present LES simulation, a DNS simulation on a finer gird was also implemented by present FMLB-D3Q19 model. Comparisons of detailed computed various turbulence statistics with available benchmark data of DNS showed quite well agreement.

A Grid Infrastructure for Supporting Space-based Science Operations

NASA Technical Reports Server (NTRS)

Bradford, Robert N.; Redman, Sandra H.; McNair, Ann R. (Technical Monitor)

2002-01-01

Emerging technologies for computational grid infrastructures have the potential for revolutionizing the way computers are used in all aspects of our lives. Computational grids are currently being implemented to provide a large-scale, dynamic, and secure research and engineering environments based on standards and next-generation reusable software, enabling greater science and engineering productivity through shared resources and distributed computing for less cost than traditional architectures. Combined with the emerging technologies of high-performance networks, grids provide researchers, scientists and engineers the first real opportunity for an effective distributed collaborative environment with access to resources such as computational and storage systems, instruments, and software tools and services for the most computationally challenging applications.

Impact of Load Balancing on Unstructured Adaptive Grid Computations for Distributed-Memory Multiprocessors

NASA Technical Reports Server (NTRS)

Sohn, Andrew; Biswas, Rupak; Simon, Horst D.

1996-01-01

The computational requirements for an adaptive solution of unsteady problems change as the simulation progresses. This causes workload imbalance among processors on a parallel machine which, in turn, requires significant data movement at runtime. We present a new dynamic load-balancing framework, called JOVE, that balances the workload across all processors with a global view. Whenever the computational mesh is adapted, JOVE is activated to eliminate the load imbalance. JOVE has been implemented on an IBM SP2 distributed-memory machine in MPI for portability. Experimental results for two model meshes demonstrate that mesh adaption with load balancing gives more than a sixfold improvement over one without load balancing. We also show that JOVE gives a 24-fold speedup on 64 processors compared to sequential execution.

Aeroacoustic Simulation of Nose Landing Gear on Adaptive Unstructured Grids With FUN3D

NASA Technical Reports Server (NTRS)

Vatsa, Veer N.; Khorrami, Mehdi R.; Park, Michael A.; Lockard, David P.

2013-01-01

Numerical simulations have been performed for a partially-dressed, cavity-closed nose landing gear configuration that was tested in NASA Langley s closed-wall Basic Aerodynamic Research Tunnel (BART) and in the University of Florida's open-jet acoustic facility known as the UFAFF. The unstructured-grid flow solver FUN3D, developed at NASA Langley Research center, is used to compute the unsteady flow field for this configuration. Starting with a coarse grid, a series of successively finer grids were generated using the adaptive gridding methodology available in the FUN3D code. A hybrid Reynolds-averaged Navier-Stokes/large eddy simulation (RANS/LES) turbulence model is used for these computations. Time-averaged and instantaneous solutions obtained on these grids are compared with the measured data. In general, the correlation with the experimental data improves with grid refinement. A similar trend is observed for sound pressure levels obtained by using these CFD solutions as input to a FfowcsWilliams-Hawkings noise propagation code to compute the farfield noise levels. In general, the numerical solutions obtained on adapted grids compare well with the hand-tuned enriched fine grid solutions and experimental data. In addition, the grid adaption strategy discussed here simplifies the grid generation process, and results in improved computational efficiency of CFD simulations.

Global Optimization of N-Maneuver, High-Thrust Trajectories Using Direct Multiple Shooting

NASA Technical Reports Server (NTRS)

Vavrina, Matthew A.; Englander, Jacob A.; Ellison, Donald H.

2016-01-01

The performance of impulsive, gravity-assist trajectories often improves with the inclusion of one or more maneuvers between flybys. However, grid-based scans over the entire design space can become computationally intractable for even one deep-space maneuver, and few global search routines are capable of an arbitrary number of maneuvers. To address this difficulty a trajectory transcription allowing for any number of maneuvers is developed within a multi-objective, global optimization framework for constrained, multiple gravity-assist trajectories. The formulation exploits a robust shooting scheme and analytic derivatives for computational efficiency. The approach is applied to several complex, interplanetary problems, achieving notable performance without a user-supplied initial guess.

Enhancing GIS Capabilities for High Resolution Earth Science Grids

NASA Astrophysics Data System (ADS)

Koziol, B. W.; Oehmke, R.; Li, P.; O'Kuinghttons, R.; Theurich, G.; DeLuca, C.

2017-12-01

Applications for high performance GIS will continue to increase as Earth system models pursue more realistic representations of Earth system processes. Finer spatial resolution model input and output, unstructured or irregular modeling grids, data assimilation, and regional coordinate systems present novel challenges for GIS frameworks operating in the Earth system modeling domain. This presentation provides an overview of two GIS-driven applications that combine high performance software with big geospatial datasets to produce value-added tools for the modeling and geoscientific community. First, a large-scale interpolation experiment using National Hydrography Dataset (NHD) catchments, a high resolution rectilinear CONUS grid, and the Earth System Modeling Framework's (ESMF) conservative interpolation capability will be described. ESMF is a parallel, high-performance software toolkit that provides capabilities (e.g. interpolation) for building and coupling Earth science applications. ESMF is developed primarily by the NOAA Environmental Software Infrastructure and Interoperability (NESII) group. The purpose of this experiment was to test and demonstrate the utility of high performance scientific software in traditional GIS domains. Special attention will be paid to the nuanced requirements for dealing with high resolution, unstructured grids in scientific data formats. Second, a chunked interpolation application using ESMF and OpenClimateGIS (OCGIS) will demonstrate how spatial subsetting can virtually remove computing resource ceilings for very high spatial resolution interpolation operations. OCGIS is a NESII-developed Python software package designed for the geospatial manipulation of high-dimensional scientific datasets. An overview of the data processing workflow, why a chunked approach is required, and how the application could be adapted to meet operational requirements will be discussed here. In addition, we'll provide a general overview of OCGIS's parallel subsetting capabilities including challenges in the design and implementation of a scientific data subsetter.

Influence of Gridded Standoff Measurement Resolution on Numerical Bathymetric Inversion

NASA Astrophysics Data System (ADS)

Hesser, T.; Farthing, M. W.; Brodie, K.

2016-02-01

The bathymetry from the surfzone to the shoreline incurs frequent, active movement due to wave energy interacting with the seafloor. Methodologies to measure bathymetry range from point-source in-situ instruments, vessel-mounted single-beam or multi-beam sonar surveys, airborne bathymetric lidar, as well as inversion techniques from standoff measurements of wave processes from video or radar imagery. Each type of measurement has unique sources of error and spatial and temporal resolution and availability. Numerical bathymetry estimation frameworks can use these disparate data types in combination with model-based inversion techniques to produce a "best-estimate of bathymetry" at a given time. Understanding how the sources of error and varying spatial or temporal resolution of each data type affect the end result is critical for determining best practices and in turn increase the accuracy of bathymetry estimation techniques. In this work, we consider an initial step in the development of a complete framework for estimating bathymetry in the nearshore by focusing on gridded standoff measurements and in-situ point observations in model-based inversion at the U.S. Army Corps of Engineers Field Research Facility in Duck, NC. The standoff measurement methods return wave parameters computed using linear wave theory from the direct measurements. These gridded datasets can range in temporal and spatial resolution that do not match the desired model parameters and therefore could lead to a reduction in the accuracy of these methods. Specifically, we investigate the affect of numerical resolution on the accuracy of an Ensemble Kalman Filter bathymetric inversion technique in relation to the spatial and temporal resolution of the gridded standoff measurements. The accuracies of the bathymetric estimates are compared with both high-resolution Real Time Kinematic (RTK) single-beam surveys as well as alternative direct in-situ measurements using sonic altimeters.

Advances in Chimera Grid Tools for Multi-Body Dynamics Simulations and Script Creation

NASA Technical Reports Server (NTRS)

Chan, William M.

2004-01-01

This viewgraph presentation contains information about (1) Framework for multi-body dynamics - Geometry Manipulation Protocol (GMP), (2) Simulation procedure using Chimera Grid Tools (CGT) and OVERFLOW-2 (3) Further recent developments in Chimera Grid Tools OVERGRID, Grid modules, Script library and (4) Future work.

A High-Order Method Using Unstructured Grids for the Aeroacoustic Analysis of Realistic Aircraft Configurations

NASA Technical Reports Server (NTRS)

Atkins, Harold L.; Lockard, David P.

1999-01-01

A method for the prediction of acoustic scatter from complex geometries is presented. The discontinuous Galerkin method provides a framework for the development of a high-order method using unstructured grids. The method's compact form contributes to its accuracy and efficiency, and makes the method well suited for distributed memory parallel computing platforms. Mesh refinement studies are presented to validate the expected convergence properties of the method, and to establish the absolute levels of a error one can expect at a given level of resolution. For a two-dimensional shear layer instability wave and for three-dimensional wave propagation, the method is demonstrated to be insensitive to mesh smoothness. Simulations of scatter from a two-dimensional slat configuration and a three-dimensional blended-wing-body demonstrate the capability of the method to efficiently treat realistic geometries.

Statistical Analysis of CFD Solutions from the 6th AIAA CFD Drag Prediction Workshop

NASA Technical Reports Server (NTRS)

Derlaga, Joseph M.; Morrison, Joseph H.

2017-01-01

A graphical framework is used for statistical analysis of the results from an extensive N- version test of a collection of Reynolds-averaged Navier-Stokes computational uid dynam- ics codes. The solutions were obtained by code developers and users from North America, Europe, Asia, and South America using both common and custom grid sequencees as well as multiple turbulence models for the June 2016 6th AIAA CFD Drag Prediction Workshop sponsored by the AIAA Applied Aerodynamics Technical Committee. The aerodynamic con guration for this workshop was the Common Research Model subsonic transport wing- body previously used for both the 4th and 5th Drag Prediction Workshops. This work continues the statistical analysis begun in the earlier workshops and compares the results from the grid convergence study of the most recent workshop with previous workshops.

Time-Dependent Simulations of Turbopump Flows

NASA Technical Reports Server (NTRS)

Kris, Cetin C.; Kwak, Dochan

2001-01-01

The objective of the current effort is to provide a computational framework for design and analysis of the entire fuel supply system of a liquid rocket engine, including high-fidelity unsteady turbopump flow analysis. This capability is needed to support the design of pump sub-systems for advanced space transportation vehicles that are likely to involve liquid propulsion systems. To date, computational tools for design/analysis of turbopump flows are based on relatively lower fidelity methods. An unsteady, three-dimensional viscous flow analysis tool involving stationary and rotational components for the entire turbopump assembly has not been available for real-world engineering applications. The present effort will provide developers with information such as transient flow phenomena at start up, impact of non-uniform inflows, system vibration and impact on the structure. In the proposed paper, the progress toward the capability of complete simulation of the turbo-pump for a liquid rocket engine is reported. The Space Shuttle Main Engine (SSME) turbo-pump is used as a test case for evaluation of the hybrid MPI/Open-MP and MLP versions of the INS3D code. The relative motion of the grid systems for the rotor-stator interaction was obtained using overset grid techniques. Time-accuracy of the scheme has been evaluated with simple test cases. Unsteady computations for the SSME turbo-pump, which contains 114 zones with 34.5 million grid points, are carried out on Origin 2000 systems at NASA Ames Research Center. Results from these time-accurate simulations with moving boundary capability will be presented along with the performance of parallel versions of the code.

Probabilistic Learning by Rodent Grid Cells

PubMed Central

Cheung, Allen

2016-01-01

Mounting evidence shows mammalian brains are probabilistic computers, but the specific cells involved remain elusive. Parallel research suggests that grid cells of the mammalian hippocampal formation are fundamental to spatial cognition but their diverse response properties still defy explanation. No plausible model exists which explains stable grids in darkness for twenty minutes or longer, despite being one of the first results ever published on grid cells. Similarly, no current explanation can tie together grid fragmentation and grid rescaling, which show very different forms of flexibility in grid responses when the environment is varied. Other properties such as attractor dynamics and grid anisotropy seem to be at odds with one another unless additional properties are assumed such as a varying velocity gain. Modelling efforts have largely ignored the breadth of response patterns, while also failing to account for the disastrous effects of sensory noise during spatial learning and recall, especially in darkness. Here, published electrophysiological evidence from a range of experiments are reinterpreted using a novel probabilistic learning model, which shows that grid cell responses are accurately predicted by a probabilistic learning process. Diverse response properties of probabilistic grid cells are statistically indistinguishable from rat grid cells across key manipulations. A simple coherent set of probabilistic computations explains stable grid fields in darkness, partial grid rescaling in resized arenas, low-dimensional attractor grid cell dynamics, and grid fragmentation in hairpin mazes. The same computations also reconcile oscillatory dynamics at the single cell level with attractor dynamics at the cell ensemble level. Additionally, a clear functional role for boundary cells is proposed for spatial learning. These findings provide a parsimonious and unified explanation of grid cell function, and implicate grid cells as an accessible neuronal population readout of a set of probabilistic spatial computations. PMID:27792723

Cost benefit analysis for smart grid projects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karali, Nihan; He, Gang; Mauzey, J

The U.S. is unusual in that a definition of the term “smart grid” was written into legislation, appearing in the Energy Independence and Security Act (2007). When the recession called for stimulus spending and the American Recovery and Reinvestment Act (ARRA, 2009) was passed, a framework already existed for identification of smart grid projects. About $4.5B of the U.S. Department of Energy’s (U.S. DOE’s) $37B allocation from ARRA was directed to smart grid projects of two types, investment grants and demonstrations. Matching funds from other sources more than doubled the total value of ARRA-funded smart grid projects. The Smart Gridmore » Investment Grant Program (SGIG) consumed all but $620M of the ARRA funds, which was available for the 32 projects in the Smart Grid Demonstration Program (SGDP, or demonstrations). Given the economic potential of these projects and the substantial investments required, there was keen interest in estimating the benefits of the projects (i.e., quantifying and monetizing the performance of smart grid technologies). Common method development and application, data collection, and analysis to calculate and publicize the benefits were central objectives of the program. For this purpose standard methods and a software tool, the Smart Grid Computational Tool (SGCT), were developed by U.S. DOE and a spreadsheet model was made freely available to grantees and other analysts. The methodology was intended to define smart grid technologies or assets, the mechanisms by which they generate functions, their impacts and, ultimately, their benefits. The SGCT and its application to the Demonstration Projects are described, and actual projects in Southern California and in China are selected to test and illustrate the tool. The usefulness of the methodology and tool for international analyses is then assessed.« less

VisIVO: A Library and Integrated Tools for Large Astrophysical Dataset Exploration

NASA Astrophysics Data System (ADS)

Becciani, U.; Costa, A.; Ersotelos, N.; Krokos, M.; Massimino, P.; Petta, C.; Vitello, F.

2012-09-01

VisIVO provides an integrated suite of tools and services that can be used in many scientific fields. VisIVO development starts in the Virtual Observatory framework. VisIVO allows users to visualize meaningfully highly-complex, large-scale datasets and create movies of these visualizations based on distributed infrastructures. VisIVO supports high-performance, multi-dimensional visualization of large-scale astrophysical datasets. Users can rapidly obtain meaningful visualizations while preserving full and intuitive control of the relevant parameters. VisIVO consists of VisIVO Desktop - a stand-alone application for interactive visualization on standard PCs, VisIVO Server - a platform for high performance visualization, VisIVO Web - a custom designed web portal, VisIVOSmartphone - an application to exploit the VisIVO Server functionality and the latest VisIVO features: VisIVO Library allows a job running on a computational system (grid, HPC, etc.) to produce movies directly with the code internal data arrays without the need to produce intermediate files. This is particularly important when running on large computational facilities, where the user wants to have a look at the results during the data production phase. For example, in grid computing facilities, images can be produced directly in the grid catalogue while the user code is running in a system that cannot be directly accessed by the user (a worker node). The deployment of VisIVO on the DG and gLite is carried out with the support of EDGI and EGI-Inspire projects. Depending on the structure and size of datasets under consideration, the data exploration process could take several hours of CPU for creating customized views and the production of movies could potentially last several days. For this reason an MPI parallel version of VisIVO could play a fundamental role in increasing performance, e.g. it could be automatically deployed on nodes that are MPI aware. A central concept in our development is thus to produce unified code that can run either on serial nodes or in parallel by using HPC oriented grid nodes. Another important aspect, to obtain as high performance as possible, is the integration of VisIVO processes with grid nodes where GPUs are available. We have selected CUDA for implementing a range of computationally heavy modules. VisIVO is supported by EGI-Inspire, EDGI and SCI-BUS projects.

Computer Aided Grid Interface: An Interactive CFD Pre-Processor

NASA Technical Reports Server (NTRS)

Soni, Bharat K.

1997-01-01

NASA maintains an applications oriented computational fluid dynamics (CFD) efforts complementary to and in support of the aerodynamic-propulsion design and test activities. This is especially true at NASA/MSFC where the goal is to advance and optimize present and future liquid-fueled rocket engines. Numerical grid generation plays a significant role in the fluid flow simulations utilizing CFD. An overall goal of the current project was to develop a geometry-grid generation tool that will help engineers, scientists and CFD practitioners to analyze design problems involving complex geometries in a timely fashion. This goal is accomplished by developing the CAGI: Computer Aided Grid Interface system. The CAGI system is developed by integrating CAD/CAM (Computer Aided Design/Computer Aided Manufacturing) geometric system output and/or Initial Graphics Exchange Specification (IGES) files (including all the NASA-IGES entities), geometry manipulations and generations associated with grid constructions, and robust grid generation methodologies. This report describes the development process of the CAGI system.

Computer Aided Grid Interface: An Interactive CFD Pre-Processor

NASA Technical Reports Server (NTRS)

Soni, Bharat K.

1996-01-01

NASA maintains an applications oriented computational fluid dynamics (CFD) efforts complementary to and in support of the aerodynamic-propulsion design and test activities. This is especially true at NASA/MSFC where the goal is to advance and optimize present and future liquid-fueled rocket engines. Numerical grid generation plays a significant role in the fluid flow simulations utilizing CFD. An overall goal of the current project was to develop a geometry-grid generation tool that will help engineers, scientists and CFD practitioners to analyze design problems involving complex geometries in a timely fashion. This goal is accomplished by developing the Computer Aided Grid Interface system (CAGI). The CAGI system is developed by integrating CAD/CAM (Computer Aided Design/Computer Aided Manufacturing) geometric system output and / or Initial Graphics Exchange Specification (IGES) files (including all the NASA-IGES entities), geometry manipulations and generations associated with grid constructions, and robust grid generation methodologies. This report describes the development process of the CAGI system.

Grid computing in large pharmaceutical molecular modeling.

PubMed

Claus, Brian L; Johnson, Stephen R

2008-07-01

Most major pharmaceutical companies have employed grid computing to expand their compute resources with the intention of minimizing additional financial expenditure. Historically, one of the issues restricting widespread utilization of the grid resources in molecular modeling is the limited set of suitable applications amenable to coarse-grained parallelization. Recent advances in grid infrastructure technology coupled with advances in application research and redesign will enable fine-grained parallel problems, such as quantum mechanics and molecular dynamics, which were previously inaccessible to the grid environment. This will enable new science as well as increase resource flexibility to load balance and schedule existing workloads.

Multiple-grid convergence acceleration of viscous and inviscid flow computations

NASA Technical Reports Server (NTRS)

Johnson, G. M.

1983-01-01

A multiple-grid algorithm for use in efficiently obtaining steady solution to the Euler and Navier-Stokes equations is presented. The convergence of a simple, explicit fine-grid solution procedure is accelerated on a sequence of successively coarser grids by a coarse-grid information propagation method which rapidly eliminates transients from the computational domain. This use of multiple-gridding to increase the convergence rate results in substantially reduced work requirements for the numerical solution of a wide range of flow problems. Computational results are presented for subsonic and transonic inviscid flows and for laminar and turbulent, attached and separated, subsonic viscous flows. Work reduction factors as large as eight, in comparison to the basic fine-grid algorithm, were obtained. Possibilities for further performance improvement are discussed.

2-dimensional implicit hydrodynamics on adaptive grids

NASA Astrophysics Data System (ADS)

Stökl, A.; Dorfi, E. A.

2007-12-01

We present a numerical scheme for two-dimensional hydrodynamics computations using a 2D adaptive grid together with an implicit discretization. The combination of these techniques has offered favorable numerical properties applicable to a variety of one-dimensional astrophysical problems which motivated us to generalize this approach for two-dimensional applications. Due to the different topological nature of 2D grids compared to 1D problems, grid adaptivity has to avoid severe grid distortions which necessitates additional smoothing parameters to be included into the formulation of a 2D adaptive grid. The concept of adaptivity is described in detail and several test computations demonstrate the effectivity of smoothing. The coupled solution of this grid equation together with the equations of hydrodynamics is illustrated by computation of a 2D shock tube problem.

Grids, virtualization, and clouds at Fermilab

DOE PAGES

Timm, S.; Chadwick, K.; Garzoglio, G.; ...

2014-06-11

Fermilab supports a scientific program that includes experiments and scientists located across the globe. To better serve this community, in 2004, the (then) Computing Division undertook the strategy of placing all of the High Throughput Computing (HTC) resources in a Campus Grid known as FermiGrid, supported by common shared services. In 2007, the FermiGrid Services group deployed a service infrastructure that utilized Xen virtualization, LVS network routing and MySQL circular replication to deliver highly available services that offered significant performance, reliability and serviceability improvements. This deployment was further enhanced through the deployment of a distributed redundant network core architecture andmore » the physical distribution of the systems that host the virtual machines across multiple buildings on the Fermilab Campus. In 2010, building on the experience pioneered by FermiGrid in delivering production services in a virtual infrastructure, the Computing Sector commissioned the FermiCloud, General Physics Computing Facility and Virtual Services projects to serve as platforms for support of scientific computing (FermiCloud 6 GPCF) and core computing (Virtual Services). Lastly, this work will present the evolution of the Fermilab Campus Grid, Virtualization and Cloud Computing infrastructure together with plans for the future.« less

Grids, virtualization, and clouds at Fermilab

NASA Astrophysics Data System (ADS)

Timm, S.; Chadwick, K.; Garzoglio, G.; Noh, S.

2014-06-01

Fermilab supports a scientific program that includes experiments and scientists located across the globe. To better serve this community, in 2004, the (then) Computing Division undertook the strategy of placing all of the High Throughput Computing (HTC) resources in a Campus Grid known as FermiGrid, supported by common shared services. In 2007, the FermiGrid Services group deployed a service infrastructure that utilized Xen virtualization, LVS network routing and MySQL circular replication to deliver highly available services that offered significant performance, reliability and serviceability improvements. This deployment was further enhanced through the deployment of a distributed redundant network core architecture and the physical distribution of the systems that host the virtual machines across multiple buildings on the Fermilab Campus. In 2010, building on the experience pioneered by FermiGrid in delivering production services in a virtual infrastructure, the Computing Sector commissioned the FermiCloud, General Physics Computing Facility and Virtual Services projects to serve as platforms for support of scientific computing (FermiCloud 6 GPCF) and core computing (Virtual Services). This work will present the evolution of the Fermilab Campus Grid, Virtualization and Cloud Computing infrastructure together with plans for the future.

Application of advanced grid generation techniques for flow field computations about complex configurations

NASA Technical Reports Server (NTRS)

Kathong, Monchai; Tiwari, Surendra N.

1988-01-01

In the computation of flowfields about complex configurations, it is very difficult to construct a boundary-fitted coordinate system. An alternative approach is to use several grids at once, each of which is generated independently. This procedure is called the multiple grids or zonal grids approach; its applications are investigated. The method conservative providing conservation of fluxes at grid interfaces. The Euler equations are solved numerically on such grids for various configurations. The numerical scheme used is the finite-volume technique with a three-stage Runge-Kutta time integration. The code is vectorized and programmed to run on the CDC VPS-32 computer. Steady state solutions of the Euler equations are presented and discussed. The solutions include: low speed flow over a sphere, high speed flow over a slender body, supersonic flow through a duct, and supersonic internal/external flow interaction for an aircraft configuration at various angles of attack. The results demonstrate that the multiple grids approach along with the conservative interfacing is capable of computing the flows about the complex configurations where the use of a single grid system is not possible.

Near real-time traffic routing

NASA Technical Reports Server (NTRS)

Yang, Chaowei (Inventor); Xie, Jibo (Inventor); Zhou, Bin (Inventor); Cao, Ying (Inventor)

2012-01-01

A near real-time physical transportation network routing system comprising: a traffic simulation computing grid and a dynamic traffic routing service computing grid. The traffic simulator produces traffic network travel time predictions for a physical transportation network using a traffic simulation model and common input data. The physical transportation network is divided into a multiple sections. Each section has a primary zone and a buffer zone. The traffic simulation computing grid includes multiple of traffic simulation computing nodes. The common input data includes static network characteristics, an origin-destination data table, dynamic traffic information data and historical traffic data. The dynamic traffic routing service computing grid includes multiple dynamic traffic routing computing nodes and generates traffic route(s) using the traffic network travel time predictions.

Toward Immersed Boundary Simulation of High Reynolds Number Flows

NASA Technical Reports Server (NTRS)

Kalitzin, Georgi; Iaccarino, Gianluca

2003-01-01

In the immersed boundary (IB) method, the surface of an object is reconstructed with forcing terms in the underlying flow field equations. The surface may split a computational cell removing the constraint of the near wall gridlines to be aligned with the surface. This feature greatly simplifies the grid generation process which is cumbersome and expensive in particular for structured grids and complex geometries. The IB method is ideally suited for Cartesian flow solvers. The flow equations written in Cartesian coordinates appear in a very simple form and several numerical algorithms can be used for an efficient solution of the equations. In addition, the accuracy of numerical algorithms is dependent on the underlying grid and it usually deteriorates when the grid deviates from a Cartesian mesh. The challenge for the IB method lies in the representation of the wall boundaries and in providing an adequate near wall flow field resolution. The issue of enforcing no-slip boundary conditions at the immersed surface has been addressed by several authors by imposing a local reconstruction of the solution. Initial work by Verzicco et al. was based on a simple linear, one-dimensional operator and this approach proved to be accurate for boundaries largely aligned with the grid lines. Majumdar et al. used various multidimensional and high order polynomial interpolations schemes. These high order schemes, however, are keen to introduce wiggles and spurious extrema. Iaccarino & Verzicco and Kalitzin & Iaccarino proposed a tri-linear reconstruction for the velocity components and the turbulent scalars. A modified implementation that has proven to be more robust is reported in this paper. The issue of adequate near wall resolution in a Cartesian framework can initially be addressed by using a non-uniform mesh which is stretched near the surface. In this paper, we investigate an unstructured approach for local grid refinement that utilizes Cartesian mesh features. The computation of high Reynolds number wall bounded flows is particularly challenging as it requires the consideration of thin turbulent boundary layers, i.e. near wall regions with large gradients of the flow field variables. For such flows, the representation of the wall boundary has a large impact on the accuracy of the computation. It is also critical for the robustness and convergence of the flow solver.

Parallel Proximity Detection for Computer Simulation

NASA Technical Reports Server (NTRS)

Steinman, Jeffrey S. (Inventor); Wieland, Frederick P. (Inventor)

1997-01-01

The present invention discloses a system for performing proximity detection in computer simulations on parallel processing architectures utilizing a distribution list which includes movers and sensor coverages which check in and out of grids. Each mover maintains a list of sensors that detect the mover's motion as the mover and sensor coverages check in and out of the grids. Fuzzy grids are includes by fuzzy resolution parameters to allow movers and sensor coverages to check in and out of grids without computing exact grid crossings. The movers check in and out of grids while moving sensors periodically inform the grids of their coverage. In addition, a lookahead function is also included for providing a generalized capability without making any limiting assumptions about the particular application to which it is applied. The lookahead function is initiated so that risk-free synchronization strategies never roll back grid events. The lookahead function adds fixed delays as events are scheduled for objects on other nodes.

Parallel Proximity Detection for Computer Simulations

NASA Technical Reports Server (NTRS)

Steinman, Jeffrey S. (Inventor); Wieland, Frederick P. (Inventor)

1998-01-01

The present invention discloses a system for performing proximity detection in computer simulations on parallel processing architectures utilizing a distribution list which includes movers and sensor coverages which check in and out of grids. Each mover maintains a list of sensors that detect the mover's motion as the mover and sensor coverages check in and out of the grids. Fuzzy grids are included by fuzzy resolution parameters to allow movers and sensor coverages to check in and out of grids without computing exact grid crossings. The movers check in and out of grids while moving sensors periodically inform the grids of their coverage. In addition, a lookahead function is also included for providing a generalized capability without making any limiting assumptions about the particular application to which it is applied. The lookahead function is initiated so that risk-free synchronization strategies never roll back grid events. The lookahead function adds fixed delays as events are scheduled for objects on other nodes.

Faster than Real-Time Dynamic Simulation for Large-Size Power System with Detailed Dynamic Models using High-Performance Computing Platform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Renke; Jin, Shuangshuang; Chen, Yousu

This paper presents a faster-than-real-time dynamic simulation software package that is designed for large-size power system dynamic simulation. It was developed on the GridPACKTM high-performance computing (HPC) framework. The key features of the developed software package include (1) faster-than-real-time dynamic simulation for a WECC system (17,000 buses) with different types of detailed generator, controller, and relay dynamic models, (2) a decoupled parallel dynamic simulation algorithm with optimized computation architecture to better leverage HPC resources and technologies, (3) options for HPC-based linear and iterative solvers, (4) hidden HPC details, such as data communication and distribution, to enable development centered on mathematicalmore » models and algorithms rather than on computational details for power system researchers, and (5) easy integration of new dynamic models and related algorithms into the software package.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Snow, Dr., Joel

This final report is presented by Langston University (LU) for the project entitled "Langston University High Energy Physics" (LUHEP) under the direction of principal investigator (PI) and project director Professor Joel Snow. The project encompassed high energy physics research performed at hadron colliders. The PI is a collaborator on the DZero experiment at Fermi National Accelerator Laboratory in Batavia, IL, USA and the ATLAS experiment at CERN in Geneva, Switzerland and was during the entire project period from April 1, 1999 until May 14, 2012. Both experiments seek to understand the fundamental constituents of the physical universe and the forcesmore » that govern their interactions. In 1999 as member of the Online Systems group for Run 2 the PI developed a cross-platform Python-based, Graphical User Interface (GUI) application for monitoring and control of EPICS based devices for control room use. This served as a model for other developers to enhance and build on for further monitoring and control tasks written in Python. Subsequently the PI created and developed a cross-platform C++ GUI utilizing a networked client-server paradigm and based on ROOT, the object oriented analysis framework from CERN. The GUI served as a user interface to the Examine tasks running in the D\\O\\ control room which monitored the status and integrity of data taking for Run 2. The PI developed the histogram server/control interface to the GUI client for the EXAMINE processes. The histogram server was built from the ROOT framework and was integrated into the D\\O\\ framework used for online monitoring programs and offline analysis. The PI developed the first implementation of displaying histograms dynamically generated by ROOT in a Web Browser. The PI's work resulted in several talks and papers at international conferences and workshops. The PI established computing software infrastructure at LU and U. Oklahoma (OU) to do analysis of DZero production data and produce simulation data for the experiment. Eventually this included the FNAL SAM data grid system, the SAMGrid (SG) infrastructure, and the Open Science Grid software stacks for computing and storage elements. At the end of 2003 Snow took on the role of global Monte Carlo production coordinator for the DØ experiment. A role which continues til this day. In January of 2004 Snow started working with the SAMGrid development team to help debug, deploy, and integrate SAMGrid with DØ Monte Carlo production. Snow installed and configured SG execution and client sites at LUHEP and OUHEP, and a SG scheduler site at LUHEP. The PI developed a python based GUI (DAJ) that acts as a front end for job submission to SAMGrid. The GUI interfaces to the DZero Mone Carlo (MC) request system that uses SAM to manage MC requests by the physics analysis groups. DAJ significantly simplified SG job submission and was deployed in DZero in an effort to increase the user base of SG. The following year was the advent of SAMGrid job submission to the Open Science Grid (OSG) and LHC Computing Grid (LCG) through a forwarding mechanism. The PI oversaw the integration of these grids into the existing production infrastructure. The PI developed an automatic MC (Automc) request processing system capable of operating without user intervention (other than getting grid credentials), and able to submit to any number of sites on various grids. The system manages production at all but 2 sites. The system was deployed at Fermilab and remains operating there today. The PI's work in distributed computing resulted in several talks at international conferences. UTA, OU, and LU were chosen as the collaborating institutions that form the Southwest Tier 2 Center (SWT2) for ATLAS. During the project period the PI contributed to the online and offline software infrastructure through his work with the Run 2 online group, and played a major role in Monte Carlo production for DZero. During the part of the project period in which the PI served as MC production coordinator MC production increased very significantly. In the first year of the PI's tenure as production coordinator production was 159M events and 6.7~TB of data. During the last year of the project period production was 2,342~M events and 262~TB of data. That is a factor of 15 increase in events and 39 in data volume. The increase occurred with improvements in computer hardware and networks, through the use of grid technology on diverse resources, and through increased automation and efficiency of the production process. LU HEP developed and deployed the automatic MC request processing system in use at FNAL. The complementary strategies of automation and grid production served DZero well. Fermilab has recognized LU HEP's contribution to DZero by allowing the PI to devote full time to research activities by appointing him a guest scientist for the last six years of the project period.« less

Deep learning for classification of islanding and grid disturbance based on multi-resolution singular spectrum entropy

NASA Astrophysics Data System (ADS)

Li, Tie; He, Xiaoyang; Tang, Junci; Zeng, Hui; Zhou, Chunying; Zhang, Nan; Liu, Hui; Lu, Zhuoxin; Kong, Xiangrui; Yan, Zheng

2018-02-01

Forasmuch as the distinguishment of islanding is easy to be interfered by grid disturbance, island detection device may make misjudgment thus causing the consequence of photovoltaic out of service. The detection device must provide with the ability to differ islanding from grid disturbance. In this paper, the concept of deep learning is introduced into classification of islanding and grid disturbance for the first time. A novel deep learning framework is proposed to detect and classify islanding or grid disturbance. The framework is a hybrid of wavelet transformation, multi-resolution singular spectrum entropy, and deep learning architecture. As a signal processing method after wavelet transformation, multi-resolution singular spectrum entropy combines multi-resolution analysis and spectrum analysis with entropy as output, from which we can extract the intrinsic different features between islanding and grid disturbance. With the features extracted, deep learning is utilized to classify islanding and grid disturbance. Simulation results indicate that the method can achieve its goal while being highly accurate, so the photovoltaic system mistakenly withdrawing from power grids can be avoided.

Self-consistent field theory simulations of polymers on arbitrary domains

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ouaknin, Gaddiel, E-mail: gaddielouaknin@umail.ucsb.edu; Laachi, Nabil; Delaney, Kris

2016-12-15

We introduce a framework for simulating the mesoscale self-assembly of block copolymers in arbitrary confined geometries subject to Neumann boundary conditions. We employ a hybrid finite difference/volume approach to discretize the mean-field equations on an irregular domain represented implicitly by a level-set function. The numerical treatment of the Neumann boundary conditions is sharp, i.e. it avoids an artificial smearing in the irregular domain boundary. This strategy enables the study of self-assembly in confined domains and enables the computation of physically meaningful quantities at the domain interface. In addition, we employ adaptive grids encoded with Quad-/Oc-trees in parallel to automatically refinemore » the grid where the statistical fields vary rapidly as well as at the boundary of the confined domain. This approach results in a significant reduction in the number of degrees of freedom and makes the simulations in arbitrary domains using effective boundary conditions computationally efficient in terms of both speed and memory requirement. Finally, in the case of regular periodic domains, where pseudo-spectral approaches are superior to finite differences in terms of CPU time and accuracy, we use the adaptive strategy to store chain propagators, reducing the memory footprint without loss of accuracy in computed physical observables.« less

A coarse-grid projection method for accelerating incompressible flow computations

NASA Astrophysics Data System (ADS)

San, Omer; Staples, Anne E.

2013-01-01

We present a coarse-grid projection (CGP) method for accelerating incompressible flow computations, which is applicable to methods involving Poisson equations as incompressibility constraints. The CGP methodology is a modular approach that facilitates data transfer with simple interpolations and uses black-box solvers for the Poisson and advection-diffusion equations in the flow solver. After solving the Poisson equation on a coarsened grid, an interpolation scheme is used to obtain the fine data for subsequent time stepping on the full grid. A particular version of the method is applied here to the vorticity-stream function, primitive variable, and vorticity-velocity formulations of incompressible Navier-Stokes equations. We compute several benchmark flow problems on two-dimensional Cartesian and non-Cartesian grids, as well as a three-dimensional flow problem. The method is found to accelerate these computations while retaining a level of accuracy close to that of the fine resolution field, which is significantly better than the accuracy obtained for a similar computation performed solely using a coarse grid. A linear acceleration rate is obtained for all the cases we consider due to the linear-cost elliptic Poisson solver used, with reduction factors in computational time between 2 and 42. The computational savings are larger when a suboptimal Poisson solver is used. We also find that the computational savings increase with increasing distortion ratio on non-Cartesian grids, making the CGP method a useful tool for accelerating generalized curvilinear incompressible flow solvers.

DIRAC distributed secure framework

NASA Astrophysics Data System (ADS)

Casajus, A.; Graciani, R.; LHCb DIRAC Team

2010-04-01

DIRAC, the LHCb community Grid solution, provides access to a vast amount of computing and storage resources to a large number of users. In DIRAC users are organized in groups with different needs and permissions. In order to ensure that only allowed users can access the resources and to enforce that there are no abuses, security is mandatory. All DIRAC services and clients use secure connections that are authenticated using certificates and grid proxies. Once a client has been authenticated, authorization rules are applied to the requested action based on the presented credentials. These authorization rules and the list of users and groups are centrally managed in the DIRAC Configuration Service. Users submit jobs to DIRAC using their local credentials. From then on, DIRAC has to interact with different Grid services on behalf of this user. DIRAC has a proxy management service where users upload short-lived proxies to be used when DIRAC needs to act on behalf of them. Long duration proxies are uploaded by users to a MyProxy service, and DIRAC retrieves new short delegated proxies when necessary. This contribution discusses the details of the implementation of this security infrastructure in DIRAC.

GRID2D/3D: A computer program for generating grid systems in complex-shaped two- and three-dimensional spatial domains. Part 2: User's manual and program listing

NASA Technical Reports Server (NTRS)

Bailey, R. T.; Shih, T. I.-P.; Nguyen, H. L.; Roelke, R. J.

1990-01-01

An efficient computer program, called GRID2D/3D, was developed to generate single and composite grid systems within geometrically complex two- and three-dimensional (2- and 3-D) spatial domains that can deform with time. GRID2D/3D generates single grid systems by using algebraic grid generation methods based on transfinite interpolation in which the distribution of grid points within the spatial domain is controlled by stretching functions. All single grid systems generated by GRID2D/3D can have grid lines that are continuous and differentiable everywhere up to the second-order. Also, grid lines can intersect boundaries of the spatial domain orthogonally. GRID2D/3D generates composite grid systems by patching together two or more single grid systems. The patching can be discontinuous or continuous. For continuous composite grid systems, the grid lines are continuous and differentiable everywhere up to the second-order except at interfaces where different single grid systems meet. At interfaces where different single grid systems meet, the grid lines are only differentiable up to the first-order. For 2-D spatial domains, the boundary curves are described by using either cubic or tension spline interpolation. For 3-D spatial domains, the boundary surfaces are described by using either linear Coon's interpolation, bi-hyperbolic spline interpolation, or a new technique referred to as 3-D bi-directional Hermite interpolation. Since grid systems generated by algebraic methods can have grid lines that overlap one another, GRID2D/3D contains a graphics package for evaluating the grid systems generated. With the graphics package, the user can generate grid systems in an interactive manner with the grid generation part of GRID2D/3D. GRID2D/3D is written in FORTRAN 77 and can be run on any IBM PC, XT, or AT compatible computer. In order to use GRID2D/3D on workstations or mainframe computers, some minor modifications must be made in the graphics part of the program; no modifications are needed in the grid generation part of the program. The theory and method used in GRID2D/3D is described.

GRID2D/3D: A computer program for generating grid systems in complex-shaped two- and three-dimensional spatial domains. Part 1: Theory and method

NASA Technical Reports Server (NTRS)

Shih, T. I.-P.; Bailey, R. T.; Nguyen, H. L.; Roelke, R. J.

1990-01-01

An efficient computer program, called GRID2D/3D was developed to generate single and composite grid systems within geometrically complex two- and three-dimensional (2- and 3-D) spatial domains that can deform with time. GRID2D/3D generates single grid systems by using algebraic grid generation methods based on transfinite interpolation in which the distribution of grid points within the spatial domain is controlled by stretching functions. All single grid systems generated by GRID2D/3D can have grid lines that are continuous and differentiable everywhere up to the second-order. Also, grid lines can intersect boundaries of the spatial domain orthogonally. GRID2D/3D generates composite grid systems by patching together two or more single grid systems. The patching can be discontinuous or continuous. For continuous composite grid systems, the grid lines are continuous and differentiable everywhere up to the second-order except at interfaces where different single grid systems meet. At interfaces where different single grid systems meet, the grid lines are only differentiable up to the first-order. For 2-D spatial domains, the boundary curves are described by using either cubic or tension spline interpolation. For 3-D spatial domains, the boundary surfaces are described by using either linear Coon's interpolation, bi-hyperbolic spline interpolation, or a new technique referred to as 3-D bi-directional Hermite interpolation. Since grid systems generated by algebraic methods can have grid lines that overlap one another, GRID2D/3D contains a graphics package for evaluating the grid systems generated. With the graphics package, the user can generate grid systems in an interactive manner with the grid generation part of GRID2D/3D. GRID2D/3D is written in FORTRAN 77 and can be run on any IBM PC, XT, or AT compatible computer. In order to use GRID2D/3D on workstations or mainframe computers, some minor modifications must be made in the graphics part of the program; no modifications are needed in the grid generation part of the program. This technical memorandum describes the theory and method used in GRID2D/3D.

Efficient grid-based techniques for density functional theory

NASA Astrophysics Data System (ADS)

Rodriguez-Hernandez, Juan Ignacio

Understanding the chemical and physical properties of molecules and materials at a fundamental level often requires quantum-mechanical models for these substance's electronic structure. This type of many body quantum mechanics calculation is computationally demanding, hindering its application to substances with more than a few hundreds atoms. The supreme goal of many researches in quantum chemistry---and the topic of this dissertation---is to develop more efficient computational algorithms for electronic structure calculations. In particular, this dissertation develops two new numerical integration techniques for computing molecular and atomic properties within conventional Kohn-Sham-Density Functional Theory (KS-DFT) of molecular electronic structure. The first of these grid-based techniques is based on the transformed sparse grid construction. In this construction, a sparse grid is generated in the unit cube and then mapped to real space according to the pro-molecular density using the conditional distribution transformation. The transformed sparse grid was implemented in program deMon2k, where it is used as the numerical integrator for the exchange-correlation energy and potential in the KS-DFT procedure. We tested our grid by computing ground state energies, equilibrium geometries, and atomization energies. The accuracy on these test calculations shows that our grid is more efficient than some previous integration methods: our grids use fewer points to obtain the same accuracy. The transformed sparse grids were also tested for integrating, interpolating and differentiating in different dimensions (n = 1,2,3,6). The second technique is a grid-based method for computing atomic properties within QTAIM. It was also implemented in deMon2k. The performance of the method was tested by computing QTAIM atomic energies, charges, dipole moments, and quadrupole moments. For medium accuracy, our method is the fastest one we know of.

Aeroelastic Modeling of a Nozzle Startup Transient

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Zhao, Xiang; Zhang, Sijun; Chen, Yen-Sen

2014-01-01

Lateral nozzle forces are known to cause severe structural damage to any new rocket engine in development during test. While three-dimensional, transient, turbulent, chemically reacting computational fluid dynamics methodology has been demonstrated to capture major side load physics with rigid nozzles, hot-fire tests often show nozzle structure deformation during major side load events, leading to structural damages if structural strengthening measures were not taken. The modeling picture is incomplete without the capability to address the two-way responses between the structure and fluid. The objective of this study is to develop a tightly coupled aeroelastic modeling algorithm by implementing the necessary structural dynamics component into an anchored computational fluid dynamics methodology. The computational fluid dynamics component is based on an unstructured-grid, pressure-based computational fluid dynamics formulation, while the computational structural dynamics component is developed under the framework of modal analysis. Transient aeroelastic nozzle startup analyses at sea level were performed, and the computed transient nozzle fluid-structure interaction physics presented,

Development of an Aeroelastic Modeling Capability for Transient Nozzle Side Load Analysis

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Zhao, Xiang; Zhang, Sijun; Chen, Yen-Sen

2013-01-01

Lateral nozzle forces are known to cause severe structural damage to any new rocket engine in development during test. While three-dimensional, transient, turbulent, chemically reacting computational fluid dynamics methodology has been demonstrated to capture major side load physics with rigid nozzles, hot-fire tests often show nozzle structure deformation during major side load events, leading to structural damages if structural strengthening measures were not taken. The modeling picture is incomplete without the capability to address the two-way responses between the structure and fluid. The objective of this study is to develop a coupled aeroelastic modeling capability by implementing the necessary structural dynamics component into an anchored computational fluid dynamics methodology. The computational fluid dynamics component is based on an unstructured-grid, pressure-based computational fluid dynamics formulation, while the computational structural dynamics component is developed in the framework of modal analysis. Transient aeroelastic nozzle startup analyses of the Block I Space Shuttle Main Engine at sea level were performed. The computed results from the aeroelastic nozzle modeling are presented.

A Debugger for Computational Grid Applications

NASA Technical Reports Server (NTRS)

Hood, Robert; Jost, Gabriele

2000-01-01

The p2d2 project at NAS has built a debugger for applications running on heterogeneous computational grids. It employs a client-server architecture to simplify the implementation. Its user interface has been designed to provide process control and state examination functions on a computation containing a large number of processes. It can find processes participating in distributed computations even when those processes were not created under debugger control. These process identification techniques work both on conventional distributed executions as well as those on a computational grid.

Rapid Airplane Parametric Input Design(RAPID)

NASA Technical Reports Server (NTRS)

Smith, Robert E.; Bloor, Malcolm I. G.; Wilson, Michael J.; Thomas, Almuttil M.

2004-01-01

An efficient methodology is presented for defining a class of airplane configurations. Inclusive in this definition are surface grids, volume grids, and grid sensitivity. A small set of design parameters and grid control parameters govern the process. The general airplane configuration has wing, fuselage, vertical tail, horizontal tail, and canard components. The wing, tail, and canard components are manifested by solving a fourth-order partial differential equation subject to Dirichlet and Neumann boundary conditions. The design variables are incorporated into the boundary conditions, and the solution is expressed as a Fourier series. The fuselage has circular cross section, and the radius is an algebraic function of four design parameters and an independent computational variable. Volume grids are obtained through an application of the Control Point Form method. Grid sensitivity is obtained by applying the automatic differentiation precompiler ADIFOR to software for the grid generation. The computed surface grids, volume grids, and sensitivity derivatives are suitable for a wide range of Computational Fluid Dynamics simulation and configuration optimizations.

Multidisciplinary Simulation Acceleration using Multiple Shared-Memory Graphical Processing Units

NASA Astrophysics Data System (ADS)

Kemal, Jonathan Yashar

For purposes of optimizing and analyzing turbomachinery and other designs, the unsteady Favre-averaged flow-field differential equations for an ideal compressible gas can be solved in conjunction with the heat conduction equation. We solve all equations using the finite-volume multiple-grid numerical technique, with the dual time-step scheme used for unsteady simulations. Our numerical solver code targets CUDA-capable Graphical Processing Units (GPUs) produced by NVIDIA. Making use of MPI, our solver can run across networked compute notes, where each MPI process can use either a GPU or a Central Processing Unit (CPU) core for primary solver calculations. We use NVIDIA Tesla C2050/C2070 GPUs based on the Fermi architecture, and compare our resulting performance against Intel Zeon X5690 CPUs. Solver routines converted to CUDA typically run about 10 times faster on a GPU for sufficiently dense computational grids. We used a conjugate cylinder computational grid and ran a turbulent steady flow simulation using 4 increasingly dense computational grids. Our densest computational grid is divided into 13 blocks each containing 1033x1033 grid points, for a total of 13.87 million grid points or 1.07 million grid points per domain block. To obtain overall speedups, we compare the execution time of the solver's iteration loop, including all resource intensive GPU-related memory copies. Comparing the performance of 8 GPUs to that of 8 CPUs, we obtain an overall speedup of about 6.0 when using our densest computational grid. This amounts to an 8-GPU simulation running about 39.5 times faster than running than a single-CPU simulation.

Grid Generation for Multidisciplinary Design and Optimization of an Aerospace Vehicle: Issues and Challenges

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.

2000-01-01

The purpose of this paper is to discuss grid generation issues and to challenge the grid generation community to develop tools suitable for automated multidisciplinary analysis and design optimization of aerospace vehicles. Special attention is given to the grid generation issues of computational fluid dynamics and computational structural mechanics disciplines.

Task Scheduling in Desktop Grids: Open Problems

NASA Astrophysics Data System (ADS)

Chernov, Ilya; Nikitina, Natalia; Ivashko, Evgeny

2017-12-01

We survey the areas of Desktop Grid task scheduling that seem to be insufficiently studied so far and are promising for efficiency, reliability, and quality of Desktop Grid computing. These topics include optimal task grouping, "needle in a haystack" paradigm, game-theoretical scheduling, domain-imposed approaches, special optimization of the final stage of the batch computation, and Enterprise Desktop Grids.

Benchmarking Memory Performance with the Data Cube Operator

NASA Technical Reports Server (NTRS)

Frumkin, Michael A.; Shabanov, Leonid V.

2004-01-01

Data movement across a computer memory hierarchy and across computational grids is known to be a limiting factor for applications processing large data sets. We use the Data Cube Operator on an Arithmetic Data Set, called ADC, to benchmark capabilities of computers and of computational grids to handle large distributed data sets. We present a prototype implementation of a parallel algorithm for computation of the operatol: The algorithm follows a known approach for computing views from the smallest parent. The ADC stresses all levels of grid memory and storage by producing some of 2d views of an Arithmetic Data Set of d-tuples described by a small number of integers. We control data intensity of the ADC by selecting the tuple parameters, the sizes of the views, and the number of realized views. Benchmarking results of memory performance of a number of computer architectures and of a small computational grid are presented.

External Boundary Conditions for Three-Dimensional Problems of Computational Aerodynamics

NASA Technical Reports Server (NTRS)

Tsynkov, Semyon V.

1997-01-01

We consider an unbounded steady-state flow of viscous fluid over a three-dimensional finite body or configuration of bodies. For the purpose of solving this flow problem numerically, we discretize the governing equations (Navier-Stokes) on a finite-difference grid. The grid obviously cannot stretch from the body up to infinity, because the number of the discrete variables in that case would not be finite. Therefore, prior to the discretization we truncate the original unbounded flow domain by introducing some artificial computational boundary at a finite distance of the body. Typically, the artificial boundary is introduced in a natural way as the external boundary of the domain covered by the grid. The flow problem formulated only on the finite computational domain rather than on the original infinite domain is clearly subdefinite unless some artificial boundary conditions (ABC's) are specified at the external computational boundary. Similarly, the discretized flow problem is subdefinite (i.e., lacks equations with respect to unknowns) unless a special closing procedure is implemented at this artificial boundary. The closing procedure in the discrete case is called the ABC's as well. In this paper, we present an innovative approach to constructing highly accurate ABC's for three-dimensional flow computations. The approach extends our previous technique developed for the two-dimensional case; it employs the finite-difference counterparts to Calderon's pseudodifferential boundary projections calculated in the framework of the difference potentials method (DPM) by Ryaben'kii. The resulting ABC's appear spatially nonlocal but particularly easy to implement along with the existing solvers. The new boundary conditions have been successfully combined with the NASA-developed production code TLNS3D and used for the analysis of wing-shaped configurations in subsonic (including incompressible limit) and transonic flow regimes. As demonstrated by the computational experiments and comparisons with the standard (local) methods, the DPM-based ABC's allow one to greatly reduce the size of the computational domain while still maintaining high accuracy of the numerical solution. Moreover, they may provide for a noticeable increase of the convergence rate of multigrid iterations.

Obesity Policy Action framework and analysis grids for a comprehensive policy approach to reducing obesity.

PubMed

Sacks, G; Swinburn, B; Lawrence, M

2009-01-01

A comprehensive policy approach is needed to control the growing obesity epidemic. This paper proposes the Obesity Policy Action (OPA) framework, modified from the World Health Organization framework for the implementation of the Global Strategy on Diet, Physical Activity and Health, to provide specific guidance for governments to systematically identify areas for obesity policy action. The proposed framework incorporates three different public health approaches to addressing obesity: (i) 'upstream' policies influence either the broad social and economic conditions of society (e.g. taxation, education, social security) or the food and physical activity environments to make healthy eating and physical activity choices easier; (ii) 'midstream' policies are aimed at directly influencing population behaviours; and (iii) 'downstream' policies support health services and clinical interventions. A set of grids for analysing potential policies to support obesity prevention and management is presented. The general pattern that emerges from populating the analysis grids as they relate to the Australian context is that all sectors and levels of government, non-governmental organizations and private businesses have multiple opportunities to contribute to reducing obesity. The proposed framework and analysis grids provide a comprehensive approach to mapping the policy environment related to obesity, and a tool for identifying policy gaps, barriers and opportunities.

Database of extended radiation maps and its access system

NASA Astrophysics Data System (ADS)

Verkhodanov, O. V.; Naiden, Ya. V.; Chernenkov, V. N.; Verkhodanova, N. V.

2014-01-01

We describe the architecture of the developed computing web server http://cmb.sao.ru allowing to synthesize the maps of extended radiation on the full sphere from the spherical harmonics in the GLESP pixelization grid, smooth them with the power beam pattern with various angular resolutions in the multipole space, and identify regions of the sky with given coordinates. We describe the server access and administration systems as well as the technique constructing the sky region maps, organized in Python in the Django web-application development framework.

Near-Body Grid Adaption for Overset Grids

NASA Technical Reports Server (NTRS)

Buning, Pieter G.; Pulliam, Thomas H.

2016-01-01

A solution adaption capability for curvilinear near-body grids has been implemented in the OVERFLOW overset grid computational fluid dynamics code. The approach follows closely that used for the Cartesian off-body grids, but inserts refined grids in the computational space of original near-body grids. Refined curvilinear grids are generated using parametric cubic interpolation, with one-sided biasing based on curvature and stretching ratio of the original grid. Sensor functions, grid marking, and solution interpolation tasks are implemented in the same fashion as for off-body grids. A goal-oriented procedure, based on largest error first, is included for controlling growth rate and maximum size of the adapted grid system. The adaption process is almost entirely parallelized using MPI, resulting in a capability suitable for viscous, moving body simulations. Two- and three-dimensional examples are presented.

FermiGrid - experience and future plans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chadwick, K.; Berman, E.; Canal, P.

2007-09-01

Fermilab supports a scientific program that includes experiments and scientists located across the globe. In order to better serve this community, Fermilab has placed its production computer resources in a Campus Grid infrastructure called 'FermiGrid'. The FermiGrid infrastructure allows the large experiments at Fermilab to have priority access to their own resources, enables sharing of these resources in an opportunistic fashion, and movement of work (jobs, data) between the Campus Grid and National Grids such as Open Science Grid and the WLCG. FermiGrid resources support multiple Virtual Organizations (VOs), including VOs from the Open Science Grid (OSG), EGEE and themore » Worldwide LHC Computing Grid Collaboration (WLCG). Fermilab also makes leading contributions to the Open Science Grid in the areas of accounting, batch computing, grid security, job management, resource selection, site infrastructure, storage management, and VO services. Through the FermiGrid interfaces, authenticated and authorized VOs and individuals may access our core grid services, the 10,000+ Fermilab resident CPUs, near-petabyte (including CMS) online disk pools and the multi-petabyte Fermilab Mass Storage System. These core grid services include a site wide Globus gatekeeper, VO management services for several VOs, Fermilab site authorization services, grid user mapping services, as well as job accounting and monitoring, resource selection and data movement services. Access to these services is via standard and well-supported grid interfaces. We will report on the user experience of using the FermiGrid campus infrastructure interfaced to a national cyberinfrastructure--the successes and the problems.« less

User-level framework for performance monitoring of HPC applications

NASA Astrophysics Data System (ADS)

Hristova, R.; Goranov, G.

2013-10-01

HP-SEE is an infrastructure that links the existing HPC facilities in South East Europe in a common infrastructure. The analysis of the performance monitoring of the High-Performance Computing (HPC) applications in the infrastructure can be useful for the end user as diagnostic for the overall performance of his applications. The existing monitoring tools for HP-SEE provide to the end user only aggregated information for all applications. Usually, the user does not have permissions to select only the relevant information for him and for his applications. In this article we present a framework for performance monitoring of the HPC applications in the HP-SEE infrastructure. The framework provides standardized performance metrics, which every user can use in order to monitor his applications. Furthermore as a part of the framework a program interface is developed. The interface allows the user to publish metrics data from his application and to read and analyze gathered information. Publishing and reading through the framework is possible only with grid certificate valid for the infrastructure. Therefore the user is authorized to access only the data for his applications.

An Efficient and Adaptive Mutual Authentication Framework for Heterogeneous Wireless Sensor Network-Based Applications

PubMed Central

Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae

2014-01-01

Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications. PMID:24521942

An efficient and adaptive mutual authentication framework for heterogeneous wireless sensor network-based applications.

PubMed

Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae

2014-02-11

Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications.

Conservative zonal schemes for patched grids in 2 and 3 dimensions

NASA Technical Reports Server (NTRS)

Hessenius, Kristin A.

1987-01-01

The computation of flow over complex geometries, such as realistic aircraft configurations, poses difficult grid generation problems for computational aerodynamicists. The creation of a traditional, single-module grid of acceptable quality about an entire configuration may be impossible even with the most sophisticated of grid generation techniques. A zonal approach, wherein the flow field is partitioned into several regions within which grids are independently generated, is a practical alternative for treating complicated geometries. This technique not only alleviates the problems of discretizing a complex region, but also facilitates a block processing approach to computation thereby circumventing computer memory limitations. The use of such a zonal scheme, however, requires the development of an interfacing procedure that ensures a stable, accurate, and conservative calculation for the transfer of information across the zonal borders.

Computational System For Rapid CFD Analysis In Engineering

NASA Technical Reports Server (NTRS)

Barson, Steven L.; Ascoli, Edward P.; Decroix, Michelle E.; Sindir, Munir M.

1995-01-01

Computational system comprising modular hardware and software sub-systems developed to accelerate and facilitate use of techniques of computational fluid dynamics (CFD) in engineering environment. Addresses integration of all aspects of CFD analysis process, including definition of hardware surfaces, generation of computational grids, CFD flow solution, and postprocessing. Incorporates interfaces for integration of all hardware and software tools needed to perform complete CFD analysis. Includes tools for efficient definition of flow geometry, generation of computational grids, computation of flows on grids, and postprocessing of flow data. System accepts geometric input from any of three basic sources: computer-aided design (CAD), computer-aided engineering (CAE), or definition by user.

Multi-grid finite element method used for enhancing the reconstruction accuracy in Cerenkov luminescence tomography

NASA Astrophysics Data System (ADS)

Guo, Hongbo; He, Xiaowei; Liu, Muhan; Zhang, Zeyu; Hu, Zhenhua; Tian, Jie

2017-03-01

Cerenkov luminescence tomography (CLT), as a promising optical molecular imaging modality, can be applied to cancer diagnostic and therapeutic. Most researches about CLT reconstruction are based on the finite element method (FEM) framework. However, the quality of FEM mesh grid is still a vital factor to restrict the accuracy of the CLT reconstruction result. In this paper, we proposed a multi-grid finite element method framework, which was able to improve the accuracy of reconstruction. Meanwhile, the multilevel scheme adaptive algebraic reconstruction technique (MLS-AART) based on a modified iterative algorithm was applied to improve the reconstruction accuracy. In numerical simulation experiments, the feasibility of our proposed method were evaluated. Results showed that the multi-grid strategy could obtain 3D spatial information of Cerenkov source more accurately compared with the traditional single-grid FEM.

Effects of Land Surface Heterogeneity on Simulated Boundary-Layer Structures from the LES to the Mesoscale

NASA Astrophysics Data System (ADS)

Poll, Stefan; Shrestha, Prabhakar; Simmer, Clemens

2017-04-01

Land heterogeneity influences the atmospheric boundary layer (ABL) structure including organized (secondary) circulations which feed back on land-atmosphere exchange fluxes. Especially the latter effects cannot be incorporated explicitly in regional and climate models due to their coarse computational spatial grids, but must be parameterized. Current parameterizations lead, however, to uncertainties in modeled surface fluxes and boundary layer evolution, which feed back to cloud initiation and precipitation. This study analyzes the impact of different horizontal grid resolutions on the simulated boundary layer structures in terms of stability, height and induced secondary circulations. The ICON-LES (Icosahedral Nonhydrostatic in LES mode) developed by the MPI-M and the German weather service (DWD) and conducted within the framework of HD(CP)2 is used. ICON is dynamically downscaled through multiple scales of 20 km, 7 km, 2.8 km, 625 m, 312 m, and 156 m grid spacing for several days over Germany and partial neighboring countries for different synoptic conditions. We examined the entropy spectrum of the land surface heterogeneity at these grid resolutions for several locations close to measurement sites, such as Lindenberg, Jülich, Cabauw and Melpitz, and studied its influence on the surface fluxes and the evolution of the boundary layer profiles.

Sustaining and Extending the Open Science Grid: Science Innovation on a PetaScale Nationwide Facility (DE-FC02-06ER41436) SciDAC-2 Closeout Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Livny, Miron; Shank, James; Ernst, Michael

Under this SciDAC-2 grant the project’s goal w a s t o stimulate new discoveries by providing scientists with effective and dependable access to an unprecedented national distributed computational facility: the Open Science Grid (OSG). We proposed to achieve this through the work of the Open Science Grid Consortium: a unique hands-on multi-disciplinary collaboration of scientists, software developers and providers of computing resources. Together the stakeholders in this consortium sustain and use a shared distributed computing environment that transforms simulation and experimental science in the US. The OSG consortium is an open collaboration that actively engages new research communities. Wemore » operate an open facility that brings together a broad spectrum of compute, storage, and networking resources and interfaces to other cyberinfrastructures, including the US XSEDE (previously TeraGrid), the European Grids for ESciencE (EGEE), as well as campus and regional grids. We leverage middleware provided by computer science groups, facility IT support organizations, and computing programs of application communities for the benefit of consortium members and the US national CI.« less

Parallel stochastic simulation of macroscopic calcium currents.

PubMed

González-Vélez, Virginia; González-Vélez, Horacio

2007-06-01

This work introduces MACACO, a macroscopic calcium currents simulator. It provides a parameter-sweep framework which computes macroscopic Ca(2+) currents from the individual aggregation of unitary currents, using a stochastic model for L-type Ca(2+) channels. MACACO uses a simplified 3-state Markov model to simulate the response of each Ca(2+) channel to different voltage inputs to the cell. In order to provide an accurate systematic view for the stochastic nature of the calcium channels, MACACO is composed of an experiment generator, a central simulation engine and a post-processing script component. Due to the computational complexity of the problem and the dimensions of the parameter space, the MACACO simulation engine employs a grid-enabled task farm. Having been designed as a computational biology tool, MACACO heavily borrows from the way cell physiologists conduct and report their experimental work.

Discrete element weld model, phase 2

NASA Technical Reports Server (NTRS)

Prakash, C.; Samonds, M.; Singhal, A. K.

1987-01-01

A numerical method was developed for analyzing the tungsten inert gas (TIG) welding process. The phenomena being modeled include melting under the arc and the flow in the melt under the action of buoyancy, surface tension, and electromagnetic forces. The latter entails the calculation of the electric potential and the computation of electric current and magnetic field therefrom. Melting may occur at a single temperature or over a temperature range, and the electrical and thermal conductivities can be a function of temperature. Results of sample calculations are presented and discussed at length. A major research contribution has been the development of numerical methodology for the calculation of phase change problems in a fixed grid framework. The model has been implemented on CHAM's general purpose computer code PHOENICS. The inputs to the computer model include: geometric parameters, material properties, and weld process parameters.

Using Computing and Data Grids for Large-Scale Science and Engineering

NASA Technical Reports Server (NTRS)

Johnston, William E.

2001-01-01

We use the term "Grid" to refer to a software system that provides uniform and location independent access to geographically and organizationally dispersed, heterogeneous resources that are persistent and supported. These emerging data and computing Grids promise to provide a highly capable and scalable environment for addressing large-scale science problems. We describe the requirements for science Grids, the resulting services and architecture of NASA's Information Power Grid (IPG) and DOE's Science Grid, and some of the scaling issues that have come up in their implementation.

Collar grids for intersecting geometric components within the Chimera overlapped grid scheme

NASA Technical Reports Server (NTRS)

Parks, Steven J.; Buning, Pieter G.; Chan, William M.; Steger, Joseph L.

1991-01-01

A method for overcoming problems with using the Chimera overset grid scheme in the region of intersecting geometry components is presented. A 'collar grid' resolves the intersection region and provides communication between the component grids. This approach is validated by comparing computed and experimental data for a flow about a wing/body configuration. Application of the collar grid scheme to the Orbiter fuselage and vertical tail intersection in a computation of the full Space Shuttle launch vehicle demonstrates its usefulness for simulation of flow about complex aerospace vehicles.

Integrating Grid Services into the Cray XT4 Environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

NERSC; Cholia, Shreyas; Lin, Hwa-Chun Wendy

2009-05-01

The 38640 core Cray XT4"Franklin" system at the National Energy Research Scientific Computing Center (NERSC) is a massively parallel resource available to Department of Energy researchers that also provides on-demand grid computing to the Open Science Grid. The integration of grid services on Franklin presented various challenges, including fundamental differences between the interactive and compute nodes, a stripped down compute-node operating system without dynamic library support, a shared-root environment and idiosyncratic application launching. Inour work, we describe how we resolved these challenges on a running, general-purpose production system to provide on-demand compute, storage, accounting and monitoring services through generic gridmore » interfaces that mask the underlying system-specific details for the end user.« less

Computation of Flow Over a Drag Prediction Workshop Wing/Body Transport Configuration Using CFL3D

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.; Biedron, Robert T.

2001-01-01

A Drag Prediction Workshop was held in conjunction with the 19th AIAA Applied Aerodynamics Conference in June 2001. The purpose of the workshop was to assess the prediction of drag by computational methods for a wing/body configuration (DLR-F4) representative of subsonic transport aircraft. This report details computed results submitted to this workshop using the Reynolds-averaged Navier-Stokes code CFL3D. Two supplied grids were used: a point-matched 1-to-1 multi-block grid, and an overset multi-block grid. The 1-to-1 grid, generally of much poorer quality and with less streamwise resolution than the overset grid, is found to be too coarse to adequately resolve the surface pressures. However, the global forces and moments are nonetheless similar to those computed using the overset grid. The effect of three different turbulence models is assessed using the 1-to-1 grid. Surface pressures are very similar overall, and the drag variation due to turbulence model is 18 drag counts. Most of this drag variation is in the friction component, and is attributed in part to insufficient grid resolution of the 1-to-1 grid. The misnomer of 'fully turbulent' computations is discussed; comparisons are made using different transition locations and their effects on the global forces and moments are quantified. Finally, the effect of two different versions of a widely used one-equation turbulence model is explored.

DICOMGrid: a middleware to integrate PACS and EELA-2 grid infrastructure

NASA Astrophysics Data System (ADS)

Moreno, Ramon A.; de Sá Rebelo, Marina; Gutierrez, Marco A.

2010-03-01

Medical images provide lots of information for physicians, but the huge amount of data produced by medical image equipments in a modern Health Institution is not completely explored in its full potential yet. Nowadays medical images are used in hospitals mostly as part of routine activities while its intrinsic value for research is underestimated. Medical images can be used for the development of new visualization techniques, new algorithms for patient care and new image processing techniques. These research areas usually require the use of huge volumes of data to obtain significant results, along with enormous computing capabilities. Such qualities are characteristics of grid computing systems such as EELA-2 infrastructure. The grid technologies allow the sharing of data in large scale in a safe and integrated environment and offer high computing capabilities. In this paper we describe the DicomGrid to store and retrieve medical images, properly anonymized, that can be used by researchers to test new processing techniques, using the computational power offered by grid technology. A prototype of the DicomGrid is under evaluation and permits the submission of jobs into the EELA-2 grid infrastructure while offering a simple interface that requires minimal understanding of the grid operation.

Minimizing Cache Misses Using Minimum-Surface Bodies

NASA Technical Reports Server (NTRS)

Frumkin, Michael; VanderWijngaart, Rob; Biegel, Bryan (Technical Monitor)

2002-01-01

A number of known techniques for improving cache performance in scientific computations involve the reordering of the iteration space. Some of these reorderings can be considered as coverings of the iteration space with the sets having good surface-to-volume ratio. Use of such sets reduces the number of cache misses in computations of local operators having the iteration space as a domain. First, we derive lower bounds which any algorithm must suffer while computing a local operator on a grid. Then we explore coverings of iteration spaces represented by structured and unstructured grids which allow us to approach these lower bounds. For structured grids we introduce a covering by successive minima tiles of the interference lattice of the grid. We show that the covering has low surface-to-volume ratio and present a computer experiment showing actual reduction of the cache misses achieved by using these tiles. For planar unstructured grids we show existence of a covering which reduces the number of cache misses to the level of structured grids. On the other hand, we present a triangulation of a 3-dimensional cube such that any local operator on the corresponding grid has significantly larger number of cache misses than a similar operator on a structured grid.

How to deal with petabytes of data: the LHC Grid project

NASA Astrophysics Data System (ADS)

Britton, D.; Lloyd, S. L.

2014-06-01

We review the Grid computing system developed by the international community to deal with the petabytes of data coming from the Large Hadron Collider at CERN in Geneva with particular emphasis on the ATLAS experiment and the UK Grid project, GridPP. Although these developments were started over a decade ago, this article explains their continued relevance as part of the ‘Big Data’ problem and how the Grid has been forerunner of today's cloud computing.

Preprocessor that Enables the Use of GridProTM Grids for Unsteady Reynolds-Averaged Navier-Stokes Code TURBO

NASA Technical Reports Server (NTRS)

Shyam, Vikram

2010-01-01

A preprocessor for the Computational Fluid Dynamics (CFD) code TURBO has been developed and tested. The preprocessor converts grids produced by GridPro (Program Development Company (PDC)) into a format readable by TURBO and generates the necessary input files associated with the grid. The preprocessor also generates information that enables the user to decide how to allocate the computational load in a multiple block per processor scenario.

Methodological Approaches for Estimating the Benefits and Costs of Smart Grid Demonstration Projects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Russell

This report presents a comprehensive framework for estimating the benefits and costs of Smart Grid projects and a step-by-step approach for making these estimates. The framework identifies the basic categories of benefits, the beneficiaries of these benefits, and the Smart Grid functionalities that lead to different benefits and proposes ways to estimate these benefits, including their monetization. The report covers cost-effectiveness evaluation, uncertainty, and issues in estimating baseline conditions against which a project would be compared. The report also suggests metrics suitable for describing principal characteristics of a modern Smart Grid to which a project can contribute. This first sectionmore » of the report presents background information on the motivation for the report and its purpose. Section 2 introduces the methodological framework, focusing on the definition of benefits and a sequential, logical process for estimating them. Beginning with the Smart Grid technologies and functions of a project, it maps these functions to the benefits they produce. Section 3 provides a hypothetical example to illustrate the approach. Section 4 describes each of the 10 steps in the approach. Section 5 covers issues related to estimating benefits of the Smart Grid. Section 6 summarizes the next steps. The methods developed in this study will help improve future estimates - both retrospective and prospective - of the benefits of Smart Grid investments. These benefits, including those to consumers, society in general, and utilities, can then be weighed against the investments. Such methods would be useful in total resource cost tests and in societal versions of such tests. As such, the report will be of interest not only to electric utilities, but also to a broad constituency of stakeholders. Significant aspects of the methodology were used by the U.S. Department of Energy (DOE) to develop its methods for estimating the benefits and costs of its renewable and distributed systems integration demonstration projects as well as its Smart Grid Investment Grant projects and demonstration projects funded under the American Recovery and Reinvestment Act (ARRA). The goal of this report, which was cofunded by the Electric Power Research Institute (EPRI) and DOE, is to present a comprehensive set of methods for estimating the benefits and costs of Smart Grid projects. By publishing this report, EPRI seeks to contribute to the development of methods that will establish the benefits associated with investments in Smart Grid technologies. EPRI does not endorse the contents of this report or make any representations as to the accuracy and appropriateness of its contents. The purpose of this report is to present a methodological framework that will provide a standardized approach for estimating the benefits and costs of Smart Grid demonstration projects. The framework also has broader application to larger projects, such as those funded under the ARRA. Moreover, with additional development, it will provide the means for extrapolating the results of pilots and trials to at-scale investments in Smart Grid technologies. The framework was developed by a panel whose members provided a broad range of expertise.« less

Techniques for grid manipulation and adaptation. [computational fluid dynamics

NASA Technical Reports Server (NTRS)

Choo, Yung K.; Eisemann, Peter R.; Lee, Ki D.

1992-01-01

Two approaches have been taken to provide systematic grid manipulation for improved grid quality. One is the control point form (CPF) of algebraic grid generation. It provides explicit control of the physical grid shape and grid spacing through the movement of the control points. It works well in the interactive computer graphics environment and hence can be a good candidate for integration with other emerging technologies. The other approach is grid adaptation using a numerical mapping between the physical space and a parametric space. Grid adaptation is achieved by modifying the mapping functions through the effects of grid control sources. The adaptation process can be repeated in a cyclic manner if satisfactory results are not achieved after a single application.

Current Grid operation and future role of the Grid

NASA Astrophysics Data System (ADS)

Smirnova, O.

2012-12-01

Grid-like technologies and approaches became an integral part of HEP experiments. Some other scientific communities also use similar technologies for data-intensive computations. The distinct feature of Grid computing is the ability to federate heterogeneous resources of different ownership into a seamless infrastructure, accessible via a single log-on. Like other infrastructures of similar nature, Grid functioning requires not only technologically sound basis, but also reliable operation procedures, monitoring and accounting. The two aspects, technological and operational, are closely related: weaker is the technology, more burden is on operations, and other way around. As of today, Grid technologies are still evolving: at CERN alone, every LHC experiment uses an own Grid-like system. This inevitably creates a heavy load on operations. Infrastructure maintenance, monitoring and incident response are done on several levels, from local system administrators to large international organisations, involving massive human effort worldwide. The necessity to commit substantial resources is one of the obstacles faced by smaller research communities when moving computing to the Grid. Moreover, most current Grid solutions were developed under significant influence of HEP use cases, and thus need additional effort to adapt them to other applications. Reluctance of many non-HEP researchers to use Grid negatively affects the outlook for national Grid organisations, which strive to provide multi-science services. We started from the situation where Grid organisations were fused with HEP laboratories and national HEP research programmes; we hope to move towards the world where Grid will ultimately reach the status of generic public computing and storage service provider and permanent national and international Grid infrastructures will be established. How far will we be able to advance along this path, depends on us. If no standardisation and convergence efforts will take place, Grid will become limited to HEP; if however the current multitude of Grid-like systems will converge to a generic, modular and extensible solution, Grid will become true to its name.

The CMS Tier0 goes cloud and grid for LHC Run 2

DOE PAGES

Hufnagel, Dirk

2015-12-23

In 2015, CMS will embark on a new era of collecting LHC collisions at unprecedented rates and complexity. This will put a tremendous stress on our computing systems. Prompt Processing of the raw data by the Tier-0 infrastructure will no longer be constrained to CERN alone due to the significantly increased resource requirements. In LHC Run 2, we will need to operate it as a distributed system utilizing both the CERN Cloud-based Agile Infrastructure and a significant fraction of the CMS Tier-1 Grid resources. In another big change for LHC Run 2, we will process all data using the multi-threadedmore » framework to deal with the increased event complexity and to ensure efficient use of the resources. Furthermore, this contribution will cover the evolution of the Tier-0 infrastructure and present scale testing results and experiences from the first data taking in 2015.« less

PLUM: Parallel Load Balancing for Adaptive Unstructured Meshes

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Biswas, Rupak; Saini, Subhash (Technical Monitor)

1998-01-01

Mesh adaption is a powerful tool for efficient unstructured-grid computations but causes load imbalance among processors on a parallel machine. We present a novel method called PLUM to dynamically balance the processor workloads with a global view. This paper presents the implementation and integration of all major components within our dynamic load balancing strategy for adaptive grid calculations. Mesh adaption, repartitioning, processor assignment, and remapping are critical components of the framework that must be accomplished rapidly and efficiently so as not to cause a significant overhead to the numerical simulation. A data redistribution model is also presented that predicts the remapping cost on the SP2. This model is required to determine whether the gain from a balanced workload distribution offsets the cost of data movement. Results presented in this paper demonstrate that PLUM is an effective dynamic load balancing strategy which remains viable on a large number of processors.

The CMS TierO goes Cloud and Grid for LHC Run 2

NASA Astrophysics Data System (ADS)

Hufnagel, Dirk

2015-12-01

In 2015, CMS will embark on a new era of collecting LHC collisions at unprecedented rates and complexity. This will put a tremendous stress on our computing systems. Prompt Processing of the raw data by the Tier-0 infrastructure will no longer be constrained to CERN alone due to the significantly increased resource requirements. In LHC Run 2, we will need to operate it as a distributed system utilizing both the CERN Cloud-based Agile Infrastructure and a significant fraction of the CMS Tier-1 Grid resources. In another big change for LHC Run 2, we will process all data using the multi-threaded framework to deal with the increased event complexity and to ensure efficient use of the resources. This contribution will cover the evolution of the Tier-0 infrastructure and present scale testing results and experiences from the first data taking in 2015.

IceProd 2 Usage Experience

NASA Astrophysics Data System (ADS)

Delventhal, D.; Schultz, D.; Diaz Velez, J. C.

2017-10-01

IceProd is a data processing and management framework developed by the IceCube Neutrino Observatory for processing of Monte Carlo simulations, detector data, and data driven analysis. It runs as a separate layer on top of grid and batch systems. This is accomplished by a set of daemons which process job workflow, maintaining configuration and status information on the job before, during, and after processing. IceProd can also manage complex workflow DAGs across distributed computing grids in order to optimize usage of resources. IceProd has recently been rewritten to increase its scaling capabilities, handle user analysis workflows together with simulation production, and facilitate the integration with 3rd party scheduling tools. IceProd 2, the second generation of IceProd, has been running in production for several months now. We share our experience setting up the system and things we’ve learned along the way.

Global Discrete Artificial Boundary Conditions for Time-Dependent Wave Propagation

NASA Technical Reports Server (NTRS)

Ryabenkii, V. S.; Tsynkov, S. V.; Turchaninov, V. I.; Bushnell, Dennis M. (Technical Monitor)

2001-01-01

We construct global artificial boundary conditions (ABCs) for the numerical simulation of wave processes on unbounded domains using a special non-deteriorating algorithm that has been developed previously for the long-term computation of wave-radiation solutions. The ABCs are obtained directly for the discrete formulation of the problem; in so doing, neither a rational approximation of 'non-reflecting kernels,' nor discretization of the continuous boundary conditions is required. The extent of temporal nonlocality of the new ABCs appears fixed and limited; in addition, the ABCs can handle artificial boundaries of irregular shape on regular grids with no fitting/adaptation needed and no accuracy loss induced. The non-deteriorating algorithm, which is the core of the new ABCs is inherently three-dimensional, it guarantees temporally uniform grid convergence of the solution driven by a continuously operating source on arbitrarily long time intervals, and provides unimprovable linear computational complexity with respect to the grid dimension. The algorithm is based on the presence of lacunae, i.e., aft fronts of the waves, in wave-type solutions in odd-dimension spaces, It can, in fact, be built as a modification on top of any consistent and stable finite-difference scheme, making its grid convergence uniform in time and at the same time keeping the rate of convergence the same as that of the non-modified scheme. In the paper, we delineate the construction of the global lacunae-based ABCs in the framework of a discretized wave equation. The ABCs are obtained for the most general formulation of the problem that involves radiation of waves by moving sources (e.g., radiation of acoustic waves by a maneuvering aircraft). We also present systematic numerical results that corroborate the theoretical design properties of the ABCs' algorithm.

An improved resource management model based on MDS

NASA Astrophysics Data System (ADS)

Yuan, Man; Sun, Changying; Li, Pengfei; Sun, Yongdong; He, Rui

2005-11-01

GRID technology provides a kind of convenient method for managing GRID resources. This service is so-called monitoring, discovering service. This method is proposed by Globus Alliance, in this GRID environment, all kinds of resources, such as computational resources, storage resources and other resources can be organized by MDS specifications. However, this MDS is a theory framework, particularly, in a small world intranet, in the case of limit of resources, the MDS has its own limitation. Based on MDS, an improved light method for managing corporation computational resources and storage resources is proposed in intranet(IMDS). Firstly, in MDS, all kinds of resource description information is stored in LDAP, it is well known although LDAP is a light directory access protocol, in practice, programmers rarely master how to access and store resource information into LDAP store, in such way, it limits MDS to be used. So, in intranet, these resources' description information can be stored in RDBMS, programmers and users can access this information by standard SQL. Secondly, in MDS, how to monitor all kinds of resources in GRID is not transparent for programmers and users. In such way, it limits its application scope, in general, resource monitoring method base on SNMP is widely employed in intranet, therefore, a kind of resource monitoring method based on SNMP is integrated into MDS. Finally, all kinds of resources in the intranet can be described by XML, and all kinds of resources' description information is stored in RDBMS, such as MySql, and retrieved by standard SQL, dynamic information for all kinds of resources can be sent to resource storage by SNMP, A prototype resource description, monitoring is designed and implemented in intranet.

Global Discrete Artificial Boundary Conditions for Time-Dependent Wave Propagation

NASA Astrophysics Data System (ADS)

Ryaben'kii, V. S.; Tsynkov, S. V.; Turchaninov, V. I.

2001-12-01

We construct global artificial boundary conditions (ABCs) for the numerical simulation of wave processes on unbounded domains using a special nondeteriorating algorithm that has been developed previously for the long-term computation of wave-radiation solutions. The ABCs are obtained directly for the discrete formulation of the problem; in so doing, neither a rational approximation of “nonreflecting kernels” nor discretization of the continuous boundary conditions is required. The extent of temporal nonlocality of the new ABCs appears fixed and limited; in addition, the ABCs can handle artificial boundaries of irregular shape on regular grids with no fitting/adaptation needed and no accuracy loss induced. The nondeteriorating algorithm, which is the core of the new ABCs, is inherently three-dimensional, it guarantees temporally uniform grid convergence of the solution driven by a continuously operating source on arbitrarily long time intervals and provides unimprovable linear computational complexity with respect to the grid dimension. The algorithm is based on the presence of lacunae, i.e., aft fronts of the waves, in wave-type solutions in odd-dimensional spaces. It can, in fact, be built as a modification on top of any consistent and stable finite-difference scheme, making its grid convergence uniform in time and at the same time keeping the rate of convergence the same as that of the unmodified scheme. In this paper, we delineate the construction of the global lacunae-based ABCs in the framework of a discretized wave equation. The ABCs are obtained for the most general formulation of the problem that involves radiation of waves by moving sources (e.g., radiation of acoustic waves by a maneuvering aircraft). We also present systematic numerical results that corroborate the theoretical design properties of the ABC algorithm.

The research and application of the power big data

NASA Astrophysics Data System (ADS)

Zhang, Suxiang; Zhang, Dong; Zhang, Yaping; Cao, Jinping; Xu, Huiming

2017-01-01

Facing the increasing environment crisis, how to improve energy efficiency is the important problem. Power big data is main support tool to realize demand side management and response. With the promotion of smart power consumption, distributed clean energy and electric vehicles etc get wide application; meanwhile, the continuous development of the Internet of things technology, more applications access the endings in the grid power link, which leads to that a large number of electric terminal equipment, new energy access smart grid, and it will produce massive heterogeneous and multi-state electricity data. These data produce the power grid enterprise's precious wealth, as the power big data. How to transform it into valuable knowledge and effective operation becomes an important problem, it needs to interoperate in the smart grid. In this paper, we had researched the various applications of power big data and integrate the cloud computing and big data technology, which include electricity consumption online monitoring, the short-term power load forecasting and the analysis of the energy efficiency. Based on Hadoop, HBase and Hive etc., we realize the ETL and OLAP functions; and we also adopt the parallel computing framework to achieve the power load forecasting algorithms and propose a parallel locally weighted linear regression model; we study on energy efficiency rating model to comprehensive evaluate the level of energy consumption of electricity users, which allows users to understand their real-time energy consumption situation, adjust their electricity behavior to reduce energy consumption, it provides decision-making basis for the user. With an intelligent industrial park as example, this paper complete electricity management. Therefore, in the future, power big data will provide decision-making support tools for energy conservation and emissions reduction.

Two-boundary grid generation for the solution of the three dimensional compressible Navier-Stokes equations. Ph.D. Thesis - Old Dominion Univ.

NASA Technical Reports Server (NTRS)

Smith, R. E.

1981-01-01

A grid generation technique called the two boundary technique is developed and applied for the solution of the three dimensional Navier-Stokes equations. The Navier-Stokes equations are transformed from a cartesian coordinate system to a computational coordinate system, and the grid generation technique provides the Jacobian matrix describing the transformation. The two boundary technique is based on algebraically defining two distinct boundaries of a flow domain and the distribution of the grid is achieved by applying functions to the uniform computational grid which redistribute the computational independent variables and consequently concentrate or disperse the grid points in the physical domain. The Navier-Stokes equations are solved using a MacCormack time-split technique. Grids and supersonic laminar flow solutions are obtained for a family of three dimensional corners and two spike-nosed bodies.

Computing for Finance

ScienceCinema

None

2018-01-24

The finance sector is one of the driving forces for the use of distributed or Grid computing for business purposes. The speakers will review the state-of-the-art of high performance computing in the financial sector, and provide insight into how different types of Grid computing – from local clusters to global networks - are being applied to financial applications. They will also describe the use of software and techniques from physics, such as Monte Carlo simulations, in the financial world. There will be four talks of 20min each. The talk abstracts and speaker bios are listed below. This will be followed by a Q&A; panel session with the speakers. From 19:00 onwards there will be a networking cocktail for audience and speakers. This is an EGEE / CERN openlab event organized in collaboration with the regional business network rezonance.ch. A webcast of the event will be made available for subsequent viewing, along with powerpoint material presented by the speakers. Attendance is free and open to all. Registration is mandatory via www.rezonance.ch, including for CERN staff. 1. Overview of High Performance Computing in the Financial Industry Michael Yoo, Managing Director, Head of the Technical Council, UBS Presentation will describe the key business challenges driving the need for HPC solutions, describe the means in which those challenges are being addressed within UBS (such as GRID) as well as the limitations of some of these solutions, and assess some of the newer HPC technologies which may also play a role in the Financial Industry in the future. Speaker Bio: Michael originally joined the former Swiss Bank Corporation in 1994 in New York as a developer on a large data warehouse project. In 1996 he left SBC and took a role with Fidelity Investments in Boston. Unable to stay away for long, he returned to SBC in 1997 while working for Perot Systems in Singapore. Finally, in 1998 he formally returned to UBS in Stamford following the merger with SBC and has remained with UBS for the past 9 years. During his tenure at UBS, he has had a number of leadership roles within IT in development, support and architecture. In 2006 Michael relocated to Switzerland to take up his current role as head of the UBS IB Technical Council, responsible for the overall technology strategy and vision of the Investment Bank. One of Michael's key responsibilities is to manage the UBS High Performance Computing Research Lab and he has been involved in a number of initiatives in the HPC space. 2. Grid in the Commercial WorldFred Gedling, Chief Technology Officer EMEA and Senior Vice President Global Services, DataSynapse Grid computing gets mentions in the press for community programs starting last decade with Seti@Home. Government, national and supranational initiatives in grid receive some press. One of the IT-industries' best-kept secrets is the use of grid computing by commercial organizations with spectacular results. Grid Computing and its evolution into Application Virtualization is discussed and how this is key to the next generation data center. Speaker Bio: Fred Gedling holds the joint roles of Chief Technology Officer for EMEA and Senior Vice President of Global Services at DataSynapse, a global provider of application virtualisation software. Based in London and working closely with organisations seeking to optimise their IT infrastructures, Fred offers unique insights into the technology of virtualisation as well as the methodology of establishing ROI and rapid deployment to the immediate advantage of the business. Fred has more than fifteen years experience of enterprise middleware and high-performance infrastructures. Prior to DataSynapse he worked in high performance CRM middleware and was the CTO EMEA for New Era of Networks (NEON) during the rapid growth of Enterprise Application Integration. His 25-year career in technology also includes management positions at Goldman Sachs and Stratus Computer. Fred holds a First Class Bsc (Hons) degree in Physics with Astrophysics from the University of Leeds and had the privilege of being a summer student at CERN.3. Opportunities for gLite in finance and related industriesAdam Vile, Head of Grid, HPC and Technical Computing, Excelian Ltd.gLite, the Grid software developed by the EGEE project, has been exceedingly successful as an enabling infrastructure, and has been a massive success in bringing together scientific and technical communities to provide the compute power to address previously incomputable problems. Not so in the finance industry. In its current form gLite would be a business disabler. There are other middleware tools that solve the finance communities compute problems much better. Things are moving on, however. There are moves afoot in the open source community to evolve the technology to address other, more sophisticated needs such as utility and interactive computing. In this talk, I will describe how Excelian is providing Grid consultancy services for the finance community and how, through its relationship to the EGEE project, Excelian is helping to identify and exploit opportunities as the research and business worlds converge. Because of the strong third party presence in the finance industry, such opportunities are few and far between, but they are there, especially as we expand sideways into related verticals such as the smaller hedge funds and energy companies. This talk will give an overview of the barriers to adoption of gLite in the finance industry and highlight some of the opportunities offered in this and related industries as the ideas around Grid mature. Speaker Bio: Dr Adam Vile is a senior consultant and head of the Grid and HPC practice at Excelian, a consultancy that focuses on financial markets professional services. He has spent many years in investment banking, as a developer, project manager and architect in both front and back office. Before joining Excelian he was senior Grid and HPC architect at Barclays Capital. Prior to joining investment banking, Adam spent a number of years lecturing in IT and mathematics at a UK University and maintains links with academia through lectures, research and through validation and steering of postgraduate courses. He is a chartered mathematician and was the conference chair of the Institute of Mathematics and its Applications first conference in computational Finance. 4. From Monte Carlo to Wall Street Daniel Egloff, Head of Financial Engineering Computing Unit, Zürich Cantonal Bank High performance computing techniques provide new means to solve computationally hard problems in the financial service industry. First I consider Monte Carlo simulation and illustrate how it can be used to implement a sophisticated credit risk management and economic capital framework. From a HPC perspective, basic Monte Carlo simulation is embarrassingly parallel and can be implemented efficiently on distributed memory clusters. Additional difficulties arise for adaptive variance reduction schemes, if the information content in a sample is very small, and if the amount of simulated date becomes huge such that incremental processing algorithms are indispensable. We discuss the business value of an advanced credit risk quantification which is particularly compelling in these days. While Monte Carlo simulation is a very versatile tool it is not always the preferred solution for the pricing of complex products like multi asset options, structured products, or credit derivatives. As a second application I show how operator methods can be used to develop a pricing framework. The scalability of operator methods relies heavily on optimized dense matrix-matrix multiplications and requires specialized BLAS level-3 implementations provided by specialized FPGA or GPU boards. Speaker Bio: Daniel Egloff studied mathematics, theoretical physics, and computer science at the University of Zurich and the ETH Zurich. He holds a PhD in Mathematics from University of Fribourg, Switzerland. After his PhD he started to work for a large Swiss insurance company in the area of asset and liability management. He continued his professional career in the consulting industry. At KPMG and Arthur Andersen he consulted international clients and implemented quantitative risk management solutions for financial institutions and insurance companies. In 2002 he joined Zurich Cantonal Bank. He was assigned to develop and implement credit portfolio risk and economic capital methodologies. He built up a competence center for high performance and cluster computing. Currently, Daniel Egloff is heading the Financial Computing unit in the ZKB Financial Engineering division. He and his team is engineering and operating high performance cluster applications for computationally intensive problems in financial risk management.

Computing for Finance

ScienceCinema

None

2018-06-20

The finance sector is one of the driving forces for the use of distributed or Grid computing for business purposes. The speakers will review the state-of-the-art of high performance computing in the financial sector, and provide insight into how different types of Grid computing – from local clusters to global networks - are being applied to financial applications. They will also describe the use of software and techniques from physics, such as Monte Carlo simulations, in the financial world. There will be four talks of 20min each. The talk abstracts and speaker bios are listed below. This will be followed by a Q&A; panel session with the speakers. From 19:00 onwards there will be a networking cocktail for audience and speakers. This is an EGEE / CERN openlab event organized in collaboration with the regional business network rezonance.ch. A webcast of the event will be made available for subsequent viewing, along with powerpoint material presented by the speakers. Attendance is free and open to all. Registration is mandatory via www.rezonance.ch, including for CERN staff. 1. Overview of High Performance Computing in the Financial Industry. Michael Yoo, Managing Director, Head of the Technical Council, UBS. Presentation will describe the key business challenges driving the need for HPC solutions, describe the means in which those challenges are being addressed within UBS (such as GRID) as well as the limitations of some of these solutions, and assess some of the newer HPC technologies which may also play a role in the Financial Industry in the future. Speaker Bio: Michael originally joined the former Swiss Bank Corporation in 1994 in New York as a developer on a large data warehouse project. In 1996 he left SBC and took a role with Fidelity Investments in Boston. Unable to stay away for long, he returned to SBC in 1997 while working for Perot Systems in Singapore. Finally, in 1998 he formally returned to UBS in Stamford following the merger with SBC and has remained with UBS for the past 9 years. During his tenure at UBS, he has had a number of leadership roles within IT in development, support and architecture. In 2006 Michael relocated to Switzerland to take up his current role as head of the UBS IB Technical Council, responsible for the overall technology strategy and vision of the Investment Bank. One of Michael's key responsibilities is to manage the UBS High Performance Computing Research Lab and he has been involved in a number of initiatives in the HPC space. 2. Grid in the Commercial WorldFred Gedling, Chief Technology Officer EMEA and Senior Vice President Global Services, DataSynapse. Grid computing gets mentions in the press for community programs starting last decade with "Seti@Home". Government, national and supranational initiatives in grid receive some press. One of the IT-industries' best-kept secrets is the use of grid computing by commercial organizations with spectacular results. Grid Computing and its evolution into Application Virtualization is discussed and how this is key to the next generation data center. Speaker Bio: Fred Gedling holds the joint roles of Chief Technology Officer for EMEA and Senior Vice President of Global Services at DataSynapse, a global provider of application virtualisation software. Based in London and working closely with organisations seeking to optimise their IT infrastructures, Fred offers unique insights into the technology of virtualisation as well as the methodology of establishing ROI and rapid deployment to the immediate advantage of the business. Fred has more than fifteen years experience of enterprise middleware and high-performance infrastructures. Prior to DataSynapse he worked in high performance CRM middleware and was the CTO EMEA for New Era of Networks (NEON) during the rapid growth of Enterprise Application Integration. His 25-year career in technology also includes management positions at Goldman Sachs and Stratus Computer. Fred holds a First Class Bsc (Hons) degree in Physics with Astrophysics from the University of Leeds and had the privilege of being a summer student at CERN.3. Opportunities for gLite in finance and related industriesAdam Vile, Head of Grid, HPC and Technical Computing, Excelian Ltd.gLite, the Grid software developed by the EGEE project, has been exceedingly successful as an enabling infrastructure, and has been a massive success in bringing together scientific and technical communities to provide the compute power to address previously incomputable problems. Not so in the finance industry. In its current form gLite would be a business disabler. There are other middleware tools that solve the finance communities compute problems much better. Things are moving on, however. There are moves afoot in the open source community to evolve the technology to address other, more sophisticated needs such as utility and interactive computing. In this talk, I will describe how Excelian is providing Grid consultancy services for the finance community and how, through its relationship to the EGEE project, Excelian is helping to identify and exploit opportunities as the research and business worlds converge. Because of the strong third party presence in the finance industry, such opportunities are few and far between, but they are there, especially as we expand sideways into related verticals such as the smaller hedge funds and energy companies. This talk will give an overview of the barriers to adoption of gLite in the finance industry and highlight some of the opportunities offered in this and related industries as the ideas around Grid mature. Speaker Bio: Dr Adam Vile is a senior consultant and head of the Grid and HPC practice at Excelian, a consultancy that focuses on financial markets professional services. He has spent many years in investment banking, as a developer, project manager and architect in both front and back office. Before joining Excelian he was senior Grid and HPC architect at Barclays Capital. Prior to joining investment banking, Adam spent a number of years lecturing in IT and mathematics at a UK University and maintains links with academia through lectures, research and through validation and steering of postgraduate courses. He is a chartered mathematician and was the conference chair of the Institute of Mathematics and its Applications first conference in computational Finance.4. From Monte Carlo to Wall Street Daniel Egloff, Head of Financial Engineering Computing Unit, Zürich Cantonal Bank High performance computing techniques provide new means to solve computationally hard problems in the financial service industry. First I consider Monte Carlo simulation and illustrate how it can be used to implement a sophisticated credit risk management and economic capital framework. From a HPC perspective, basic Monte Carlo simulation is embarrassingly parallel and can be implemented efficiently on distributed memory clusters. Additional difficulties arise for adaptive variance reduction schemes, if the information content in a sample is very small, and if the amount of simulated date becomes huge such that incremental processing algorithms are indispensable. We discuss the business value of an advanced credit risk quantification which is particularly compelling in these days. While Monte Carlo simulation is a very versatile tool it is not always the preferred solution for the pricing of complex products like multi asset options, structured products, or credit derivatives. As a second application I show how operator methods can be used to develop a pricing framework. The scalability of operator methods relies heavily on optimized dense matrix-matrix multiplications and requires specialized BLAS level-3 implementations provided by specialized FPGA or GPU boards. Speaker Bio: Daniel Egloff studied mathematics, theoretical physics, and computer science at the University of Zurich and the ETH Zurich. He holds a PhD in Mathematics from University of Fribourg, Switzerland. After his PhD he started to work for a large Swiss insurance company in the area of asset and liability management. He continued his professional career in the consulting industry. At KPMG and Arthur Andersen he consulted international clients and implemented quantitative risk management solutions for financial institutions and insurance companies. In 2002 he joined Zurich Cantonal Bank. He was assigned to develop and implement credit portfolio risk and economic capital methodologies. He built up a competence center for high performance and cluster computing. Currently, Daniel Egloff is heading the Financial Computing unit in the ZKB Financial Engineering division. He and his team is engineering and operating high performance cluster applications for computationally intensive problems in financial risk management.

Computing for Finance

ScienceCinema

None

2018-01-25

The finance sector is one of the driving forces for the use of distributed or Grid computing for business purposes. The speakers will review the state-of-the-art of high performance computing in the financial sector, and provide insight into how different types of Grid computing – from local clusters to global networks - are being applied to financial applications. They will also describe the use of software and techniques from physics, such as Monte Carlo simulations, in the financial world. There will be four talks of 20min each. The talk abstracts and speaker bios are listed below. This will be followed by a Q&A; panel session with the speakers. From 19:00 onwards there will be a networking cocktail for audience and speakers. This is an EGEE / CERN openlab event organized in collaboration with the regional business network rezonance.ch. A webcast of the event will be made available for subsequent viewing, along with powerpoint material presented by the speakers. Attendance is free and open to all. Registration is mandatory via www.rezonance.ch, including for CERN staff. 1. Overview of High Performance Computing in the Financial Industry Michael Yoo, Managing Director, Head of the Technical Council, UBS Presentation will describe the key business challenges driving the need for HPC solutions, describe the means in which those challenges are being addressed within UBS (such as GRID) as well as the limitations of some of these solutions, and assess some of the newer HPC technologies which may also play a role in the Financial Industry in the future. Speaker Bio: Michael originally joined the former Swiss Bank Corporation in 1994 in New York as a developer on a large data warehouse project. In 1996 he left SBC and took a role with Fidelity Investments in Boston. Unable to stay away for long, he returned to SBC in 1997 while working for Perot Systems in Singapore. Finally, in 1998 he formally returned to UBS in Stamford following the merger with SBC and has remained with UBS for the past 9 years. During his tenure at UBS, he has had a number of leadership roles within IT in development, support and architecture. In 2006 Michael relocated to Switzerland to take up his current role as head of the UBS IB Technical Council, responsible for the overall technology strategy and vision of the Investment Bank. One of Michael's key responsibilities is to manage the UBS High Performance Computing Research Lab and he has been involved in a number of initiatives in the HPC space. 2. Grid in the Commercial WorldFred Gedling, Chief Technology Officer EMEA and Senior Vice President Global Services, DataSynapse Grid computing gets mentions in the press for community programs starting last decade with Government, national and supranational initiatives in grid receive some press. One of the IT-industries' best-kept secrets is the use of grid computing by commercial organizations with spectacular results. Grid Computing and its evolution into Application Virtualization is discussed and how this is key to the next generation data center. Speaker Bio: Fred Gedling holds the joint roles of Chief Technology Officer for EMEA and Senior Vice President of Global Services at DataSynapse, a global provider of application virtualisation software. Based in London and working closely with organisations seeking to optimise their IT infrastructures, Fred offers unique insights into the technology of virtualisation as well as the methodology of establishing ROI and rapid deployment to the immediate advantage of the business. Fred has more than fifteen years experience of enterprise middleware and high-performance infrastructures. Prior to DataSynapse he worked in high performance CRM middleware and was the CTO EMEA for New Era of Networks (NEON) during the rapid growth of Enterprise Application Integration. His 25-year career in technology also includes management positions at Goldman Sachs and Stratus Computer. Fred holds a First Class Bsc (Hons) degree in Physics with Astrophysics from the University of Leeds and had the privilege of being a summer student at CERN.3. Opportunities for gLite in finance and related industries Adam Vile, Head of Grid, HPC and Technical Computing, Excelian Ltd.gLite, the Grid software developed by the EGEE project, has been exceedingly successful as an enabling infrastructure, and has been a massive success in bringing together scientific and technical communities to provide the compute power to address previously incomputable problems. Not so in the finance industry. In its current form gLite would be a business disabler. There are other middleware tools that solve the finance communities compute problems much better. Things are moving on, however. There are moves afoot in the open source community to evolve the technology to address other, more sophisticated needs such as utility and interactive computing. In this talk, I will describe how Excelian is providing Grid consultancy services for the finance community and how, through its relationship to the EGEE project, Excelian is helping to identify and exploit opportunities as the research and business worlds converge. Because of the strong third party presence in the finance industry, such opportunities are few and far between, but they are there, especially as we expand sideways into related verticals such as the smaller hedge funds and energy companies. This talk will give an overview of the barriers to adoption of gLite in the finance industry and highlight some of the opportunities offered in this and related industries as the ideas around Grid mature. Speaker Bio: Dr Adam Vile is a senior consultant and head of the Grid and HPC practice at Excelian, a consultancy that focuses on financial markets professional services. He has spent many years in investment banking, as a developer, project manager and architect in both front and back office. Before joining Excelian he was senior Grid and HPC architect at Barclays Capital. Prior to joining investment banking, Adam spent a number of years lecturing in IT and mathematics at a UK University and maintains links with academia through lectures, research and through validation and steering of postgraduate courses. He is a chartered mathematician and was the conference chair of the Institute of Mathematics and its Applications first conference in computational Finance.4. From Monte Carlo to Wall Street Daniel Egloff, Head of Financial Engineering Computing Unit, Zürich Cantonal Bank High performance computing techniques provide new means to solve computationally hard problems in the financial service industry. First I consider Monte Carlo simulation and illustrate how it can be used to implement a sophisticated credit risk management and economic capital framework. From a HPC perspective, basic Monte Carlo simulation is embarrassingly parallel and can be implemented efficiently on distributed memory clusters. Additional difficulties arise for adaptive variance reduction schemes, if the information content in a sample is very small, and if the amount of simulated date becomes huge such that incremental processing algorithms are indispensable. We discuss the business value of an advanced credit risk quantification which is particularly compelling in these days. While Monte Carlo simulation is a very versatile tool it is not always the preferred solution for the pricing of complex products like multi asset options, structured products, or credit derivatives. As a second application I show how operator methods can be used to develop a pricing framework. The scalability of operator methods relies heavily on optimized dense matrix-matrix multiplications and requires specialized BLAS level-3 implementations provided by specialized FPGA or GPU boards. Speaker Bio: Daniel Egloff studied mathematics, theoretical physics, and computer science at the University of Zurich and the ETH Zurich. He holds a PhD in Mathematics from University of Fribourg, Switzerland. After his PhD he started to work for a large Swiss insurance company in the area of asset and liability management. He continued his professional career in the consulting industry. At KPMG and Arthur Andersen he consulted international clients and implemented quantitative risk management solutions for financial institutions and insurance companies. In 2002 he joined Zurich Cantonal Bank. He was assigned to develop and implement credit portfolio risk and economic capital methodologies. He built up a competence center for high performance and cluster computing. Currently, Daniel Egloff is heading the Financial Computing unit in the ZKB Financial Engineering division. He and his team is engineering and operating high performance cluster applications for computationally intensive problems in financial risk management.

Computing for Finance

ScienceCinema

None

2018-02-02

The finance sector is one of the driving forces for the use of distributed or Grid computing for business purposes. The speakers will review the state-of-the-art of high performance computing in the financial sector, and provide insight into how different types of Grid computing – from local clusters to global networks - are being applied to financial applications. They will also describe the use of software and techniques from physics, such as Monte Carlo simulations, in the financial world. There will be four talks of 20min each. The talk abstracts and speaker bios are listed below. This will be followed by a Q&A; panel session with the speakers. From 19:00 onwards there will be a networking cocktail for audience and speakers. This is an EGEE / CERN openlab event organized in collaboration with the regional business network rezonance.ch. A webcast of the event will be made available for subsequent viewing, along with powerpoint material presented by the speakers. Attendance is free and open to all. Registration is mandatory via www.rezonance.ch, including for CERN staff. 1. Overview of High Performance Computing in the Financial Industry Michael Yoo, Managing Director, Head of the Technical Council, UBS Presentation will describe the key business challenges driving the need for HPC solutions, describe the means in which those challenges are being addressed within UBS (such as GRID) as well as the limitations of some of these solutions, and assess some of the newer HPC technologies which may also play a role in the Financial Industry in the future. Speaker Bio: Michael originally joined the former Swiss Bank Corporation in 1994 in New York as a developer on a large data warehouse project. In 1996 he left SBC and took a role with Fidelity Investments in Boston. Unable to stay away for long, he returned to SBC in 1997 while working for Perot Systems in Singapore. Finally, in 1998 he formally returned to UBS in Stamford following the merger with SBC and has remained with UBS for the past 9 years. During his tenure at UBS, he has had a number of leadership roles within IT in development, support and architecture. In 2006 Michael relocated to Switzerland to take up his current role as head of the UBS IB Technical Council, responsible for the overall technology strategy and vision of the Investment Bank. One of Michael's key responsibilities is to manage the UBS High Performance Computing Research Lab and he has been involved in a number of initiatives in the HPC space. 2. Grid in the Commercial WorldFred Gedling, Chief Technology Officer EMEA and Senior Vice President Global Services, DataSynapse Grid computing gets mentions in the press for community programs starting last decade with Government, national and supranational initiatives in grid receive some press. One of the IT-industries' best-kept secrets is the use of grid computing by commercial organizations with spectacular results. Grid Computing and its evolution into Application Virtualization is discussed and how this is key to the next generation data center. Speaker Bio: Fred Gedling holds the joint roles of Chief Technology Officer for EMEA and Senior Vice President of Global Services at DataSynapse, a global provider of application virtualisation software. Based in London and working closely with organisations seeking to optimise their IT infrastructures, Fred offers unique insights into the technology of virtualisation as well as the methodology of establishing ROI and rapid deployment to the immediate advantage of the business. Fred has more than fifteen years experience of enterprise middleware and high-performance infrastructures. Prior to DataSynapse he worked in high performance CRM middleware and was the CTO EMEA for New Era of Networks (NEON) during the rapid growth of Enterprise Application Integration. His 25-year career in technology also includes management positions at Goldman Sachs and Stratus Computer. Fred holds a First Class Bsc (Hons) degree in Physics with Astrophysics from the University of Leeds and had the privilege of being a summer student at CERN.3. Opportunities for gLite in finance and related industriesAdam Vile, Head of Grid, HPC and Technical Computing, Excelian Ltd.gLite, the Grid software developed by the EGEE project, has been exceedingly successful as an enabling infrastructure, and has been a massive success in bringing together scientific and technical communities to provide the compute power to address previously incomputable problems. Not so in the finance industry. In its current form gLite would be a business disabler. There are other middleware tools that solve the finance communities compute problems much better. Things are moving on, however. There are moves afoot in the open source community to evolve the technology to address other, more sophisticated needs such as utility and interactive computing. In this talk, I will describe how Excelian is providing Grid consultancy services for the finance community and how, through its relationship to the EGEE project, Excelian is helping to identify and exploit opportunities as the research and business worlds converge. Because of the strong third party presence in the finance industry, such opportunities are few and far between, but they are there, especially as we expand sideways into related verticals such as the smaller hedge funds and energy companies. This talk will give an overview of the barriers to adoption of gLite in the finance industry and highlight some of the opportunities offered in this and related industries as the ideas around Grid mature. Speaker Bio: Dr Adam Vile is a senior consultant and head of the Grid and HPC practice at Excelian, a consultancy that focuses on financial markets professional services. He has spent many years in investment banking, as a developer, project manager and architect in both front and back office. Before joining Excelian he was senior Grid and HPC architect at Barclays Capital. Prior to joining investment banking, Adam spent a number of years lecturing in IT and mathematics at a UK University and maintains links with academia through lectures, research and through validation and steering of postgraduate courses. He is a chartered mathematician and was the conference chair of the Institute of Mathematics and its Applications first conference in computational Finance. 4. From Monte Carlo to Wall Street Daniel Egloff, Head of Financial Engineering Computing Unit, Zürich Cantonal Bank High performance computing techniques provide new means to solve computationally hard problems in the financial service industry. First I consider Monte Carlo simulation and illustrate how it can be used to implement a sophisticated credit risk management and economic capital framework. From a HPC perspective, basic Monte Carlo simulation is embarrassingly parallel and can be implemented efficiently on distributed memory clusters. Additional difficulties arise for adaptive variance reduction schemes, if the information content in a sample is very small, and if the amount of simulated date becomes huge such that incremental processing algorithms are indispensable. We discuss the business value of an advanced credit risk quantification which is particularly compelling in these days. While Monte Carlo simulation is a very versatile tool it is not always the preferred solution for the pricing of complex products like multi asset options, structured products, or credit derivatives. As a second application I show how operator methods can be used to develop a pricing framework. The scalability of operator methods relies heavily on optimized dense matrix-matrix multiplications and requires specialized BLAS level-3 implementations provided by specialized FPGA or GPU boards. Speaker Bio: Daniel Egloff studied mathematics, theoretical physics, and computer science at the University of Zurich and the ETH Zurich. He holds a PhD in Mathematics from University of Fribourg, Switzerland. After his PhD he started to work for a large Swiss insurance company in the area of asset and liability management. He continued his professional career in the consulting industry. At KPMG and Arthur Andersen he consulted international clients and implemented quantitative risk management solutions for financial institutions and insurance companies. In 2002 he joined Zurich Cantonal Bank. He was assigned to develop and implement credit portfolio risk and economic capital methodologies. He built up a competence center for high performance and cluster computing. Currently, Daniel Egloff is heading the Financial Computing unit in the ZKB Financial Engineering division. He and his team is engineering and operating high performance cluster applications for computationally intensive problems in financial risk management.

Computing for Finance

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

The finance sector is one of the driving forces for the use of distributed or Grid computing for business purposes. The speakers will review the state-of-the-art of high performance computing in the financial sector, and provide insight into how different types of Grid computing – from local clusters to global networks - are being applied to financial applications. They will also describe the use of software and techniques from physics, such as Monte Carlo simulations, in the financial world. There will be four talks of 20min each. The talk abstracts and speaker bios are listed below. This will be followedmore » by a Q&A; panel session with the speakers. From 19:00 onwards there will be a networking cocktail for audience and speakers. This is an EGEE / CERN openlab event organized in collaboration with the regional business network rezonance.ch. A webcast of the event will be made available for subsequent viewing, along with powerpoint material presented by the speakers. Attendance is free and open to all. Registration is mandatory via www.rezonance.ch, including for CERN staff. 1. Overview of High Performance Computing in the Financial Industry Michael Yoo, Managing Director, Head of the Technical Council, UBS Presentation will describe the key business challenges driving the need for HPC solutions, describe the means in which those challenges are being addressed within UBS (such as GRID) as well as the limitations of some of these solutions, and assess some of the newer HPC technologies which may also play a role in the Financial Industry in the future. Speaker Bio: Michael originally joined the former Swiss Bank Corporation in 1994 in New York as a developer on a large data warehouse project. In 1996 he left SBC and took a role with Fidelity Investments in Boston. Unable to stay away for long, he returned to SBC in 1997 while working for Perot Systems in Singapore. Finally, in 1998 he formally returned to UBS in Stamford following the merger with SBC and has remained with UBS for the past 9 years. During his tenure at UBS, he has had a number of leadership roles within IT in development, support and architecture. In 2006 Michael relocated to Switzerland to take up his current role as head of the UBS IB Technical Council, responsible for the overall technology strategy and vision of the Investment Bank. One of Michael's key responsibilities is to manage the UBS High Performance Computing Research Lab and he has been involved in a number of initiatives in the HPC space. 2. Grid in the Commercial WorldFred Gedling, Chief Technology Officer EMEA and Senior Vice President Global Services, DataSynapse Grid computing gets mentions in the press for community programs starting last decade with Seti@Home. Government, national and supranational initiatives in grid receive some press. One of the IT-industries' best-kept secrets is the use of grid computing by commercial organizations with spectacular results. Grid Computing and its evolution into Application Virtualization is discussed and how this is key to the next generation data center. Speaker Bio: Fred Gedling holds the joint roles of Chief Technology Officer for EMEA and Senior Vice President of Global Services at DataSynapse, a global provider of application virtualisation software. Based in London and working closely with organisations seeking to optimise their IT infrastructures, Fred offers unique insights into the technology of virtualisation as well as the methodology of establishing ROI and rapid deployment to the immediate advantage of the business. Fred has more than fifteen years experience of enterprise middleware and high-performance infrastructures. Prior to DataSynapse he worked in high performance CRM middleware and was the CTO EMEA for New Era of Networks (NEON) during the rapid growth of Enterprise Application Integration. His 25-year career in technology also includes management positions at Goldman Sachs and Stratus Computer. Fred holds a First Class Bsc (Hons) degree in Physics with Astrophysics from the University of Leeds and had the privilege of being a summer student at CERN.3. Opportunities for gLite in finance and related industriesAdam Vile, Head of Grid, HPC and Technical Computing, Excelian Ltd.gLite, the Grid software developed by the EGEE project, has been exceedingly successful as an enabling infrastructure, and has been a massive success in bringing together scientific and technical communities to provide the compute power to address previously incomputable problems. Not so in the finance industry. In its current form gLite would be a business disabler. There are other middleware tools that solve the finance communities compute problems much better. Things are moving on, however. There are moves afoot in the open source community to evolve the technology to address other, more sophisticated needs such as utility and interactive computing. In this talk, I will describe how Excelian is providing Grid consultancy services for the finance community and how, through its relationship to the EGEE project, Excelian is helping to identify and exploit opportunities as the research and business worlds converge. Because of the strong third party presence in the finance industry, such opportunities are few and far between, but they are there, especially as we expand sideways into related verticals such as the smaller hedge funds and energy companies. This talk will give an overview of the barriers to adoption of gLite in the finance industry and highlight some of the opportunities offered in this and related industries as the ideas around Grid mature. Speaker Bio: Dr Adam Vile is a senior consultant and head of the Grid and HPC practice at Excelian, a consultancy that focuses on financial markets professional services. He has spent many years in investment banking, as a developer, project manager and architect in both front and back office. Before joining Excelian he was senior Grid and HPC architect at Barclays Capital. Prior to joining investment banking, Adam spent a number of years lecturing in IT and mathematics at a UK University and maintains links with academia through lectures, research and through validation and steering of postgraduate courses. He is a chartered mathematician and was the conference chair of the Institute of Mathematics and its Applications first conference in computational Finance. 4. From Monte Carlo to Wall Street Daniel Egloff, Head of Financial Engineering Computing Unit, Zürich Cantonal Bank High performance computing techniques provide new means to solve computationally hard problems in the financial service industry. First I consider Monte Carlo simulation and illustrate how it can be used to implement a sophisticated credit risk management and economic capital framework. From a HPC perspective, basic Monte Carlo simulation is embarrassingly parallel and can be implemented efficiently on distributed memory clusters. Additional difficulties arise for adaptive variance reduction schemes, if the information content in a sample is very small, and if the amount of simulated date becomes huge such that incremental processing algorithms are indispensable. We discuss the business value of an advanced credit risk quantification which is particularly compelling in these days. While Monte Carlo simulation is a very versatile tool it is not always the preferred solution for the pricing of complex products like multi asset options, structured products, or credit derivatives. As a second application I show how operator methods can be used to develop a pricing framework. The scalability of operator methods relies heavily on optimized dense matrix-matrix multiplications and requires specialized BLAS level-3 implementations provided by specialized FPGA or GPU boards. Speaker Bio: Daniel Egloff studied mathematics, theoretical physics, and computer science at the University of Zurich and the ETH Zurich. He holds a PhD in Mathematics from University of Fribourg, Switzerland. After his PhD he started to work for a large Swiss insurance company in the area of asset and liability management. He continued his professional career in the consulting industry. At KPMG and Arthur Andersen he consulted international clients and implemented quantitative risk management solutions for financial institutions and insurance companies. In 2002 he joined Zurich Cantonal Bank. He was assigned to develop and implement credit portfolio risk and economic capital methodologies. He built up a competence center for high performance and cluster computing. Currently, Daniel Egloff is heading the Financial Computing unit in the ZKB Financial Engineering division. He and his team is engineering and operating high performance cluster applications for computationally intensive problems in financial risk management.« less

Computing for Finance

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

The finance sector is one of the driving forces for the use of distributed or Grid computing for business purposes. The speakers will review the state-of-the-art of high performance computing in the financial sector, and provide insight into how different types of Grid computing – from local clusters to global networks - are being applied to financial applications. They will also describe the use of software and techniques from physics, such as Monte Carlo simulations, in the financial world. There will be four talks of 20min each. The talk abstracts and speaker bios are listed below. This will be followedmore » by a Q&A; panel session with the speakers. From 19:00 onwards there will be a networking cocktail for audience and speakers. This is an EGEE / CERN openlab event organized in collaboration with the regional business network rezonance.ch. A webcast of the event will be made available for subsequent viewing, along with powerpoint material presented by the speakers. Attendance is free and open to all. Registration is mandatory via www.rezonance.ch, including for CERN staff. 1. Overview of High Performance Computing in the Financial Industry. Michael Yoo, Managing Director, Head of the Technical Council, UBS. Presentation will describe the key business challenges driving the need for HPC solutions, describe the means in which those challenges are being addressed within UBS (such as GRID) as well as the limitations of some of these solutions, and assess some of the newer HPC technologies which may also play a role in the Financial Industry in the future. Speaker Bio: Michael originally joined the former Swiss Bank Corporation in 1994 in New York as a developer on a large data warehouse project. In 1996 he left SBC and took a role with Fidelity Investments in Boston. Unable to stay away for long, he returned to SBC in 1997 while working for Perot Systems in Singapore. Finally, in 1998 he formally returned to UBS in Stamford following the merger with SBC and has remained with UBS for the past 9 years. During his tenure at UBS, he has had a number of leadership roles within IT in development, support and architecture. In 2006 Michael relocated to Switzerland to take up his current role as head of the UBS IB Technical Council, responsible for the overall technology strategy and vision of the Investment Bank. One of Michael's key responsibilities is to manage the UBS High Performance Computing Research Lab and he has been involved in a number of initiatives in the HPC space. 2. Grid in the Commercial WorldFred Gedling, Chief Technology Officer EMEA and Senior Vice President Global Services, DataSynapse. Grid computing gets mentions in the press for community programs starting last decade with "Seti@Home". Government, national and supranational initiatives in grid receive some press. One of the IT-industries' best-kept secrets is the use of grid computing by commercial organizations with spectacular results. Grid Computing and its evolution into Application Virtualization is discussed and how this is key to the next generation data center. Speaker Bio: Fred Gedling holds the joint roles of Chief Technology Officer for EMEA and Senior Vice President of Global Services at DataSynapse, a global provider of application virtualisation software. Based in London and working closely with organisations seeking to optimise their IT infrastructures, Fred offers unique insights into the technology of virtualisation as well as the methodology of establishing ROI and rapid deployment to the immediate advantage of the business. Fred has more than fifteen years experience of enterprise middleware and high-performance infrastructures. Prior to DataSynapse he worked in high performance CRM middleware and was the CTO EMEA for New Era of Networks (NEON) during the rapid growth of Enterprise Application Integration. His 25-year career in technology also includes management positions at Goldman Sachs and Stratus Computer. Fred holds a First Class Bsc (Hons) degree in Physics with Astrophysics from the University of Leeds and had the privilege of being a summer student at CERN.3. Opportunities for gLite in finance and related industriesAdam Vile, Head of Grid, HPC and Technical Computing, Excelian Ltd.gLite, the Grid software developed by the EGEE project, has been exceedingly successful as an enabling infrastructure, and has been a massive success in bringing together scientific and technical communities to provide the compute power to address previously incomputable problems. Not so in the finance industry. In its current form gLite would be a business disabler. There are other middleware tools that solve the finance communities compute problems much better. Things are moving on, however. There are moves afoot in the open source community to evolve the technology to address other, more sophisticated needs such as utility and interactive computing. In this talk, I will describe how Excelian is providing Grid consultancy services for the finance community and how, through its relationship to the EGEE project, Excelian is helping to identify and exploit opportunities as the research and business worlds converge. Because of the strong third party presence in the finance industry, such opportunities are few and far between, but they are there, especially as we expand sideways into related verticals such as the smaller hedge funds and energy companies. This talk will give an overview of the barriers to adoption of gLite in the finance industry and highlight some of the opportunities offered in this and related industries as the ideas around Grid mature. Speaker Bio: Dr Adam Vile is a senior consultant and head of the Grid and HPC practice at Excelian, a consultancy that focuses on financial markets professional services. He has spent many years in investment banking, as a developer, project manager and architect in both front and back office. Before joining Excelian he was senior Grid and HPC architect at Barclays Capital. Prior to joining investment banking, Adam spent a number of years lecturing in IT and mathematics at a UK University and maintains links with academia through lectures, research and through validation and steering of postgraduate courses. He is a chartered mathematician and was the conference chair of the Institute of Mathematics and its Applications first conference in computational Finance.4. From Monte Carlo to Wall Street Daniel Egloff, Head of Financial Engineering Computing Unit, Zürich Cantonal Bank High performance computing techniques provide new means to solve computationally hard problems in the financial service industry. First I consider Monte Carlo simulation and illustrate how it can be used to implement a sophisticated credit risk management and economic capital framework. From a HPC perspective, basic Monte Carlo simulation is embarrassingly parallel and can be implemented efficiently on distributed memory clusters. Additional difficulties arise for adaptive variance reduction schemes, if the information content in a sample is very small, and if the amount of simulated date becomes huge such that incremental processing algorithms are indispensable. We discuss the business value of an advanced credit risk quantification which is particularly compelling in these days. While Monte Carlo simulation is a very versatile tool it is not always the preferred solution for the pricing of complex products like multi asset options, structured products, or credit derivatives. As a second application I show how operator methods can be used to develop a pricing framework. The scalability of operator methods relies heavily on optimized dense matrix-matrix multiplications and requires specialized BLAS level-3 implementations provided by specialized FPGA or GPU boards. Speaker Bio: Daniel Egloff studied mathematics, theoretical physics, and computer science at the University of Zurich and the ETH Zurich. He holds a PhD in Mathematics from University of Fribourg, Switzerland. After his PhD he started to work for a large Swiss insurance company in the area of asset and liability management. He continued his professional career in the consulting industry. At KPMG and Arthur Andersen he consulted international clients and implemented quantitative risk management solutions for financial institutions and insurance companies. In 2002 he joined Zurich Cantonal Bank. He was assigned to develop and implement credit portfolio risk and economic capital methodologies. He built up a competence center for high performance and cluster computing. Currently, Daniel Egloff is heading the Financial Computing unit in the ZKB Financial Engineering division. He and his team is engineering and operating high performance cluster applications for computationally intensive problems in financial risk management.« less

Computing for Finance

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

The finance sector is one of the driving forces for the use of distributed or Grid computing for business purposes. The speakers will review the state-of-the-art of high performance computing in the financial sector, and provide insight into how different types of Grid computing – from local clusters to global networks - are being applied to financial applications. They will also describe the use of software and techniques from physics, such as Monte Carlo simulations, in the financial world. There will be four talks of 20min each. The talk abstracts and speaker bios are listed below. This will be followedmore » by a Q&A; panel session with the speakers. From 19:00 onwards there will be a networking cocktail for audience and speakers. This is an EGEE / CERN openlab event organized in collaboration with the regional business network rezonance.ch. A webcast of the event will be made available for subsequent viewing, along with powerpoint material presented by the speakers. Attendance is free and open to all. Registration is mandatory via www.rezonance.ch, including for CERN staff. 1. Overview of High Performance Computing in the Financial Industry Michael Yoo, Managing Director, Head of the Technical Council, UBS Presentation will describe the key business challenges driving the need for HPC solutions, describe the means in which those challenges are being addressed within UBS (such as GRID) as well as the limitations of some of these solutions, and assess some of the newer HPC technologies which may also play a role in the Financial Industry in the future. Speaker Bio: Michael originally joined the former Swiss Bank Corporation in 1994 in New York as a developer on a large data warehouse project. In 1996 he left SBC and took a role with Fidelity Investments in Boston. Unable to stay away for long, he returned to SBC in 1997 while working for Perot Systems in Singapore. Finally, in 1998 he formally returned to UBS in Stamford following the merger with SBC and has remained with UBS for the past 9 years. During his tenure at UBS, he has had a number of leadership roles within IT in development, support and architecture. In 2006 Michael relocated to Switzerland to take up his current role as head of the UBS IB Technical Council, responsible for the overall technology strategy and vision of the Investment Bank. One of Michael's key responsibilities is to manage the UBS High Performance Computing Research Lab and he has been involved in a number of initiatives in the HPC space. 2. Grid in the Commercial WorldFred Gedling, Chief Technology Officer EMEA and Senior Vice President Global Services, DataSynapse Grid computing gets mentions in the press for community programs starting last decade with Government, national and supranational initiatives in grid receive some press. One of the IT-industries' best-kept secrets is the use of grid computing by commercial organizations with spectacular results. Grid Computing and its evolution into Application Virtualization is discussed and how this is key to the next generation data center. Speaker Bio: Fred Gedling holds the joint roles of Chief Technology Officer for EMEA and Senior Vice President of Global Services at DataSynapse, a global provider of application virtualisation software. Based in London and working closely with organisations seeking to optimise their IT infrastructures, Fred offers unique insights into the technology of virtualisation as well as the methodology of establishing ROI and rapid deployment to the immediate advantage of the business. Fred has more than fifteen years experience of enterprise middleware and high-performance infrastructures. Prior to DataSynapse he worked in high performance CRM middleware and was the CTO EMEA for New Era of Networks (NEON) during the rapid growth of Enterprise Application Integration. His 25-year career in technology also includes management positions at Goldman Sachs and Stratus Computer. Fred holds a First Class Bsc (Hons) degree in Physics with Astrophysics from the University of Leeds and had the privilege of being a summer student at CERN.3. Opportunities for gLite in finance and related industriesAdam Vile, Head of Grid, HPC and Technical Computing, Excelian Ltd.gLite, the Grid software developed by the EGEE project, has been exceedingly successful as an enabling infrastructure, and has been a massive success in bringing together scientific and technical communities to provide the compute power to address previously incomputable problems. Not so in the finance industry. In its current form gLite would be a business disabler. There are other middleware tools that solve the finance communities compute problems much better. Things are moving on, however. There are moves afoot in the open source community to evolve the technology to address other, more sophisticated needs such as utility and interactive computing. In this talk, I will describe how Excelian is providing Grid consultancy services for the finance community and how, through its relationship to the EGEE project, Excelian is helping to identify and exploit opportunities as the research and business worlds converge. Because of the strong third party presence in the finance industry, such opportunities are few and far between, but they are there, especially as we expand sideways into related verticals such as the smaller hedge funds and energy companies. This talk will give an overview of the barriers to adoption of gLite in the finance industry and highlight some of the opportunities offered in this and related industries as the ideas around Grid mature. Speaker Bio: Dr Adam Vile is a senior consultant and head of the Grid and HPC practice at Excelian, a consultancy that focuses on financial markets professional services. He has spent many years in investment banking, as a developer, project manager and architect in both front and back office. Before joining Excelian he was senior Grid and HPC architect at Barclays Capital. Prior to joining investment banking, Adam spent a number of years lecturing in IT and mathematics at a UK University and maintains links with academia through lectures, research and through validation and steering of postgraduate courses. He is a chartered mathematician and was the conference chair of the Institute of Mathematics and its Applications first conference in computational Finance. 4. From Monte Carlo to Wall Street Daniel Egloff, Head of Financial Engineering Computing Unit, Zürich Cantonal Bank High performance computing techniques provide new means to solve computationally hard problems in the financial service industry. First I consider Monte Carlo simulation and illustrate how it can be used to implement a sophisticated credit risk management and economic capital framework. From a HPC perspective, basic Monte Carlo simulation is embarrassingly parallel and can be implemented efficiently on distributed memory clusters. Additional difficulties arise for adaptive variance reduction schemes, if the information content in a sample is very small, and if the amount of simulated date becomes huge such that incremental processing algorithms are indispensable. We discuss the business value of an advanced credit risk quantification which is particularly compelling in these days. While Monte Carlo simulation is a very versatile tool it is not always the preferred solution for the pricing of complex products like multi asset options, structured products, or credit derivatives. As a second application I show how operator methods can be used to develop a pricing framework. The scalability of operator methods relies heavily on optimized dense matrix-matrix multiplications and requires specialized BLAS level-3 implementations provided by specialized FPGA or GPU boards. Speaker Bio: Daniel Egloff studied mathematics, theoretical physics, and computer science at the University of Zurich and the ETH Zurich. He holds a PhD in Mathematics from University of Fribourg, Switzerland. After his PhD he started to work for a large Swiss insurance company in the area of asset and liability management. He continued his professional career in the consulting industry. At KPMG and Arthur Andersen he consulted international clients and implemented quantitative risk management solutions for financial institutions and insurance companies. In 2002 he joined Zurich Cantonal Bank. He was assigned to develop and implement credit portfolio risk and economic capital methodologies. He built up a competence center for high performance and cluster computing. Currently, Daniel Egloff is heading the Financial Computing unit in the ZKB Financial Engineering division. He and his team is engineering and operating high performance cluster applications for computationally intensive problems in financial risk management.« less

Computing for Finance

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

The finance sector is one of the driving forces for the use of distributed or Grid computing for business purposes. The speakers will review the state-of-the-art of high performance computing in the financial sector, and provide insight into how different types of Grid computing – from local clusters to global networks - are being applied to financial applications. They will also describe the use of software and techniques from physics, such as Monte Carlo simulations, in the financial world. There will be four talks of 20min each. The talk abstracts and speaker bios are listed below. This will be followedmore » by a Q&A; panel session with the speakers. From 19:00 onwards there will be a networking cocktail for audience and speakers. This is an EGEE / CERN openlab event organized in collaboration with the regional business network rezonance.ch. A webcast of the event will be made available for subsequent viewing, along with powerpoint material presented by the speakers. Attendance is free and open to all. Registration is mandatory via www.rezonance.ch, including for CERN staff. 1. Overview of High Performance Computing in the Financial Industry Michael Yoo, Managing Director, Head of the Technical Council, UBS Presentation will describe the key business challenges driving the need for HPC solutions, describe the means in which those challenges are being addressed within UBS (such as GRID) as well as the limitations of some of these solutions, and assess some of the newer HPC technologies which may also play a role in the Financial Industry in the future. Speaker Bio: Michael originally joined the former Swiss Bank Corporation in 1994 in New York as a developer on a large data warehouse project. In 1996 he left SBC and took a role with Fidelity Investments in Boston. Unable to stay away for long, he returned to SBC in 1997 while working for Perot Systems in Singapore. Finally, in 1998 he formally returned to UBS in Stamford following the merger with SBC and has remained with UBS for the past 9 years. During his tenure at UBS, he has had a number of leadership roles within IT in development, support and architecture. In 2006 Michael relocated to Switzerland to take up his current role as head of the UBS IB Technical Council, responsible for the overall technology strategy and vision of the Investment Bank. One of Michael's key responsibilities is to manage the UBS High Performance Computing Research Lab and he has been involved in a number of initiatives in the HPC space. 2. Grid in the Commercial WorldFred Gedling, Chief Technology Officer EMEA and Senior Vice President Global Services, DataSynapse Grid computing gets mentions in the press for community programs starting last decade with Government, national and supranational initiatives in grid receive some press. One of the IT-industries' best-kept secrets is the use of grid computing by commercial organizations with spectacular results. Grid Computing and its evolution into Application Virtualization is discussed and how this is key to the next generation data center. Speaker Bio: Fred Gedling holds the joint roles of Chief Technology Officer for EMEA and Senior Vice President of Global Services at DataSynapse, a global provider of application virtualisation software. Based in London and working closely with organisations seeking to optimise their IT infrastructures, Fred offers unique insights into the technology of virtualisation as well as the methodology of establishing ROI and rapid deployment to the immediate advantage of the business. Fred has more than fifteen years experience of enterprise middleware and high-performance infrastructures. Prior to DataSynapse he worked in high performance CRM middleware and was the CTO EMEA for New Era of Networks (NEON) during the rapid growth of Enterprise Application Integration. His 25-year career in technology also includes management positions at Goldman Sachs and Stratus Computer. Fred holds a First Class Bsc (Hons) degree in Physics with Astrophysics from the University of Leeds and had the privilege of being a summer student at CERN.3. Opportunities for gLite in finance and related industriesAdam Vile, Head of Grid, HPC and Technical Computing, Excelian Ltd.gLite, the Grid software developed by the EGEE project, has been exceedingly successful as an enabling infrastructure, and has been a massive success in bringing together scientific and technical communities to provide the compute power to address previously incomputable problems. Not so in the finance industry. In its current form gLite would be a business disabler. There are other middleware tools that solve the finance communities compute problems much better. Things are moving on, however. There are moves afoot in the open source community to evolve the technology to address other, more sophisticated needs such as utility and interactive computing. In this talk, I will describe how Excelian is providing Grid consultancy services for the finance community and how, through its relationship to the EGEE project, Excelian is helping to identify and exploit opportunities as the research and business worlds converge. Because of the strong third party presence in the finance industry, such opportunities are few and far between, but they are there, especially as we expand sideways into related verticals such as the smaller hedge funds and energy companies. This talk will give an overview of the barriers to adoption of gLite in the finance industry and highlight some of the opportunities offered in this and related industries as the ideas around Grid mature. Speaker Bio: Dr Adam Vile is a senior consultant and head of the Grid and HPC practice at Excelian, a consultancy that focuses on financial markets professional services. He has spent many years in investment banking, as a developer, project manager and architect in both front and back office. Before joining Excelian he was senior Grid and HPC architect at Barclays Capital. Prior to joining investment banking, Adam spent a number of years lecturing in IT and mathematics at a UK University and maintains links with academia through lectures, research and through validation and steering of postgraduate courses. He is a chartered mathematician and was the conference chair of the Institute of Mathematics and its Applications first conference in computational Finance.4. From Monte Carlo to Wall Street Daniel Egloff, Head of Financial Engineering Computing Unit, Zürich Cantonal Bank High performance computing techniques provide new means to solve computationally hard problems in the financial service industry. First I consider Monte Carlo simulation and illustrate how it can be used to implement a sophisticated credit risk management and economic capital framework. From a HPC perspective, basic Monte Carlo simulation is embarrassingly parallel and can be implemented efficiently on distributed memory clusters. Additional difficulties arise for adaptive variance reduction schemes, if the information content in a sample is very small, and if the amount of simulated date becomes huge such that incremental processing algorithms are indispensable. We discuss the business value of an advanced credit risk quantification which is particularly compelling in these days. While Monte Carlo simulation is a very versatile tool it is not always the preferred solution for the pricing of complex products like multi asset options, structured products, or credit derivatives. As a second application I show how operator methods can be used to develop a pricing framework. The scalability of operator methods relies heavily on optimized dense matrix-matrix multiplications and requires specialized BLAS level-3 implementations provided by specialized FPGA or GPU boards. Speaker Bio: Daniel Egloff studied mathematics, theoretical physics, and computer science at the University of Zurich and the ETH Zurich. He holds a PhD in Mathematics from University of Fribourg, Switzerland. After his PhD he started to work for a large Swiss insurance company in the area of asset and liability management. He continued his professional career in the consulting industry. At KPMG and Arthur Andersen he consulted international clients and implemented quantitative risk management solutions for financial institutions and insurance companies. In 2002 he joined Zurich Cantonal Bank. He was assigned to develop and implement credit portfolio risk and economic capital methodologies. He built up a competence center for high performance and cluster computing. Currently, Daniel Egloff is heading the Financial Computing unit in the ZKB Financial Engineering division. He and his team is engineering and operating high performance cluster applications for computationally intensive problems in financial risk management.« less

Computing for Finance

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

The finance sector is one of the driving forces for the use of distributed or Grid computing for business purposes. The speakers will review the state-of-the-art of high performance computing in the financial sector, and provide insight into how different types of Grid computing – from local clusters to global networks - are being applied to financial applications. They will also describe the use of software and techniques from physics, such as Monte Carlo simulations, in the financial world. There will be four talks of 20min each. The talk abstracts and speaker bios are listed below. This will be followedmore » by a Q&A; panel session with the speakers. From 19:00 onwards there will be a networking cocktail for audience and speakers. This is an EGEE / CERN openlab event organized in collaboration with the regional business network rezonance.ch. A webcast of the event will be made available for subsequent viewing, along with powerpoint material presented by the speakers. Attendance is free and open to all. Registration is mandatory via www.rezonance.ch, including for CERN staff. 1. Overview of High Performance Computing in the Financial Industry Michael Yoo, Managing Director, Head of the Technical Council, UBS Presentation will describe the key business challenges driving the need for HPC solutions, describe the means in which those challenges are being addressed within UBS (such as GRID) as well as the limitations of some of these solutions, and assess some of the newer HPC technologies which may also play a role in the Financial Industry in the future. Speaker Bio: Michael originally joined the former Swiss Bank Corporation in 1994 in New York as a developer on a large data warehouse project. In 1996 he left SBC and took a role with Fidelity Investments in Boston. Unable to stay away for long, he returned to SBC in 1997 while working for Perot Systems in Singapore. Finally, in 1998 he formally returned to UBS in Stamford following the merger with SBC and has remained with UBS for the past 9 years. During his tenure at UBS, he has had a number of leadership roles within IT in development, support and architecture. In 2006 Michael relocated to Switzerland to take up his current role as head of the UBS IB Technical Council, responsible for the overall technology strategy and vision of the Investment Bank. One of Michael's key responsibilities is to manage the UBS High Performance Computing Research Lab and he has been involved in a number of initiatives in the HPC space. 2. Grid in the Commercial WorldFred Gedling, Chief Technology Officer EMEA and Senior Vice President Global Services, DataSynapse Grid computing gets mentions in the press for community programs starting last decade with Government, national and supranational initiatives in grid receive some press. One of the IT-industries' best-kept secrets is the use of grid computing by commercial organizations with spectacular results. Grid Computing and its evolution into Application Virtualization is discussed and how this is key to the next generation data center. Speaker Bio: Fred Gedling holds the joint roles of Chief Technology Officer for EMEA and Senior Vice President of Global Services at DataSynapse, a global provider of application virtualisation software. Based in London and working closely with organisations seeking to optimise their IT infrastructures, Fred offers unique insights into the technology of virtualisation as well as the methodology of establishing ROI and rapid deployment to the immediate advantage of the business. Fred has more than fifteen years experience of enterprise middleware and high-performance infrastructures. Prior to DataSynapse he worked in high performance CRM middleware and was the CTO EMEA for New Era of Networks (NEON) during the rapid growth of Enterprise Application Integration. His 25-year career in technology also includes management positions at Goldman Sachs and Stratus Computer. Fred holds a First Class Bsc (Hons) degree in Physics with Astrophysics from the University of Leeds and had the privilege of being a summer student at CERN.3. Opportunities for gLite in finance and related industries Adam Vile, Head of Grid, HPC and Technical Computing, Excelian Ltd.gLite, the Grid software developed by the EGEE project, has been exceedingly successful as an enabling infrastructure, and has been a massive success in bringing together scientific and technical communities to provide the compute power to address previously incomputable problems. Not so in the finance industry. In its current form gLite would be a business disabler. There are other middleware tools that solve the finance communities compute problems much better. Things are moving on, however. There are moves afoot in the open source community to evolve the technology to address other, more sophisticated needs such as utility and interactive computing. In this talk, I will describe how Excelian is providing Grid consultancy services for the finance community and how, through its relationship to the EGEE project, Excelian is helping to identify and exploit opportunities as the research and business worlds converge. Because of the strong third party presence in the finance industry, such opportunities are few and far between, but they are there, especially as we expand sideways into related verticals such as the smaller hedge funds and energy companies. This talk will give an overview of the barriers to adoption of gLite in the finance industry and highlight some of the opportunities offered in this and related industries as the ideas around Grid mature. Speaker Bio: Dr Adam Vile is a senior consultant and head of the Grid and HPC practice at Excelian, a consultancy that focuses on financial markets professional services. He has spent many years in investment banking, as a developer, project manager and architect in both front and back office. Before joining Excelian he was senior Grid and HPC architect at Barclays Capital. Prior to joining investment banking, Adam spent a number of years lecturing in IT and mathematics at a UK University and maintains links with academia through lectures, research and through validation and steering of postgraduate courses. He is a chartered mathematician and was the conference chair of the Institute of Mathematics and its Applications first conference in computational Finance.4. From Monte Carlo to Wall Street Daniel Egloff, Head of Financial Engineering Computing Unit, Zürich Cantonal Bank High performance computing techniques provide new means to solve computationally hard problems in the financial service industry. First I consider Monte Carlo simulation and illustrate how it can be used to implement a sophisticated credit risk management and economic capital framework. From a HPC perspective, basic Monte Carlo simulation is embarrassingly parallel and can be implemented efficiently on distributed memory clusters. Additional difficulties arise for adaptive variance reduction schemes, if the information content in a sample is very small, and if the amount of simulated date becomes huge such that incremental processing algorithms are indispensable. We discuss the business value of an advanced credit risk quantification which is particularly compelling in these days. While Monte Carlo simulation is a very versatile tool it is not always the preferred solution for the pricing of complex products like multi asset options, structured products, or credit derivatives. As a second application I show how operator methods can be used to develop a pricing framework. The scalability of operator methods relies heavily on optimized dense matrix-matrix multiplications and requires specialized BLAS level-3 implementations provided by specialized FPGA or GPU boards. Speaker Bio: Daniel Egloff studied mathematics, theoretical physics, and computer science at the University of Zurich and the ETH Zurich. He holds a PhD in Mathematics from University of Fribourg, Switzerland. After his PhD he started to work for a large Swiss insurance company in the area of asset and liability management. He continued his professional career in the consulting industry. At KPMG and Arthur Andersen he consulted international clients and implemented quantitative risk management solutions for financial institutions and insurance companies. In 2002 he joined Zurich Cantonal Bank. He was assigned to develop and implement credit portfolio risk and economic capital methodologies. He built up a competence center for high performance and cluster computing. Currently, Daniel Egloff is heading the Financial Computing unit in the ZKB Financial Engineering division. He and his team is engineering and operating high performance cluster applications for computationally intensive problems in financial risk management.« less

Computing for Finance

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

The finance sector is one of the driving forces for the use of distributed or Grid computing for business purposes. The speakers will review the state-of-the-art of high performance computing in the financial sector, and provide insight into how different types of Grid computing – from local clusters to global networks - are being applied to financial applications. They will also describe the use of software and techniques from physics, such as Monte Carlo simulations, in the financial world. There will be four talks of 20min each. The talk abstracts and speaker bios are listed below. This will be followedmore » by a Q&A; panel session with the speakers. From 19:00 onwards there will be a networking cocktail for audience and speakers. This is an EGEE / CERN openlab event organized in collaboration with the regional business network rezonance.ch. A webcast of the event will be made available for subsequent viewing, along with powerpoint material presented by the speakers. Attendance is free and open to all. Registration is mandatory via www.rezonance.ch, including for CERN staff. 1. Overview of High Performance Computing in the Financial Industry Michael Yoo, Managing Director, Head of the Technical Council, UBS Presentation will describe the key business challenges driving the need for HPC solutions, describe the means in which those challenges are being addressed within UBS (such as GRID) as well as the limitations of some of these solutions, and assess some of the newer HPC technologies which may also play a role in the Financial Industry in the future. Speaker Bio: Michael originally joined the former Swiss Bank Corporation in 1994 in New York as a developer on a large data warehouse project. In 1996 he left SBC and took a role with Fidelity Investments in Boston. Unable to stay away for long, he returned to SBC in 1997 while working for Perot Systems in Singapore. Finally, in 1998 he formally returned to UBS in Stamford following the merger with SBC and has remained with UBS for the past 9 years. During his tenure at UBS, he has had a number of leadership roles within IT in development, support and architecture. In 2006 Michael relocated to Switzerland to take up his current role as head of the UBS IB Technical Council, responsible for the overall technology strategy and vision of the Investment Bank. One of Michael's key responsibilities is to manage the UBS High Performance Computing Research Lab and he has been involved in a number of initiatives in the HPC space. 2. Grid in the Commercial WorldFred Gedling, Chief Technology Officer EMEA and Senior Vice President Global Services, DataSynapse Grid computing gets mentions in the press for community programs starting last decade with Seti@Home. Government, national and supranational initiatives in grid receive some press. One of the IT-industries' best-kept secrets is the use of grid computing by commercial organizations with spectacular results. Grid Computing and its evolution into Application Virtualization is discussed and how this is key to the next generation data center. Speaker Bio: Fred Gedling holds the joint roles of Chief Technology Officer for EMEA and Senior Vice President of Global Services at DataSynapse, a global provider of application virtualisation software. Based in London and working closely with organisations seeking to optimise their IT infrastructures, Fred offers unique insights into the technology of virtualisation as well as the methodology of establishing ROI and rapid deployment to the immediate advantage of the business. Fred has more than fifteen years experience of enterprise middleware and high-performance infrastructures. Prior to DataSynapse he worked in high performance CRM middleware and was the CTO EMEA for New Era of Networks (NEON) during the rapid growth of Enterprise Application Integration. His 25-year career in technology also includes management positions at Goldman Sachs and Stratus Computer. Fred holds a First Class Bsc (Hons) degree in Physics with Astrophysics from the University of Leeds and had the privilege of being a summer student at CERN. 3. Opportunities for gLite in finance and related industriesAdam Vile, Head of Grid, HPC and Technical Computing, Excelian Ltd.gLite, the Grid software developed by the EGEE project, has been exceedingly successful as an enabling infrastructure, and has been a massive success in bringing together scientific and technical communities to provide the compute power to address previously incomputable problems. Not so in the finance industry. In its current form gLite would be a business disabler. There are other middleware tools that solve the finance communities compute problems much better. Things are moving on, however. There are moves afoot in the open source community to evolve the technology to address other, more sophisticated needs such as utility and interactive computing. In this talk, I will describe how Excelian is providing Grid consultancy services for the finance community and how, through its relationship to the EGEE project, Excelian is helping to identify and exploit opportunities as the research and business worlds converge. Because of the strong third party presence in the finance industry, such opportunities are few and far between, but they are there, especially as we expand sideways into related verticals such as the smaller hedge funds and energy companies. This talk will give an overview of the barriers to adoption of gLite in the finance industry and highlight some of the opportunities offered in this and related industries as the ideas around Grid mature. Speaker Bio: Dr Adam Vile is a senior consultant and head of the Grid and HPC practice at Excelian, a consultancy that focuses on financial markets professional services. He has spent many years in investment banking, as a developer, project manager and architect in both front and back office. Before joining Excelian he was senior Grid and HPC architect at Barclays Capital. Prior to joining investment banking, Adam spent a number of years lecturing in IT and mathematics at a UK University and maintains links with academia through lectures, research and through validation and steering of postgraduate courses. He is a chartered mathematician and was the conference chair of the Institute of Mathematics and its Applications first conference in computational Finance.4. From Monte Carlo to Wall Street Daniel Egloff, Head of Financial Engineering Computing Unit, Zürich Cantonal Bank High performance computing techniques provide new means to solve computationally hard problems in the financial service industry. First I consider Monte Carlo simulation and illustrate how it can be used to implement a sophisticated credit risk management and economic capital framework. From a HPC perspective, basic Monte Carlo simulation is embarrassingly parallel and can be implemented efficiently on distributed memory clusters. Additional difficulties arise for adaptive variance reduction schemes, if the information content in a sample is very small, and if the amount of simulated date becomes huge such that incremental processing algorithms are indispensable. We discuss the business value of an advanced credit risk quantification which is particularly compelling in these days. While Monte Carlo simulation is a very versatile tool it is not always the preferred solution for the pricing of complex products like multi asset options, structured products, or credit derivatives. As a second application I show how operator methods can be used to develop a pricing framework. The scalability of operator methods relies heavily on optimized dense matrix-matrix multiplications and requires specialized BLAS level-3 implementations provided by specialized FPGA or GPU boards. Speaker Bio: Daniel Egloff studied mathematics, theoretical physics, and computer science at the University of Zurich and the ETH Zurich. He holds a PhD in Mathematics from University of Fribourg, Switzerland. After his PhD he started to work for a large Swiss insurance company in the area of asset and liability management. He continued his professional career in the consulting industry. At KPMG and Arthur Andersen he consulted international clients and implemented quantitative risk management solutions for financial institutions and insurance companies. In 2002 he joined Zurich Cantonal Bank. He was assigned to develop and implement credit portfolio risk and economic capital methodologies. He built up a competence center for high performance and cluster computing. Currently, Daniel Egloff is heading the Financial Computing unit in the ZKB Financial Engineering division. He and his team is engineering and operating high performance cluster applications for computationally intensive problems in financial risk management.« less

Computing for Finance

ScienceCinema

None

2018-02-01

The finance sector is one of the driving forces for the use of distributed or Grid computing for business purposes. The speakers will review the state-of-the-art of high performance computing in the financial sector, and provide insight into how different types of Grid computing – from local clusters to global networks - are being applied to financial applications. They will also describe the use of software and techniques from physics, such as Monte Carlo simulations, in the financial world. There will be four talks of 20min each. The talk abstracts and speaker bios are listed below. This will be followed by a Q&A; panel session with the speakers. From 19:00 onwards there will be a networking cocktail for audience and speakers. This is an EGEE / CERN openlab event organized in collaboration with the regional business network rezonance.ch. A webcast of the event will be made available for subsequent viewing, along with powerpoint material presented by the speakers. Attendance is free and open to all. Registration is mandatory via www.rezonance.ch, including for CERN staff. 1. Overview of High Performance Computing in the Financial Industry Michael Yoo, Managing Director, Head of the Technical Council, UBS Presentation will describe the key business challenges driving the need for HPC solutions, describe the means in which those challenges are being addressed within UBS (such as GRID) as well as the limitations of some of these solutions, and assess some of the newer HPC technologies which may also play a role in the Financial Industry in the future. Speaker Bio: Michael originally joined the former Swiss Bank Corporation in 1994 in New York as a developer on a large data warehouse project. In 1996 he left SBC and took a role with Fidelity Investments in Boston. Unable to stay away for long, he returned to SBC in 1997 while working for Perot Systems in Singapore. Finally, in 1998 he formally returned to UBS in Stamford following the merger with SBC and has remained with UBS for the past 9 years. During his tenure at UBS, he has had a number of leadership roles within IT in development, support and architecture. In 2006 Michael relocated to Switzerland to take up his current role as head of the UBS IB Technical Council, responsible for the overall technology strategy and vision of the Investment Bank. One of Michael's key responsibilities is to manage the UBS High Performance Computing Research Lab and he has been involved in a number of initiatives in the HPC space. 2. Grid in the Commercial WorldFred Gedling, Chief Technology Officer EMEA and Senior Vice President Global Services, DataSynapse Grid computing gets mentions in the press for community programs starting last decade with Government, national and supranational initiatives in grid receive some press. One of the IT-industries' best-kept secrets is the use of grid computing by commercial organizations with spectacular results. Grid Computing and its evolution into Application Virtualization is discussed and how this is key to the next generation data center. Speaker Bio: Fred Gedling holds the joint roles of Chief Technology Officer for EMEA and Senior Vice President of Global Services at DataSynapse, a global provider of application virtualisation software. Based in London and working closely with organisations seeking to optimise their IT infrastructures, Fred offers unique insights into the technology of virtualisation as well as the methodology of establishing ROI and rapid deployment to the immediate advantage of the business. Fred has more than fifteen years experience of enterprise middleware and high-performance infrastructures. Prior to DataSynapse he worked in high performance CRM middleware and was the CTO EMEA for New Era of Networks (NEON) during the rapid growth of Enterprise Application Integration. His 25-year career in technology also includes management positions at Goldman Sachs and Stratus Computer. Fred holds a First Class Bsc (Hons) degree in Physics with Astrophysics from the University of Leeds and had the privilege of being a summer student at CERN.3. Opportunities for gLite in finance and related industriesAdam Vile, Head of Grid, HPC and Technical Computing, Excelian Ltd.gLite, the Grid software developed by the EGEE project, has been exceedingly successful as an enabling infrastructure, and has been a massive success in bringing together scientific and technical communities to provide the compute power to address previously incomputable problems. Not so in the finance industry. In its current form gLite would be a business disabler. There are other middleware tools that solve the finance communities compute problems much better. Things are moving on, however. There are moves afoot in the open source community to evolve the technology to address other, more sophisticated needs such as utility and interactive computing. In this talk, I will describe how Excelian is providing Grid consultancy services for the finance community and how, through its relationship to the EGEE project, Excelian is helping to identify and exploit opportunities as the research and business worlds converge. Because of the strong third party presence in the finance industry, such opportunities are few and far between, but they are there, especially as we expand sideways into related verticals such as the smaller hedge funds and energy companies. This talk will give an overview of the barriers to adoption of gLite in the finance industry and highlight some of the opportunities offered in this and related industries as the ideas around Grid mature. Speaker Bio: Dr Adam Vile is a senior consultant and head of the Grid and HPC practice at Excelian, a consultancy that focuses on financial markets professional services. He has spent many years in investment banking, as a developer, project manager and architect in both front and back office. Before joining Excelian he was senior Grid and HPC architect at Barclays Capital. Prior to joining investment banking, Adam spent a number of years lecturing in IT and mathematics at a UK University and maintains links with academia through lectures, research and through validation and steering of postgraduate courses. He is a chartered mathematician and was the conference chair of the Institute of Mathematics and its Applications first conference in computational Finance.4. From Monte Carlo to Wall Street Daniel Egloff, Head of Financial Engineering Computing Unit, Zürich Cantonal Bank High performance computing techniques provide new means to solve computationally hard problems in the financial service industry. First I consider Monte Carlo simulation and illustrate how it can be used to implement a sophisticated credit risk management and economic capital framework. From a HPC perspective, basic Monte Carlo simulation is embarrassingly parallel and can be implemented efficiently on distributed memory clusters. Additional difficulties arise for adaptive variance reduction schemes, if the information content in a sample is very small, and if the amount of simulated date becomes huge such that incremental processing algorithms are indispensable. We discuss the business value of an advanced credit risk quantification which is particularly compelling in these days. While Monte Carlo simulation is a very versatile tool it is not always the preferred solution for the pricing of complex products like multi asset options, structured products, or credit derivatives. As a second application I show how operator methods can be used to develop a pricing framework. The scalability of operator methods relies heavily on optimized dense matrix-matrix multiplications and requires specialized BLAS level-3 implementations provided by specialized FPGA or GPU boards. Speaker Bio: Daniel Egloff studied mathematics, theoretical physics, and computer science at the University of Zurich and the ETH Zurich. He holds a PhD in Mathematics from University of Fribourg, Switzerland. After his PhD he started to work for a large Swiss insurance company in the area of asset and liability management. He continued his professional career in the consulting industry. At KPMG and Arthur Andersen he consulted international clients and implemented quantitative risk management solutions for financial institutions and insurance companies. In 2002 he joined Zurich Cantonal Bank. He was assigned to develop and implement credit portfolio risk and economic capital methodologies. He built up a competence center for high performance and cluster computing. Currently, Daniel Egloff is heading the Financial Computing unit in the ZKB Financial Engineering division. He and his team is engineering and operating high performance cluster applications for computationally intensive problems in financial risk management.

Computing for Finance

ScienceCinema

None

2018-01-24

The finance sector is one of the driving forces for the use of distributed or Grid computing for business purposes. The speakers will review the state-of-the-art of high performance computing in the financial sector, and provide insight into how different types of Grid computing – from local clusters to global networks - are being applied to financial applications. They will also describe the use of software and techniques from physics, such as Monte Carlo simulations, in the financial world. There will be four talks of 20min each. The talk abstracts and speaker bios are listed below. This will be followed by a Q&A; panel session with the speakers. From 19:00 onwards there will be a networking cocktail for audience and speakers. This is an EGEE / CERN openlab event organized in collaboration with the regional business network rezonance.ch. A webcast of the event will be made available for subsequent viewing, along with powerpoint material presented by the speakers. Attendance is free and open to all. Registration is mandatory via www.rezonance.ch, including for CERN staff. 1. Overview of High Performance Computing in the Financial Industry Michael Yoo, Managing Director, Head of the Technical Council, UBS Presentation will describe the key business challenges driving the need for HPC solutions, describe the means in which those challenges are being addressed within UBS (such as GRID) as well as the limitations of some of these solutions, and assess some of the newer HPC technologies which may also play a role in the Financial Industry in the future. Speaker Bio: Michael originally joined the former Swiss Bank Corporation in 1994 in New York as a developer on a large data warehouse project. In 1996 he left SBC and took a role with Fidelity Investments in Boston. Unable to stay away for long, he returned to SBC in 1997 while working for Perot Systems in Singapore. Finally, in 1998 he formally returned to UBS in Stamford following the merger with SBC and has remained with UBS for the past 9 years. During his tenure at UBS, he has had a number of leadership roles within IT in development, support and architecture. In 2006 Michael relocated to Switzerland to take up his current role as head of the UBS IB Technical Council, responsible for the overall technology strategy and vision of the Investment Bank. One of Michael's key responsibilities is to manage the UBS High Performance Computing Research Lab and he has been involved in a number of initiatives in the HPC space. 2. Grid in the Commercial WorldFred Gedling, Chief Technology Officer EMEA and Senior Vice President Global Services, DataSynapse Grid computing gets mentions in the press for community programs starting last decade with Seti@Home. Government, national and supranational initiatives in grid receive some press. One of the IT-industries' best-kept secrets is the use of grid computing by commercial organizations with spectacular results. Grid Computing and its evolution into Application Virtualization is discussed and how this is key to the next generation data center. Speaker Bio: Fred Gedling holds the joint roles of Chief Technology Officer for EMEA and Senior Vice President of Global Services at DataSynapse, a global provider of application virtualisation software. Based in London and working closely with organisations seeking to optimise their IT infrastructures, Fred offers unique insights into the technology of virtualisation as well as the methodology of establishing ROI and rapid deployment to the immediate advantage of the business. Fred has more than fifteen years experience of enterprise middleware and high-performance infrastructures. Prior to DataSynapse he worked in high performance CRM middleware and was the CTO EMEA for New Era of Networks (NEON) during the rapid growth of Enterprise Application Integration. His 25-year career in technology also includes management positions at Goldman Sachs and Stratus Computer. Fred holds a First Class Bsc (Hons) degree in Physics with Astrophysics from the University of Leeds and had the privilege of being a summer student at CERN. 3. Opportunities for gLite in finance and related industriesAdam Vile, Head of Grid, HPC and Technical Computing, Excelian Ltd.gLite, the Grid software developed by the EGEE project, has been exceedingly successful as an enabling infrastructure, and has been a massive success in bringing together scientific and technical communities to provide the compute power to address previously incomputable problems. Not so in the finance industry. In its current form gLite would be a business disabler. There are other middleware tools that solve the finance communities compute problems much better. Things are moving on, however. There are moves afoot in the open source community to evolve the technology to address other, more sophisticated needs such as utility and interactive computing. In this talk, I will describe how Excelian is providing Grid consultancy services for the finance community and how, through its relationship to the EGEE project, Excelian is helping to identify and exploit opportunities as the research and business worlds converge. Because of the strong third party presence in the finance industry, such opportunities are few and far between, but they are there, especially as we expand sideways into related verticals such as the smaller hedge funds and energy companies. This talk will give an overview of the barriers to adoption of gLite in the finance industry and highlight some of the opportunities offered in this and related industries as the ideas around Grid mature. Speaker Bio: Dr Adam Vile is a senior consultant and head of the Grid and HPC practice at Excelian, a consultancy that focuses on financial markets professional services. He has spent many years in investment banking, as a developer, project manager and architect in both front and back office. Before joining Excelian he was senior Grid and HPC architect at Barclays Capital. Prior to joining investment banking, Adam spent a number of years lecturing in IT and mathematics at a UK University and maintains links with academia through lectures, research and through validation and steering of postgraduate courses. He is a chartered mathematician and was the conference chair of the Institute of Mathematics and its Applications first conference in computational Finance.4. From Monte Carlo to Wall Street Daniel Egloff, Head of Financial Engineering Computing Unit, Zürich Cantonal Bank High performance computing techniques provide new means to solve computationally hard problems in the financial service industry. First I consider Monte Carlo simulation and illustrate how it can be used to implement a sophisticated credit risk management and economic capital framework. From a HPC perspective, basic Monte Carlo simulation is embarrassingly parallel and can be implemented efficiently on distributed memory clusters. Additional difficulties arise for adaptive variance reduction schemes, if the information content in a sample is very small, and if the amount of simulated date becomes huge such that incremental processing algorithms are indispensable. We discuss the business value of an advanced credit risk quantification which is particularly compelling in these days. While Monte Carlo simulation is a very versatile tool it is not always the preferred solution for the pricing of complex products like multi asset options, structured products, or credit derivatives. As a second application I show how operator methods can be used to develop a pricing framework. The scalability of operator methods relies heavily on optimized dense matrix-matrix multiplications and requires specialized BLAS level-3 implementations provided by specialized FPGA or GPU boards. Speaker Bio: Daniel Egloff studied mathematics, theoretical physics, and computer science at the University of Zurich and the ETH Zurich. He holds a PhD in Mathematics from University of Fribourg, Switzerland. After his PhD he started to work for a large Swiss insurance company in the area of asset and liability management. He continued his professional career in the consulting industry. At KPMG and Arthur Andersen he consulted international clients and implemented quantitative risk management solutions for financial institutions and insurance companies. In 2002 he joined Zurich Cantonal Bank. He was assigned to develop and implement credit portfolio risk and economic capital methodologies. He built up a competence center for high performance and cluster computing. Currently, Daniel Egloff is heading the Financial Computing unit in the ZKB Financial Engineering division. He and his team is engineering and operating high performance cluster applications for computationally intensive problems in financial risk management.

Overset grid applications on distributed memory MIMD computers

NASA Technical Reports Server (NTRS)

Chawla, Kalpana; Weeratunga, Sisira

1994-01-01

Analysis of modern aerospace vehicles requires the computation of flowfields about complex three dimensional geometries composed of regions with varying spatial resolution requirements. Overset grid methods allow the use of proven structured grid flow solvers to address the twin issues of geometrical complexity and the resolution variation by decomposing the complex physical domain into a collection of overlapping subdomains. This flexibility is accompanied by the need for irregular intergrid boundary communication among the overlapping component grids. This study investigates a strategy for implementing such a static overset grid implicit flow solver on distributed memory, MIMD computers; i.e., the 128 node Intel iPSC/860 and the 208 node Intel Paragon. Performance data for two composite grid configurations characteristic of those encountered in present day aerodynamic analysis are also presented.

AGIS: The ATLAS Grid Information System

NASA Astrophysics Data System (ADS)

Anisenkov, Alexey; Belov, Sergey; Di Girolamo, Alessandro; Gayazov, Stavro; Klimentov, Alexei; Oleynik, Danila; Senchenko, Alexander

2012-12-01

ATLAS is a particle physics experiment at the Large Hadron Collider at CERN. The experiment produces petabytes of data annually through simulation production and tens petabytes of data per year from the detector itself. The ATLAS Computing model embraces the Grid paradigm and a high degree of decentralization and computing resources able to meet ATLAS requirements of petabytes scale data operations. In this paper we present ATLAS Grid Information System (AGIS) designed to integrate configuration and status information about resources, services and topology of whole ATLAS Grid needed by ATLAS Distributed Computing applications and services.

Selected computations of transonic cavity flows

NASA Technical Reports Server (NTRS)

Atwood, Christopher A.

1993-01-01

An efficient diagonal scheme implemented in an overset mesh framework has permitted the analysis of geometrically complex cavity flows via the Reynolds averaged Navier-Stokes equations. Use of rapid hyperbolic and algebraic grid methods has allowed simple specification of critical turbulent regions with an algebraic turbulence model. Comparisons between numerical and experimental results are made in two dimensions for the following problems: a backward-facing step; a resonating cavity; and two quieted cavity configurations. In three-dimensions the flow about three early concepts of the stratospheric Observatory For Infrared Astronomy (SOFIA) are compared to wind-tunnel data. Shedding frequencies of resolved shear layer structures are compared against experiment for the quieted cavities. The results demonstrate the progress of computational assessment of configuration safety and performance.

[Parallel virtual reality visualization of extreme large medical datasets].

PubMed

Tang, Min

2010-04-01

On the basis of a brief description of grid computing, the essence and critical techniques of parallel visualization of extreme large medical datasets are discussed in connection with Intranet and common-configuration computers of hospitals. In this paper are introduced several kernel techniques, including the hardware structure, software framework, load balance and virtual reality visualization. The Maximum Intensity Projection algorithm is realized in parallel using common PC cluster. In virtual reality world, three-dimensional models can be rotated, zoomed, translated and cut interactively and conveniently through the control panel built on virtual reality modeling language (VRML). Experimental results demonstrate that this method provides promising and real-time results for playing the role in of a good assistant in making clinical diagnosis.

Tear film dynamics with evaporation, wetting, and time-dependent flux boundary condition on an eye-shaped domain

PubMed Central

Li, Longfei; Braun, R. J.; Maki, K. L.; Henshaw, W. D.; King-Smith, P. E.

2014-01-01

We study tear film dynamics with evaporation on a wettable eye-shaped ocular surface using a lubrication model. The mathematical model has a time-dependent flux boundary condition that models the cycles of tear fluid supply and drainage; it mimics blinks on a stationary eye-shaped domain. We generate computational grids and solve the nonlinear governing equations using the OVERTURE computational framework. In vivo experimental results using fluorescent imaging are used to visualize the influx and redistribution of tears for an open eye. Results from the numerical simulations are compared with the experiment. The model captures the flow around the meniscus and other dynamic features of human tear film observed in vivo. PMID:24926191

Grid today, clouds on the horizon

NASA Astrophysics Data System (ADS)

Shiers, Jamie

2009-04-01

By the time of CCP 2008, the largest scientific machine in the world - the Large Hadron Collider - had been cooled down as scheduled to its operational temperature of below 2 degrees Kelvin and injection tests were starting. Collisions of proton beams at 5+5 TeV were expected within one to two months of the initial tests, with data taking at design energy ( 7+7 TeV) foreseen for 2009. In order to process the data from this world machine, we have put our "Higgs in one basket" - that of Grid computing [The Worldwide LHC Computing Grid (WLCG), in: Proceedings of the Conference on Computational Physics 2006 (CCP 2006), vol. 177, 2007, pp. 219-223]. After many years of preparation, 2008 saw a final "Common Computing Readiness Challenge" (CCRC'08) - aimed at demonstrating full readiness for 2008 data taking, processing and analysis. By definition, this relied on a world-wide production Grid infrastructure. But change - as always - is on the horizon. The current funding model for Grids - which in Europe has been through 3 generations of EGEE projects, together with related projects in other parts of the world, including South America - is evolving towards a long-term, sustainable e-infrastructure, like the European Grid Initiative (EGI) [The European Grid Initiative Design Study, website at http://web.eu-egi.eu/]. At the same time, potentially new paradigms, such as that of "Cloud Computing" are emerging. This paper summarizes the results of CCRC'08 and discusses the potential impact of future Grid funding on both regional and international application communities. It contrasts Grid and Cloud computing models from both technical and sociological points of view. Finally, it discusses the requirements from production application communities, in terms of stability and continuity in the medium to long term.

FermiGrid—experience and future plans

NASA Astrophysics Data System (ADS)

Chadwick, K.; Berman, E.; Canal, P.; Hesselroth, T.; Garzoglio, G.; Levshina, T.; Sergeev, V.; Sfiligoi, I.; Sharma, N.; Timm, S.; Yocum, D. R.

2008-07-01

Fermilab supports a scientific program that includes experiments and scientists located across the globe. In order to better serve this community, Fermilab has placed its production computer resources in a Campus Grid infrastructure called 'FermiGrid'. The FermiGrid infrastructure allows the large experiments at Fermilab to have priority access to their own resources, enables sharing of these resources in an opportunistic fashion, and movement of work (jobs, data) between the Campus Grid and National Grids such as Open Science Grid (OSG) and the Worldwide LHC Computing Grid Collaboration (WLCG). FermiGrid resources support multiple Virtual Organizations (VOs), including VOs from the OSG, EGEE, and the WLCG. Fermilab also makes leading contributions to the Open Science Grid in the areas of accounting, batch computing, grid security, job management, resource selection, site infrastructure, storage management, and VO services. Through the FermiGrid interfaces, authenticated and authorized VOs and individuals may access our core grid services, the 10,000+ Fermilab resident CPUs, near-petabyte (including CMS) online disk pools and the multi-petabyte Fermilab Mass Storage System. These core grid services include a site wide Globus gatekeeper, VO management services for several VOs, Fermilab site authorization services, grid user mapping services, as well as job accounting and monitoring, resource selection and data movement services. Access to these services is via standard and well-supported grid interfaces. We will report on the user experience of using the FermiGrid campus infrastructure interfaced to a national cyberinfrastructure - the successes and the problems.

A chimera grid scheme. [multiple overset body-conforming mesh system for finite difference adaptation to complex aircraft configurations

NASA Technical Reports Server (NTRS)

Steger, J. L.; Dougherty, F. C.; Benek, J. A.

1983-01-01

A mesh system composed of multiple overset body-conforming grids is described for adapting finite-difference procedures to complex aircraft configurations. In this so-called 'chimera mesh,' a major grid is generated about a main component of the configuration and overset minor grids are used to resolve all other features. Methods for connecting overset multiple grids and modifications of flow-simulation algorithms are discussed. Computational tests in two dimensions indicate that the use of multiple overset grids can simplify the task of grid generation without an adverse effect on flow-field algorithms and computer code complexity.

Smart Grid Constraint Violation Management for Balancing and Regulating Purposes

DOE PAGES

Bhattarai, Bishnu; Kouzelis, Konstantinos; Mendaza, Iker; ...

2017-03-29

The gradual active load penetration in low voltage distribution grids is expected to challenge their network capacity in the near future. Distribution system operators should for this reason resort to either costly grid reinforcements or to demand side management mechanisms. Since demand side management implementation is usually cheaper, it is also the favorable solution. To this end, this article presents a framework for handling grid limit violations, both voltage and current, to ensure a secure and qualitative operation of the distribution grid. This framework consists of two steps, namely a proactive centralized and subsequently a reactive decentralized control scheme. Themore » former is employed to balance the one hour ahead load while the latter aims at regulating the consumption in real-time. In both cases, the importance of fair use of electricity demand flexibility is emphasized. Thus, it is demonstrated that this methodology aids in keeping the grid status within preset limits while utilizing flexibility from all flexibility participants.« less

Development of an Aeroelastic Modeling Capability for Transient Nozzle Side Load Analysis

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Zhao, Xiang; Zhang, Sijun; Chen, Yen-Sen

2013-01-01

Lateral nozzle forces are known to cause severe structural damage to any new rocket engine in development. Currently there is no fully coupled computational tool to analyze this fluid/structure interaction process. The objective of this study was to develop a fully coupled aeroelastic modeling capability to describe the fluid/structure interaction process during the transient nozzle operations. The aeroelastic model composes of three components: the computational fluid dynamics component based on an unstructured-grid, pressure-based computational fluid dynamics formulation, the computational structural dynamics component developed in the framework of modal analysis, and the fluid-structural interface component. The developed aeroelastic model was applied to the transient nozzle startup process of the Space Shuttle Main Engine at sea level. The computed nozzle side loads and the axial nozzle wall pressure profiles from the aeroelastic nozzle are compared with those of the published rigid nozzle results, and the impact of the fluid/structure interaction on nozzle side loads is interrogated and presented.

An atomic orbital based real-time time-dependent density functional theory for computing electronic circular dichroism band spectra

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goings, Joshua J.; Li, Xiaosong, E-mail: xsli@uw.edu

2016-06-21

One of the challenges of interpreting electronic circular dichroism (ECD) band spectra is that different states may have different rotatory strength signs, determined by their absolute configuration. If the states are closely spaced and opposite in sign, observed transitions may be washed out by nearby states, unlike absorption spectra where transitions are always positive additive. To accurately compute ECD bands, it is necessary to compute a large number of excited states, which may be prohibitively costly if one uses the linear-response time-dependent density functional theory (TDDFT) framework. Here we implement a real-time, atomic-orbital based TDDFT method for computing the entiremore » ECD spectrum simultaneously. The method is advantageous for large systems with a high density of states. In contrast to previous implementations based on real-space grids, the method is variational, independent of nuclear orientation, and does not rely on pseudopotential approximations, making it suitable for computation of chiroptical properties well into the X-ray regime.« less

20 plus Years of Computational Fluid Dynamics for the Space Shuttle

NASA Technical Reports Server (NTRS)

Gomez, Reynaldo J., III

2011-01-01

This slide presentation reviews the use of computational fluid dynamics in performing analysis of the space shuttle with particular reference to the return to flight analysis and other shuttle problems. Slides show a comparison of pressure coefficient with the shuttle ascent configuration between the wind tunnel test and the computed values. the evolution of the grid system for the space shuttle launch vehicle (SSLv) from the early 80's to one in 2004, the grid configuration of the bipod ramp redesign from the original design to the current configuration, charts with the computations showing solid rocket booster surface pressures from wind tunnel data, calculated over two grid systems (i.e., the original 14 grid system, and the enhanced 113 grid system), and the computed flight orbiter wing loads are compared with strain gage data on STS-50 during flight. The loss of STS-107 initiated an unprecedented review of all external environments. The current SSLV grid system of 600+ grids, 1.8 Million surface points and 95+ million volume points is shown. The inflight entry analyses is shown, and the use of Overset CFD as a key part to many external tank redesign and debris assessments is discussed. The work that still remains to be accomplished for future shuttle flights is discussed.

Development of numerical methods for overset grids with applications for the integrated Space Shuttle vehicle

NASA Technical Reports Server (NTRS)

Chan, William M.

1995-01-01

Algorithms and computer code developments were performed for the overset grid approach to solving computational fluid dynamics problems. The techniques developed are applicable to compressible Navier-Stokes flow for any general complex configurations. The computer codes developed were tested on different complex configurations with the Space Shuttle launch vehicle configuration as the primary test bed. General, efficient and user-friendly codes were produced for grid generation, flow solution and force and moment computation.

Koopman Operator Framework for Time Series Modeling and Analysis

NASA Astrophysics Data System (ADS)

Surana, Amit

2018-01-01

We propose an interdisciplinary framework for time series classification, forecasting, and anomaly detection by combining concepts from Koopman operator theory, machine learning, and linear systems and control theory. At the core of this framework is nonlinear dynamic generative modeling of time series using the Koopman operator which is an infinite-dimensional but linear operator. Rather than working with the underlying nonlinear model, we propose two simpler linear representations or model forms based on Koopman spectral properties. We show that these model forms are invariants of the generative model and can be readily identified directly from data using techniques for computing Koopman spectral properties without requiring the explicit knowledge of the generative model. We also introduce different notions of distances on the space of such model forms which is essential for model comparison/clustering. We employ the space of Koopman model forms equipped with distance in conjunction with classical machine learning techniques to develop a framework for automatic feature generation for time series classification. The forecasting/anomaly detection framework is based on using Koopman model forms along with classical linear systems and control approaches. We demonstrate the proposed framework for human activity classification, and for time series forecasting/anomaly detection in power grid application.

Information Power Grid Posters

NASA Technical Reports Server (NTRS)

Vaziri, Arsi

2003-01-01

This document is a summary of the accomplishments of the Information Power Grid (IPG). Grids are an emerging technology that provide seamless and uniform access to the geographically dispersed, computational, data storage, networking, instruments, and software resources needed for solving large-scale scientific and engineering problems. The goal of the NASA IPG is to use NASA's remotely located computing and data system resources to build distributed systems that can address problems that are too large or complex for a single site. The accomplishments outlined in this poster presentation are: access to distributed data, IPG heterogeneous computing, integration of large-scale computing node into distributed environment, remote access to high data rate instruments,and exploratory grid environment.

Solution of Poisson equations for 3-dimensional grid generations. [computations of a flow field over a thin delta wing

NASA Technical Reports Server (NTRS)

Fujii, K.

1983-01-01

A method for generating three dimensional, finite difference grids about complicated geometries by using Poisson equations is developed. The inhomogenous terms are automatically chosen such that orthogonality and spacing restrictions at the body surface are satisfied. Spherical variables are used to avoid the axis singularity, and an alternating-direction-implicit (ADI) solution scheme is used to accelerate the computations. Computed results are presented that show the capability of the method. Since most of the results presented have been used as grids for flow-field computations, this is indicative that the method is a useful tool for generating three-dimensional grids about complicated geometries.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhattarai, Bishnu; Kouzelis, Konstantinos; Mendaza, Iker

The gradual active load penetration in low voltage distribution grids is expected to challenge their network capacity in the near future. Distribution system operators should for this reason resort to either costly grid reinforcements or to demand side management mechanisms. Since demand side management implementation is usually cheaper, it is also the favorable solution. To this end, this article presents a framework for handling grid limit violations, both voltage and current, to ensure a secure and qualitative operation of the distribution grid. This framework consists of two steps, namely a proactive centralized and subsequently a reactive decentralized control scheme. Themore » former is employed to balance the one hour ahead load while the latter aims at regulating the consumption in real-time. In both cases, the importance of fair use of electricity demand flexibility is emphasized. Thus, it is demonstrated that this methodology aids in keeping the grid status within preset limits while utilizing flexibility from all flexibility participants.« less

Evaluation of the UnTRIM model for 3-D tidal circulation

USGS Publications Warehouse

Cheng, R.T.; Casulli, V.; ,

2001-01-01

A family of numerical models, known as the TRIM models, shares the same modeling philosophy for solving the shallow water equations. A characteristic analysis of the shallow water equations points out that the numerical instability is controlled by the gravity wave terms in the momentum equations and by the transport terms in the continuity equation. A semi-implicit finite-difference scheme has been formulated so that these terms and the vertical diffusion terms are treated implicitly and the remaining terms explicitly to control the numerical stability and the computations are carried out over a uniform finite-difference computational mesh without invoking horizontal or vertical coordinate transformations. An unstructured grid version of TRIM model is introduced, or UnTRIM (pronounces as "you trim"), which preserves these basic numerical properties and modeling philosophy, only the computations are carried out over an unstructured orthogonal grid. The unstructured grid offers the flexibilities in representing complex study areas so that fine grid resolution can be placed in regions of interest, and coarse grids are used to cover the remaining domain. Thus, the computational efforts are concentrated in areas of importance, and an overall computational saving can be achieved because the total number of grid-points is dramatically reduced. To use this modeling approach, an unstructured grid mesh must be generated to properly reflect the properties of the domain of the investigation. The new modeling flexibility in grid structure is accompanied by new challenges associated with issues of grid generation. To take full advantage of this new model flexibility, the model grid generation should be guided by insights into the physics of the problems; and the insights needed may require a higher degree of modeling skill.

A Grid Metadata Service for Earth and Environmental Sciences

NASA Astrophysics Data System (ADS)

Fiore, Sandro; Negro, Alessandro; Aloisio, Giovanni

2010-05-01

Critical challenges for climate modeling researchers are strongly connected with the increasingly complex simulation models and the huge quantities of produced datasets. Future trends in climate modeling will only increase computational and storage requirements. For this reason the ability to transparently access to both computational and data resources for large-scale complex climate simulations must be considered as a key requirement for Earth Science and Environmental distributed systems. From the data management perspective (i) the quantity of data will continuously increases, (ii) data will become more and more distributed and widespread, (iii) data sharing/federation will represent a key challenging issue among different sites distributed worldwide, (iv) the potential community of users (large and heterogeneous) will be interested in discovery experimental results, searching of metadata, browsing collections of files, compare different results, display output, etc.; A key element to carry out data search and discovery, manage and access huge and distributed amount of data is the metadata handling framework. What we propose for the management of distributed datasets is the GRelC service (a data grid solution focusing on metadata management). Despite the classical approaches, the proposed data-grid solution is able to address scalability, transparency, security and efficiency and interoperability. The GRelC service we propose is able to provide access to metadata stored in different and widespread data sources (relational databases running on top of MySQL, Oracle, DB2, etc. leveraging SQL as query language, as well as XML databases - XIndice, eXist, and libxml2 based documents, adopting either XPath or XQuery) providing a strong data virtualization layer in a grid environment. Such a technological solution for distributed metadata management leverages on well known adopted standards (W3C, OASIS, etc.); (ii) supports role-based management (based on VOMS), which increases flexibility and scalability; (iii) provides full support for Grid Security Infrastructure, which means (authorization, mutual authentication, data integrity, data confidentiality and delegation); (iv) is compatible with existing grid middleware such as gLite and Globus and finally (v) is currently adopted at the Euro-Mediterranean Centre for Climate Change (CMCC - Italy) to manage the entire CMCC data production activity as well as in the international Climate-G testbed.

The National Grid Project: A system overview

NASA Technical Reports Server (NTRS)

Gaither, Adam; Gaither, Kelly; Jean, Brian; Remotigue, Michael; Whitmire, John; Soni, Bharat; Thompson, Joe; Dannenhoffer,, John; Weatherill, Nigel

1995-01-01

The National Grid Project (NGP) is a comprehensive numerical grid generation software system that is being developed at the National Science Foundation (NSF) Engineering Research Center (ERC) for Computational Field Simulation (CFS) at Mississippi State University (MSU). NGP is supported by a coalition of U.S. industries and federal laboratories. The objective of the NGP is to significantly decrease the amount of time it takes to generate a numerical grid for complex geometries and to increase the quality of these grids to enable computational field simulations for applications in industry. A geometric configuration can be discretized into grids (or meshes) that have two fundamental forms: structured and unstructured. Structured grids are formed by intersecting curvilinear coordinate lines and are composed of quadrilateral (2D) and hexahedral (3D) logically rectangular cells. The connectivity of a structured grid provides for trivial identification of neighboring points by incrementing coordinate indices. Unstructured grids are composed of cells of any shape (commonly triangles, quadrilaterals, tetrahedra and hexahedra), but do not have trivial identification of neighbors by incrementing an index. For unstructured grids, a set of points and an associated connectivity table is generated to define unstructured cell shapes and neighboring points. Hybrid grids are a combination of structured grids and unstructured grids. Chimera (overset) grids are intersecting or overlapping structured grids. The NGP system currently provides a user interface that integrates both 2D and 3D structured and unstructured grid generation, a solid modeling topology data management system, an internal Computer Aided Design (CAD) system based on Non-Uniform Rational B-Splines (NURBS), a journaling language, and a grid/solution visualization system.

Sean Esterly | NREL

Science.gov Websites

, micro and mini-grid policies and regulations, and international clean energy policy analysis. He has technologies, such as micro- and mini-grids. Strategic energy planning, focusing on both renewable and energy Considerations and Good Practices, NREL Technical Report (2015) Quality Assurance Framework for Mini-Grids, NREL

WRF4SG: A Scientific Gateway for climate experiment workflows

NASA Astrophysics Data System (ADS)

Blanco, Carlos; Cofino, Antonio S.; Fernandez-Quiruelas, Valvanuz

2013-04-01

The Weather Research and Forecasting model (WRF) is a community-driven and public domain model widely used by the weather and climate communities. As opposite to other application-oriented models, WRF provides a flexible and computationally-efficient framework which allows solving a variety of problems for different time-scales, from weather forecast to climate change projection. Furthermore, WRF is also widely used as a research tool in modeling physics, dynamics, and data assimilation by the research community. Climate experiment workflows based on Weather Research and Forecasting (WRF) are nowadays among the one of the most cutting-edge applications. These workflows are complex due to both large storage and the huge number of simulations executed. In order to manage that, we have developed a scientific gateway (SG) called WRF for Scientific Gateway (WRF4SG) based on WS-PGRADE/gUSE and WRF4G frameworks to ease achieve WRF users needs (see [1] and [2]). WRF4SG provides services for different use cases that describe the different interactions between WRF users and the WRF4SG interface in order to show how to run a climate experiment. As WS-PGRADE/gUSE uses portlets (see [1]) to interact with users, its portlets will support these use cases. A typical experiment to be carried on by a WRF user will consist on a high-resolution regional re-forecast. These re-forecasts are common experiments used as input data form wind power energy and natural hazards (wind and precipitation fields). In the cases below, the user is able to access to different resources such as Grid due to the fact that WRF needs a huge amount of computing resources in order to generate useful simulations: * Resource configuration and user authentication: The first step is to authenticate on users' Grid resources by virtual organizations. After login, the user is able to select which virtual organization is going to be used by the experiment. * Data assimilation: In order to assimilate the data sources, the user has to select them browsing through LFC Portlet. * Design Experiment workflow: In order to configure the experiment, the user will define the type of experiment (i.e. re-forecast), and its attributes to simulate. In this case the main attributes are: the field of interest (wind, precipitation, ...), the start and end date simulation and the requirements of the experiment. * Monitor workflow: In order to monitor the experiment the user will receive notification messages based on events and also the gateway will display the progress of the experiment. * Data storage: Like Data assimilation case, the user is able to browse and view the output data simulations using LFC Portlet. The objectives of WRF4SG can be described by considering two goals. The first goal is to show how WRF4SG facilitates to execute, monitor and manage climate workflows based on the WRF4G framework. And the second goal of WRF4SG is to help WRF users to execute their experiment workflows concurrently using heterogeneous computing resources such as HPC and Grid. [1] Kacsuk, P.: P-GRADE portal family for grid infrastructures. Concurrency and Computation: Practice and Experience. 23, 235-245 (2011). [2] http://www.meteo.unican.es/software/wrf4g

AstroGrid-D: Grid technology for astronomical science

NASA Astrophysics Data System (ADS)

Enke, Harry; Steinmetz, Matthias; Adorf, Hans-Martin; Beck-Ratzka, Alexander; Breitling, Frank; Brüsemeister, Thomas; Carlson, Arthur; Ensslin, Torsten; Högqvist, Mikael; Nickelt, Iliya; Radke, Thomas; Reinefeld, Alexander; Reiser, Angelika; Scholl, Tobias; Spurzem, Rainer; Steinacker, Jürgen; Voges, Wolfgang; Wambsganß, Joachim; White, Steve

2011-02-01

We present status and results of AstroGrid-D, a joint effort of astrophysicists and computer scientists to employ grid technology for scientific applications. AstroGrid-D provides access to a network of distributed machines with a set of commands as well as software interfaces. It allows simple use of computer and storage facilities and to schedule or monitor compute tasks and data management. It is based on the Globus Toolkit middleware (GT4). Chapter 1 describes the context which led to the demand for advanced software solutions in Astrophysics, and we state the goals of the project. We then present characteristic astrophysical applications that have been implemented on AstroGrid-D in chapter 2. We describe simulations of different complexity, compute-intensive calculations running on multiple sites (Section 2.1), and advanced applications for specific scientific purposes (Section 2.2), such as a connection to robotic telescopes (Section 2.2.3). We can show from these examples how grid execution improves e.g. the scientific workflow. Chapter 3 explains the software tools and services that we adapted or newly developed. Section 3.1 is focused on the administrative aspects of the infrastructure, to manage users and monitor activity. Section 3.2 characterises the central components of our architecture: The AstroGrid-D information service to collect and store metadata, a file management system, the data management system, and a job manager for automatic submission of compute tasks. We summarise the successfully established infrastructure in chapter 4, concluding with our future plans to establish AstroGrid-D as a platform of modern e-Astronomy.

Communication Simulations for Power System Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fuller, Jason C.; Ciraci, Selim; Daily, Jeffrey A.

2013-05-29

New smart grid technologies and concepts, such as dynamic pricing, demand response, dynamic state estimation, and wide area monitoring, protection, and control, are expected to require considerable communication resources. As the cost of retrofit can be high, future power grids will require the integration of high-speed, secure connections with legacy communication systems, while still providing adequate system control and security. While considerable work has been performed to create co-simulators for the power domain with load models and market operations, limited work has been performed in integrating communications directly into a power domain solver. The simulation of communication and power systemsmore » will become more important as the two systems become more inter-related. This paper will discuss ongoing work at Pacific Northwest National Laboratory to create a flexible, high-speed power and communication system co-simulator for smart grid applications. The framework for the software will be described, including architecture considerations for modular, high performance computing and large-scale scalability (serialization, load balancing, partitioning, cross-platform support, etc.). The current simulator supports the ns-3 (telecommunications) and GridLAB-D (distribution systems) simulators. Ongoing and future work will be described, including planned future expansions for a traditional transmission solver. A test case using the co-simulator, utilizing a transactive demand response system created for the Olympic Peninsula and AEP gridSMART demonstrations, requiring two-way communication between distributed and centralized market devices, will be used to demonstrate the value and intended purpose of the co-simulation environment.« less

ICASE Workshop on Programming Computational Grids

DTIC Science & Technology

2001-09-01

ICASE Workshop on Programming Computational Grids Thomas M. Eidson and Merrell L. Patrick ICASE, Hampton, Virginia ICASE NASA Langley Research Center...Computational Grids Contract Number Grant Number Program Element Number Author(s) Thomas M. Eidson and Merrell L. Patrick Project Number Task Number...clear that neither group fully understood the ideas and problems of the other. It was also clear that neither group is given the time and support to

Differences in Visual-Spatial Input May Underlie Different Compression Properties of Firing Fields for Grid Cell Modules in Medial Entorhinal Cortex

PubMed Central

Raudies, Florian; Hasselmo, Michael E.

2015-01-01

Firing fields of grid cells in medial entorhinal cortex show compression or expansion after manipulations of the location of environmental barriers. This compression or expansion could be selective for individual grid cell modules with particular properties of spatial scaling. We present a model for differences in the response of modules to barrier location that arise from different mechanisms for the influence of visual features on the computation of location that drives grid cell firing patterns. These differences could arise from differences in the position of visual features within the visual field. When location was computed from the movement of visual features on the ground plane (optic flow) in the ventral visual field, this resulted in grid cell spatial firing that was not sensitive to barrier location in modules modeled with small spacing between grid cell firing fields. In contrast, when location was computed from static visual features on walls of barriers, i.e. in the more dorsal visual field, this resulted in grid cell spatial firing that compressed or expanded based on the barrier locations in modules modeled with large spacing between grid cell firing fields. This indicates that different grid cell modules might have differential properties for computing location based on visual cues, or the spatial radius of sensitivity to visual cues might differ between modules. PMID:26584432

Comprehensive framework for visualizing and analyzing spatio-temporal dynamics of racial diversity in the entire United States

PubMed Central

Netzel, Pawel

2017-01-01

The United States is increasingly becoming a multi-racial society. To understand multiple consequences of this overall trend to our neighborhoods we need a methodology capable of spatio-temporal analysis of racial diversity at the local level but also across the entire U.S. Furthermore, such methodology should be accessible to stakeholders ranging from analysts to decision makers. In this paper we present a comprehensive framework for visualizing and analyzing diversity data that fulfills such requirements. The first component of our framework is a U.S.-wide, multi-year database of race sub-population grids which is freely available for download. These 30 m resolution grids have being developed using dasymetric modeling and are available for 1990-2000-2010. We summarize numerous advantages of gridded population data over commonly used Census tract-aggregated data. Using these grids frees analysts from constructing their own and allows them to focus on diversity analysis. The second component of our framework is a set of U.S.-wide, multi-year diversity maps at 30 m resolution. A diversity map is our product that classifies the gridded population into 39 communities based on their degrees of diversity, dominant race, and population density. It provides spatial information on diversity in a single, easy-to-understand map that can be utilized by analysts and end users alike. Maps based on subsequent Censuses provide information about spatio-temporal dynamics of diversity. Diversity maps are accessible through the GeoWeb application SocScape (http://sil.uc.edu/webapps/socscape_usa/) for an immediate online exploration. The third component of our framework is a proposal to quantitatively analyze diversity maps using a set of landscape metrics. Because of its form, a grid-based diversity map could be thought of as a diversity “landscape” and analyzed quantitatively using landscape metrics. We give a brief summary of most pertinent metrics and demonstrate how they can be applied to diversity maps. PMID:28358862

Aeroacoustic Simulations of a Nose Landing Gear with FUN3D: A Grid Refinement Study

NASA Technical Reports Server (NTRS)

Vatsa, Veer N.; Khorrami, Mehdi R.; Lockard, David P.

2017-01-01

A systematic grid refinement study is presented for numerical simulations of a partially-dressed, cavity-closed (PDCC) nose landing gear configuration that was tested in the University of Florida's open-jet acoustic facility known as the UFAFF. The unstructured-grid flow solver FUN3D is used to compute the unsteady flow field for this configuration. Mixed-element grids generated using the Pointwise (Registered Trademark) grid generation software are used for numerical simulations. Particular care is taken to ensure quality cells and proper resolution in critical areas of interest in an effort to minimize errors introduced by numerical artifacts. A set of grids was generated in this manner to create a family of uniformly refined grids. The finest grid was then modified to coarsen the wall-normal spacing to create a grid suitable for the wall-function implementation in FUN3D code. A hybrid Reynolds-averaged Navier-Stokes/large eddy simulation (RANS/LES) turbulence modeling approach is used for these simulations. Time-averaged and instantaneous solutions obtained on these grids are compared with the measured data. These CFD solutions are used as input to a FfowcsWilliams-Hawkings (FW-H) noise propagation code to compute the farfield noise levels. The agreement of the computed results with the experimental data improves as the grid is refined.

Stability and error estimation for Component Adaptive Grid methods

NASA Technical Reports Server (NTRS)

Oliger, Joseph; Zhu, Xiaolei

1994-01-01

Component adaptive grid (CAG) methods for solving hyperbolic partial differential equations (PDE's) are discussed in this paper. Applying recent stability results for a class of numerical methods on uniform grids. The convergence of these methods for linear problems on component adaptive grids is established here. Furthermore, the computational error can be estimated on CAG's using the stability results. Using these estimates, the error can be controlled on CAG's. Thus, the solution can be computed efficiently on CAG's within a given error tolerance. Computational results for time dependent linear problems in one and two space dimensions are presented.

A Simple XML Producer-Consumer Protocol

NASA Technical Reports Server (NTRS)

Smith, Warren; Gunter, Dan; Quesnel, Darcy; Biegel, Bryan (Technical Monitor)

2001-01-01

There are many different projects from government, academia, and industry that provide services for delivering events in distributed environments. The problem with these event services is that they are not general enough to support all uses and they speak different protocols so that they cannot interoperate. We require such interoperability when we, for example, wish to analyze the performance of an application in a distributed environment. Such an analysis might require performance information from the application, computer systems, networks, and scientific instruments. In this work we propose and evaluate a standard XML-based protocol for the transmission of events in distributed systems. One recent trend in government and academic research is the development and deployment of computational grids. Computational grids are large-scale distributed systems that typically consist of high-performance compute, storage, and networking resources. Examples of such computational grids are the DOE Science Grid, the NASA Information Power Grid (IPG), and the NSF Partnerships for Advanced Computing Infrastructure (PACIs). The major effort to deploy these grids is in the area of developing the software services to allow users to execute applications on these large and diverse sets of resources. These services include security, execution of remote applications, managing remote data, access to information about resources and services, and so on. There are several toolkits for providing these services such as Globus, Legion, and Condor. As part of these efforts to develop computational grids, the Global Grid Forum is working to standardize the protocols and APIs used by various grid services. This standardization will allow interoperability between the client and server software of the toolkits that are providing the grid services. The goal of the Performance Working Group of the Grid Forum is to standardize protocols and representations related to the storage and distribution of performance data. These standard protocols and representations must support tasks such as profiling parallel applications, monitoring the status of computers and networks, and monitoring the performance of services provided by a computational grid. This paper describes a proposed protocol and data representation for the exchange of events in a distributed system. The protocol exchanges messages formatted in XML and it can be layered atop any low-level communication protocol such as TCP or UDP Further, we describe Java and C++ implementations of this protocol and discuss their performance. The next section will provide some further background information. Section 3 describes the main communication patterns of our protocol. Section 4 describes how we represent events and related information using XML. Section 5 describes our protocol and Section 6 discusses the performance of two implementations of the protocol. Finally, an appendix provides the XML Schema definition of our protocol and event information.

Collaborative Science Using Web Services and the SciFlo Grid Dataflow Engine

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Manipon, G.; Xing, Z.; Yunck, T.

2006-12-01

The General Earth Science Investigation Suite (GENESIS) project is a NASA-sponsored partnership between the Jet Propulsion Laboratory, academia, and NASA data centers to develop a new suite of Web Services tools to facilitate multi-sensor investigations in Earth System Science. The goal of GENESIS is to enable large-scale, multi-instrument atmospheric science using combined datasets from the AIRS, MODIS, MISR, and GPS sensors. Investigations include cross-comparison of spaceborne climate sensors, cloud spectral analysis, study of upper troposphere-stratosphere water transport, study of the aerosol indirect cloud effect, and global climate model validation. The challenges are to bring together very large datasets, reformat and understand the individual instrument retrievals, co-register or re-grid the retrieved physical parameters, perform computationally-intensive data fusion and data mining operations, and accumulate complex statistics over months to years of data. To meet these challenges, we have developed a Grid computing and dataflow framework, named SciFlo, in which we are deploying a set of versatile and reusable operators for data access, subsetting, registration, mining, fusion, compression, and advanced statistical analysis. SciFlo leverages remote Web Services, called via Simple Object Access Protocol (SOAP) or REST (one-line) URLs, and the Grid Computing standards (WS-* &Globus Alliance toolkits), and enables scientists to do multi-instrument Earth Science by assembling reusable Web Services and native executables into a distributed computing flow (tree of operators). The SciFlo client &server engines optimize the execution of such distributed data flows and allow the user to transparently find and use datasets and operators without worrying about the actual location of the Grid resources. In particular, SciFlo exploits the wealth of datasets accessible by OpenGIS Consortium (OGC) Web Mapping Servers & Web Coverage Servers (WMS/WCS), and by Open Data Access Protocol (OpenDAP) servers. The scientist injects a distributed computation into the Grid by simply filling out an HTML form or directly authoring the underlying XML dataflow document, and results are returned directly to the scientist's desktop. Once an analysis has been specified for a chunk or day of data, it can be easily repeated with different control parameters or over months of data. Recently, the Earth Science Information Partners (ESIP) Federation sponsored a collaborative activity in which several ESIP members advertised their respective WMS/WCS and SOAP services, developed some collaborative science scenarios for atmospheric and aerosol science, and then choreographed services from multiple groups into demonstration workflows using the SciFlo engine and a Business Process Execution Language (BPEL) workflow engine. For several scenarios, the same collaborative workflow was executed in three ways: using hand-coded scripts, by executing a SciFlo document, and by executing a BPEL workflow document. We will discuss the lessons learned from this activity, the need for standardized interfaces (like WMS/WCS), the difficulty in agreeing on even simple XML formats and interfaces, and further collaborations that are being pursued.

On the effects of grid ill-conditioning in three dimensional finite element vector potential magnetostatic field computations

NASA Technical Reports Server (NTRS)

Wang, R.; Demerdash, N. A.

1990-01-01

The effects of finite element grid geometries and associated ill-conditioning were studied in single medium and multi-media (air-iron) three dimensional magnetostatic field computation problems. The sensitivities of these 3D field computations to finite element grid geometries were investigated. It was found that in single medium applications the unconstrained magnetic vector potential curl-curl formulation in conjunction with first order finite elements produce global results which are almost totally insensitive to grid geometries. However, it was found that in multi-media (air-iron) applications first order finite element results are sensitive to grid geometries and consequent elemental shape ill-conditioning. These sensitivities were almost totally eliminated by means of the use of second order finite elements in the field computation algorithms. Practical examples are given in this paper to demonstrate these aspects mentioned above.

A Framework for Testing Automated Detection, Diagnosis, and Remediation Systems on the Smart Grid

NASA Technical Reports Server (NTRS)

Lau, Shing-hon

2011-01-01

America's electrical grid is currently undergoing a multi-billion dollar modernization effort aimed at producing a highly reliable critical national infrastructure for power - a Smart Grid. While the goals for the Smart Grid include upgrades to accommodate large quantities of clean, but transient, renewable energy and upgrades to provide customers with real-time pricing information, perhaps the most important objective is to create an electrical grid with a greatly increased robustness.

Toward a Grid and Group Interpretation of School Culture.

ERIC Educational Resources Information Center

Harris, Edward L.

1995-01-01

Mary Douglas's typology, using grid and group dimensions, provides a means to classify and compare social environments in terms of their differing cultural constraints on individual autonomy. This article uses the Douglas typology to examine the grid and group characteristics of four diverse schools to determine the framework's applicability to…

Dissecting obesogenic environments: the development and application of a framework for identifying and prioritizing environmental interventions for obesity.

PubMed

Swinburn, B; Egger, G; Raza, F

1999-12-01

The "obesogenicity" of modern environments is fueling the obesity pandemic. We describe a framework, known as ANGELO (analysis grid for environments linked to obesity), which is a conceptual model for understanding the obesogenicity of environments and a practical tool for prioritizing environmental elements for research and intervention. Development of the ANGELO framework. The basic framework is a 2 x 4 grid which dissects the environment into environmental size (micro and macro) by type: physical (what is available), economic (what are the costs), political (what are the "rules"), and sociocultural (what are the attitudes and beliefs). Within this grid, the elements which influence food intake and physical activity are characterized as obesogenic or "leptogenic" (promoting leanness). Application of the ANGELO framework. The ANGELO framework has been piloted at the population level (island communities) to prioritize the settings/sectors for intervention and at the setting level (fast food outlets) to prioritize research needs and interventions. Environmental elements were prioritized by rating their validity (evidence of impact), relevance (to the local context), and potential changeability. The ANGELO framework appears to be a flexible and robust instrument for the needs analysis and problem identification stages of reducing the obesogenicity of modern environments. Copyright 1999 American Health Foundation and Academic Press.

The Integration of CloudStack and OCCI/OpenNebula with DIRAC

NASA Astrophysics Data System (ADS)

Méndez Muñoz, Víctor; Fernández Albor, Víctor; Graciani Diaz, Ricardo; Casajús Ramo, Adriàn; Fernández Pena, Tomás; Merino Arévalo, Gonzalo; José Saborido Silva, Juan

2012-12-01

The increasing availability of Cloud resources is arising as a realistic alternative to the Grid as a paradigm for enabling scientific communities to access large distributed computing resources. The DIRAC framework for distributed computing is an easy way to efficiently access to resources from both systems. This paper explains the integration of DIRAC with two open-source Cloud Managers: OpenNebula (taking advantage of the OCCI standard) and CloudStack. These are computing tools to manage the complexity and heterogeneity of distributed data center infrastructures, allowing to create virtual clusters on demand, including public, private and hybrid clouds. This approach has required to develop an extension to the previous DIRAC Virtual Machine engine, which was developed for Amazon EC2, allowing the connection with these new cloud managers. In the OpenNebula case, the development has been based on the CernVM Virtual Software Appliance with appropriate contextualization, while in the case of CloudStack, the infrastructure has been kept more general, which permits other Virtual Machine sources and operating systems being used. In both cases, CernVM File System has been used to facilitate software distribution to the computing nodes. With the resulting infrastructure, the cloud resources are transparent to the users through a friendly interface, like the DIRAC Web Portal. The main purpose of this integration is to get a system that can manage cloud and grid resources at the same time. This particular feature pushes DIRAC to a new conceptual denomination as interware, integrating different middleware. Users from different communities do not need to care about the installation of the standard software that is available at the nodes, nor the operating system of the host machine which is transparent to the user. This paper presents an analysis of the overhead of the virtual layer, doing some tests to compare the proposed approach with the existing Grid solution. License Notice: Published under licence in Journal of Physics: Conference Series by IOP Publishing Ltd.

Efficient non-hydrostatic modelling of 3D wave-induced currents using a subgrid approach

NASA Astrophysics Data System (ADS)

Rijnsdorp, Dirk P.; Smit, Pieter B.; Zijlema, Marcel; Reniers, Ad J. H. M.

2017-08-01

Wave-induced currents are an ubiquitous feature in coastal waters that can spread material over the surf zone and the inner shelf. These currents are typically under resolved in non-hydrostatic wave-flow models due to computational constraints. Specifically, the low vertical resolutions adequate to describe the wave dynamics - and required to feasibly compute at the scales of a field site - are too coarse to account for the relevant details of the three-dimensional (3D) flow field. To describe the relevant dynamics of both wave and currents, while retaining a model framework that can be applied at field scales, we propose a two grid approach to solve the governing equations. With this approach, the vertical accelerations and non-hydrostatic pressures are resolved on a relatively coarse vertical grid (which is sufficient to accurately resolve the wave dynamics), whereas the horizontal velocities and turbulent stresses are resolved on a much finer subgrid (of which the resolution is dictated by the vertical scale of the mean flows). This approach ensures that the discrete pressure Poisson equation - the solution of which dominates the computational effort - is evaluated on the coarse grid scale, thereby greatly improving efficiency, while providing a fine vertical resolution to resolve the vertical variation of the mean flow. This work presents the general methodology, and discusses the numerical implementation in the SWASH wave-flow model. Model predictions are compared with observations of three flume experiments to demonstrate that the subgrid approach captures both the nearshore evolution of the waves, and the wave-induced flows like the undertow profile and longshore current. The accuracy of the subgrid predictions is comparable to fully resolved 3D simulations - but at much reduced computational costs. The findings of this work thereby demonstrate that the subgrid approach has the potential to make 3D non-hydrostatic simulations feasible at the scale of a realistic coastal region.

Development of a mechanics-based model of brain deformations during intracerebral hemorrhage evacuation

NASA Astrophysics Data System (ADS)

Narasimhan, Saramati; Weis, Jared A.; Godage, Isuru S.; Webster, Robert; Weaver, Kyle; Miga, Michael I.

2017-03-01

Intracerebral hemorrhages (ICHs) occur in 24 out of 100,000 people annually and have high morbidity and mortality rates. The standard treatment is conservative. We hypothesize that a patient-specific, mechanical model coupled with a robotic steerable needle, used to aspirate a hematoma, would result in a minimally invasive approach to ICH management that will improve outcomes. As a preliminary study, three realizations of a tissue aspiration framework are explored within the context of a biphasic finite element model based on Biot's consolidation theory. Short-term transient effects were neglected in favor of steady state formulation. The Galerkin Method of Weighted Residuals was used to solve coupled partial differential equations using linear basis functions, and assumptions of plane strain and homogeneous isotropic properties. All aspiration models began with the application of aspiration pressure sink(s), calculated pressures and displacements, and the use of von Mises stresses within a tissue failure criterion. With respect to aspiration strategies, one model employs an element-deletion strategy followed by aspiration redeployment on the remaining grid, while the other approaches use principles of superposition on a fixed grid. While the element-deletion approach had some intuitive appeal, without incorporating a dynamic grid strategy, it evolved into a less realistic result. The superposition strategy overcame this, but would require empirical investigations to determine the optimum distribution of aspiration sinks to match material removal. While each modeling framework demonstrated some promise, the superposition method's ease of computation, ability to incorporate the surgical plan, and better similarity to existing empirical observational data, makes it favorable.

Impact of temporal upscaling and chemical transport model horizontal resolution on reducing ozone exposure misclassification

NASA Astrophysics Data System (ADS)

Xu, Yadong; Serre, Marc L.; Reyes, Jeanette M.; Vizuete, William

2017-10-01

We have developed a Bayesian Maximum Entropy (BME) framework that integrates observations from a surface monitoring network and predictions from a Chemical Transport Model (CTM) to create improved exposure estimates that can be resolved into any spatial and temporal resolution. The flexibility of the framework allows for input of data in any choice of time scales and CTM predictions of any spatial resolution with varying associated degrees of estimation error and cost in terms of implementation and computation. This study quantifies the impact on exposure estimation error due to these choices by first comparing estimations errors when BME relied on ozone concentration data either as an hourly average, the daily maximum 8-h average (DM8A), or the daily 24-h average (D24A). Our analysis found that the use of DM8A and D24A data, although less computationally intensive, reduced estimation error more when compared to the use of hourly data. This was primarily due to the poorer CTM model performance in the hourly average predicted ozone. Our second analysis compared spatial variability and estimation errors when BME relied on CTM predictions with a grid cell resolution of 12 × 12 km2 versus a coarser resolution of 36 × 36 km2. Our analysis found that integrating the finer grid resolution CTM predictions not only reduced estimation error, but also increased the spatial variability in daily ozone estimates by 5 times. This improvement was due to the improved spatial gradients and model performance found in the finer resolved CTM simulation. The integration of observational and model predictions that is permitted in a BME framework continues to be a powerful approach for improving exposure estimates of ambient air pollution. The results of this analysis demonstrate the importance of also understanding model performance variability and its implications on exposure error.

GEMSS: grid-infrastructure for medical service provision.

PubMed

Benkner, S; Berti, G; Engelbrecht, G; Fingberg, J; Kohring, G; Middleton, S E; Schmidt, R

2005-01-01

The European GEMSS Project is concerned with the creation of medical Grid service prototypes and their evaluation in a secure service-oriented infrastructure for distributed on demand/supercomputing. Key aspects of the GEMSS Grid middleware include negotiable QoS support for time-critical service provision, flexible support for business models, and security at all levels in order to ensure privacy of patient data as well as compliance to EU law. The GEMSS Grid infrastructure is based on a service-oriented architecture and is being built on top of existing standard Grid and Web technologies. The GEMSS infrastructure offers a generic Grid service provision framework that hides the complexity of transforming existing applications into Grid services. For the development of client-side applications or portals, a pluggable component framework has been developed, providing developers with full control over business processes, service discovery, QoS negotiation, and workflow, while keeping their underlying implementation hidden from view. A first version of the GEMSS Grid infrastructure is operational and has been used for the set-up of a Grid test-bed deploying six medical Grid service prototypes including maxillo-facial surgery simulation, neuro-surgery support, radio-surgery planning, inhaled drug-delivery simulation, cardiovascular simulation and advanced image reconstruction. The GEMSS Grid infrastructure is based on standard Web Services technology with an anticipated future transition path towards the OGSA standard proposed by the Global Grid Forum. GEMSS demonstrates that the Grid can be used to provide medical practitioners and researchers with access to advanced simulation and image processing services for improved preoperative planning and near real-time surgical support.

An open source software for fast grid-based data-mining in spatial epidemiology (FGBASE).

PubMed

Baker, David M; Valleron, Alain-Jacques

2014-10-30

Examining whether disease cases are clustered in space is an important part of epidemiological research. Another important part of spatial epidemiology is testing whether patients suffering from a disease are more, or less, exposed to environmental factors of interest than adequately defined controls. Both approaches involve determining the number of cases and controls (or population at risk) in specific zones. For cluster searches, this often must be done for millions of different zones. Doing this by calculating distances can lead to very lengthy computations. In this work we discuss the computational advantages of geographical grid-based methods, and introduce an open source software (FGBASE) which we have created for this purpose. Geographical grids based on the Lambert Azimuthal Equal Area projection are well suited for spatial epidemiology because they preserve area: each cell of the grid has the same area. We describe how data is projected onto such a grid, as well as grid-based algorithms for spatial epidemiological data-mining. The software program (FGBASE), that we have developed, implements these grid-based methods. The grid based algorithms perform extremely fast. This is particularly the case for cluster searches. When applied to a cohort of French Type 1 Diabetes (T1D) patients, as an example, the grid based algorithms detected potential clusters in a few seconds on a modern laptop. This compares very favorably to an equivalent cluster search using distance calculations instead of a grid, which took over 4 hours on the same computer. In the case study we discovered 4 potential clusters of T1D cases near the cities of Le Havre, Dunkerque, Toulouse and Nantes. One example of environmental analysis with our software was to study whether a significant association could be found between distance to vineyards with heavy pesticide. None was found. In both examples, the software facilitates the rapid testing of hypotheses. Grid-based algorithms for mining spatial epidemiological data provide advantages in terms of computational complexity thus improving the speed of computations. We believe that these methods and this software tool (FGBASE) will lower the computational barriers to entry for those performing epidemiological research.

FNCS: A Framework for Power System and Communication Networks Co-Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ciraci, Selim; Daily, Jeffrey A.; Fuller, Jason C.

2014-04-13

This paper describes the Fenix framework that uses a federated approach for integrating power grid and communication network simulators. Compared existing approaches, Fenix al- lows co-simulation of both transmission and distribution level power grid simulators with the communication network sim- ulator. To reduce the performance overhead of time synchro- nization, Fenix utilizes optimistic synchronization strategies that make speculative decisions about when the simulators are going to exchange messages. GridLAB-D (a distribution simulator), PowerFlow (a transmission simulator), and ns-3 (a telecommunication simulator) are integrated with the frame- work and are used to illustrate the enhanced performance pro- vided by speculative multi-threadingmore » on a smart grid applica- tion. Our speculative multi-threading approach achieved on average 20% improvement over the existing synchronization methods« less

Partitioning medical image databases for content-based queries on a Grid.

PubMed

Montagnat, J; Breton, V; E Magnin, I

2005-01-01

In this paper we study the impact of executing a medical image database query application on the grid. For lowering the total computation time, the image database is partitioned into subsets to be processed on different grid nodes. A theoretical model of the application complexity and estimates of the grid execution overhead are used to efficiently partition the database. We show results demonstrating that smart partitioning of the database can lead to significant improvements in terms of total computation time. Grids are promising for content-based image retrieval in medical databases.

Lambda Data Grid: Communications Architecture in Support of Grid Computing

DTIC Science & Technology

2006-12-21

number of paradigm shifts in the 20th century, including the growth of large geographically dispersed teams and the use of simulations and computational...get results. The work in this thesis automates the orchestration of networks with other resources, better utilizing all resources in a time efficient...domains, over transatlantic links in around minute. The main goal of this thesis is to build a new grid-computing paradigm that fully harnesses the

Grids: The Top Ten Questions

DOE PAGES

Schopf, Jennifer M.; Nitzberg, Bill

2002-01-01

The design and implementation of a national computing system and data grid has become a reachable goal from both the computer science and computational science point of view. A distributed infrastructure capable of sophisticated computational functions can bring many benefits to scientific work, but poses many challenges, both technical and socio-political. Technical challenges include having basic software tools, higher-level services, functioning and pervasive security, and standards, while socio-political issues include building a user community, adding incentives for sites to be part of a user-centric environment, and educating funding sources about the needs of this community. This paper details the areasmore » relating to Grid research that we feel still need to be addressed to fully leverage the advantages of the Grid.« less

Job Superscheduler Architecture and Performance in Computational Grid Environments

NASA Technical Reports Server (NTRS)

Shan, Hongzhang; Oliker, Leonid; Biswas, Rupak

2003-01-01

Computational grids hold great promise in utilizing geographically separated heterogeneous resources to solve large-scale complex scientific problems. However, a number of major technical hurdles, including distributed resource management and effective job scheduling, stand in the way of realizing these gains. In this paper, we propose a novel grid superscheduler architecture and three distributed job migration algorithms. We also model the critical interaction between the superscheduler and autonomous local schedulers. Extensive performance comparisons with ideal, central, and local schemes using real workloads from leading computational centers are conducted in a simulation environment. Additionally, synthetic workloads are used to perform a detailed sensitivity analysis of our superscheduler. Several key metrics demonstrate that substantial performance gains can be achieved via smart superscheduling in distributed computational grids.

A computing method for spatial accessibility based on grid partition

NASA Astrophysics Data System (ADS)

Ma, Linbing; Zhang, Xinchang

2007-06-01

An accessibility computing method and process based on grid partition was put forward in the paper. As two important factors impacting on traffic, density of road network and relative spatial resistance for difference land use was integrated into computing traffic cost in each grid. A* algorithms was inducted to searching optimum traffic cost of grids path, a detailed searching process and definition of heuristic evaluation function was described in the paper. Therefore, the method can be implemented more simply and its data source is obtained more easily. Moreover, by changing heuristic searching information, more reasonable computing result can be obtained. For confirming our research, a software package was developed with C# language under ArcEngine9 environment. Applying the computing method, a case study on accessibility of business districts in Guangzhou city was carried out.

GreenView and GreenLand Applications Development on SEE-GRID Infrastructure

NASA Astrophysics Data System (ADS)

Mihon, Danut; Bacu, Victor; Gorgan, Dorian; Mészáros, Róbert; Gelybó, Györgyi; Stefanut, Teodor

2010-05-01

The GreenView and GreenLand applications [1] have been developed through the SEE-GRID-SCI (SEE-GRID eInfrastructure for regional eScience) FP7 project co-funded by the European Commission [2]. The development of environment applications is a challenge for Grid technologies and software development methodologies. This presentation exemplifies the development of the GreenView and GreenLand applications over the SEE-GRID infrastructure by the Grid Application Development Methodology [3]. Today's environmental applications are used in vary domains of Earth Science such as meteorology, ground and atmospheric pollution, ground metal detection or weather prediction. These applications run on satellite images (e.g. Landsat, MERIS, MODIS, etc.) and the accuracy of output results depends mostly of the quality of these images. The main drawback of such environmental applications regards the need of computation power and storage power (some images are almost 1GB in size), in order to process such a large data volume. Actually, almost applications requiring high computation resources have approached the migration onto the Grid infrastructure. This infrastructure offers the computing power by running the atomic application components on different Grid nodes in sequential or parallel mode. The middleware used between the Grid infrastructure and client applications is ESIP (Environment Oriented Satellite Image Processing Platform), which is based on gProcess platform [4]. In its current format, gProcess is used for launching new processes on the Grid nodes, but also for monitoring the execution status of these processes. This presentation highlights two case studies of Grid based environmental applications, GreenView and GreenLand [5]. GreenView is used in correlation with MODIS (Moderate Resolution Imaging Spectroradiometer) satellite images and meteorological datasets, in order to produce pseudo colored temperature and vegetation maps for different geographical CEE (Central Eastern Europe) regions. On the other hand, GreenLand is used for generating maps for different vegetation indexes (e.g. NDVI, EVI, SAVI, GEMI) based on Landsat satellite images. Both applications are using interpolation and random value generation algorithms, but also specific formulas for computing vegetation index values. The GreenView and GreenLand applications have been experimented over the SEE-GRID infrastructure and the performance evaluation is reported in [6]. The improvement of the execution time (obtained through a better parallelization of jobs), the extension of geographical areas to other parts of the Earth, and new user interaction techniques on spatial data and large set of satellite images are the goals of the future work. References [1] GreenView application on Wiki, http://wiki.egee-see.org/index.php/GreenView [2] SEE-GRID-SCI Project, http://www.see-grid-sci.eu/ [3] Gorgan D., Stefanut T., Bâcu V., Mihon D., Grid based Environment Application Development Methodology, SCICOM, 7th International Conference on "Large-Scale Scientific Computations", 4-8 June, 2009, Sozopol, Bulgaria, (To be published by Springer), (2009). [4] Gorgan D., Bacu V., Stefanut T., Rodila D., Mihon D., Grid based Satellite Image Processing Platform for Earth Observation Applications Development. IDAACS'2009 - IEEE Fifth International Workshop on "Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications", 21-23 September, Cosenza, Italy, IEEE Published in Computer Press, 247-252 (2009). [5] Mihon D., Bacu V., Stefanut T., Gorgan D., "Grid Based Environment Application Development - GreenView Application". ICCP2009 - IEEE 5th International Conference on Intelligent Computer Communication and Processing, 27 Aug, 2009 Cluj-Napoca. Published by IEEE Computer Press, pp. 275-282 (2009). [6] Danut Mihon, Victor Bacu, Dorian Gorgan, Róbert Mészáros, Györgyi Gelybó, Teodor Stefanut, Practical Considerations on the GreenView Application Development and Execution over SEE-GRID. SEE-GRID-SCI User Forum, 9-10 Dec 2009, Bogazici University, Istanbul, Turkey, ISBN: 978-975-403-510-0, pp. 167-175 (2009).

Finite volume model for two-dimensional shallow environmental flow

USGS Publications Warehouse

Simoes, F.J.M.

2011-01-01

This paper presents the development of a two-dimensional, depth integrated, unsteady, free-surface model based on the shallow water equations. The development was motivated by the desire of balancing computational efficiency and accuracy by selective and conjunctive use of different numerical techniques. The base framework of the discrete model uses Godunov methods on unstructured triangular grids, but the solution technique emphasizes the use of a high-resolution Riemann solver where needed, switching to a simpler and computationally more efficient upwind finite volume technique in the smooth regions of the flow. Explicit time marching is accomplished with strong stability preserving Runge-Kutta methods, with additional acceleration techniques for steady-state computations. A simplified mass-preserving algorithm is used to deal with wet/dry fronts. Application of the model is made to several benchmark cases that show the interplay of the diverse solution techniques.

TADS: A CFD-based turbomachinery and analysis design system with GUI. Volume 2: User's manual

NASA Technical Reports Server (NTRS)

Myers, R. A.; Topp, D. A.; Delaney, R. A.

1995-01-01

The primary objective of this study was the development of a computational fluid dynamics (CFD) based turbomachinery airfoil analysis and design system, controlled by a graphical user interface (GUI). The computer codes resulting from this effort are referred to as the Turbomachinery Analysis and Design System (TADS). This document is intended to serve as a user's manual for the computer programs which comprise the TADS system. TADS couples a throughflow solver (ADPAC) with a quasi-3D blade-to-blade solver (RVCQ3D) in an interactive package. Throughflow analysis capability was developed in ADPAC through the addition of blade force and blockage terms to the governing equations. A GUI was developed to simplify user input and automate the many tasks required to perform turbomachinery analysis and design. The coupling of various programs was done in a way that alternative solvers or grid generators could be easily incorporated into the TADS framework.

Pervasive access to images and data--the use of computing grids and mobile/wireless devices across healthcare enterprises.

PubMed

Pohjonen, Hanna; Ross, Peeter; Blickman, Johan G; Kamman, Richard

2007-01-01

Emerging technologies are transforming the workflows in healthcare enterprises. Computing grids and handheld mobile/wireless devices are providing clinicians with enterprise-wide access to all patient data and analysis tools on a pervasive basis. In this paper, emerging technologies are presented that provide computing grids and streaming-based access to image and data management functions, and system architectures that enable pervasive computing on a cost-effective basis. Finally, the implications of such technologies are investigated regarding the positive impacts on clinical workflows.

AGIS: The ATLAS Grid Information System

NASA Astrophysics Data System (ADS)

Anisenkov, A.; Di Girolamo, A.; Klimentov, A.; Oleynik, D.; Petrosyan, A.; Atlas Collaboration

2014-06-01

ATLAS, a particle physics experiment at the Large Hadron Collider at CERN, produced petabytes of data annually through simulation production and tens of petabytes of data per year from the detector itself. The ATLAS computing model embraces the Grid paradigm and a high degree of decentralization and computing resources able to meet ATLAS requirements of petabytes scale data operations. In this paper we describe the ATLAS Grid Information System (AGIS), designed to integrate configuration and status information about resources, services and topology of the computing infrastructure used by the ATLAS Distributed Computing applications and services.

Domain Decomposition By the Advancing-Partition Method for Parallel Unstructured Grid Generation

NASA Technical Reports Server (NTRS)

Pirzadeh, Shahyar Z.; Zagaris, George

2009-01-01

A new method of domain decomposition has been developed for generating unstructured grids in subdomains either sequentially or using multiple computers in parallel. Domain decomposition is a crucial and challenging step for parallel grid generation. Prior methods are generally based on auxiliary, complex, and computationally intensive operations for defining partition interfaces and usually produce grids of lower quality than those generated in single domains. The new technique, referred to as "Advancing Partition," is based on the Advancing-Front method, which partitions a domain as part of the volume mesh generation in a consistent and "natural" way. The benefits of this approach are: 1) the process of domain decomposition is highly automated, 2) partitioning of domain does not compromise the quality of the generated grids, and 3) the computational overhead for domain decomposition is minimal. The new method has been implemented in NASA's unstructured grid generation code VGRID.

Three-dimensional computational fluid dynamics modeling of particle uptake by an occupational air sampler using manually-scaled and adaptive grids

PubMed Central

Landázuri, Andrea C.; Sáez, A. Eduardo; Anthony, T. Renée

2016-01-01

This work presents fluid flow and particle trajectory simulation studies to determine the aspiration efficiency of a horizontally oriented occupational air sampler using computational fluid dynamics (CFD). Grid adaption and manual scaling of the grids were applied to two sampler prototypes based on a 37-mm cassette. The standard k–ε model was used to simulate the turbulent air flow and a second order streamline-upwind discretization scheme was used to stabilize convective terms of the Navier–Stokes equations. Successively scaled grids for each configuration were created manually and by means of grid adaption using the velocity gradient in the main flow direction. Solutions were verified to assess iterative convergence, grid independence and monotonic convergence. Particle aspiration efficiencies determined for both prototype samplers were undistinguishable, indicating that the porous filter does not play a noticeable role in particle aspiration. Results conclude that grid adaption is a powerful tool that allows to refine specific regions that require lots of detail and therefore better resolve flow detail. It was verified that adaptive grids provided a higher number of locations with monotonic convergence than the manual grids and required the least computational effort. PMID:26949268

ATLAS user analysis on private cloud resources at GoeGrid

NASA Astrophysics Data System (ADS)

Glaser, F.; Nadal Serrano, J.; Grabowski, J.; Quadt, A.

2015-12-01

User analysis job demands can exceed available computing resources, especially before major conferences. ATLAS physics results can potentially be slowed down due to the lack of resources. For these reasons, cloud research and development activities are now included in the skeleton of the ATLAS computing model, which has been extended by using resources from commercial and private cloud providers to satisfy the demands. However, most of these activities are focused on Monte-Carlo production jobs, extending the resources at Tier-2. To evaluate the suitability of the cloud-computing model for user analysis jobs, we developed a framework to launch an ATLAS user analysis cluster in a cloud infrastructure on demand and evaluated two solutions. The first solution is entirely integrated in the Grid infrastructure by using the same mechanism, which is already in use at Tier-2: A designated Panda-Queue is monitored and additional worker nodes are launched in a cloud environment and assigned to a corresponding HTCondor queue according to the demand. Thereby, the use of cloud resources is completely transparent to the user. However, using this approach, submitted user analysis jobs can still suffer from a certain delay introduced by waiting time in the queue and the deployed infrastructure lacks customizability. Therefore, our second solution offers the possibility to easily deploy a totally private, customizable analysis cluster on private cloud resources belonging to the university.

Image Harvest: an open-source platform for high-throughput plant image processing and analysis

PubMed Central

Knecht, Avi C.; Campbell, Malachy T.; Caprez, Adam; Swanson, David R.; Walia, Harkamal

2016-01-01

High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. PMID:27141917

Rapid Airplane Parametric Input Design (RAPID)

NASA Technical Reports Server (NTRS)

Smith, Robert E.

1995-01-01

RAPID is a methodology and software system to define a class of airplane configurations and directly evaluate surface grids, volume grids, and grid sensitivity on and about the configurations. A distinguishing characteristic which separates RAPID from other airplane surface modellers is that the output grids and grid sensitivity are directly applicable in CFD analysis. A small set of design parameters and grid control parameters govern the process which is incorporated into interactive software for 'real time' visual analysis and into batch software for the application of optimization technology. The computed surface grids and volume grids are suitable for a wide range of Computational Fluid Dynamics (CFD) simulation. The general airplane configuration has wing, fuselage, horizontal tail, and vertical tail components. The double-delta wing and tail components are manifested by solving a fourth order partial differential equation (PDE) subject to Dirichlet and Neumann boundary conditions. The design parameters are incorporated into the boundary conditions and therefore govern the shapes of the surfaces. The PDE solution yields a smooth transition between boundaries. Surface grids suitable for CFD calculation are created by establishing an H-type topology about the configuration and incorporating grid spacing functions in the PDE equation for the lifting components and the fuselage definition equations. User specified grid parameters govern the location and degree of grid concentration. A two-block volume grid about a configuration is calculated using the Control Point Form (CPF) technique. The interactive software, which runs on Silicon Graphics IRIS workstations, allows design parameters to be continuously varied and the resulting surface grid to be observed in real time. The batch software computes both the surface and volume grids and also computes the sensitivity of the output grid with respect to the input design parameters by applying the precompiler tool ADIFOR to the grid generation program. The output of ADIFOR is a new source code containing the old code plus expressions for derivatives of specified dependent variables (grid coordinates) with respect to specified independent variables (design parameters). The RAPID methodology and software provide a means of rapidly defining numerical prototypes, grids, and grid sensitivity of a class of airplane configurations. This technology and software is highly useful for CFD research for preliminary design and optimization processes.

Quality Assurance Framework Implementation Guide for Isolated Community Power Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Esterly, Sean R.; Baring-Gould, Edward I.; Burman, Kari A.

This implementation guide is a companion document to the 'Quality Assurance Framework for Mini-Grids' technical report. This document is intended to be used by one of the many stakeholder groups that take part in the implementation of isolated power systems. Although the QAF could be applied to a single system, it was designed primarily to be used within the context of a larger national or regional rural electrification program in which many individual systems are being installed. This guide includes a detailed overview of the Quality Assurance Framework and provides guidance focused on the implementation of the Framework from themore » perspective of the different stakeholders that are commonly involved in expanding energy development within specific communities or regions. For the successful long-term implementation of a specific rural electrification program using mini-grid systems, six key stakeholders have been identified that are typically engaged, each with a different set of priorities 1. Regulatory agency 2. Governmental ministry 3. System developers 4. Mini-utility 5. Investors 6. Customers/consumers. This document is broken into two distinct sections. The first focuses on the administrative processes in the development and operation of community-based mini-grid programs, while the second focuses on the process around the installation of the mini-grid project itself.« less

DIRAC File Replica and Metadata Catalog

NASA Astrophysics Data System (ADS)

Tsaregorodtsev, A.; Poss, S.

2012-12-01

File replica and metadata catalogs are essential parts of any distributed data management system, which are largely determining its functionality and performance. A new File Catalog (DFC) was developed in the framework of the DIRAC Project that combines both replica and metadata catalog functionality. The DFC design is based on the practical experience with the data management system of the LHCb Collaboration. It is optimized for the most common patterns of the catalog usage in order to achieve maximum performance from the user perspective. The DFC supports bulk operations for replica queries and allows quick analysis of the storage usage globally and for each Storage Element separately. It supports flexible ACL rules with plug-ins for various policies that can be adopted by a particular community. The DFC catalog allows to store various types of metadata associated with files and directories and to perform efficient queries for the data based on complex metadata combinations. Definition of file ancestor-descendent relation chains is also possible. The DFC catalog is implemented in the general DIRAC distributed computing framework following the standard grid security architecture. In this paper we describe the design of the DFC and its implementation details. The performance measurements are compared with other grid file catalog implementations. The experience of the DFC Catalog usage in the CLIC detector project are discussed.

ED(MF)n: Humidity-Convection Feedbacks in a Mass Flux Scheme Based on Resolved Size Densities

NASA Astrophysics Data System (ADS)

Neggers, R.

2014-12-01

Cumulus cloud populations remain at least partially unresolved in present-day numerical simulations of global weather and climate, and accordingly their impact on the larger-scale flow has to be represented through parameterization. Various methods have been developed over the years, ranging in complexity from the early bulk models relying on a single plume to more recent approaches that attempt to reconstruct the underlying probability density functions, such as statistical schemes and multiple plume approaches. Most of these "classic" methods capture key aspects of cumulus cloud populations, and have been successfully implemented in operational weather and climate models. However, the ever finer discretizations of operational circulation models, driven by advances in the computational efficiency of supercomputers, is creating new problems for existing sub-grid schemes. Ideally, a sub-grid scheme should automatically adapt its impact on the resolved scales to the dimension of the grid-box within which it is supposed to act. It can be argued that this is only possible when i) the scheme is aware of the range of scales of the processes it represents, and ii) it can distinguish between contributions as a function of size. How to conceptually represent this knowledge of scale in existing parameterization schemes remains an open question that is actively researched. This study considers a relatively new class of models for sub-grid transport in which ideas from the field of population dynamics are merged with the concept of multi plume modelling. More precisely, a multiple mass flux framework for moist convective transport is formulated in which the ensemble of plumes is created in "size-space". It is argued that thus resolving the underlying size-densities creates opportunities for introducing scale-awareness and scale-adaptivity in the scheme. The behavior of an implementation of this framework in the Eddy Diffusivity Mass Flux (EDMF) model, named ED(MF)n, is examined for a standard case of subtropical marine shallow cumulus. We ask if a system of multiple independently resolved plumes is able to automatically create the vertical profile of bulk (mass) flux at which the sub-grid scale transport balances the imposed larger-scale forcings in the cloud layer.

A weakly-compressible Cartesian grid approach for hydrodynamic flows

NASA Astrophysics Data System (ADS)

Bigay, P.; Oger, G.; Guilcher, P.-M.; Le Touzé, D.

2017-11-01

The present article aims at proposing an original strategy to solve hydrodynamic flows. In introduction, the motivations for this strategy are developed. It aims at modeling viscous and turbulent flows including complex moving geometries, while avoiding meshing constraints. The proposed approach relies on a weakly-compressible formulation of the Navier-Stokes equations. Unlike most hydrodynamic CFD (Computational Fluid Dynamics) solvers usually based on implicit incompressible formulations, a fully-explicit temporal scheme is used. A purely Cartesian grid is adopted for numerical accuracy and algorithmic simplicity purposes. This characteristic allows an easy use of Adaptive Mesh Refinement (AMR) methods embedded within a massively parallel framework. Geometries are automatically immersed within the Cartesian grid with an AMR compatible treatment. The method proposed uses an Immersed Boundary Method (IBM) adapted to the weakly-compressible formalism and imposed smoothly through a regularization function, which stands as another originality of this work. All these features have been implemented within an in-house solver based on this WCCH (Weakly-Compressible Cartesian Hydrodynamic) method which meets the above requirements whilst allowing the use of high-order (> 3) spatial schemes rarely used in existing hydrodynamic solvers. The details of this WCCH method are presented and validated in this article.

Analysis of Complex Valve and Feed Systems

NASA Technical Reports Server (NTRS)

Ahuja, Vineet; Hosangadi, Ashvin; Shipman, Jeremy; Cavallo, Peter; Dash, Sanford

2007-01-01

A numerical framework for analysis of complex valve systems supports testing of propulsive systems by simulating key valve and control system components in the test loop. In particular, it is designed to enhance the analysis capability in terms of identifying system transients and quantifying the valve response to these transients. This system has analysis capability for simulating valve motion in complex systems operating in diverse flow regimes ranging from compressible gases to cryogenic liquids. A key feature is the hybrid, unstructured framework with sub-models for grid movement and phase change including cryogenic cavitations. The multi-element unstructured framework offers improved predictions of valve performance characteristics under steady conditions for structurally complex valves such as pressure regulator valve. Unsteady simulations of valve motion using this computational approach have been carried out for various valves in operation at Stennis Space Center such as the split-body valve and the 10-in. (approx.25.4-cm) LOX (liquid oxygen) valve and the 4-in. (approx.10 cm) Y-pattern valve (liquid nitrogen). Such simulations make use of variable grid topologies, thereby permitting solution accuracy and resolving important flow physics in the seat region of the moving valve. An advantage to this software includes possible reduction in testing costs incurred due to disruptions relating to unexpected flow transients or functioning of valve/flow control systems. Prediction of the flow anomalies leading to system vibrations, flow resonance, and valve stall can help in valve scheduling and significantly reduce the need for activation tests. This framework has been evaluated for its ability to predict performance metrics like flow coefficient for cavitating venturis and valve coefficient curves, and could be a valuable tool in predicting and understanding anomalous behavior of system components at rocket propulsion testing and design sites.

Failure Impact Analysis of Key Management in AMI Using Cybernomic Situational Assessment (CSA)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abercrombie, Robert K; Sheldon, Frederick T; Hauser, Katie R

2013-01-01

In earlier work, we presented a computational framework for quantifying the security of a system in terms of the average loss a stakeholder stands to sustain as a result of threats to the system. We named this system, the Cyberspace Security Econometrics System (CSES). In this paper, we refine the framework and apply it to cryptographic key management within the Advanced Metering Infrastructure (AMI) as an example. The stakeholders, requirements, components, and threats are determined. We then populate the matrices with justified values by addressing the AMI at a higher level, rather than trying to consider every piece of hardwaremore » and software involved. We accomplish this task by leveraging the recently established NISTR 7628 guideline for smart grid security. This allowed us to choose the stakeholders, requirements, components, and threats realistically. We reviewed the literature and selected an industry technical working group to select three representative threats from a collection of 29 threats. From this subset, we populate the stakes, dependency, and impact matrices, and the threat vector with realistic numbers. Each Stakeholder s Mean Failure Cost is then computed.« less

VieSLAF Framework: Enabling Adaptive and Versatile SLA-Management

NASA Astrophysics Data System (ADS)

Brandic, Ivona; Music, Dejan; Leitner, Philipp; Dustdar, Schahram

Novel computing paradigms like Grid and Cloud computing demand guarantees on non-functional requirements such as application execution time or price. Such requirements are usually negotiated following a specific Quality of Service (QoS) model and are expressed using Service Level Agreements (SLAs). Currently available QoS models assume either that service provider and consumer have matching SLA templates and common understanding of the negotiated terms or provide public templates, which can be downloaded and utilized by the end users. On the one hand, matching SLA templates represent an unrealistic assumption in systems where service consumer and provider meet dynamically and on demand. On the other hand, handling of public templates seems to be a rather challenging issue, especially if the templates do not reflect users’ needs. In this paper we present VieSLAF, a novel framework for the specification and management of SLA mappings. Using VieSLAF users may specify, manage, and apply SLA mapping bridging the gap between non-matching SLA templates. Moreover, based on the predefined learning functions and considering accumulated SLA mappings, domain specific public SLA templates can be derived reflecting users’ needs.

Block-structured grids for complex aerodynamic configurations: Current status

NASA Technical Reports Server (NTRS)

Vatsa, Veer N.; Sanetrik, Mark D.; Parlette, Edward B.

1995-01-01

The status of CFD methods based on the use of block-structured grids for analyzing viscous flows over complex configurations is examined. The objective of the present study is to make a realistic assessment of the usability of such grids for routine computations typically encountered in the aerospace industry. It is recognized at the very outset that the total turnaround time, from the moment the configuration is identified until the computational results have been obtained and postprocessed, is more important than just the computational time. Pertinent examples will be cited to demonstrate the feasibility of solving flow over practical configurations of current interest on block-structured grids.

Implicit schemes and parallel computing in unstructured grid CFD

NASA Technical Reports Server (NTRS)

Venkatakrishnam, V.

1995-01-01

The development of implicit schemes for obtaining steady state solutions to the Euler and Navier-Stokes equations on unstructured grids is outlined. Applications are presented that compare the convergence characteristics of various implicit methods. Next, the development of explicit and implicit schemes to compute unsteady flows on unstructured grids is discussed. Next, the issues involved in parallelizing finite volume schemes on unstructured meshes in an MIMD (multiple instruction/multiple data stream) fashion are outlined. Techniques for partitioning unstructured grids among processors and for extracting parallelism in explicit and implicit solvers are discussed. Finally, some dynamic load balancing ideas, which are useful in adaptive transient computations, are presented.

SAGE: The Self-Adaptive Grid Code. 3

NASA Technical Reports Server (NTRS)

Davies, Carol B.; Venkatapathy, Ethiraj

1999-01-01

The multi-dimensional self-adaptive grid code, SAGE, is an important tool in the field of computational fluid dynamics (CFD). It provides an efficient method to improve the accuracy of flow solutions while simultaneously reducing computer processing time. Briefly, SAGE enhances an initial computational grid by redistributing the mesh points into more appropriate locations. The movement of these points is driven by an equal-error-distribution algorithm that utilizes the relationship between high flow gradients and excessive solution errors. The method also provides a balance between clustering points in the high gradient regions and maintaining the smoothness and continuity of the adapted grid, The latest version, Version 3, includes the ability to change the boundaries of a given grid to more efficiently enclose flow structures and provides alternative redistribution algorithms.

PHOTOCHEMICAL SIMULATIONS OF POINT SOURCE EMISSIONS WITH THE MODELS-3 CMAQ PLUME-IN-GRID APPROACH

EPA Science Inventory

A plume-in-grid (PinG) approach has been designed to provide a realistic treatment for the simulation the dynamic and chemical processes impacting pollutant species in major point source plumes during a subgrid scale phase within an Eulerian grid modeling framework. The PinG sci...

Transformation of OODT CAS to Perform Larger Tasks

NASA Technical Reports Server (NTRS)

Mattmann, Chris; Freeborn, Dana; Crichton, Daniel; Hughes, John; Ramirez, Paul; Hardman, Sean; Woollard, David; Kelly, Sean

2008-01-01

A computer program denoted OODT CAS has been transformed to enable performance of larger tasks that involve greatly increased data volumes and increasingly intensive processing of data on heterogeneous, geographically dispersed computers. Prior to the transformation, OODT CAS (also alternatively denoted, simply, 'CAS') [wherein 'OODT' signifies 'Object-Oriented Data Technology' and 'CAS' signifies 'Catalog and Archive Service'] was a proven software component used to manage scientific data from spaceflight missions. In the transformation, CAS was split into two separate components representing its canonical capabilities: file management and workflow management. In addition, CAS was augmented by addition of a resource-management component. This third component enables CAS to manage heterogeneous computing by use of diverse resources, including high-performance clusters of computers, commodity computing hardware, and grid computing infrastructures. CAS is now more easily maintainable, evolvable, and reusable. These components can be used separately or, taking advantage of synergies, can be used together. Other elements of the transformation included addition of a separate Web presentation layer that supports distribution of data products via Really Simple Syndication (RSS) feeds, and provision for full Resource Description Framework (RDF) exports of metadata.

Adaptive mesh refinement and load balancing based on multi-level block-structured Cartesian mesh

NASA Astrophysics Data System (ADS)

Misaka, Takashi; Sasaki, Daisuke; Obayashi, Shigeru

2017-11-01

We developed a framework for a distributed-memory parallel computer that enables dynamic data management for adaptive mesh refinement and load balancing. We employed simple data structure of the building cube method (BCM) where a computational domain is divided into multi-level cubic domains and each cube has the same number of grid points inside, realising a multi-level block-structured Cartesian mesh. Solution adaptive mesh refinement, which works efficiently with the help of the dynamic load balancing, was implemented by dividing cubes based on mesh refinement criteria. The framework was investigated with the Laplace equation in terms of adaptive mesh refinement, load balancing and the parallel efficiency. It was then applied to the incompressible Navier-Stokes equations to simulate a turbulent flow around a sphere. We considered wall-adaptive cube refinement where a non-dimensional wall distance y+ near the sphere is used for a criterion of mesh refinement. The result showed the load imbalance due to y+ adaptive mesh refinement was corrected by the present approach. To utilise the BCM framework more effectively, we also tested a cube-wise algorithm switching where an explicit and implicit time integration schemes are switched depending on the local Courant-Friedrichs-Lewy (CFL) condition in each cube.

Custom Sky-Image Mosaics from NASA's Information Power Grid

NASA Technical Reports Server (NTRS)

Jacob, Joseph; Collier, James; Craymer, Loring; Curkendall, David

2005-01-01

yourSkyG is the second generation of the software described in yourSky: Custom Sky-Image Mosaics via the Internet (NPO-30556), NASA Tech Briefs, Vol. 27, No. 6 (June 2003), page 45. Like its predecessor, yourSkyG supplies custom astronomical image mosaics of sky regions specified by requesters using client computers connected to the Internet. Whereas yourSky constructs mosaics on a local multiprocessor system, yourSkyG performs the computations on NASA s Information Power Grid (IPG), which is capable of performing much larger mosaicking tasks. (The IPG is high-performance computation and data grid that integrates geographically distributed 18 NASA Tech Briefs, September 2005 computers, databases, and instruments.) A user of yourSkyG can specify parameters describing a mosaic to be constructed. yourSkyG then constructs the mosaic on the IPG and makes it available for downloading by the user. The complexities of determining which input images are required to construct a mosaic, retrieving the required input images from remote sky-survey archives, uploading the images to the computers on the IPG, performing the computations remotely on the Grid, and downloading the resulting mosaic from the Grid are all transparent to the user

Three-dimensional hydrogeologic framework model for use with a steady-state numerical ground-water flow model of the Death Valley regional flow system, Nevada and California

USGS Publications Warehouse

Belcher, Wayne R.; Faunt, Claudia C.; D'Agnese, Frank A.

2002-01-01

The U.S. Geological Survey, in cooperation with the Department of Energy and other Federal, State, and local agencies, is evaluating the hydrogeologic characteristics of the Death Valley regional ground-water flow system. The ground-water flow system covers an area of about 100,000 square kilometers from latitude 35? to 38?15' North to longitude 115? to 118? West, with the flow system proper comprising about 45,000 square kilometers. The Death Valley regional ground-water flow system is one of the larger flow systems within the Southwestern United States and includes in its boundaries the Nevada Test Site, Yucca Mountain, and much of Death Valley. Part of this study includes the construction of a three-dimensional hydrogeologic framework model to serve as the foundation for the development of a steady-state regional ground-water flow model. The digital framework model provides a computer-based description of the geometry and composition of the hydrogeologic units that control regional flow. The framework model of the region was constructed by merging two previous framework models constructed for the Yucca Mountain Project and the Environmental Restoration Program Underground Test Area studies at the Nevada Test Site. The hydrologic characteristics of the region result from a currently arid climate and complex geology. Interbasinal regional ground-water flow occurs through a thick carbonate-rock sequence of Paleozoic age, a locally thick volcanic-rock sequence of Tertiary age, and basin-fill alluvium of Tertiary and Quaternary age. Throughout the system, deep and shallow ground-water flow may be controlled by extensive and pervasive regional and local faults and fractures. The framework model was constructed using data from several sources to define the geometry of the regional hydrogeologic units. These data sources include (1) a 1:250,000-scale hydrogeologic-map compilation of the region; (2) regional-scale geologic cross sections; (3) borehole information, and (4) gridded surfaces from a previous three-dimensional geologic model. In addition, digital elevation model data were used in conjunction with these data to define ground-surface altitudes. These data, properly oriented in three dimensions by using geographic information systems, were combined and gridded to produce the upper surfaces of the hydrogeologic units used in the flow model. The final geometry of the framework model is constructed as a volumetric model by incorporating the intersections of these gridded surfaces and by applying fault truncation rules to structural features from the geologic map and cross sections. The cells defining the geometry of the hydrogeologic framework model can be assigned several attributes such as lithology, hydrogeologic unit, thickness, and top and bottom altitudes.

The data storage grid: the next generation of fault-tolerant storage for backup and disaster recovery of clinical images

NASA Astrophysics Data System (ADS)

King, Nelson E.; Liu, Brent; Zhou, Zheng; Documet, Jorge; Huang, H. K.

2005-04-01

Grid Computing represents the latest and most exciting technology to evolve from the familiar realm of parallel, peer-to-peer and client-server models that can address the problem of fault-tolerant storage for backup and recovery of clinical images. We have researched and developed a novel Data Grid testbed involving several federated PAC systems based on grid architecture. By integrating a grid computing architecture to the DICOM environment, a failed PACS archive can recover its image data from others in the federation in a timely and seamless fashion. The design reflects the five-layer architecture of grid computing: Fabric, Resource, Connectivity, Collective, and Application Layers. The testbed Data Grid architecture representing three federated PAC systems, the Fault-Tolerant PACS archive server at the Image Processing and Informatics Laboratory, Marina del Rey, the clinical PACS at Saint John's Health Center, Santa Monica, and the clinical PACS at the Healthcare Consultation Center II, USC Health Science Campus, will be presented. The successful demonstration of the Data Grid in the testbed will provide an understanding of the Data Grid concept in clinical image data backup as well as establishment of benchmarks for performance from future grid technology improvements and serve as a road map for expanded research into large enterprise and federation level data grids to guarantee 99.999 % up time.

Efficient modeling of laser-plasma accelerator staging experiments using INF&RNO

NASA Astrophysics Data System (ADS)

Benedetti, C.; Schroeder, C. B.; Geddes, C. G. R.; Esarey, E.; Leemans, W. P.

2017-03-01

The computational framework INF&RNO (INtegrated Fluid & paRticle simulatioN cOde) allows for fast and accurate modeling, in 2D cylindrical geometry, of several aspects of laser-plasma accelerator physics. In this paper, we present some of the new features of the code, including the quasistatic Particle-In-Cell (PIC)/fluid modality, and describe using different computational grids and time steps for the laser envelope and the plasma wake. These and other features allow for a speedup of several orders of magnitude compared to standard full 3D PIC simulations while still retaining physical fidelity. INF&RNO is used to support the experimental activity at the BELLA Center, and we will present an example of the application of the code to the laser-plasma accelerator staging experiment.

Integration of Geographical Information Systems and Geophysical Applications with Distributed Computing Technologies.

NASA Astrophysics Data System (ADS)

Pierce, M. E.; Aktas, M. S.; Aydin, G.; Fox, G. C.; Gadgil, H.; Sayar, A.

2005-12-01

We examine the application of Web Service Architectures and Grid-based distributed computing technologies to geophysics and geo-informatics. We are particularly interested in the integration of Geographical Information System (GIS) services with distributed data mining applications. GIS services provide the general purpose framework for building archival data services, real time streaming data services, and map-based visualization services that may be integrated with data mining and other applications through the use of distributed messaging systems and Web Service orchestration tools. Building upon on our previous work in these areas, we present our current research efforts. These include fundamental investigations into increasing XML-based Web service performance, supporting real time data streams, and integrating GIS mapping tools with audio/video collaboration systems for shared display and annotation.

Extension of local front reconstruction method with controlled coalescence model

NASA Astrophysics Data System (ADS)

Rajkotwala, A. H.; Mirsandi, H.; Peters, E. A. J. F.; Baltussen, M. W.; van der Geld, C. W. M.; Kuerten, J. G. M.; Kuipers, J. A. M.

2018-02-01

The physics of droplet collisions involves a wide range of length scales. This poses a challenge to accurately simulate such flows with standard fixed grid methods due to their inability to resolve all relevant scales with an affordable number of computational grid cells. A solution is to couple a fixed grid method with subgrid models that account for microscale effects. In this paper, we improved and extended the Local Front Reconstruction Method (LFRM) with a film drainage model of Zang and Law [Phys. Fluids 23, 042102 (2011)]. The new framework is first validated by (near) head-on collision of two equal tetradecane droplets using experimental film drainage times. When the experimental film drainage times are used, the LFRM method is better in predicting the droplet collisions, especially at high velocity in comparison with other fixed grid methods (i.e., the front tracking method and the coupled level set and volume of fluid method). When the film drainage model is invoked, the method shows a good qualitative match with experiments, but a quantitative correspondence of the predicted film drainage time with the experimental drainage time is not obtained indicating that further development of film drainage model is required. However, it can be safely concluded that the LFRM coupled with film drainage models is much better in predicting the collision dynamics than the traditional methods.

Interactive algebraic grid-generation technique

NASA Technical Reports Server (NTRS)

Smith, R. E.; Wiese, M. R.

1986-01-01

An algebraic grid generation technique and use of an associated interactive computer program are described. The technique, called the two boundary technique, is based on Hermite cubic interpolation between two fixed, nonintersecting boundaries. The boundaries are referred to as the bottom and top, and they are defined by two ordered sets of points. Left and right side boundaries which intersect the bottom and top boundaries may also be specified by two ordered sets of points. when side boundaries are specified, linear blending functions are used to conform interior interpolation to the side boundaries. Spacing between physical grid coordinates is determined as a function of boundary data and uniformly space computational coordinates. Control functions relating computational coordinates to parametric intermediate variables that affect the distance between grid points are embedded in the interpolation formulas. A versatile control function technique with smooth-cubic-spline functions is presented. The technique works best in an interactive graphics environment where computational displays and user responses are quickly exchanged. An interactive computer program based on the technique and called TBGG (two boundary grid generation) is also described.

Computation of Asteroid Proper Elements on the Grid

NASA Astrophysics Data System (ADS)

Novakovic, B.; Balaz, A.; Knezevic, Z.; Potocnik, M.

2009-12-01

A procedure of gridification of the computation of asteroid proper orbital elements is described. The need to speed up the time consuming computations and make them more efficient is justified by the large increase of observational data expected from the next generation all sky surveys. We give the basic notion of proper elements and of the contemporary theories and methods used to compute them for different populations of objects. Proper elements for nearly 70,000 asteroids are derived since the beginning of use of the Grid infrastructure for the purpose. The average time for the catalogs update is significantly shortened with respect to the time needed with stand-alone workstations. We also present basics of the Grid computing, the concepts of Grid middleware and its Workload management system. The practical steps we undertook to efficiently gridify our application are described in full detail. We present the results of a comprehensive testing of the performance of different Grid sites, and offer some practical conclusions based on the benchmark results and on our experience. Finally, we propose some possibilities for the future work.

GLIDE: a grid-based light-weight infrastructure for data-intensive environments

NASA Technical Reports Server (NTRS)

Mattmann, Chris A.; Malek, Sam; Beckman, Nels; Mikic-Rakic, Marija; Medvidovic, Nenad; Chrichton, Daniel J.

2005-01-01

The promise of the grid is that it will enable public access and sharing of immense amounts of computational and data resources among dynamic coalitions of individuals and institutions. However, the current grid solutions make several limiting assumptions that curtail their widespread adoption. To address these limitations, we present GLIDE, a prototype light-weight, data-intensive middleware infrastructure that enables access to the robust data and computational power of the grid on DREAM platforms.

Tight Bounds for Minimax Grid Matching, with Applications to the Average Case Analysis of Algorithms.

DTIC Science & Technology

1986-05-01

AD-ft?l 552 TIGHT BOUNDS FOR NININAX GRID MATCHING WITH i APPLICATIONS TO THE AVERAGE C.. (U) MASSACHUSETTS INST OF TECH CAMBRIDGE LAS FOR COMPUTER...MASSACHUSETTS LABORATORYFORNSTITUTE OF COMPUTER SCIENCE TECHNOLOGY MIT/LCS/TM-298 TIGHT BOUNDS FOR MINIMAX GRID MATCHING, WITH APPLICATIONS TO THE AVERAGE...PERIOD COVERED Tight bounds for minimax grid matching, Interim research with applications to the average case May 1986 analysis of algorithms. 6

Schwarz-Christoffel Conformal Mapping based Grid Generation for Global Oceanic Circulation Models

NASA Astrophysics Data System (ADS)

Xu, Shiming

2015-04-01

We propose new grid generation algorithms for global ocean general circulation models (OGCMs). Contrary to conventional, analytical forms based dipolar or tripolar grids, the new algorithm are based on Schwarz-Christoffel (SC) conformal mapping with prescribed boundary information. While dealing with the conventional grid design problem of pole relocation, it also addresses more advanced issues of computational efficiency and the new requirements on OGCM grids arisen from the recent trend of high-resolution and multi-scale modeling. The proposed grid generation algorithm could potentially achieve the alignment of grid lines to coastlines, enhanced spatial resolution in coastal regions, and easier computational load balance. Since the generated grids are still orthogonal curvilinear, they can be readily 10 utilized in existing Bryan-Cox-Semtner type ocean models. The proposed methodology can also be applied to the grid generation task for regional ocean modeling when complex land-ocean distribution is present.

TBGG- INTERACTIVE ALGEBRAIC GRID GENERATION

NASA Technical Reports Server (NTRS)

Smith, R. E.

1994-01-01

TBGG, Two-Boundary Grid Generation, applies an interactive algebraic grid generation technique in two dimensions. The program incorporates mathematical equations that relate the computational domain to the physical domain. TBGG has application to a variety of problems using finite difference techniques, such as computational fluid dynamics. Examples include the creation of a C-type grid about an airfoil and a nozzle configuration in which no left or right boundaries are specified. The underlying two-boundary technique of grid generation is based on Hermite cubic interpolation between two fixed, nonintersecting boundaries. The boundaries are defined by two ordered sets of points, referred to as the top and bottom. Left and right side boundaries may also be specified, and call upon linear blending functions to conform interior interpolation to the side boundaries. Spacing between physical grid coordinates is determined as a function of boundary data and uniformly spaced computational coordinates. Control functions relating computational coordinates to parametric intermediate variables that affect the distance between grid points are embedded in the interpolation formulas. A versatile control function technique with smooth cubic spline functions is also presented. The TBGG program is written in FORTRAN 77. It works best in an interactive graphics environment where computational displays and user responses are quickly exchanged. The program has been implemented on a CDC Cyber 170 series computer using NOS 2.4 operating system, with a central memory requirement of 151,700 (octal) 60 bit words. TBGG requires a Tektronix 4015 terminal and the DI-3000 Graphics Library of Precision Visuals, Inc. TBGG was developed in 1986.

Grid enablement of OpenGeospatial Web Services: the G-OWS Working Group

NASA Astrophysics Data System (ADS)

Mazzetti, Paolo

2010-05-01

In last decades two main paradigms for resource sharing emerged and reached maturity: the Web and the Grid. They both demonstrate suitable for building Distributed Computing Infrastructures (DCIs) supporting the coordinated sharing of resources (i.e. data, information, services, etc) on the Internet. Grid and Web DCIs have much in common as a result of their underlying Internet technology (protocols, models and specifications). However, being based on different requirements and architectural approaches, they show some differences as well. The Web's "major goal was to be a shared information space through which people and machines could communicate" [Berners-Lee 1996]. The success of the Web, and its consequent pervasiveness, made it appealing for building specialized systems like the Spatial Data Infrastructures (SDIs). In this systems the introduction of Web-based geo-information technologies enables specialized services for geospatial data sharing and processing. The Grid was born to achieve "flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions, and resources" [Foster 2001]. It specifically focuses on large-scale resource sharing, innovative applications, and, in some cases, high-performance orientation. In the Earth and Space Sciences (ESS) the most part of handled information is geo-referred (geo-information) since spatial and temporal meta-information is of primary importance in many application domains: Earth Sciences, Disasters Management, Environmental Sciences, etc. On the other hand, in several application areas there is the need of running complex models which require the large processing and storage capabilities that the Grids are able to provide. Therefore the integration of geo-information and Grid technologies might be a valuable approach in order to enable advanced ESS applications. Currently both geo-information and Grid technologies have reached a high level of maturity, allowing to build such an integration on existing solutions. More specifically, the Open Geospatial Consortium (OGC) Web Services (OWS) specifications play a fundamental role in geospatial information sharing (e.g. in INSPIRE Implementing Rules, GEOSS architecture, GMES Services, etc.). On the Grid side, the gLite middleware, developed in the European EGEE (Enabling Grids for E-sciencE) Projects, is widely spread in Europe and beyond, proving its high scalability and it is one of the middleware chosen for the future European Grid Infrastructure (EGI) initiative. Therefore the convergence between OWS and gLite technologies would be desirable for a seamless access to the Grid capabilities through OWS-compliant systems. Anyway, to achieve this harmonization there are some obstacles to overcome. Firstly, a semantics mismatch must be addressed: gLite handle low-level (e.g. close to the machine) concepts like "file", "data", "instruments", "job", etc., while geo-information services handle higher-level (closer to the human) concepts like "coverage", "observation", "measurement", "model", etc. Secondly, an architectural mismatch must be addressed: OWS implements a Web Service-Oriented-Architecture which is stateless, synchronous and with no embedded security (which is demanded to other specs), while gLite implements the Grid paradigm in an architecture which is stateful, asynchronous (even not fully event-based) and with strong embedded security (based on the VO paradigm). In recent years many initiatives and projects have worked out possible approaches for implementing Grid-enabled OWSs. Just to mention some: (i) in 2007 the OGC has signed a Memorandum of Understanding with the Open Grid Forum, "a community of users, developers, and vendors leading the global standardization effort for grid computing."; (ii) the OGC identified "WPS Profiles - Conflation; and Grid processing" as one of the tasks in the Geo Processing Workflow theme of the OWS Phase 6 (OWS-6); (iii) several national, European and international projects investigated different aspects of this integration, developing demonstrators and Proof-of-Concepts; In this context, "gLite enablement of OpenGeospatial Web Services" (G-OWS) is an initiative started in 2008 by the European CYCLOPS, GENESI-DR, and DORII Projects Consortia in order to collect/coordinate experiences on the enablement of OWS on top of the gLite middleware [GOWS]. Currently G-OWS counts ten member organizations from Europe and beyond, and four European Projects involved. It broadened its scope to the development of Spatial Data and Information Infrastructures (SDI and SII) based on the Grid/Cloud capacity in order to enable Earth Science applications and tools. Its operational objectives are the following: i) to contribute to the OGC-OGF initiative; ii) to release a reference implementation as standard gLite APIs (under the gLite software license); iii) to release a reference model (including procedures and guidelines) for OWS Grid-ification, as far as gLite is concerned; iv) to foster and promote the formation of consortiums for participation to projects/initiatives aimed at building Grid-enabled SDIs To achieve this objectives G-OWS bases its activities on two main guiding principles: a) the adoption of a service-oriented architecture based on the information modelling approach, and b) standardization as a means of achieving interoperability (i.e. adoption of standards from ISO TC211, OGC OWS, OGF). In the first year of activity G-OWS has designed a general architectural framework stemming from the FP6 CYCLOPS studies and enriched by the outcomes of other projects and initiatives involved (i.e. FP7 GENESI-DR, FP7 DORII, AIST GeoGrid, etc.). Some proof-of-concepts have been developed to demonstrate the flexibility and scalability of such architectural framework. The G-OWS WG developed implementations of gLite-enabled Web Coverage Service (WCS) and Web Processing Service (WPS), and an implementation of a Shibboleth authentication for gLite-enabled OWS in order to evaluate the possible integration of Web and Grid security models. The presentation will aim to communicate the G-OWS organization, activities, future plans and means to involve the ESSI community. References [Berners-Lee 1996] T. Berners-Lee, "WWW: Past, present, and future". IEEE Computer, 29(10), Oct. 1996, pp. 69-77. [Foster 2001] I. Foster, C. Kesselman and S. Tuecke, "The Anatomy of the Grid. The International Journal ofHigh Performance Computing Applications", 15(3):200-222, Fall 2001 [GOWS] G-OWS WG, https://www.g-ows.org/, accessed: 15 January 2010

Improving the analysis, storage and sharing of neuroimaging data using relational databases and distributed computing.

PubMed

Hasson, Uri; Skipper, Jeremy I; Wilde, Michael J; Nusbaum, Howard C; Small, Steven L

2008-01-15

The increasingly complex research questions addressed by neuroimaging research impose substantial demands on computational infrastructures. These infrastructures need to support management of massive amounts of data in a way that affords rapid and precise data analysis, to allow collaborative research, and to achieve these aims securely and with minimum management overhead. Here we present an approach that overcomes many current limitations in data analysis and data sharing. This approach is based on open source database management systems that support complex data queries as an integral part of data analysis, flexible data sharing, and parallel and distributed data processing using cluster computing and Grid computing resources. We assess the strengths of these approaches as compared to current frameworks based on storage of binary or text files. We then describe in detail the implementation of such a system and provide a concrete description of how it was used to enable a complex analysis of fMRI time series data.

Agents in bioinformatics, computational and systems biology.

PubMed

Merelli, Emanuela; Armano, Giuliano; Cannata, Nicola; Corradini, Flavio; d'Inverno, Mark; Doms, Andreas; Lord, Phillip; Martin, Andrew; Milanesi, Luciano; Möller, Steffen; Schroeder, Michael; Luck, Michael

2007-01-01

The adoption of agent technologies and multi-agent systems constitutes an emerging area in bioinformatics. In this article, we report on the activity of the Working Group on Agents in Bioinformatics (BIOAGENTS) founded during the first AgentLink III Technical Forum meeting on the 2nd of July, 2004, in Rome. The meeting provided an opportunity for seeding collaborations between the agent and bioinformatics communities to develop a different (agent-based) approach of computational frameworks both for data analysis and management in bioinformatics and for systems modelling and simulation in computational and systems biology. The collaborations gave rise to applications and integrated tools that we summarize and discuss in context of the state of the art in this area. We investigate on future challenges and argue that the field should still be explored from many perspectives ranging from bio-conceptual languages for agent-based simulation, to the definition of bio-ontology-based declarative languages to be used by information agents, and to the adoption of agents for computational grids.

Improving the Analysis, Storage and Sharing of Neuroimaging Data using Relational Databases and Distributed Computing

PubMed Central

Hasson, Uri; Skipper, Jeremy I.; Wilde, Michael J.; Nusbaum, Howard C.; Small, Steven L.

2007-01-01

The increasingly complex research questions addressed by neuroimaging research impose substantial demands on computational infrastructures. These infrastructures need to support management of massive amounts of data in a way that affords rapid and precise data analysis, to allow collaborative research, and to achieve these aims securely and with minimum management overhead. Here we present an approach that overcomes many current limitations in data analysis and data sharing. This approach is based on open source database management systems that support complex data queries as an integral part of data analysis, flexible data sharing, and parallel and distributed data processing using cluster computing and Grid computing resources. We assess the strengths of these approaches as compared to current frameworks based on storage of binary or text files. We then describe in detail the implementation of such a system and provide a concrete description of how it was used to enable a complex analysis of fMRI time series data. PMID:17964812

Modelling noise propagation using Grid Resources. Progress within GDI-Grid

NASA Astrophysics Data System (ADS)

Kiehle, Christian; Mayer, Christian; Padberg, Alexander; Stapelfeld, Hartmut

2010-05-01

Modelling noise propagation using Grid Resources. Progress within GDI-Grid. GDI-Grid (english: SDI-Grid) is a research project funded by the German Ministry for Science and Education (BMBF). It aims at bridging the gaps between OGC Web Services (OWS) and Grid infrastructures and identifying the potential of utilizing the superior storage capacities and computational power of grid infrastructures for geospatial applications while keeping the well-known service interfaces specified by the OGC. The project considers all major OGC webservice interfaces for Web Mapping (WMS), Feature access (Web Feature Service), Coverage access (Web Coverage Service) and processing (Web Processing Service). The major challenge within GDI-Grid is the harmonization of diverging standards as defined by standardization bodies for Grid computing and spatial information exchange. The project started in 2007 and will continue until June 2010. The concept for the gridification of OWS developed by lat/lon GmbH and the Department of Geography of the University of Bonn is applied to three real-world scenarios in order to check its practicability: a flood simulation, a scenario for emergency routing and a noise propagation simulation. The latter scenario is addressed by the Stapelfeldt Ingenieurgesellschaft mbH located in Dortmund adapting their LimA software to utilize grid resources. Noise mapping of e.g. traffic noise in urban agglomerates and along major trunk roads is a reoccurring demand of the EU Noise Directive. Input data requires road net and traffic, terrain, buildings and noise protection screens as well as population distribution. Noise impact levels are generally calculated in 10 m grid and along relevant building facades. For each receiver position sources within a typical range of 2000 m are split down into small segments, depending on local geometry. For each of the segments propagation analysis includes diffraction effects caused by all obstacles on the path of sound propagation. This immense intensive calculation needs to be performed for a major part of European landscape. A LINUX version of the commercial LimA software for noise mapping analysis has been implemented on a test cluster within the German D-GRID computer network. Results and performance indicators will be presented. The presentation is an extension to last-years presentation "Spatial Data Infrastructures and Grid Computing: the GDI-Grid project" that described the gridification concept developed in the GDI-Grid project and provided an overview of the conceptual gaps between Grid Computing and Spatial Data Infrastructures. Results from the GDI-Grid project are incorporated in the OGC-OGF (Open Grid Forum) collaboration efforts as well as the OGC WPS 2.0 standards working group developing the next major version of the WPS specification.

omniClassifier: a Desktop Grid Computing System for Big Data Prediction Modeling

PubMed Central

Phan, John H.; Kothari, Sonal; Wang, May D.

2016-01-01

Robust prediction models are important for numerous science, engineering, and biomedical applications. However, best-practice procedures for optimizing prediction models can be computationally complex, especially when choosing models from among hundreds or thousands of parameter choices. Computational complexity has further increased with the growth of data in these fields, concurrent with the era of “Big Data”. Grid computing is a potential solution to the computational challenges of Big Data. Desktop grid computing, which uses idle CPU cycles of commodity desktop machines, coupled with commercial cloud computing resources can enable research labs to gain easier and more cost effective access to vast computing resources. We have developed omniClassifier, a multi-purpose prediction modeling application that provides researchers with a tool for conducting machine learning research within the guidelines of recommended best-practices. omniClassifier is implemented as a desktop grid computing system using the Berkeley Open Infrastructure for Network Computing (BOINC) middleware. In addition to describing implementation details, we use various gene expression datasets to demonstrate the potential scalability of omniClassifier for efficient and robust Big Data prediction modeling. A prototype of omniClassifier can be accessed at http://omniclassifier.bme.gatech.edu/. PMID:27532062

Cloud Bursting with GlideinWMS: Means to satisfy ever increasing computing needs for Scientific Workflows

NASA Astrophysics Data System (ADS)

Mhashilkar, Parag; Tiradani, Anthony; Holzman, Burt; Larson, Krista; Sfiligoi, Igor; Rynge, Mats

2014-06-01

Scientific communities have been in the forefront of adopting new technologies and methodologies in the computing. Scientific computing has influenced how science is done today, achieving breakthroughs that were impossible to achieve several decades ago. For the past decade several such communities in the Open Science Grid (OSG) and the European Grid Infrastructure (EGI) have been using GlideinWMS to run complex application workflows to effectively share computational resources over the grid. GlideinWMS is a pilot-based workload management system (WMS) that creates on demand, a dynamically sized overlay HTCondor batch system on grid resources. At present, the computational resources shared over the grid are just adequate to sustain the computing needs. We envision that the complexity of the science driven by "Big Data" will further push the need for computational resources. To fulfill their increasing demands and/or to run specialized workflows, some of the big communities like CMS are investigating the use of cloud computing as Infrastructure-As-A-Service (IAAS) with GlideinWMS as a potential alternative to fill the void. Similarly, communities with no previous access to computing resources can use GlideinWMS to setup up a batch system on the cloud infrastructure. To enable this, the architecture of GlideinWMS has been extended to enable support for interfacing GlideinWMS with different Scientific and commercial cloud providers like HLT, FutureGrid, FermiCloud and Amazon EC2. In this paper, we describe a solution for cloud bursting with GlideinWMS. The paper describes the approach, architectural changes and lessons learned while enabling support for cloud infrastructures in GlideinWMS.

Cloud Bursting with GlideinWMS: Means to satisfy ever increasing computing needs for Scientific Workflows

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mhashilkar, Parag; Tiradani, Anthony; Holzman, Burt

Scientific communities have been in the forefront of adopting new technologies and methodologies in the computing. Scientific computing has influenced how science is done today, achieving breakthroughs that were impossible to achieve several decades ago. For the past decade several such communities in the Open Science Grid (OSG) and the European Grid Infrastructure (EGI) have been using GlideinWMS to run complex application workflows to effectively share computational resources over the grid. GlideinWMS is a pilot-based workload management system (WMS) that creates on demand, a dynamically sized overlay HTCondor batch system on grid resources. At present, the computational resources shared overmore » the grid are just adequate to sustain the computing needs. We envision that the complexity of the science driven by 'Big Data' will further push the need for computational resources. To fulfill their increasing demands and/or to run specialized workflows, some of the big communities like CMS are investigating the use of cloud computing as Infrastructure-As-A-Service (IAAS) with GlideinWMS as a potential alternative to fill the void. Similarly, communities with no previous access to computing resources can use GlideinWMS to setup up a batch system on the cloud infrastructure. To enable this, the architecture of GlideinWMS has been extended to enable support for interfacing GlideinWMS with different Scientific and commercial cloud providers like HLT, FutureGrid, FermiCloud and Amazon EC2. In this paper, we describe a solution for cloud bursting with GlideinWMS. The paper describes the approach, architectural changes and lessons learned while enabling support for cloud infrastructures in GlideinWMS.« less

Aspects of Unstructured Grids and Finite-Volume Solvers for the Euler and Navier-Stokes Equations

NASA Technical Reports Server (NTRS)

Barth, Timothy J.

1992-01-01

One of the major achievements in engineering science has been the development of computer algorithms for solving nonlinear differential equations such as the Navier-Stokes equations. In the past, limited computer resources have motivated the development of efficient numerical schemes in computational fluid dynamics (CFD) utilizing structured meshes. The use of structured meshes greatly simplifies the implementation of CFD algorithms on conventional computers. Unstructured grids on the other hand offer an alternative to modeling complex geometries. Unstructured meshes have irregular connectivity and usually contain combinations of triangles, quadrilaterals, tetrahedra, and hexahedra. The generation and use of unstructured grids poses new challenges in CFD. The purpose of this note is to present recent developments in the unstructured grid generation and flow solution technology.

Long Range Debye-Hückel Correction for Computation of Grid-based Electrostatic Forces Between Biomacromolecules

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mereghetti, Paolo; Martinez, M.; Wade, Rebecca C.

Brownian dynamics (BD) simulations can be used to study very large molecular systems, such as models of the intracellular environment, using atomic-detail structures. Such simulations require strategies to contain the computational costs, especially for the computation of interaction forces and energies. A common approach is to compute interaction forces between macromolecules by precomputing their interaction potentials on three-dimensional discretized grids. For long-range interactions, such as electrostatics, grid-based methods are subject to finite size errors. We describe here the implementation of a Debye-Hückel correction to the grid-based electrostatic potential used in the SDA BD simulation software that was applied to simulatemore » solutions of bovine serum albumin and of hen egg white lysozyme.« less

Parallel grid generation algorithm for distributed memory computers

NASA Technical Reports Server (NTRS)

Moitra, Stuti; Moitra, Anutosh

1994-01-01

A parallel grid-generation algorithm and its implementation on the Intel iPSC/860 computer are described. The grid-generation scheme is based on an algebraic formulation of homotopic relations. Methods for utilizing the inherent parallelism of the grid-generation scheme are described, and implementation of multiple levELs of parallelism on multiple instruction multiple data machines are indicated. The algorithm is capable of providing near orthogonality and spacing control at solid boundaries while requiring minimal interprocessor communications. Results obtained on the Intel hypercube for a blended wing-body configuration are used to demonstrate the effectiveness of the algorithm. Fortran implementations bAsed on the native programming model of the iPSC/860 computer and the Express system of software tools are reported. Computational gains in execution time speed-up ratios are given.

Two-Dimensional Grids About Airfoils and Other Shapes

NASA Technical Reports Server (NTRS)

Sorenson, R.

1982-01-01

GRAPE computer program generates two-dimensional finite-difference grids about airfoils and other shapes by use of Poisson differential equation. GRAPE can be used with any boundary shape, even one specified by tabulated points and including limited number of sharp corners. Numerically stable and computationally fast, GRAPE provides aerodynamic analyst with efficient and consistant means of grid generation.

Numerical simulation of three dimensional transonic flows

NASA Technical Reports Server (NTRS)

Sahu, Jubaraj; Steger, Joseph L.

1987-01-01

The three-dimensional flow over a projectile has been computed using an implicit, approximately factored, partially flux-split algorithm. A simple composite grid scheme has been developed in which a single grid is partitioned into a series of smaller grids for applications which require an external large memory device such as the SSD of the CRAY X-MP/48, or multitasking. The accuracy and stability of the composite grid scheme has been tested by numerically simulating the flow over an ellipsoid at angle of attack and comparing the solution with a single grid solution. The flowfield over a projectile at M = 0.96 and 4 deg angle-of-attack has been computed using a fine grid, and compared with experiment.

Free-wake computation of helicopter rotor flowfields in forward flight

NASA Technical Reports Server (NTRS)

Ramachandran, K.; Schlechtriem, S.; Caradonna, F. X.; Steinhoff, John

1993-01-01

A new method has been developed for computing advancing rotor flows. This method uses the Vorticity Embedding technique, which has been developed and validated over the last several years for hovering rotor problems. In this work, the unsteady full potential equation is solved on an Eulerian grid with an embedded vortical velocity field. This vortical velocity accounts for the influence of the wake. Dynamic grid changes that are required to accommodate prescribed blade motion and deformation are included using a novel grid blending method. Free wake computations have been performed on a two-bladed AH-1G rotor at low advance ratios including blade motion. Computed results are compared with experimental data. The sudden variations in airloads due to blade-vortex interactions on the advancing and retreating sides are well captured. The sensitivity of the computed solution to various factors like core size, time step and grids has been investigated. Computed wake geometries and their influence on the aerodynamic loads at these advance ratios are also discussed.

Achieving Accuracy Requirements for Forest Biomass Mapping: A Data Fusion Method for Estimating Forest Biomass and LiDAR Sampling Error with Spaceborne Data

NASA Technical Reports Server (NTRS)

Montesano, P. M.; Cook, B. D.; Sun, G.; Simard, M.; Zhang, Z.; Nelson, R. F.; Ranson, K. J.; Lutchke, S.; Blair, J. B.

2012-01-01

The synergistic use of active and passive remote sensing (i.e., data fusion) demonstrates the ability of spaceborne light detection and ranging (LiDAR), synthetic aperture radar (SAR) and multispectral imagery for achieving the accuracy requirements of a global forest biomass mapping mission. This data fusion approach also provides a means to extend 3D information from discrete spaceborne LiDAR measurements of forest structure across scales much larger than that of the LiDAR footprint. For estimating biomass, these measurements mix a number of errors including those associated with LiDAR footprint sampling over regional - global extents. A general framework for mapping above ground live forest biomass (AGB) with a data fusion approach is presented and verified using data from NASA field campaigns near Howland, ME, USA, to assess AGB and LiDAR sampling errors across a regionally representative landscape. We combined SAR and Landsat-derived optical (passive optical) image data to identify forest patches, and used image and simulated spaceborne LiDAR data to compute AGB and estimate LiDAR sampling error for forest patches and 100m, 250m, 500m, and 1km grid cells. Forest patches were delineated with Landsat-derived data and airborne SAR imagery, and simulated spaceborne LiDAR (SSL) data were derived from orbit and cloud cover simulations and airborne data from NASA's Laser Vegetation Imaging Sensor (L VIS). At both the patch and grid scales, we evaluated differences in AGB estimation and sampling error from the combined use of LiDAR with both SAR and passive optical and with either SAR or passive optical alone. This data fusion approach demonstrates that incorporating forest patches into the AGB mapping framework can provide sub-grid forest information for coarser grid-level AGB reporting, and that combining simulated spaceborne LiDAR with SAR and passive optical data are most useful for estimating AGB when measurements from LiDAR are limited because they minimized forest AGB sampling errors by 15 - 38%. Furthermore, spaceborne global scale accuracy requirements were achieved. At least 80% of the grid cells at 100m, 250m, 500m, and 1km grid levels met AGB density accuracy requirements using a combination of passive optical and SAR along with machine learning methods to predict vegetation structure metrics for forested areas without LiDAR samples. Finally, using either passive optical or SAR, accuracy requirements were met at the 500m and 250m grid level, respectively.

Extending the Fermi-LAT Data Processing Pipeline to the Grid

NASA Astrophysics Data System (ADS)

Zimmer, S.; Arrabito, L.; Glanzman, T.; Johnson, T.; Lavalley, C.; Tsaregorodtsev, A.

2012-12-01

The Data Handling Pipeline (“Pipeline”) has been developed for the Fermi Gamma-Ray Space Telescope (Fermi) Large Area Telescope (LAT) which launched in June 2008. Since then it has been in use to completely automate the production of data quality monitoring quantities, reconstruction and routine analysis of all data received from the satellite and to deliver science products to the collaboration and the Fermi Science Support Center. Aside from the reconstruction of raw data from the satellite (Level 1), data reprocessing and various event-level analyses are also reasonably heavy loads on the pipeline and computing resources. These other loads, unlike Level 1, can run continuously for weeks or months at a time. In addition it receives heavy use in performing production Monte Carlo tasks. In daily use it receives a new data download every 3 hours and launches about 2000 jobs to process each download, typically completing the processing of the data before the next download arrives. The need for manual intervention has been reduced to less than 0.01% of submitted jobs. The Pipeline software is written almost entirely in Java and comprises several modules. The software comprises web-services that allow online monitoring and provides charts summarizing work flow aspects and performance information. The server supports communication with several batch systems such as LSF and BQS and recently also Sun Grid Engine and Condor. This is accomplished through dedicated job control services that for Fermi are running at SLAC and the other computing site involved in this large scale framework, the Lyon computing center of IN2P3. While being different in the logic of a task, we evaluate a separate interface to the Dirac system in order to communicate with EGI sites to utilize Grid resources, using dedicated Grid optimized systems rather than developing our own. More recently the Pipeline and its associated data catalog have been generalized for use by other experiments, and are currently being used by the Enriched Xenon Observatory (EXO), Cryogenic Dark Matter Search (CDMS) experiments as well as for Monte Carlo simulations for the future Cherenkov Telescope Array (CTA).

Digital overlaying of the universal transverse Mercator grid with LANDSAT data derived products

NASA Technical Reports Server (NTRS)

Graham, M. H.

1977-01-01

Picture elements of data from the LANDSAT multispectral scanner are correlated with the universal tranverse Mercator grid. In the procedure, a series of computer modules was used to make approximations of universal transverse Mercator grid locations for all picture elements from the grid locations of a limited number of known control points and to provide display and digital storage of the data. The software has been written in FORTRAN 4 language for a Varian 70-series computer.

MrGrid: A Portable Grid Based Molecular Replacement Pipeline

PubMed Central

Reboul, Cyril F.; Androulakis, Steve G.; Phan, Jennifer M. N.; Whisstock, James C.; Goscinski, Wojtek J.; Abramson, David; Buckle, Ashley M.

2010-01-01

Background The crystallographic determination of protein structures can be computationally demanding and for difficult cases can benefit from user-friendly interfaces to high-performance computing resources. Molecular replacement (MR) is a popular protein crystallographic technique that exploits the structural similarity between proteins that share some sequence similarity. But the need to trial permutations of search models, space group symmetries and other parameters makes MR time- and labour-intensive. However, MR calculations are embarrassingly parallel and thus ideally suited to distributed computing. In order to address this problem we have developed MrGrid, web-based software that allows multiple MR calculations to be executed across a grid of networked computers, allowing high-throughput MR. Methodology/Principal Findings MrGrid is a portable web based application written in Java/JSP and Ruby, and taking advantage of Apple Xgrid technology. Designed to interface with a user defined Xgrid resource the package manages the distribution of multiple MR runs to the available nodes on the Xgrid. We evaluated MrGrid using 10 different protein test cases on a network of 13 computers, and achieved an average speed up factor of 5.69. Conclusions MrGrid enables the user to retrieve and manage the results of tens to hundreds of MR calculations quickly and via a single web interface, as well as broadening the range of strategies that can be attempted. This high-throughput approach allows parameter sweeps to be performed in parallel, improving the chances of MR success. PMID:20386612

Direct numerical simulation of particulate flows with an overset grid method

NASA Astrophysics Data System (ADS)

Koblitz, A. R.; Lovett, S.; Nikiforakis, N.; Henshaw, W. D.

2017-08-01

We evaluate an efficient overset grid method for two-dimensional and three-dimensional particulate flows for small numbers of particles at finite Reynolds number. The rigid particles are discretised using moving overset grids overlaid on a Cartesian background grid. This allows for strongly-enforced boundary conditions and local grid refinement at particle surfaces, thereby accurately capturing the viscous boundary layer at modest computational cost. The incompressible Navier-Stokes equations are solved with a fractional-step scheme which is second-order-accurate in space and time, while the fluid-solid coupling is achieved with a partitioned approach including multiple sub-iterations to increase stability for light, rigid bodies. Through a series of benchmark studies we demonstrate the accuracy and efficiency of this approach compared to other boundary conformal and static grid methods in the literature. In particular, we find that fully resolving boundary layers at particle surfaces is crucial to obtain accurate solutions to many common test cases. With our approach we are able to compute accurate solutions using as little as one third the number of grid points as uniform grid computations in the literature. A detailed convergence study shows a 13-fold decrease in CPU time over a uniform grid test case whilst maintaining comparable solution accuracy.

Virtualizing access to scientific applications with the Application Hosting Environment

NASA Astrophysics Data System (ADS)

Zasada, S. J.; Coveney, P. V.

2009-12-01

The growing power and number of high performance computing resources made available through computational grids present major opportunities as well as a number of challenges to the user. At issue is how these resources can be accessed and how their power can be effectively exploited. In this paper we first present our views on the usability of contemporary high-performance computational resources. We introduce the concept of grid application virtualization as a solution to some of the problems with grid-based HPC usability. We then describe a middleware tool that we have developed to realize the virtualization of grid applications, the Application Hosting Environment (AHE), and describe the features of the new release, AHE 2.0, which provides access to a common platform of federated computational grid resources in standard and non-standard ways. Finally, we describe a case study showing how AHE supports clinical use of whole brain blood flow modelling in a routine and automated fashion. Program summaryProgram title: Application Hosting Environment 2.0 Catalogue identifier: AEEJ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEEJ_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU Public Licence, Version 2 No. of lines in distributed program, including test data, etc.: not applicable No. of bytes in distributed program, including test data, etc.: 1 685 603 766 Distribution format: tar.gz Programming language: Perl (server), Java (Client) Computer: x86 Operating system: Linux (Server), Linux/Windows/MacOS (Client) RAM: 134 217 728 (server), 67 108 864 (client) bytes Classification: 6.5 External routines: VirtualBox (server), Java (client) Nature of problem: The middleware that makes grid computing possible has been found by many users to be too unwieldy, and presents an obstacle to use rather than providing assistance [1,2]. Such problems are compounded when one attempts to harness the power of a grid, or a federation of different grids, rather than just a single resource on the grid. Solution method: To address the above problem, we have developed AHE, a lightweight interface, designed to simplify the process of running scientific codes on a grid of HPC and local resources. AHE does this by introducing a layer of middleware between the user and the grid, which encapsulates much of the complexity associated with launching grid applications. Unusual features: The server is distributed as a VirtualBox virtual machine. VirtualBox ( http://www.virtualbox.org) must be downloaded and installed in order to run the AHE server virtual machine. Details of how to do this are given in the AHE 2.0 Quick Start Guide. Running time: Not applicable References:J. Chin, P.V. Coveney, Towards tractable toolkits for the grid: A plea for lightweight, useable middleware, NeSC Technical Report, 2004, http://nesc.ac.uk/technical_papers/UKeS-2004-01.pdf. P.V. Coveney, R.S. Saksena, S.J. Zasada, M. McKeown, S. Pickles, The Application Hosting Environment: Lightweight middleware for grid-based computational science, Computer Physics Communications 176 (2007) 406-418.

Fast generation of three-dimensional computational boundary-conforming periodic grids of C-type. [for turbine blades and propellers

NASA Technical Reports Server (NTRS)

Dulikravich, D. S.

1982-01-01

A fast computer program, GRID3C, was developed to generate multilevel three dimensional, C type, periodic, boundary conforming grids for the calculation of realistic turbomachinery and propeller flow fields. The technique is based on two analytic functions that conformally map a cascade of semi-infinite slits to a cascade of doubly infinite strips on different Riemann sheets. Up to four consecutively refined three dimensional grids are automatically generated and permanently stored on four different computer tapes. Grid nonorthogonality is introduced by a separate coordinate shearing and stretching performed in each of three coordinate directions. The grids are easily clustered closer to the blade surface, the trailing and leading edges and the hub or shroud regions by changing appropriate input parameters. Hub and duct (or outer free boundary) have different axisymmetric shapes. A vortex sheet of arbitrary thickness emanating smoothly from the blade trailing edge is generated automatically by GRID3C. Blade cross sectional shape, chord length, twist angle, sweep angle, and dihedral angle can vary in an arbitrary smooth fashion in the spanwise direction.

Acceleration of incremental-pressure-correction incompressible flow computations using a coarse-grid projection method

NASA Astrophysics Data System (ADS)

Kashefi, Ali; Staples, Anne

2016-11-01

Coarse grid projection (CGP) methodology is a novel multigrid method for systems involving decoupled nonlinear evolution equations and linear elliptic equations. The nonlinear equations are solved on a fine grid and the linear equations are solved on a corresponding coarsened grid. Mapping functions transfer data between the two grids. Here we propose a version of CGP for incompressible flow computations using incremental pressure correction methods, called IFEi-CGP (implicit-time-integration, finite-element, incremental coarse grid projection). Incremental pressure correction schemes solve Poisson's equation for an intermediate variable and not the pressure itself. This fact contributes to IFEi-CGP's efficiency in two ways. First, IFEi-CGP preserves the velocity field accuracy even for a high level of pressure field grid coarsening and thus significant speedup is achieved. Second, because incremental schemes reduce the errors that arise from boundaries with artificial homogenous Neumann conditions, CGP generates undamped flows for simulations with velocity Dirichlet boundary conditions. Comparisons of the data accuracy and CPU times for the incremental-CGP versus non-incremental-CGP computations are presented.

Distribution Grid Integration Costs Under High PV Penetrations Workshop |

Science.gov Websites

grids. These distribution grid integration costs are one component of a complete cost-benefit analysis . Engaging stakeholders to coalesce around transparent and mutually acceptable frameworks for cost-benefit -voltage only). In particular, there was be a focus on methods most appropriate for cost-benefit analysis

Efficient Redundancy Techniques in Cloud and Desktop Grid Systems using MAP/G/c-type Queues

NASA Astrophysics Data System (ADS)

Chakravarthy, Srinivas R.; Rumyantsev, Alexander

2018-03-01

Cloud computing is continuing to prove its flexibility and versatility in helping industries and businesses as well as academia as a way of providing needed computing capacity. As an important alternative to cloud computing, desktop grids allow to utilize the idle computer resources of an enterprise/community by means of distributed computing system, providing a more secure and controllable environment with lower operational expenses. Further, both cloud computing and desktop grids are meant to optimize limited resources and at the same time to decrease the expected latency for users. The crucial parameter for optimization both in cloud computing and in desktop grids is the level of redundancy (replication) for service requests/workunits. In this paper we study the optimal replication policies by considering three variations of Fork-Join systems in the context of a multi-server queueing system with a versatile point process for the arrivals. For services we consider phase type distributions as well as shifted exponential and Weibull. We use both analytical and simulation approach in our analysis and report some interesting qualitative results.

An Advanced User Interface Approach for Complex Parameter Study Process Specification in the Information Power Grid

NASA Technical Reports Server (NTRS)

Yarrow, Maurice; McCann, Karen M.; Biswas, Rupak; VanderWijngaart, Rob; Yan, Jerry C. (Technical Monitor)

2000-01-01

The creation of parameter study suites has recently become a more challenging problem as the parameter studies have now become multi-tiered and the computational environment has become a supercomputer grid. The parameter spaces are vast, the individual problem sizes are getting larger, and researchers are now seeking to combine several successive stages of parameterization and computation. Simultaneously, grid-based computing offers great resource opportunity but at the expense of great difficulty of use. We present an approach to this problem which stresses intuitive visual design tools for parameter study creation and complex process specification, and also offers programming-free access to grid-based supercomputer resources and process automation.

Grid adaption based on modified anisotropic diffusion equations formulated in the parametic domain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagmeijer, R.

1994-11-01

A new grid-adaption algorithm for problems in computational fluid dynamics is presented. The basic equations are derived from a variational problem formulated in the parametric domain of the mapping that defines the existing grid. Modification of the basic equations provides desirable properties in boundary layers. The resulting modified anisotropic diffusion equations are solved for the computational coordinates as functions of the parametric coordinates and these functions are numerically inverted. Numerical examples show that the algorithm is robust, that shocks and boundary layers are well-resolved on the adapted grid, and that the flow solution becomes a globally smooth function of themore » computational coordinates.« less

Jungle Computing: Distributed Supercomputing Beyond Clusters, Grids, and Clouds

NASA Astrophysics Data System (ADS)

Seinstra, Frank J.; Maassen, Jason; van Nieuwpoort, Rob V.; Drost, Niels; van Kessel, Timo; van Werkhoven, Ben; Urbani, Jacopo; Jacobs, Ceriel; Kielmann, Thilo; Bal, Henri E.

In recent years, the application of high-performance and distributed computing in scientific practice has become increasingly wide spread. Among the most widely available platforms to scientists are clusters, grids, and cloud systems. Such infrastructures currently are undergoing revolutionary change due to the integration of many-core technologies, providing orders-of-magnitude speed improvements for selected compute kernels. With high-performance and distributed computing systems thus becoming more heterogeneous and hierarchical, programming complexity is vastly increased. Further complexities arise because urgent desire for scalability and issues including data distribution, software heterogeneity, and ad hoc hardware availability commonly force scientists into simultaneous use of multiple platforms (e.g., clusters, grids, and clouds used concurrently). A true computing jungle.

DISPATCH: a numerical simulation framework for the exa-scale era - I. Fundamentals

NASA Astrophysics Data System (ADS)

Nordlund, Åke; Ramsey, Jon P.; Popovas, Andrius; Küffmeier, Michael

2018-06-01

We introduce a high-performance simulation framework that permits the semi-independent, task-based solution of sets of partial differential equations, typically manifesting as updates to a collection of `patches' in space-time. A hybrid MPI/OpenMP execution model is adopted, where work tasks are controlled by a rank-local `dispatcher' which selects, from a set of tasks generally much larger than the number of physical cores (or hardware threads), tasks that are ready for updating. The definition of a task can vary, for example, with some solving the equations of ideal magnetohydrodynamics (MHD), others non-ideal MHD, radiative transfer, or particle motion, and yet others applying particle-in-cell (PIC) methods. Tasks do not have to be grid based, while tasks that are, may use either Cartesian or orthogonal curvilinear meshes. Patches may be stationary or moving. Mesh refinement can be static or dynamic. A feature of decisive importance for the overall performance of the framework is that time-steps are determined and applied locally; this allows potentially large reductions in the total number of updates required in cases when the signal speed varies greatly across the computational domain, and therefore a corresponding reduction in computing time. Another feature is a load balancing algorithm that operates `locally' and aims to simultaneously minimize load and communication imbalance. The framework generally relies on already existing solvers, whose performance is augmented when run under the framework, due to more efficient cache usage, vectorization, local time-stepping, plus near-linear and, in principle, unlimited OpenMP and MPI scaling.

Parallel high-performance grid computing: capabilities and opportunities of a novel demanding service and business class allowing highest resource efficiency.

PubMed

Kepper, Nick; Ettig, Ramona; Dickmann, Frank; Stehr, Rene; Grosveld, Frank G; Wedemann, Gero; Knoch, Tobias A

2010-01-01

Especially in the life-science and the health-care sectors the huge IT requirements are imminent due to the large and complex systems to be analysed and simulated. Grid infrastructures play here a rapidly increasing role for research, diagnostics, and treatment, since they provide the necessary large-scale resources efficiently. Whereas grids were first used for huge number crunching of trivially parallelizable problems, increasingly parallel high-performance computing is required. Here, we show for the prime example of molecular dynamic simulations how the presence of large grid clusters including very fast network interconnects within grid infrastructures allows now parallel high-performance grid computing efficiently and thus combines the benefits of dedicated super-computing centres and grid infrastructures. The demands for this service class are the highest since the user group has very heterogeneous requirements: i) two to many thousands of CPUs, ii) different memory architectures, iii) huge storage capabilities, and iv) fast communication via network interconnects, are all needed in different combinations and must be considered in a highly dedicated manner to reach highest performance efficiency. Beyond, advanced and dedicated i) interaction with users, ii) the management of jobs, iii) accounting, and iv) billing, not only combines classic with parallel high-performance grid usage, but more importantly is also able to increase the efficiency of IT resource providers. Consequently, the mere "yes-we-can" becomes a huge opportunity like e.g. the life-science and health-care sectors as well as grid infrastructures by reaching higher level of resource efficiency.

Adaptive 3D single-block grids for the computation of viscous flows around wings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagmeijer, R.; Kok, J.C.

1996-12-31

A robust algorithm for the adaption of a 3D single-block structured grid suitable for the computation of viscous flows around a wing is presented and demonstrated by application to the ONERA M6 wing. The effects of grid adaption on the flow solution and accuracy improvements is analyzed. Reynolds number variations are studied.