The iPlant Collaborative: Cyberinfrastructure for Enabling Data to Discovery for the Life Sciences

PubMed Central

Merchant, Nirav; Lyons, Eric; Goff, Stephen; Vaughn, Matthew; Ware, Doreen; Micklos, David; Antin, Parker

2016-01-01

The iPlant Collaborative provides life science research communities access to comprehensive, scalable, and cohesive computational infrastructure for data management; identity management; collaboration tools; and cloud, high-performance, high-throughput computing. iPlant provides training, learning material, and best practice resources to help all researchers make the best use of their data, expand their computational skill set, and effectively manage their data and computation when working as distributed teams. iPlant’s platform permits researchers to easily deposit and share their data and deploy new computational tools and analysis workflows, allowing the broader community to easily use and reuse those data and computational analyses. PMID:26752627

Network Community Detection based on the Physarum-inspired Computational Framework.

PubMed

Gao, Chao; Liang, Mingxin; Li, Xianghua; Zhang, Zili; Wang, Zhen; Zhou, Zhili

2016-12-13

Community detection is a crucial and essential problem in the structure analytics of complex networks, which can help us understand and predict the characteristics and functions of complex networks. Many methods, ranging from the optimization-based algorithms to the heuristic-based algorithms, have been proposed for solving such a problem. Due to the inherent complexity of identifying network structure, how to design an effective algorithm with a higher accuracy and a lower computational cost still remains an open problem. Inspired by the computational capability and positive feedback mechanism in the wake of foraging process of Physarum, which is a large amoeba-like cell consisting of a dendritic network of tube-like pseudopodia, a general Physarum-based computational framework for community detection is proposed in this paper. Based on the proposed framework, the inter-community edges can be identified from the intra-community edges in a network and the positive feedback of solving process in an algorithm can be further enhanced, which are used to improve the efficiency of original optimization-based and heuristic-based community detection algorithms, respectively. Some typical algorithms (e.g., genetic algorithm, ant colony optimization algorithm, and Markov clustering algorithm) and real-world datasets have been used to estimate the efficiency of our proposed computational framework. Experiments show that the algorithms optimized by Physarum-inspired computational framework perform better than the original ones, in terms of accuracy and computational cost. Moreover, a computational complexity analysis verifies the scalability of our framework.

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.

The Petascale Data Storage Institute

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

Gibson, Garth; Long, Darrell; Honeyman, Peter

2013-07-01

Petascale computing infrastructures for scientific discovery make petascale demands on information storage capacity, performance, concurrency, reliability, availability, and manageability.The Petascale Data Storage Institute focuses on the data storage problems found in petascale scientific computing environments, with special attention to community issues such as interoperability, community buy-in, and shared tools.The Petascale Data Storage Institute is a collaboration between researchers at Carnegie Mellon University, National Energy Research Scientific Computing Center, Pacific Northwest National Laboratory, Oak Ridge National Laboratory, Sandia National Laboratory, Los Alamos National Laboratory, University of Michigan, and the University of California at Santa Cruz.

Overlapping Community Detection based on Network Decomposition

NASA Astrophysics Data System (ADS)

Ding, Zhuanlian; Zhang, Xingyi; Sun, Dengdi; Luo, Bin

2016-04-01

Community detection in complex network has become a vital step to understand the structure and dynamics of networks in various fields. However, traditional node clustering and relatively new proposed link clustering methods have inherent drawbacks to discover overlapping communities. Node clustering is inadequate to capture the pervasive overlaps, while link clustering is often criticized due to the high computational cost and ambiguous definition of communities. So, overlapping community detection is still a formidable challenge. In this work, we propose a new overlapping community detection algorithm based on network decomposition, called NDOCD. Specifically, NDOCD iteratively splits the network by removing all links in derived link communities, which are identified by utilizing node clustering technique. The network decomposition contributes to reducing the computation time and noise link elimination conduces to improving the quality of obtained communities. Besides, we employ node clustering technique rather than link similarity measure to discover link communities, thus NDOCD avoids an ambiguous definition of community and becomes less time-consuming. We test our approach on both synthetic and real-world networks. Results demonstrate the superior performance of our approach both in computation time and accuracy compared to state-of-the-art algorithms.

The SCEC Community Modeling Environment (SCEC/CME) - An Overview of its Architecture and Current Capabilities

NASA Astrophysics Data System (ADS)

Maechling, P. J.; Jordan, T. H.; Minster, B.; Moore, R.; Kesselman, C.; SCEC ITR Collaboration

2004-12-01

The Southern California Earthquake Center (SCEC), in collaboration with the San Diego Supercomputer Center, the USC Information Sciences Institute, the Incorporated Research Institutions for Seismology, and the U.S. Geological Survey, is developing the Southern California Earthquake Center Community Modeling Environment (CME) under a five-year grant from the National Science Foundation's Information Technology Research (ITR) Program jointly funded by the Geosciences and Computer and Information Science & Engineering Directorates. The CME system is an integrated geophysical simulation modeling framework that automates the process of selecting, configuring, and executing models of earthquake systems. During the Project's first three years, we have performed fundamental geophysical and information technology research and have also developed substantial system capabilities, software tools, and data collections that can help scientist perform systems-level earthquake science. The CME system provides collaborative tools to facilitate distributed research and development. These collaborative tools are primarily communication tools, providing researchers with access to information in ways that are convenient and useful. The CME system provides collaborators with access to significant computing and storage resources. The computing resources of the Project include in-house servers, Project allocations on USC High Performance Computing Linux Cluster, as well as allocations on NPACI Supercomputers and the TeraGrid. The CME system provides access to SCEC community geophysical models such as the Community Velocity Model, Community Fault Model, Community Crustal Motion Model, and the Community Block Model. The organizations that develop these models often provide access to them so it is not necessary to use the CME system to access these models. However, in some cases, the CME system supplements the SCEC community models with utility codes that make it easier to use or access these models. In some cases, the CME system also provides alternatives to the SCEC community models. The CME system hosts a collection of community geophysical software codes. These codes include seismic hazard analysis (SHA) programs developed by the SCEC/USGS OpenSHA group. Also, the CME system hosts anelastic wave propagation codes including Kim Olsen's Finite Difference code and Carnegie Mellon's Hercules Finite Element tool chain. The CME system can execute a workflow, that is, a series of geophysical computations using the output of one processing step as the input to a subsequent step. Our workflow capability utilizes grid-based computing software that can submit calculations to a pool of computing resources as well as data management tools that help us maintain an association between data files and metadata descriptions of those files. The CME system maintains, and provides access to, a collection of valuable geophysical data sets. The current CME Digital Library holdings include a collection of 60 ground motion simulation results calculated by a SCEC/PEER working group and a collection of Greens Functions calculated for 33 TriNet broadband receiver sites in the Los Angeles area.

Reconfigurable Computing for Computational Science: A New Focus in High Performance Computing

DTIC Science & Technology

2006-11-01

in the past decade. Researchers are regularly employing the power of large computing systems and parallel processing to tackle larger and more...complex problems in all of the physical sciences. For the past decade or so, most of this growth in computing power has been “free” with increased...the scientific computing community as a means to continued growth in computing capability. This paper offers a glimpse of the hardware and

Evaluating coastal and river valley communities evacuation network performance using macroscopic productivity.

DOT National Transportation Integrated Search

2017-06-30

The ever-increasing processing speed and computational power of computers and simulation systems has led to correspondingly larger, more sophisticated representations of evacuation traffic processes. Today, micro-level analyses can be conducted for m...

A parallel-processing approach to computing for the geographic sciences; applications and systems enhancements

USGS Publications Warehouse

Crane, Michael; Steinwand, Dan; Beckmann, Tim; Krpan, Greg; Liu, Shu-Guang; Nichols, Erin; Haga, Jim; Maddox, Brian; Bilderback, Chris; Feller, Mark; Homer, George

2001-01-01

The overarching goal of this project is to build a spatially distributed infrastructure for information science research by forming a team of information science researchers and providing them with similar hardware and software tools to perform collaborative research. Four geographically distributed Centers of the U.S. Geological Survey (USGS) are developing their own clusters of low-cost, personal computers into parallel computing environments that provide a costeffective way for the USGS to increase participation in the high-performance computing community. Referred to as Beowulf clusters, these hybrid systems provide the robust computing power required for conducting information science research into parallel computing systems and applications.

HPCCP/CAS Workshop Proceedings 1998

NASA Technical Reports Server (NTRS)

Schulbach, Catherine; Mata, Ellen (Editor); Schulbach, Catherine (Editor)

1999-01-01

This publication is a collection of extended abstracts of presentations given at the HPCCP/CAS (High Performance Computing and Communications Program/Computational Aerosciences Project) Workshop held on August 24-26, 1998, at NASA Ames Research Center, Moffett Field, California. The objective of the Workshop was to bring together the aerospace high performance computing community, consisting of airframe and propulsion companies, independent software vendors, university researchers, and government scientists and engineers. The Workshop was sponsored by the HPCCP Office at NASA Ames Research Center. The Workshop consisted of over 40 presentations, including an overview of NASA's High Performance Computing and Communications Program and the Computational Aerosciences Project; ten sessions of papers representative of the high performance computing research conducted within the Program by the aerospace industry, academia, NASA, and other government laboratories; two panel sessions; and a special presentation by Mr. James Bailey.

Architectural Principles and Experimentation of Distributed High Performance Virtual Clusters

ERIC Educational Resources Information Center

Younge, Andrew J.

2016-01-01

With the advent of virtualization and Infrastructure-as-a-Service (IaaS), the broader scientific computing community is considering the use of clouds for their scientific computing needs. This is due to the relative scalability, ease of use, advanced user environment customization abilities, and the many novel computing paradigms available for…

GPU-Meta-Storms: computing the structure similarities among massive amount of microbial community samples using GPU.

PubMed

Su, Xiaoquan; Wang, Xuetao; Jing, Gongchao; Ning, Kang

2014-04-01

The number of microbial community samples is increasing with exponential speed. Data-mining among microbial community samples could facilitate the discovery of valuable biological information that is still hidden in the massive data. However, current methods for the comparison among microbial communities are limited by their ability to process large amount of samples each with complex community structure. We have developed an optimized GPU-based software, GPU-Meta-Storms, to efficiently measure the quantitative phylogenetic similarity among massive amount of microbial community samples. Our results have shown that GPU-Meta-Storms would be able to compute the pair-wise similarity scores for 10 240 samples within 20 min, which gained a speed-up of >17 000 times compared with single-core CPU, and >2600 times compared with 16-core CPU. Therefore, the high-performance of GPU-Meta-Storms could facilitate in-depth data mining among massive microbial community samples, and make the real-time analysis and monitoring of temporal or conditional changes for microbial communities possible. GPU-Meta-Storms is implemented by CUDA (Compute Unified Device Architecture) and C++. Source code is available at http://www.computationalbioenergy.org/meta-storms.html.

Mixing HTC and HPC Workloads with HTCondor and Slurm

NASA Astrophysics Data System (ADS)

Hollowell, C.; Barnett, J.; Caramarcu, C.; Strecker-Kellogg, W.; Wong, A.; Zaytsev, A.

2017-10-01

Traditionally, the RHIC/ATLAS Computing Facility (RACF) at Brookhaven National Laboratory (BNL) has only maintained High Throughput Computing (HTC) resources for our HEP/NP user community. We’ve been using HTCondor as our batch system for many years, as this software is particularly well suited for managing HTC processor farm resources. Recently, the RACF has also begun to design/administrate some High Performance Computing (HPC) systems for a multidisciplinary user community at BNL. In this paper, we’ll discuss our experiences using HTCondor and Slurm in an HPC context, and our facility’s attempts to allow our HTC and HPC processing farms/clusters to make opportunistic use of each other’s computing resources.

Accelerated Application Development: The ORNL Titan Experience

DOE PAGES

Joubert, Wayne; Archibald, Richard K.; Berrill, Mark A.; ...

2015-05-09

The use of computational accelerators such as NVIDIA GPUs and Intel Xeon Phi processors is now widespread in the high performance computing community, with many applications delivering impressive performance gains. However, programming these systems for high performance, performance portability and software maintainability has been a challenge. In this paper we discuss experiences porting applications to the Titan system. Titan, which began planning in 2009 and was deployed for general use in 2013, was the first multi-petaflop system based on accelerator hardware. To ready applications for accelerated computing, a preparedness effort was undertaken prior to delivery of Titan. In this papermore » we report experiences and lessons learned from this process and describe how users are currently making use of computational accelerators on Titan.« less

Accelerated application development: The ORNL Titan experience

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

Joubert, Wayne; Archibald, Rick; Berrill, Mark

2015-08-01

The use of computational accelerators such as NVIDIA GPUs and Intel Xeon Phi processors is now widespread in the high performance computing community, with many applications delivering impressive performance gains. However, programming these systems for high performance, performance portability and software maintainability has been a challenge. In this paper we discuss experiences porting applications to the Titan system. Titan, which began planning in 2009 and was deployed for general use in 2013, was the first multi-petaflop system based on accelerator hardware. To ready applications for accelerated computing, a preparedness effort was undertaken prior to delivery of Titan. In this papermore » we report experiences and lessons learned from this process and describe how users are currently making use of computational accelerators on Titan.« less

The iPlant collaborative: cyberinfrastructure for enabling data to discovery for the life sciences

USDA-ARS?s Scientific Manuscript database

The iPlant Collaborative provides life science research communities access to comprehensive, scalable, and cohesive computational infrastructure for data management; identify management; collaboration tools; and cloud, high-performance, high-throughput computing. iPlant provides training, learning m...

Joint the Center for Applied Scientific Computing

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

Gamblin, Todd; Bremer, Timo; Van Essen, Brian

The Center for Applied Scientific Computing serves as Livermore Lab’s window to the broader computer science, computational physics, applied mathematics, and data science research communities. In collaboration with academic, industrial, and other government laboratory partners, we conduct world-class scientific research and development on problems critical to national security. CASC applies the power of high-performance computing and the efficiency of modern computational methods to the realms of stockpile stewardship, cyber and energy security, and knowledge discovery for intelligence applications.

Definition of performance specifications for automated Analytical Electrophoresis Facility (AAEF)

NASA Technical Reports Server (NTRS)

Brooks, D. E.

1976-01-01

In order to provide specifications for the automated Analytical Electrophoresis Facility (AAEF) that would satisfy the broadest variety of demands of a future user community, a survey was carried out of all those people who were identified as having published papers on cell electrophoresis in the past four years. A computer search was conducted of the relevant literature from which a list of 87 investigators was derived and defined as the user community for purposes of the mailing. A questionnaire was developed covering the areas of performance which required definition which was subsequently circulated to the user community. Based on the response to this survey performance specifications were assembled.

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.

NASA Center for Climate Simulation (NCCS) Advanced Technology AT5 Virtualized Infiniband Report

NASA Technical Reports Server (NTRS)

Thompson, John H.; Bledsoe, Benjamin C.; Wagner, Mark; Shakshober, John; Fromkin, Russ

2013-01-01

The NCCS is part of the Computational and Information Sciences and Technology Office (CISTO) of Goddard Space Flight Center's (GSFC) Sciences and Exploration Directorate. The NCCS's mission is to enable scientists to increase their understanding of the Earth, the solar system, and the universe by supplying state-of-the-art high performance computing (HPC) solutions. To accomplish this mission, the NCCS (https://www.nccs.nasa.gov) provides high performance compute engines, mass storage, and network solutions to meet the specialized needs of the Earth and space science user communities

A Queue Simulation Tool for a High Performance Scientific Computing Center

NASA Technical Reports Server (NTRS)

Spear, Carrie; McGalliard, James

2007-01-01

The NASA Center for Computational Sciences (NCCS) at the Goddard Space Flight Center provides high performance highly parallel processors, mass storage, and supporting infrastructure to a community of computational Earth and space scientists. Long running (days) and highly parallel (hundreds of CPUs) jobs are common in the workload. NCCS management structures batch queues and allocates resources to optimize system use and prioritize workloads. NCCS technical staff use a locally developed discrete event simulation tool to model the impacts of evolving workloads, potential system upgrades, alternative queue structures and resource allocation policies.

Running climate model on a commercial cloud computing environment: A case study using Community Earth System Model (CESM) on Amazon AWS

NASA Astrophysics Data System (ADS)

Chen, Xiuhong; Huang, Xianglei; Jiao, Chaoyi; Flanner, Mark G.; Raeker, Todd; Palen, Brock

2017-01-01

The suites of numerical models used for simulating climate of our planet are usually run on dedicated high-performance computing (HPC) resources. This study investigates an alternative to the usual approach, i.e. carrying out climate model simulations on commercially available cloud computing environment. We test the performance and reliability of running the CESM (Community Earth System Model), a flagship climate model in the United States developed by the National Center for Atmospheric Research (NCAR), on Amazon Web Service (AWS) EC2, the cloud computing environment by Amazon.com, Inc. StarCluster is used to create virtual computing cluster on the AWS EC2 for the CESM simulations. The wall-clock time for one year of CESM simulation on the AWS EC2 virtual cluster is comparable to the time spent for the same simulation on a local dedicated high-performance computing cluster with InfiniBand connections. The CESM simulation can be efficiently scaled with the number of CPU cores on the AWS EC2 virtual cluster environment up to 64 cores. For the standard configuration of the CESM at a spatial resolution of 1.9° latitude by 2.5° longitude, increasing the number of cores from 16 to 64 reduces the wall-clock running time by more than 50% and the scaling is nearly linear. Beyond 64 cores, the communication latency starts to outweigh the benefit of distributed computing and the parallel speedup becomes nearly unchanged.

Satellite broadcasting system study

NASA Technical Reports Server (NTRS)

1972-01-01

The study to develop a system model and computer program representative of broadcasting satellite systems employing community-type receiving terminals is reported. The program provides a user-oriented tool for evaluating performance/cost tradeoffs, synthesizing minimum cost systems for a given set of system requirements, and performing sensitivity analyses to identify critical parameters and technology. The performance/ costing philosophy and what is meant by a minimum cost system is shown graphically. Topics discussed include: main line control program, ground segment model, space segment model, cost models and launch vehicle selection. Several examples of minimum cost systems resulting from the computer program are presented. A listing of the computer program is also included.

AstroCV: Astronomy computer vision library

NASA Astrophysics Data System (ADS)

González, Roberto E.; Muñoz, Roberto P.; Hernández, Cristian A.

2018-04-01

AstroCV processes and analyzes big astronomical datasets, and is intended to provide a community repository of high performance Python and C++ algorithms used for image processing and computer vision. The library offers methods for object recognition, segmentation and classification, with emphasis in the automatic detection and classification of galaxies.

Improving Mathematics Learning of Kindergarten Students through Computer-Assisted Instruction

ERIC Educational Resources Information Center

Foster, Matthew E.; Anthony, Jason L.; Clements, Doug H.; Sarama, Julie; Williams, Jeffrey M.

2016-01-01

This study evaluated the effects of a mathematics software program, the Building Blocks software suite, on young children's mathematics performance. Participants included 247 Kindergartners from 37 classrooms in 9 schools located in low-income communities. Children within classrooms were randomly assigned to receive 21 weeks of computer-assisted…

Bioinformatics and Astrophysics Cluster (BinAc)

NASA Astrophysics Data System (ADS)

Krüger, Jens; Lutz, Volker; Bartusch, Felix; Dilling, Werner; Gorska, Anna; Schäfer, Christoph; Walter, Thomas

2017-09-01

BinAC provides central high performance computing capacities for bioinformaticians and astrophysicists from the state of Baden-Württemberg. The bwForCluster BinAC is part of the implementation concept for scientific computing for the universities in Baden-Württemberg. Community specific support is offered through the bwHPC-C5 project.

Determinants of microcomputer technology use: implications for education and training of health staff.

PubMed

Jayasuriya, R

1998-06-01

In hospitals and other Healthcare settings, increasingly, hands-on computer use is becoming an important behaviour for effective job performance. The literature has identified differences that relate to computer use between occupational categories in health services. The objectives of this study were to identify factors that determine computer acceptance among occupational groups in Community Health and to predict the factors that relate to computer use. A survey was administered to all Community Health staff in one health service area. Health administrators were found to have a significantly higher training in computers, a higher frequency of use and a higher level of skill for both applications (word processing (WP) and database (DB)) than nurses. The results of a regression analysis shows that about 55% of the variation in the use of WP is explained by computer skills, perceived usefulness (PU) and designation. In the case of DB use, PU was the only significant predictor explaining 53% of the variation. Both level of education and prior training were not significant predictors. The implication for health informatics education (and service training) of these findings is that, in the workplace, health professionals would use computers when they perceive it to be useful for performance in their jobs.

BridgeRank: A novel fast centrality measure based on local structure of the network

NASA Astrophysics Data System (ADS)

Salavati, Chiman; Abdollahpouri, Alireza; Manbari, Zhaleh

2018-04-01

Ranking nodes in complex networks have become an important task in many application domains. In a complex network, influential nodes are those that have the most spreading ability. Thus, identifying influential nodes based on their spreading ability is a fundamental task in different applications such as viral marketing. One of the most important centrality measures to ranking nodes is closeness centrality which is efficient but suffers from high computational complexity O(n3) . This paper tries to improve closeness centrality by utilizing the local structure of nodes and presents a new ranking algorithm, called BridgeRank centrality. The proposed method computes local centrality value for each node. For this purpose, at first, communities are detected and the relationship between communities is completely ignored. Then, by applying a centrality in each community, only one best critical node from each community is extracted. Finally, the nodes are ranked based on computing the sum of the shortest path length of nodes to obtained critical nodes. We have also modified the proposed method by weighting the original BridgeRank and selecting several nodes from each community based on the density of that community. Our method can find the best nodes with high spread ability and low time complexity, which make it applicable to large-scale networks. To evaluate the performance of the proposed method, we use the SIR diffusion model. Finally, experiments on real and artificial networks show that our method is able to identify influential nodes so efficiently, and achieves better performance compared to other recent methods.

Using Technology to Facilitate Collaboration in Community-Based Participatory Research (CBPR)

PubMed Central

Jessell, Lauren; Smith, Vivian; Jemal, Alexis; Windsor, Liliane

2017-01-01

This study explores the use of Computer-Supported Collaborative Work (CSCW) technologies, by way of a computer-based system called iCohere. This system was used to facilitate collaboration conducting Community-Based Participatory Research (CBPR). Data was gathered from 13 members of a Community Collaborative Board (CCB). Analysis revealed that iCohere served the following functions: facilitating communication, providing a depository for information and resource sharing, and allowing for remote meeting attendance. Results indicated that while iCohere was useful in performing these functions, less expensive technologies had the potential to achieve similar goals if properly implemented. Implications for future research on CSCW systems and CBPR are discussed. PMID:29056871

Development of an ADP Training Program to Serve the EPA Data Processing Community.

DTIC Science & Technology

1976-07-29

divide, compute , perform and alter statements; data representation and conversion; table processing; and indexed sequential and random access file...processing. The course workshop will include the testing of coded exercises and problems on a computer system. CLASS SIZE: Individualized METHODS/CONDUCT...familiarization with computer concepts will be helpful. OBJECTIVES OF CURRICULUM After completing this course, the student should have developed a working

A community computational challenge to predict the activity of pairs of compounds.

PubMed

Bansal, Mukesh; Yang, Jichen; Karan, Charles; Menden, Michael P; Costello, James C; Tang, Hao; Xiao, Guanghua; Li, Yajuan; Allen, Jeffrey; Zhong, Rui; Chen, Beibei; Kim, Minsoo; Wang, Tao; Heiser, Laura M; Realubit, Ronald; Mattioli, Michela; Alvarez, Mariano J; Shen, Yao; Gallahan, Daniel; Singer, Dinah; Saez-Rodriguez, Julio; Xie, Yang; Stolovitzky, Gustavo; Califano, Andrea

2014-12-01

Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction.

A feasibility study on porting the community land model onto accelerators using OpenACC

DOE PAGES

Wang, Dali; Wu, Wei; Winkler, Frank; ...

2014-01-01

As environmental models (such as Accelerated Climate Model for Energy (ACME), Parallel Reactive Flow and Transport Model (PFLOTRAN), Arctic Terrestrial Simulator (ATS), etc.) became more and more complicated, we are facing enormous challenges regarding to porting those applications onto hybrid computing architecture. OpenACC appears as a very promising technology, therefore, we have conducted a feasibility analysis on porting the Community Land Model (CLM), a terrestrial ecosystem model within the Community Earth System Models (CESM)). Specifically, we used automatic function testing platform to extract a small computing kernel out of CLM, then we apply this kernel into the actually CLM dataflowmore » procedure, and investigate the strategy of data parallelization and the benefit of data movement provided by current implementation of OpenACC. Even it is a non-intensive kernel, on a single 16-core computing node, the performance (based on the actual computation time using one GPU) of OpenACC implementation is 2.3 time faster than that of OpenMP implementation using single OpenMP thread, but it is 2.8 times slower than the performance of OpenMP implementation using 16 threads. On multiple nodes, MPI_OpenACC implementation demonstrated very good scalability on up to 128 GPUs on 128 computing nodes. This study also provides useful information for us to look into the potential benefits of “deep copy” capability and “routine” feature of OpenACC standards. In conclusion, we believe that our experience on the environmental model, CLM, can be beneficial to many other scientific research programs who are interested to porting their large scale scientific code using OpenACC onto high-end computers, empowered by hybrid computing architecture.« less

Introduction into the Virtual Olympic Games Framework for online communities.

PubMed

Stoilescu, Dorian

2009-06-01

This paper presents the design of the Virtual Olympic Games Framework (VOGF), a computer application designated for athletics, health care, general well-being, nutrition and fitness, which offers multiple benefits for its participants. A special interest in starting the design of the framework was in exploring how people can connect and participate together using existing computer technologies (i.e. gaming consoles, exercise equipment with computer interfaces, devices of measuring health, speed, force and distance and Web 2.0 applications). A stationary bike set-up offering information to users about their individual health and athletic performances has been considered as a starting model. While this model is in the design stage, some preliminary findings are encouraging, suggesting the potential for various fields: sports, medicine, theories of learning, technologies and cybercultural studies. First, this framework would allow participants to perform a variety of sports and improve their health. Second, this would involve creating an online environment able to store health information and sport performances correlated with accessing multi-media data and research about performing sports. Third, participants could share experiences with other athletes, coaches and researchers. Fourth, this framework also provides support for the research community in their future investigations.

The iPlant Collaborative: Cyberinfrastructure for Plant Biology.

PubMed

Goff, Stephen A; Vaughn, Matthew; McKay, Sheldon; Lyons, Eric; Stapleton, Ann E; Gessler, Damian; Matasci, Naim; Wang, Liya; Hanlon, Matthew; Lenards, Andrew; Muir, Andy; Merchant, Nirav; Lowry, Sonya; Mock, Stephen; Helmke, Matthew; Kubach, Adam; Narro, Martha; Hopkins, Nicole; Micklos, David; Hilgert, Uwe; Gonzales, Michael; Jordan, Chris; Skidmore, Edwin; Dooley, Rion; Cazes, John; McLay, Robert; Lu, Zhenyuan; Pasternak, Shiran; Koesterke, Lars; Piel, William H; Grene, Ruth; Noutsos, Christos; Gendler, Karla; Feng, Xin; Tang, Chunlao; Lent, Monica; Kim, Seung-Jin; Kvilekval, Kristian; Manjunath, B S; Tannen, Val; Stamatakis, Alexandros; Sanderson, Michael; Welch, Stephen M; Cranston, Karen A; Soltis, Pamela; Soltis, Doug; O'Meara, Brian; Ane, Cecile; Brutnell, Tom; Kleibenstein, Daniel J; White, Jeffery W; Leebens-Mack, James; Donoghue, Michael J; Spalding, Edgar P; Vision, Todd J; Myers, Christopher R; Lowenthal, David; Enquist, Brian J; Boyle, Brad; Akoglu, Ali; Andrews, Greg; Ram, Sudha; Ware, Doreen; Stein, Lincoln; Stanzione, Dan

2011-01-01

The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanity's projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies. The iPlant cyberinfrastructure design is based on an unprecedented period of research community input, and leverages developments in high-performance computing, data storage, and cyberinfrastructure for the physical sciences. iPlant is an open-source project with application programming interfaces that allow the community to extend the infrastructure to meet its needs. iPlant is sponsoring community-driven workshops addressing specific scientific questions via analysis tool integration and hypothesis testing. These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services.

The iPlant Collaborative: Cyberinfrastructure for Plant Biology

PubMed Central

Goff, Stephen A.; Vaughn, Matthew; McKay, Sheldon; Lyons, Eric; Stapleton, Ann E.; Gessler, Damian; Matasci, Naim; Wang, Liya; Hanlon, Matthew; Lenards, Andrew; Muir, Andy; Merchant, Nirav; Lowry, Sonya; Mock, Stephen; Helmke, Matthew; Kubach, Adam; Narro, Martha; Hopkins, Nicole; Micklos, David; Hilgert, Uwe; Gonzales, Michael; Jordan, Chris; Skidmore, Edwin; Dooley, Rion; Cazes, John; McLay, Robert; Lu, Zhenyuan; Pasternak, Shiran; Koesterke, Lars; Piel, William H.; Grene, Ruth; Noutsos, Christos; Gendler, Karla; Feng, Xin; Tang, Chunlao; Lent, Monica; Kim, Seung-Jin; Kvilekval, Kristian; Manjunath, B. S.; Tannen, Val; Stamatakis, Alexandros; Sanderson, Michael; Welch, Stephen M.; Cranston, Karen A.; Soltis, Pamela; Soltis, Doug; O'Meara, Brian; Ane, Cecile; Brutnell, Tom; Kleibenstein, Daniel J.; White, Jeffery W.; Leebens-Mack, James; Donoghue, Michael J.; Spalding, Edgar P.; Vision, Todd J.; Myers, Christopher R.; Lowenthal, David; Enquist, Brian J.; Boyle, Brad; Akoglu, Ali; Andrews, Greg; Ram, Sudha; Ware, Doreen; Stein, Lincoln; Stanzione, Dan

2011-01-01

The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanity's projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies. The iPlant cyberinfrastructure design is based on an unprecedented period of research community input, and leverages developments in high-performance computing, data storage, and cyberinfrastructure for the physical sciences. iPlant is an open-source project with application programming interfaces that allow the community to extend the infrastructure to meet its needs. iPlant is sponsoring community-driven workshops addressing specific scientific questions via analysis tool integration and hypothesis testing. These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services. PMID:22645531

Optimizing Engineering Tools Using Modern Ground Architectures

DTIC Science & Technology

2017-12-01

Considerations,” International Journal of Computer Science & Engineering Survey , vol. 5, no. 4, 2014. [10] R. Bell. (n.d). A beginner’s guide to big O notation...scientific community. Traditional computing architectures were not capable of processing the data efficiently, or in some cases, could not process the...thesis investigates how these modern computing architectures could be leveraged by industry and academia to improve the performance and capabilities of

Final Report. Institute for Ultralscale Visualization

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

Ma, Kwan-Liu; Galli, Giulia; Gygi, Francois

The SciDAC Institute for Ultrascale Visualization brought together leading experts from visualization, high-performance computing, and science application areas to make advanced visualization solutions for SciDAC scientists and the broader community. Over the five-year project, the Institute introduced many new enabling visualization techniques, which have significantly enhanced scientists’ ability to validate their simulations, interpret their data, and communicate with others about their work and findings. This Institute project involved a large number of junior and student researchers, who received the opportunities to work on some of the most challenging science applications and gain access to the most powerful high-performance computing facilitiesmore » in the world. They were readily trained and prepared for facing the greater challenges presented by extreme-scale computing. The Institute’s outreach efforts, through publications, workshops and tutorials, successfully disseminated the new knowledge and technologies to the SciDAC and the broader scientific communities. The scientific findings and experience of the Institute team helped plan the SciDAC3 program.« less

From the desktop to the grid: scalable bioinformatics via workflow conversion.

PubMed

de la Garza, Luis; Veit, Johannes; Szolek, Andras; Röttig, Marc; Aiche, Stephan; Gesing, Sandra; Reinert, Knut; Kohlbacher, Oliver

2016-03-12

Reproducibility is one of the tenets of the scientific method. Scientific experiments often comprise complex data flows, selection of adequate parameters, and analysis and visualization of intermediate and end results. Breaking down the complexity of such experiments into the joint collaboration of small, repeatable, well defined tasks, each with well defined inputs, parameters, and outputs, offers the immediate benefit of identifying bottlenecks, pinpoint sections which could benefit from parallelization, among others. Workflows rest upon the notion of splitting complex work into the joint effort of several manageable tasks. There are several engines that give users the ability to design and execute workflows. Each engine was created to address certain problems of a specific community, therefore each one has its advantages and shortcomings. Furthermore, not all features of all workflow engines are royalty-free -an aspect that could potentially drive away members of the scientific community. We have developed a set of tools that enables the scientific community to benefit from workflow interoperability. We developed a platform-free structured representation of parameters, inputs, outputs of command-line tools in so-called Common Tool Descriptor documents. We have also overcome the shortcomings and combined the features of two royalty-free workflow engines with a substantial user community: the Konstanz Information Miner, an engine which we see as a formidable workflow editor, and the Grid and User Support Environment, a web-based framework able to interact with several high-performance computing resources. We have thus created a free and highly accessible way to design workflows on a desktop computer and execute them on high-performance computing resources. Our work will not only reduce time spent on designing scientific workflows, but also make executing workflows on remote high-performance computing resources more accessible to technically inexperienced users. We strongly believe that our efforts not only decrease the turnaround time to obtain scientific results but also have a positive impact on reproducibility, thus elevating the quality of obtained scientific results.

Using the Eclipse Parallel Tools Platform to Assist Earth Science Model Development and Optimization on High Performance Computers

NASA Astrophysics Data System (ADS)

Alameda, J. C.

2011-12-01

Development and optimization of computational science models, particularly on high performance computers, and with the advent of ubiquitous multicore processor systems, practically on every system, has been accomplished with basic software tools, typically, command-line based compilers, debuggers, performance tools that have not changed substantially from the days of serial and early vector computers. However, model complexity, including the complexity added by modern message passing libraries such as MPI, and the need for hybrid code models (such as openMP and MPI) to be able to take full advantage of high performance computers with an increasing core count per shared memory node, has made development and optimization of such codes an increasingly arduous task. Additional architectural developments, such as many-core processors, only complicate the situation further. In this paper, we describe how our NSF-funded project, "SI2-SSI: A Productive and Accessible Development Workbench for HPC Applications Using the Eclipse Parallel Tools Platform" (WHPC) seeks to improve the Eclipse Parallel Tools Platform, an environment designed to support scientific code development targeted at a diverse set of high performance computing systems. Our WHPC project to improve Eclipse PTP takes an application-centric view to improve PTP. We are using a set of scientific applications, each with a variety of challenges, and using PTP to drive further improvements to both the scientific application, as well as to understand shortcomings in Eclipse PTP from an application developer perspective, to drive our list of improvements we seek to make. We are also partnering with performance tool providers, to drive higher quality performance tool integration. We have partnered with the Cactus group at Louisiana State University to improve Eclipse's ability to work with computational frameworks and extremely complex build systems, as well as to develop educational materials to incorporate into computational science and engineering codes. Finally, we are partnering with the lead PTP developers at IBM, to ensure we are as effective as possible within the Eclipse community development. We are also conducting training and outreach to our user community, including conference BOF sessions, monthly user calls, and an annual user meeting, so that we can best inform the improvements we make to Eclipse PTP. With these activities we endeavor to encourage use of modern software engineering practices, as enabled through the Eclipse IDE, with computational science and engineering applications. These practices include proper use of source code repositories, tracking and rectifying issues, measuring and monitoring code performance changes against both optimizations as well as ever-changing software stacks and configurations on HPC systems, as well as ultimately encouraging development and maintenance of testing suites -- things that have become commonplace in many software endeavors, but have lagged in the development of science applications. We view that the challenge with the increased complexity of both HPC systems and science applications demands the use of better software engineering methods, preferably enabled by modern tools such as Eclipse PTP, to help the computational science community thrive as we evolve the HPC landscape.

Multi-community command and control systems in law enforcement: An introductory planning guide

NASA Technical Reports Server (NTRS)

Sohn, R. L.; Garcia, E. A.; Kennedy, R. D.

1976-01-01

A set of planning guidelines for multi-community command and control systems in law enforcement is presented. Essential characteristics and applications of these systems are outlined. Requirements analysis, system concept design, implementation planning, and performance and cost modeling are described and demonstrated with numerous examples. Program management techniques and joint powers agreements for multicommunity programs are discussed in detail. A description of a typical multi-community computer-aided dispatch system is appended.

A parallel-processing approach to computing for the geographic sciences

USGS Publications Warehouse

Crane, Michael; Steinwand, Dan; Beckmann, Tim; Krpan, Greg; Haga, Jim; Maddox, Brian; Feller, Mark

2001-01-01

The overarching goal of this project is to build a spatially distributed infrastructure for information science research by forming a team of information science researchers and providing them with similar hardware and software tools to perform collaborative research. Four geographically distributed Centers of the U.S. Geological Survey (USGS) are developing their own clusters of low-cost personal computers into parallel computing environments that provide a costeffective way for the USGS to increase participation in the high-performance computing community. Referred to as Beowulf clusters, these hybrid systems provide the robust computing power required for conducting research into various areas, such as advanced computer architecture, algorithms to meet the processing needs for real-time image and data processing, the creation of custom datasets from seamless source data, rapid turn-around of products for emergency response, and support for computationally intense spatial and temporal modeling.

PHoToNs–A parallel heterogeneous and threads oriented code for cosmological N-body simulation

NASA Astrophysics Data System (ADS)

Wang, Qiao; Cao, Zong-Yan; Gao, Liang; Chi, Xue-Bin; Meng, Chen; Wang, Jie; Wang, Long

2018-06-01

We introduce a new code for cosmological simulations, PHoToNs, which incorporates features for performing massive cosmological simulations on heterogeneous high performance computer (HPC) systems and threads oriented programming. PHoToNs adopts a hybrid scheme to compute gravitational force, with the conventional Particle-Mesh (PM) algorithm to compute the long-range force, the Tree algorithm to compute the short range force and the direct summation Particle-Particle (PP) algorithm to compute gravity from very close particles. A self-similar space filling a Peano-Hilbert curve is used to decompose the computing domain. Threads programming is advantageously used to more flexibly manage the domain communication, PM calculation and synchronization, as well as Dual Tree Traversal on the CPU+MIC platform. PHoToNs scales well and efficiency of the PP kernel achieves 68.6% of peak performance on MIC and 74.4% on CPU platforms. We also test the accuracy of the code against the much used Gadget-2 in the community and found excellent agreement.

Scout: high-performance heterogeneous computing made simple

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

Jablin, James; Mc Cormick, Patrick; Herlihy, Maurice

2011-01-26

Researchers must often write their own simulation and analysis software. During this process they simultaneously confront both computational and scientific problems. Current strategies for aiding the generation of performance-oriented programs do not abstract the software development from the science. Furthermore, the problem is becoming increasingly complex and pressing with the continued development of many-core and heterogeneous (CPU-GPU) architectures. To acbieve high performance, scientists must expertly navigate both software and hardware. Co-design between computer scientists and research scientists can alleviate but not solve this problem. The science community requires better tools for developing, optimizing, and future-proofing codes, allowing scientists to focusmore » on their research while still achieving high computational performance. Scout is a parallel programming language and extensible compiler framework targeting heterogeneous architectures. It provides the abstraction required to buffer scientists from the constantly-shifting details of hardware while still realizing higb-performance by encapsulating software and hardware optimization within a compiler framework.« less

PDS: A Performance Database Server

DOE PAGES

Berry, Michael W.; Dongarra, Jack J.; Larose, Brian H.; ...

1994-01-01

The process of gathering, archiving, and distributing computer benchmark data is a cumbersome task usually performed by computer users and vendors with little coordination. Most important, there is no publicly available central depository of performance data for all ranges of machines from personal computers to supercomputers. We present an Internet-accessible performance database server (PDS) that can be used to extract current benchmark data and literature. As an extension to the X-Windows-based user interface (Xnetlib) to the Netlib archival system, PDS provides an on-line catalog of public domain computer benchmarks such as the LINPACK benchmark, Perfect benchmarks, and the NAS parallelmore » benchmarks. PDS does not reformat or present the benchmark data in any way that conflicts with the original methodology of any particular benchmark; it is thereby devoid of any subjective interpretations of machine performance. We believe that all branches (research laboratories, academia, and industry) of the general computing community can use this facility to archive performance metrics and make them readily available to the public. PDS can provide a more manageable approach to the development and support of a large dynamic database of published performance metrics.« less

Assessing a mini-application as a performance proxy for a finite element method engineering application

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

Lin, Paul T.; Heroux, Michael A.; Barrett, Richard F.

The performance of a large-scale, production-quality science and engineering application (‘app’) is often dominated by a small subset of the code. Even within that subset, computational and data access patterns are often repeated, so that an even smaller portion can represent the performance-impacting features. If application developers, parallel computing experts, and computer architects can together identify this representative subset and then develop a small mini-application (‘miniapp’) that can capture these primary performance characteristics, then this miniapp can be used to both improve the performance of the app as well as provide a tool for co-design for the high-performance computing community.more » However, a critical question is whether a miniapp can effectively capture key performance behavior of an app. This study provides a comparison of an implicit finite element semiconductor device modeling app on unstructured meshes with an implicit finite element miniapp on unstructured meshes. The goal is to assess whether the miniapp is predictive of the performance of the app. Finally, single compute node performance will be compared, as well as scaling up to 16,000 cores. Results indicate that the miniapp can be reasonably predictive of the performance characteristics of the app for a single iteration of the solver on a single compute node.« less

Assessing a mini-application as a performance proxy for a finite element method engineering application

DOE PAGES

Lin, Paul T.; Heroux, Michael A.; Barrett, Richard F.; ...

2015-07-30

The performance of a large-scale, production-quality science and engineering application (‘app’) is often dominated by a small subset of the code. Even within that subset, computational and data access patterns are often repeated, so that an even smaller portion can represent the performance-impacting features. If application developers, parallel computing experts, and computer architects can together identify this representative subset and then develop a small mini-application (‘miniapp’) that can capture these primary performance characteristics, then this miniapp can be used to both improve the performance of the app as well as provide a tool for co-design for the high-performance computing community.more » However, a critical question is whether a miniapp can effectively capture key performance behavior of an app. This study provides a comparison of an implicit finite element semiconductor device modeling app on unstructured meshes with an implicit finite element miniapp on unstructured meshes. The goal is to assess whether the miniapp is predictive of the performance of the app. Finally, single compute node performance will be compared, as well as scaling up to 16,000 cores. Results indicate that the miniapp can be reasonably predictive of the performance characteristics of the app for a single iteration of the solver on a single compute node.« less

Institutional Transformation.

ERIC Educational Resources Information Center

Harris, Zelema M.

Although incivility and conflict have long plagued community colleges and other educational institutions, recent budget declines have made this situation more critical. In the past, those who disagreed could be bought off and organizations tended to hire layers of people to perform tasks that one person with a personal computer can perform today.…

Lewis Structures Technology, 1988. Volume 2: Structural Mechanics

NASA Technical Reports Server (NTRS)

1988-01-01

Lewis Structures Div. performs and disseminates results of research conducted in support of aerospace engine structures. These results have a wide range of applicability to practitioners of structural engineering mechanics beyond the aerospace arena. The engineering community was familiarized with the depth and range of research performed by the division and its academic and industrial partners. Sessions covered vibration control, fracture mechanics, ceramic component reliability, parallel computing, nondestructive evaluation, constitutive models and experimental capabilities, dynamic systems, fatigue and damage, wind turbines, hot section technology (HOST), aeroelasticity, structural mechanics codes, computational methods for dynamics, structural optimization, and applications of structural dynamics, and structural mechanics computer codes.

Lawrence Livermore National Laboratories Perspective on Code Development and High Performance Computing Resources in Support of the National HED/ICF Effort

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

Clouse, C. J.; Edwards, M. J.; McCoy, M. G.

2015-07-07

Through its Advanced Scientific Computing (ASC) and Inertial Confinement Fusion (ICF) code development efforts, Lawrence Livermore National Laboratory (LLNL) provides a world leading numerical simulation capability for the National HED/ICF program in support of the Stockpile Stewardship Program (SSP). In addition the ASC effort provides high performance computing platform capabilities upon which these codes are run. LLNL remains committed to, and will work with, the national HED/ICF program community to help insure numerical simulation needs are met and to make those capabilities available, consistent with programmatic priorities and available resources.

CSDMS2.0: Computational Infrastructure for Community Surface Dynamics Modeling

NASA Astrophysics Data System (ADS)

Syvitski, J. P.; Hutton, E.; Peckham, S. D.; Overeem, I.; Kettner, A.

2012-12-01

The Community Surface Dynamic Modeling System (CSDMS) is an NSF-supported, international and community-driven program that seeks to transform the science and practice of earth-surface dynamics modeling. CSDMS integrates a diverse community of more than 850 geoscientists representing 360 international institutions (academic, government, industry) from 60 countries and is supported by a CSDMS Interagency Committee (22 Federal agencies), and a CSDMS Industrial Consortia (18 companies). CSDMS presently distributes more 200 Open Source models and modeling tools, access to high performance computing clusters in support of developing and running models, and a suite of products for education and knowledge transfer. CSDMS software architecture employs frameworks and services that convert stand-alone models into flexible "plug-and-play" components to be assembled into larger applications. CSDMS2.0 will support model applications within a web browser, on a wider variety of computational platforms, and on other high performance computing clusters to ensure robustness and sustainability of the framework. Conversion of stand-alone models into "plug-and-play" components will employ automated wrapping tools. Methods for quantifying model uncertainty are being adapted as part of the modeling framework. Benchmarking data is being incorporated into the CSDMS modeling framework to support model inter-comparison. Finally, a robust mechanism for ingesting and utilizing semantic mediation databases is being developed within the Modeling Framework. Six new community initiatives are being pursued: 1) an earth - ecosystem modeling initiative to capture ecosystem dynamics and ensuing interactions with landscapes, 2) a geodynamics initiative to investigate the interplay among climate, geomorphology, and tectonic processes, 3) an Anthropocene modeling initiative, to incorporate mechanistic models of human influences, 4) a coastal vulnerability modeling initiative, with emphasis on deltas and their multiple threats and stressors, 5) a continental margin modeling initiative, to capture extreme oceanic and atmospheric events generating turbidity currents in the Gulf of Mexico, and 6) a CZO Focus Research Group, to develop compatibility between CSDMS architecture and protocols and Critical Zone Observatory-developed models and data.

Community detection using preference networks

NASA Astrophysics Data System (ADS)

Tasgin, Mursel; Bingol, Haluk O.

2018-04-01

Community detection is the task of identifying clusters or groups of nodes in a network where nodes within the same group are more connected with each other than with nodes in different groups. It has practical uses in identifying similar functions or roles of nodes in many biological, social and computer networks. With the availability of very large networks in recent years, performance and scalability of community detection algorithms become crucial, i.e. if time complexity of an algorithm is high, it cannot run on large networks. In this paper, we propose a new community detection algorithm, which has a local approach and is able to run on large networks. It has a simple and effective method; given a network, algorithm constructs a preference network of nodes where each node has a single outgoing edge showing its preferred node to be in the same community with. In such a preference network, each connected component is a community. Selection of the preferred node is performed using similarity based metrics of nodes. We use two alternatives for this purpose which can be calculated in 1-neighborhood of nodes, i.e. number of common neighbors of selector node and its neighbors and, the spread capability of neighbors around the selector node which is calculated by the gossip algorithm of Lind et.al. Our algorithm is tested on both computer generated LFR networks and real-life networks with ground-truth community structure. It can identify communities accurately in a fast way. It is local, scalable and suitable for distributed execution on large networks.

High-Performance Compute Infrastructure in Astronomy: 2020 Is Only Months Away

NASA Astrophysics Data System (ADS)

Berriman, B.; Deelman, E.; Juve, G.; Rynge, M.; Vöckler, J. S.

2012-09-01

By 2020, astronomy will be awash with as much as 60 PB of public data. Full scientific exploitation of such massive volumes of data will require high-performance computing on server farms co-located with the data. Development of this computing model will be a community-wide enterprise that has profound cultural and technical implications. Astronomers must be prepared to develop environment-agnostic applications that support parallel processing. The community must investigate the applicability and cost-benefit of emerging technologies such as cloud computing to astronomy, and must engage the Computer Science community to develop science-driven cyberinfrastructure such as workflow schedulers and optimizers. We report here the results of collaborations between a science center, IPAC, and a Computer Science research institute, ISI. These collaborations may be considered pathfinders in developing a high-performance compute infrastructure in astronomy. These collaborations investigated two exemplar large-scale science-driver workflow applications: 1) Calculation of an infrared atlas of the Galactic Plane at 18 different wavelengths by placing data from multiple surveys on a common plate scale and co-registering all the pixels; 2) Calculation of an atlas of periodicities present in the public Kepler data sets, which currently contain 380,000 light curves. These products have been generated with two workflow applications, written in C for performance and designed to support parallel processing on multiple environments and platforms, but with different compute resource needs: the Montage image mosaic engine is I/O-bound, and the NASA Star and Exoplanet Database periodogram code is CPU-bound. Our presentation will report cost and performance metrics and lessons-learned for continuing development. Applicability of Cloud Computing: Commercial Cloud providers generally charge for all operations, including processing, transfer of input and output data, and for storage of data, and so the costs of running applications vary widely according to how they use resources. The cloud is well suited to processing CPU-bound (and memory bound) workflows such as the periodogram code, given the relatively low cost of processing in comparison with I/O operations. I/O-bound applications such as Montage perform best on high-performance clusters with fast networks and parallel file-systems. Science-driven Cyberinfrastructure: Montage has been widely used as a driver application to develop workflow management services, such as task scheduling in distributed environments, designing fault tolerance techniques for job schedulers, and developing workflow orchestration techniques. Running Parallel Applications Across Distributed Cloud Environments: Data processing will eventually take place in parallel distributed across cyber infrastructure environments having different architectures. We have used the Pegasus Work Management System (WMS) to successfully run applications across three very different environments: TeraGrid, OSG (Open Science Grid), and FutureGrid. Provisioning resources across different grids and clouds (also referred to as Sky Computing), involves establishing a distributed environment, where issues of, e.g, remote job submission, data management, and security need to be addressed. This environment also requires building virtual machine images that can run in different environments. Usually, each cloud provides basic images that can be customized with additional software and services. In most of our work, we provisioned compute resources using a custom application, called Wrangler. Pegasus WMS abstracts the architectures of the compute environments away from the end-user, and can be considered a first-generation tool suitable for scientists to run their applications on disparate environments.

Transferring Emerging Technology from ICT-115 "Computer Aided Writing" to a Three-Way Coordinated Program in Vocational Literacy.

ERIC Educational Resources Information Center

Neff, George

Vocational Literacy is a new academic field which has arisen in response to criticism from industry that vocational graduates are not sufficiently literate to perform on the job. South Seattle Community College (SSCC) in Washington has investigated the feasibility of coordinating courses in computer literacy with English and technical courses to…

Self-Concept of Computer and Math Ability: Gender Implications across Time and within ICT Studies

ERIC Educational Resources Information Center

Sainz, Milagros; Eccles, Jacquelynne

2012-01-01

The scarcity of women in ICT-related studies has been systematically reported by the scientific community for many years. This paper has three goals: to analyze gender differences in self-concept of computer and math abilities along with math performance in two consecutive academic years; to study the ontogeny of gender differences in self-concept…

LDPC decoder with a limited-precision FPGA-based floating-point multiplication coprocessor

NASA Astrophysics Data System (ADS)

Moberly, Raymond; O'Sullivan, Michael; Waheed, Khurram

2007-09-01

Implementing the sum-product algorithm, in an FPGA with an embedded processor, invites us to consider a tradeoff between computational precision and computational speed. The algorithm, known outside of the signal processing community as Pearl's belief propagation, is used for iterative soft-decision decoding of LDPC codes. We determined the feasibility of a coprocessor that will perform product computations. Our FPGA-based coprocessor (design) performs computer algebra with significantly less precision than the standard (e.g. integer, floating-point) operations of general purpose processors. Using synthesis, targeting a 3,168 LUT Xilinx FPGA, we show that key components of a decoder are feasible and that the full single-precision decoder could be constructed using a larger part. Soft-decision decoding by the iterative belief propagation algorithm is impacted both positively and negatively by a reduction in the precision of the computation. Reducing precision reduces the coding gain, but the limited-precision computation can operate faster. A proposed solution offers custom logic to perform computations with less precision, yet uses the floating-point format to interface with the software. Simulation results show the achievable coding gain. Synthesis results help theorize the the full capacity and performance of an FPGA-based coprocessor.

Whole earth modeling: developing and disseminating scientific software for computational geophysics.

NASA Astrophysics Data System (ADS)

Kellogg, L. H.

2016-12-01

Historically, a great deal of specialized scientific software for modeling and data analysis has been developed by individual researchers or small groups of scientists working on their own specific research problems. As the magnitude of available data and computer power has increased, so has the complexity of scientific problems addressed by computational methods, creating both a need to sustain existing scientific software, and expand its development to take advantage of new algorithms, new software approaches, and new computational hardware. To that end, communities like the Computational Infrastructure for Geodynamics (CIG) have been established to support the use of best practices in scientific computing for solid earth geophysics research and teaching. Working as a scientific community enables computational geophysicists to take advantage of technological developments, improve the accuracy and performance of software, build on prior software development, and collaborate more readily. The CIG community, and others, have adopted an open-source development model, in which code is developed and disseminated by the community in an open fashion, using version control and software repositories like Git. One emerging issue is how to adequately identify and credit the intellectual contributions involved in creating open source scientific software. The traditional method of disseminating scientific ideas, peer reviewed publication, was not designed for review or crediting scientific software, although emerging publication strategies such software journals are attempting to address the need. We are piloting an integrated approach in which authors are identified and credited as scientific software is developed and run. Successful software citation requires integration with the scholarly publication and indexing mechanisms as well, to assign credit, ensure discoverability, and provide provenance for software.

A world-wide databridge supported by a commercial cloud provider

NASA Astrophysics Data System (ADS)

Tat Cheung, Kwong; Field, Laurence; Furano, Fabrizio

2017-10-01

Volunteer computing has the potential to provide significant additional computing capacity for the LHC experiments. One of the challenges with exploiting volunteer computing is to support a global community of volunteers that provides heterogeneous resources. However, high energy physics applications require more data input and output than the CPU intensive applications that are typically used by other volunteer computing projects. While the so-called databridge has already been successfully proposed as a method to span the untrusted and trusted domains of volunteer computing and Grid computing respective, globally transferring data between potentially poor-performing residential networks and CERN could be unreliable, leading to wasted resources usage. The expectation is that by placing a storage endpoint that is part of a wider, flexible geographical databridge deployment closer to the volunteers, the transfer success rate and the overall performance can be improved. This contribution investigates the provision of a globally distributed databridge implemented upon a commercial cloud provider.

Center for Center for Technology for Advanced Scientific Component Software (TASCS)

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

Kostadin, Damevski

A resounding success of the Scientific Discovery through Advanced Computing (SciDAC) program is that high-performance computational science is now universally recognized as a critical aspect of scientific discovery [71], complementing both theoretical and experimental research. As scientific communities prepare to exploit unprecedented computing capabilities of emerging leadership-class machines for multi-model simulations at the extreme scale [72], it is more important than ever to address the technical and social challenges of geographically distributed teams that combine expertise in domain science, applied mathematics, and computer science to build robust and flexible codes that can incorporate changes over time. The Center for Technologymore » for Advanced Scientific Component Software (TASCS)1 tackles these these issues by exploiting component-based software development to facilitate collaborative high-performance scientific computing.« less

Purple Computational Environment With Mappings to ACE Requirements for the General Availability User Environment Capabilities

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

Barney, B; Shuler, J

2006-08-21

Purple is an Advanced Simulation and Computing (ASC) funded massively parallel supercomputer located at Lawrence Livermore National Laboratory (LLNL). The Purple Computational Environment documents the capabilities and the environment provided for the FY06 LLNL Level 1 General Availability Milestone. This document describes specific capabilities, tools, and procedures to support both local and remote users. The model is focused on the needs of the ASC user working in the secure computing environments at Los Alamos National Laboratory, Lawrence Livermore National Laboratory, and Sandia National Laboratories, but also documents needs of the LLNL and Alliance users working in the unclassified environment. Additionally,more » the Purple Computational Environment maps the provided capabilities to the Trilab ASC Computing Environment (ACE) Version 8.0 requirements. The ACE requirements reflect the high performance computing requirements for the General Availability user environment capabilities of the ASC community. Appendix A lists these requirements and includes a description of ACE requirements met and those requirements that are not met for each section of this document. The Purple Computing Environment, along with the ACE mappings, has been issued and reviewed throughout the Tri-lab community.« less

Statistical Model for Predicting Roles and Effects in Learning Community

ERIC Educational Resources Information Center

Chang, Chih-Kai; Chen, Gwo-Dong; Wang, Chin-Yeh

2011-01-01

Functional roles may explain the learning performance of groups. Detecting a functional role is critical for promoting group learning performance in computer-supported collaborative learning environments. However, it is not easy for teachers to identify the functional roles played by students in a web-based learning group, or the relationship…

Havery Mudd 2014-2015 Computer Science Conduit Clinic Final Report

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

Aspesi, G; Bai, J; Deese, R

2015-05-12

Conduit, a new open-source library developed at Lawrence Livermore National Laboratories, provides a C++ application programming interface (API) to describe and access scientific data. Conduit’s primary use is for inmemory data exchange in high performance computing (HPC) applications. Our team tested and improved Conduit to make it more appealing to potential adopters in the HPC community. We extended Conduit’s capabilities by prototyping four libraries: one for parallel communication using MPI, one for I/O functionality, one for aggregating performance data, and one for data visualization.

Sustaining a Community Computing Infrastructure for Online Teacher Professional Development: A Case Study of Designing Tapped In

NASA Astrophysics Data System (ADS)

Farooq, Umer; Schank, Patricia; Harris, Alexandra; Fusco, Judith; Schlager, Mark

Community computing has recently grown to become a major research area in human-computer interaction. One of the objectives of community computing is to support computer-supported cooperative work among distributed collaborators working toward shared professional goals in online communities of practice. A core issue in designing and developing community computing infrastructures — the underlying sociotechnical layer that supports communitarian activities — is sustainability. Many community computing initiatives fail because the underlying infrastructure does not meet end user requirements; the community is unable to maintain a critical mass of users consistently over time; it generates insufficient social capital to support significant contributions by members of the community; or, as typically happens with funded initiatives, financial and human capital resource become unavailable to further maintain the infrastructure. On the basis of more than 9 years of design experience with Tapped In-an online community of practice for education professionals — we present a case study that discusses four design interventions that have sustained the Tapped In infrastructure and its community to date. These interventions represent broader design strategies for developing online environments for professional communities of practice.

A survey of GPU-based acceleration techniques in MRI reconstructions

PubMed Central

Wang, Haifeng; Peng, Hanchuan; Chang, Yuchou

2018-01-01

Image reconstruction in magnetic resonance imaging (MRI) clinical applications has become increasingly more complicated. However, diagnostic and treatment require very fast computational procedure. Modern competitive platforms of graphics processing unit (GPU) have been used to make high-performance parallel computations available, and attractive to common consumers for computing massively parallel reconstruction problems at commodity price. GPUs have also become more and more important for reconstruction computations, especially when deep learning starts to be applied into MRI reconstruction. The motivation of this survey is to review the image reconstruction schemes of GPU computing for MRI applications and provide a summary reference for researchers in MRI community. PMID:29675361

A survey of GPU-based acceleration techniques in MRI reconstructions.

PubMed

Wang, Haifeng; Peng, Hanchuan; Chang, Yuchou; Liang, Dong

2018-03-01

Image reconstruction in magnetic resonance imaging (MRI) clinical applications has become increasingly more complicated. However, diagnostic and treatment require very fast computational procedure. Modern competitive platforms of graphics processing unit (GPU) have been used to make high-performance parallel computations available, and attractive to common consumers for computing massively parallel reconstruction problems at commodity price. GPUs have also become more and more important for reconstruction computations, especially when deep learning starts to be applied into MRI reconstruction. The motivation of this survey is to review the image reconstruction schemes of GPU computing for MRI applications and provide a summary reference for researchers in MRI community.

What do computer scientists tweet? Analyzing the link-sharing practice on Twitter.

PubMed

Schmitt, Marco; Jäschke, Robert

2017-01-01

Twitter communication has permeated every sphere of society. To highlight and share small pieces of information with possibly vast audiences or small circles of the interested has some value in almost any aspect of social life. But what is the value exactly for a scientific field? We perform a comprehensive study of computer scientists using Twitter and their tweeting behavior concerning the sharing of web links. Discerning the domains, hosts and individual web pages being tweeted and the differences between computer scientists and a Twitter sample enables us to look in depth at the Twitter-based information sharing practices of a scientific community. Additionally, we aim at providing a deeper understanding of the role and impact of altmetrics in computer science and give a glance at the publications mentioned on Twitter that are most relevant for the computer science community. Our results show a link sharing culture that concentrates more heavily on public and professional quality information than the Twitter sample does. The results also show a broad variety in linked sources and especially in linked publications with some publications clearly related to community-specific interests of computer scientists, while others with a strong relation to attention mechanisms in social media. This refers to the observation that Twitter is a hybrid form of social media between an information service and a social network service. Overall the computer scientists' style of usage seems to be more on the information-oriented side and to some degree also on professional usage. Therefore, altmetrics are of considerable use in analyzing computer science.

What do computer scientists tweet? Analyzing the link-sharing practice on Twitter

PubMed Central

Schmitt, Marco

2017-01-01

Twitter communication has permeated every sphere of society. To highlight and share small pieces of information with possibly vast audiences or small circles of the interested has some value in almost any aspect of social life. But what is the value exactly for a scientific field? We perform a comprehensive study of computer scientists using Twitter and their tweeting behavior concerning the sharing of web links. Discerning the domains, hosts and individual web pages being tweeted and the differences between computer scientists and a Twitter sample enables us to look in depth at the Twitter-based information sharing practices of a scientific community. Additionally, we aim at providing a deeper understanding of the role and impact of altmetrics in computer science and give a glance at the publications mentioned on Twitter that are most relevant for the computer science community. Our results show a link sharing culture that concentrates more heavily on public and professional quality information than the Twitter sample does. The results also show a broad variety in linked sources and especially in linked publications with some publications clearly related to community-specific interests of computer scientists, while others with a strong relation to attention mechanisms in social media. This refers to the observation that Twitter is a hybrid form of social media between an information service and a social network service. Overall the computer scientists’ style of usage seems to be more on the information-oriented side and to some degree also on professional usage. Therefore, altmetrics are of considerable use in analyzing computer science. PMID:28636619

The Centre of High-Performance Scientific Computing, Geoverbund, ABC/J - Geosciences enabled by HPSC

NASA Astrophysics Data System (ADS)

Kollet, Stefan; Görgen, Klaus; Vereecken, Harry; Gasper, Fabian; Hendricks-Franssen, Harrie-Jan; Keune, Jessica; Kulkarni, Ketan; Kurtz, Wolfgang; Sharples, Wendy; Shrestha, Prabhakar; Simmer, Clemens; Sulis, Mauro; Vanderborght, Jan

2016-04-01

The Centre of High-Performance Scientific Computing (HPSC TerrSys) was founded 2011 to establish a centre of competence in high-performance scientific computing in terrestrial systems and the geosciences enabling fundamental and applied geoscientific research in the Geoverbund ABC/J (geoscientfic research alliance of the Universities of Aachen, Cologne, Bonn and the Research Centre Jülich, Germany). The specific goals of HPSC TerrSys are to achieve relevance at the national and international level in (i) the development and application of HPSC technologies in the geoscientific community; (ii) student education; (iii) HPSC services and support also to the wider geoscientific community; and in (iv) the industry and public sectors via e.g., useful applications and data products. A key feature of HPSC TerrSys is the Simulation Laboratory Terrestrial Systems, which is located at the Jülich Supercomputing Centre (JSC) and provides extensive capabilities with respect to porting, profiling, tuning and performance monitoring of geoscientific software in JSC's supercomputing environment. We will present a summary of success stories of HPSC applications including integrated terrestrial model development, parallel profiling and its application from watersheds to the continent; massively parallel data assimilation using physics-based models and ensemble methods; quasi-operational terrestrial water and energy monitoring; and convection permitting climate simulations over Europe. The success stories stress the need for a formalized education of students in the application of HPSC technologies in future.

Facial Performance Transfer via Deformable Models and Parametric Correspondence.

PubMed

Asthana, Akshay; de la Hunty, Miles; Dhall, Abhinav; Goecke, Roland

2012-09-01

The issue of transferring facial performance from one person's face to another's has been an area of interest for the movie industry and the computer graphics community for quite some time. In recent years, deformable face models, such as the Active Appearance Model (AAM), have made it possible to track and synthesize faces in real time. Not surprisingly, deformable face model-based approaches for facial performance transfer have gained tremendous interest in the computer vision and graphics community. In this paper, we focus on the problem of real-time facial performance transfer using the AAM framework. We propose a novel approach of learning the mapping between the parameters of two completely independent AAMs, using them to facilitate the facial performance transfer in a more realistic manner than previous approaches. The main advantage of modeling this parametric correspondence is that it allows a "meaningful" transfer of both the nonrigid shape and texture across faces irrespective of the speakers' gender, shape, and size of the faces, and illumination conditions. We explore linear and nonlinear methods for modeling the parametric correspondence between the AAMs and show that the sparse linear regression method performs the best. Moreover, we show the utility of the proposed framework for a cross-language facial performance transfer that is an area of interest for the movie dubbing industry.

Enabling the First Ever Measurement of Coherent Neutrino Scattering Through Background Neutron Measurements.

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

Reyna, David; Betty, Rita

Using High Performance Computing to Examine the Processes of Neurogenesis Underlying Pattern Separation/Completion of Episodic Information - Sandia researchers developed novel methods and metrics for studying the computational function of neurogenesis,thus generating substantial impact to the neuroscience and neural computing communities. This work could benefit applications in machine learning and other analysis activities. The purpose of this project was to computationally model the impact of neural population dynamics within the neurobiological memory system in order to examine how subareas in the brain enable pattern separation and completion of information in memory across time as associated experiences.

ASC ATDM Level 2 Milestone #5325: Asynchronous Many-Task Runtime System Analysis and Assessment for Next Generation Platforms.

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

Baker, Gavin Matthew; Bettencourt, Matthew Tyler; Bova, Steven W.

2015-09-01

This report provides in-depth information and analysis to help create a technical road map for developing next- generation Orogramming mocleN and runtime systemsl that support Advanced Simulation and Computing (ASC) work- load requirements. The focus herein is on 4synchronous many-task (AMT) model and runtime systems, which are of great interest in the context of "Oriascale7 computing, as they hold the promise to address key issues associated with future extreme-scale computer architectures. This report includes a thorough qualitative and quantitative examination of three best-of-class AIM] runtime systemsHCharm-HE, Legion, and Uintah, all of which are in use as part of the Centers.more » The studies focus on each of the runtimes' programmability, performance, and mutability. Through the experiments and analysis presented, several overarching Predictive Science Academic Alliance Program II (PSAAP-II) Ascl findings emerge. From a performance perspective, AIVT11runtimes show tremendous potential for addressing extreme- scale challenges. Empirical studies show an AM11 runtime can mitigate performance heterogeneity inherent to the machine itself and that Message Passing Interface (MP1) and AM11runtimes perform comparably under balanced con- ditions. From a programmability and mutability perspective however, none of the runtimes in this study are currently ready for use in developing production-ready Sandia ASCIapplications. The report concludes by recommending a co- design path forward, wherein application, programming model, and runtime system developers work together to define requirements and solutions. Such a requirements-driven co-design approach benefits the community as a whole, with widespread community engagement mitigating risk for both application developers developers. and high-performance computing inntime systein« less

Community detection in complex networks using proximate support vector clustering

NASA Astrophysics Data System (ADS)

Wang, Feifan; Zhang, Baihai; Chai, Senchun; Xia, Yuanqing

2018-03-01

Community structure, one of the most attention attracting properties in complex networks, has been a cornerstone in advances of various scientific branches. A number of tools have been involved in recent studies concentrating on the community detection algorithms. In this paper, we propose a support vector clustering method based on a proximity graph, owing to which the introduced algorithm surpasses the traditional support vector approach both in accuracy and complexity. Results of extensive experiments undertaken on computer generated networks and real world data sets illustrate competent performances in comparison with the other counterparts.

An Application-Based Performance Evaluation of NASAs Nebula Cloud Computing Platform

NASA Technical Reports Server (NTRS)

Saini, Subhash; Heistand, Steve; Jin, Haoqiang; Chang, Johnny; Hood, Robert T.; Mehrotra, Piyush; Biswas, Rupak

2012-01-01

The high performance computing (HPC) community has shown tremendous interest in exploring cloud computing as it promises high potential. In this paper, we examine the feasibility, performance, and scalability of production quality scientific and engineering applications of interest to NASA on NASA's cloud computing platform, called Nebula, hosted at Ames Research Center. This work represents the comprehensive evaluation of Nebula using NUTTCP, HPCC, NPB, I/O, and MPI function benchmarks as well as four applications representative of the NASA HPC workload. Specifically, we compare Nebula performance on some of these benchmarks and applications to that of NASA s Pleiades supercomputer, a traditional HPC system. We also investigate the impact of virtIO and jumbo frames on interconnect performance. Overall results indicate that on Nebula (i) virtIO and jumbo frames improve network bandwidth by a factor of 5x, (ii) there is a significant virtualization layer overhead of about 10% to 25%, (iii) write performance is lower by a factor of 25x, (iv) latency for short MPI messages is very high, and (v) overall performance is 15% to 48% lower than that on Pleiades for NASA HPC applications. We also comment on the usability of the cloud platform.

P2P Technology for High-Performance Computing: An Overview

NASA Technical Reports Server (NTRS)

Follen, Gregory J. (Technical Monitor); Berry, Jason

2003-01-01

The transition from cluster computing to peer-to-peer (P2P) high-performance computing has recently attracted the attention of the computer science community. It has been recognized that existing local networks and dedicated clusters of headless workstations can serve as inexpensive yet powerful virtual supercomputers. It has also been recognized that the vast number of lower-end computers connected to the Internet stay idle for as long as 90% of the time. The growing speed of Internet connections and the high availability of free CPU time encourage exploration of the possibility to use the whole Internet rather than local clusters as massively parallel yet almost freely available P2P supercomputer. As a part of a larger project on P2P high-performance computing, it has been my goal to compile an overview of the 2P2 paradigm. I have studied various P2P platforms and I have compiled systematic brief descriptions of their most important characteristics. I have also experimented and obtained hands-on experience with selected P2P platforms focusing on those that seem promising with respect to P2P high-performance computing. I have also compiled relevant literature and web references. I have prepared a draft technical report and I have summarized my findings in a poster paper.

Sampling Approaches for Multi-Domain Internet Performance Measurement Infrastructures

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

Calyam, Prasad

2014-09-15

The next-generation of high-performance networks being developed in DOE communities are critical for supporting current and emerging data-intensive science applications. The goal of this project is to investigate multi-domain network status sampling techniques and tools to measure/analyze performance, and thereby provide “network awareness” to end-users and network operators in DOE communities. We leverage the infrastructure and datasets available through perfSONAR, which is a multi-domain measurement framework that has been widely deployed in high-performance computing and networking communities; the DOE community is a core developer and the largest adopter of perfSONAR. Our investigations include development of semantic scheduling algorithms, measurement federationmore » policies, and tools to sample multi-domain and multi-layer network status within perfSONAR deployments. We validate our algorithms and policies with end-to-end measurement analysis tools for various monitoring objectives such as network weather forecasting, anomaly detection, and fault-diagnosis. In addition, we develop a multi-domain architecture for an enterprise-specific perfSONAR deployment that can implement monitoring-objective based sampling and that adheres to any domain-specific measurement policies.« less

Mild Cognitive Impairment: What Do We Do Now?

MedlinePlus

... in studies that focus on individual health, computer use and technology, family relationships and caregiving, community services, housing, and ... Reserve Officer Training Corps Navy Research Centers Science, Technology, and ... of Education School of Performing Arts College Office of the ...

Deterministic and fuzzy-based methods to evaluate community resilience

NASA Astrophysics Data System (ADS)

Kammouh, Omar; Noori, Ali Zamani; Taurino, Veronica; Mahin, Stephen A.; Cimellaro, Gian Paolo

2018-04-01

Community resilience is becoming a growing concern for authorities and decision makers. This paper introduces two indicator-based methods to evaluate the resilience of communities based on the PEOPLES framework. PEOPLES is a multi-layered framework that defines community resilience using seven dimensions. Each of the dimensions is described through a set of resilience indicators collected from literature and they are linked to a measure allowing the analytical computation of the indicator's performance. The first method proposed in this paper requires data on previous disasters as an input and returns as output a performance function for each indicator and a performance function for the whole community. The second method exploits a knowledge-based fuzzy modeling for its implementation. This method allows a quantitative evaluation of the PEOPLES indicators using descriptive knowledge rather than deterministic data including the uncertainty involved in the analysis. The output of the fuzzy-based method is a resilience index for each indicator as well as a resilience index for the community. The paper also introduces an open source online tool in which the first method is implemented. A case study illustrating the application of the first method and the usage of the tool is also provided in the paper.

High-Performance Java Codes for Computational Fluid Dynamics

NASA Technical Reports Server (NTRS)

Riley, Christopher; Chatterjee, Siddhartha; Biswas, Rupak; Biegel, Bryan (Technical Monitor)

2001-01-01

The computational science community is reluctant to write large-scale computationally -intensive applications in Java due to concerns over Java's poor performance, despite the claimed software engineering advantages of its object-oriented features. Naive Java implementations of numerical algorithms can perform poorly compared to corresponding Fortran or C implementations. To achieve high performance, Java applications must be designed with good performance as a primary goal. This paper presents the object-oriented design and implementation of two real-world applications from the field of Computational Fluid Dynamics (CFD): a finite-volume fluid flow solver (LAURA, from NASA Langley Research Center), and an unstructured mesh adaptation algorithm (2D_TAG, from NASA Ames Research Center). This work builds on our previous experience with the design of high-performance numerical libraries in Java. We examine the performance of the applications using the currently available Java infrastructure and show that the Java version of the flow solver LAURA performs almost within a factor of 2 of the original procedural version. Our Java version of the mesh adaptation algorithm 2D_TAG performs within a factor of 1.5 of its original procedural version on certain platforms. Our results demonstrate that object-oriented software design principles are not necessarily inimical to high performance.

Implementation of Virtualization Oriented Architecture: A Healthcare Industry Case Study

NASA Astrophysics Data System (ADS)

Rao, G. Subrahmanya Vrk; Parthasarathi, Jinka; Karthik, Sundararaman; Rao, Gvn Appa; Ganesan, Suresh

This paper presents a Virtualization Oriented Architecture (VOA) and an implementation of VOA for Hridaya - a Telemedicine initiative. Hadoop Compute cloud was established at our labs and jobs which require a massive computing capability such as ECG signal analysis were submitted and the study is presented in this current paper. VOA takes advantage of inexpensive community PCs and provides added advantages such as Fault Tolerance, Scalability, Performance, High Availability.

GAMUT: GPU accelerated microRNA analysis to uncover target genes through CUDA-miRanda

PubMed Central

2014-01-01

Background Non-coding sequences such as microRNAs have important roles in disease processes. Computational microRNA target identification (CMTI) is becoming increasingly important since traditional experimental methods for target identification pose many difficulties. These methods are time-consuming, costly, and often need guidance from computational methods to narrow down candidate genes anyway. However, most CMTI methods are computationally demanding, since they need to handle not only several million query microRNA and reference RNA pairs, but also several million nucleotide comparisons within each given pair. Thus, the need to perform microRNA identification at such large scale has increased the demand for parallel computing. Methods Although most CMTI programs (e.g., the miRanda algorithm) are based on a modified Smith-Waterman (SW) algorithm, the existing parallel SW implementations (e.g., CUDASW++ 2.0/3.0, SWIPE) are unable to meet this demand in CMTI tasks. We present CUDA-miRanda, a fast microRNA target identification algorithm that takes advantage of massively parallel computing on Graphics Processing Units (GPU) using NVIDIA's Compute Unified Device Architecture (CUDA). CUDA-miRanda specifically focuses on the local alignment of short (i.e., ≤ 32 nucleotides) sequences against longer reference sequences (e.g., 20K nucleotides). Moreover, the proposed algorithm is able to report multiple alignments (up to 191 top scores) and the corresponding traceback sequences for any given (query sequence, reference sequence) pair. Results Speeds over 5.36 Giga Cell Updates Per Second (GCUPs) are achieved on a server with 4 NVIDIA Tesla M2090 GPUs. Compared to the original miRanda algorithm, which is evaluated on an Intel Xeon E5620@2.4 GHz CPU, the experimental results show up to 166 times performance gains in terms of execution time. In addition, we have verified that the exact same targets were predicted in both CUDA-miRanda and the original miRanda implementations through multiple test datasets. Conclusions We offer a GPU-based alternative to high performance compute (HPC) that can be developed locally at a relatively small cost. The community of GPU developers in the biomedical research community, particularly for genome analysis, is still growing. With increasing shared resources, this community will be able to advance CMTI in a very significant manner. Our source code is available at https://sourceforge.net/projects/cudamiranda/. PMID:25077821

Computational Aspects of Data Assimilation and the ESMF

NASA Technical Reports Server (NTRS)

daSilva, A.

2003-01-01

The scientific challenge of developing advanced data assimilation applications is a daunting task. Independently developed components may have incompatible interfaces or may be written in different computer languages. The high-performance computer (HPC) platforms required by numerically intensive Earth system applications are complex, varied, rapidly evolving and multi-part systems themselves. Since the market for high-end platforms is relatively small, there is little robust middleware available to buffer the modeler from the difficulties of HPC programming. To complicate matters further, the collaborations required to develop large Earth system applications often span initiatives, institutions and agencies, involve geoscience, software engineering, and computer science communities, and cross national borders.The Earth System Modeling Framework (ESMF) project is a concerted response to these challenges. Its goal is to increase software reuse, interoperability, ease of use and performance in Earth system models through the use of a common software framework, developed in an open manner by leaders in the modeling community. The ESMF addresses the technical and to some extent the cultural - aspects of Earth system modeling, laying the groundwork for addressing the more difficult scientific aspects, such as the physical compatibility of components, in the future. In this talk we will discuss the general philosophy and architecture of the ESMF, focussing on those capabilities useful for developing advanced data assimilation applications.

Welcome to the NASA High Performance Computing and Communications Computational Aerosciences (CAS) Workshop 2000

NASA Technical Reports Server (NTRS)

Schulbach, Catherine H. (Editor)

2000-01-01

The purpose of the CAS workshop is to bring together NASA's scientists and engineers and their counterparts in industry, other government agencies, and academia working in the Computational Aerosciences and related fields. This workshop is part of the technology transfer plan of the NASA High Performance Computing and Communications (HPCC) Program. Specific objectives of the CAS workshop are to: (1) communicate the goals and objectives of HPCC and CAS, (2) promote and disseminate CAS technology within the appropriate technical communities, including NASA, industry, academia, and other government labs, (3) help promote synergy among CAS and other HPCC scientists, and (4) permit feedback from peer researchers on issues facing High Performance Computing in general and the CAS project in particular. This year we had a number of exciting presentations in the traditional aeronautics, aerospace sciences, and high-end computing areas and in the less familiar (to many of us affiliated with CAS) earth science, space science, and revolutionary computing areas. Presentations of more than 40 high quality papers were organized into ten sessions and presented over the three-day workshop. The proceedings are organized here for easy access: by author, title and topic.

A large-scale solar dynamics observatory image dataset for computer vision applications.

PubMed

Kucuk, Ahmet; Banda, Juan M; Angryk, Rafal A

2017-01-01

The National Aeronautics Space Agency (NASA) Solar Dynamics Observatory (SDO) mission has given us unprecedented insight into the Sun's activity. By capturing approximately 70,000 images a day, this mission has created one of the richest and biggest repositories of solar image data available to mankind. With such massive amounts of information, researchers have been able to produce great advances in detecting solar events. In this resource, we compile SDO solar data into a single repository in order to provide the computer vision community with a standardized and curated large-scale dataset of several hundred thousand solar events found on high resolution solar images. This publicly available resource, along with the generation source code, will accelerate computer vision research on NASA's solar image data by reducing the amount of time spent performing data acquisition and curation from the multiple sources we have compiled. By improving the quality of the data with thorough curation, we anticipate a wider adoption and interest from the computer vision to the solar physics community.

INDIGO-DataCloud solutions for Earth Sciences

NASA Astrophysics Data System (ADS)

Aguilar Gómez, Fernando; de Lucas, Jesús Marco; Fiore, Sandro; Monna, Stephen; Chen, Yin

2017-04-01

INDIGO-DataCloud (https://www.indigo-datacloud.eu/) is a European Commission funded project aiming to develop a data and computing platform targeting scientific communities, deployable on multiple hardware and provisioned over hybrid (private or public) e-infrastructures. The development of INDIGO solutions covers the different layers in cloud computing (IaaS, PaaS, SaaS), and provides tools to exploit resources like HPC or GPGPUs. INDIGO is oriented to support European Scientific research communities, that are well represented in the project. Twelve different Case Studies have been analyzed in detail from different fields: Biological & Medical sciences, Social sciences & Humanities, Environmental and Earth sciences and Physics & Astrophysics. INDIGO-DataCloud provides solutions to emerging challenges in Earth Science like: -Enabling an easy deployment of community services at different cloud sites. Many Earth Science research infrastructures often involve distributed observation stations across countries, and also have distributed data centers to support the corresponding data acquisition and curation. There is a need to easily deploy new data center services while the research infrastructure continuous spans. As an example: LifeWatch (ESFRI, Ecosystems and Biodiversity) uses INDIGO solutions to manage the deployment of services to perform complex hydrodynamics and water quality modelling over a Cloud Computing environment, predicting algae blooms, using the Docker technology: TOSCA requirement description, Docker repository, Orchestrator for deployment, AAI (AuthN, AuthZ) and OneData (Distributed Storage System). -Supporting Big Data Analysis. Nowadays, many Earth Science research communities produce large amounts of data and and are challenged by the difficulties of processing and analysing it. A climate models intercomparison data analysis case study for the European Network for Earth System Modelling (ENES) community has been setup, based on the Ophidia big data analysis framework and the Kepler workflow management system. Such services normally involve a large and distributed set of data and computing resources. In this regard, this case study exploits the INDIGO PaaS for a flexible and dynamic allocation of the resources at the infrastructural level. -Providing Distributed Data Storage Solutions. In order to allow scientific communities to perform heavy computation on huge datasets, INDIGO provides global data access solutions allowing researchers to access data in a distributed environment like fashion regardless of its location, and also to publish and share their research results with public or close communities. INDIGO solutions that support the access to distributed data storage (OneData) are being tested on EMSO infrastructure (Ocean Sciences and Geohazards) data. Another aspect of interest for the EMSO community is in efficient data processing by exploiting INDIGO services like PaaS Orchestrator. Further, for HPC exploitation, a new solution named Udocker has been implemented, enabling users to execute docker containers in supercomputers, without requiring administration privileges. This presentation will overview INDIGO solutions that are interesting and useful for Earth science communities and will show how they can be applied to other Case Studies.

Experience Paper: Software Engineering and Community Codes Track in ATPESC

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

Dubey, Anshu; Riley, Katherine M.

Argonne Training Program in Extreme Scale Computing (ATPESC) was started by the Argonne National Laboratory with the objective of expanding the ranks of better prepared users of high performance computing (HPC) machines. One of the unique aspects of the program was inclusion of software engineering and community codes track. The inclusion was motivated by the observation that the projects with a good scientific and software process were better able to meet their scientific goals. In this paper we present our experience of running the software track from the beginning of the program until now. We discuss the motivations, the reception,more » and the evolution of the track over the years. We welcome discussion and input from the community to enhance the track in ATPESC, and also to facilitate inclusion of similar tracks in other HPC oriented training programs.« less

Simulating Microbial Community Patterning Using Biocellion

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

Kang, Seung-Hwa; Kahan, Simon H.; Momeni, Babak

2014-04-17

Mathematical modeling and computer simulation are important tools for understanding complex interactions between cells and their biotic and abiotic environment: similarities and differences between modeled and observed behavior provide the basis for hypothesis forma- tion. Momeni et al. [5] investigated pattern formation in communities of yeast strains engaging in different types of ecological interactions, comparing the predictions of mathematical modeling and simulation to actual patterns observed in wet-lab experiments. However, simu- lations of millions of cells in a three-dimensional community are ex- tremely time-consuming. One simulation run in MATLAB may take a week or longer, inhibiting exploration of the vastmore » space of parameter combinations and assumptions. Improving the speed, scale, and accu- racy of such simulations facilitates hypothesis formation and expedites discovery. Biocellion is a high performance software framework for ac- celerating discrete agent-based simulation of biological systems with millions to trillions of cells. Simulations of comparable scale and accu- racy to those taking a week of computer time using MATLAB require just hours using Biocellion on a multicore workstation. Biocellion fur- ther accelerates large scale, high resolution simulations using cluster computers by partitioning the work to run on multiple compute nodes. Biocellion targets computational biologists who have mathematical modeling backgrounds and basic C++ programming skills. This chap- ter describes the necessary steps to adapt the original Momeni et al.'s model to the Biocellion framework as a case study.« less

Three real-time architectures - A study using reward models

NASA Technical Reports Server (NTRS)

Sjogren, J. A.; Smith, R. M.

1990-01-01

Numerous applications in the area of computer system analysis can be effectively studied with Markov reward models. These models describe the evolutionary behavior of the computer system by a continuous-time Markov chain, and a reward rate is associated with each state. In reliability/availability models, upstates have reward rate 1, and down states have reward rate zero associated with them. In a combined model of performance and reliability, the reward rate of a state may be the computational capacity, or a related performance measure. Steady-state expected reward rate and expected instantaneous reward rate are clearly useful measures which can be extracted from the Markov reward model. The diversity of areas where Markov reward models may be used is illustrated with a comparative study of three examples of interest to the fault tolerant computing community.

Estimating rates of local species extinction, colonization and turnover in animal communities

USGS Publications Warehouse

Nichols, James D.; Boulinier, T.; Hines, J.E.; Pollock, K.H.; Sauer, J.R.

1998-01-01

Species richness has been identified as a useful state variable for conservation and management purposes. Changes in richness over time provide a basis for predicting and evaluating community responses to management, to natural disturbance, and to changes in factors such as community composition (e.g., the removal of a keystone species). Probabilistic capture-recapture models have been used recently to estimate species richness from species count and presence-absence data. These models do not require the common assumption that all species are detected in sampling efforts. We extend this approach to the development of estimators useful for studying the vital rates responsible for changes in animal communities over time; rates of local species extinction, turnover, and colonization. Our approach to estimation is based on capture-recapture models for closed animal populations that permit heterogeneity in detection probabilities among the different species in the sampled community. We have developed a computer program, COMDYN, to compute many of these estimators and associated bootstrap variances. Analyses using data from the North American Breeding Bird Survey (BBS) suggested that the estimators performed reasonably well. We recommend estimators based on probabilistic modeling for future work on community responses to management efforts as well as on basic questions about community dynamics.

Lewis Structures Technology, 1988. Volume 3: Structural Integrity Fatigue and Fracture Wind Turbines HOST

NASA Technical Reports Server (NTRS)

1988-01-01

The charter of the Structures Division is to perform and disseminate results of research conducted in support of aerospace engine structures. These results have a wide range of applicability to practioners of structural engineering mechanics beyond the aerospace arena. The specific purpose of the symposium was to familiarize the engineering structures community with the depth and range of research performed by the division and its academic and industrial partners. Sessions covered vibration control, fracture mechanics, ceramic component reliability, parallel computing, nondestructive evaluation, constitutive models and experimental capabilities, dynamic systems, fatigue and damage, wind turbines, hot section technology (HOST), aeroelasticity, structural mechanics codes, computational methods for dynamics, structural optimization, and applications of structural dynamics, and structural mechanics computer codes.

Online Community Detection for Large Complex Networks

PubMed Central

Pan, Gang; Zhang, Wangsheng; Wu, Zhaohui; Li, Shijian

2014-01-01

Complex networks describe a wide range of systems in nature and society. To understand complex networks, it is crucial to investigate their community structure. In this paper, we develop an online community detection algorithm with linear time complexity for large complex networks. Our algorithm processes a network edge by edge in the order that the network is fed to the algorithm. If a new edge is added, it just updates the existing community structure in constant time, and does not need to re-compute the whole network. Therefore, it can efficiently process large networks in real time. Our algorithm optimizes expected modularity instead of modularity at each step to avoid poor performance. The experiments are carried out using 11 public data sets, and are measured by two criteria, modularity and NMI (Normalized Mutual Information). The results show that our algorithm's running time is less than the commonly used Louvain algorithm while it gives competitive performance. PMID:25061683

Performance Analysis, Modeling and Scaling of HPC Applications and Tools

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

Bhatele, Abhinav

2016-01-13

E cient use of supercomputers at DOE centers is vital for maximizing system throughput, mini- mizing energy costs and enabling science breakthroughs faster. This requires complementary e orts along several directions to optimize the performance of scienti c simulation codes and the under- lying runtimes and software stacks. This in turn requires providing scalable performance analysis tools and modeling techniques that can provide feedback to physicists and computer scientists developing the simulation codes and runtimes respectively. The PAMS project is using time allocations on supercomputers at ALCF, NERSC and OLCF to further the goals described above by performing research alongmore » the following fronts: 1. Scaling Study of HPC applications; 2. Evaluation of Programming Models; 3. Hardening of Performance Tools; 4. Performance Modeling of Irregular Codes; and 5. Statistical Analysis of Historical Performance Data. We are a team of computer and computational scientists funded by both DOE/NNSA and DOE/ ASCR programs such as ECRP, XStack (Traleika Glacier, PIPER), ExaOSR (ARGO), SDMAV II (MONA) and PSAAP II (XPACC). This allocation will enable us to study big data issues when analyzing performance on leadership computing class systems and to assist the HPC community in making the most e ective use of these resources.« less

Red Storm usage model :Version 1.12.

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

Jefferson, Karen L.; Sturtevant, Judith E.

Red Storm is an Advanced Simulation and Computing (ASC) funded massively parallel supercomputer located at Sandia National Laboratories (SNL). The Red Storm Usage Model (RSUM) documents the capabilities and the environment provided for the FY05 Tri-Lab Level II Limited Availability Red Storm User Environment Milestone and the FY05 SNL Level II Limited Availability Red Storm Platform Milestone. This document describes specific capabilities, tools, and procedures to support both local and remote users. The model is focused on the needs of the ASC user working in the secure computing environments at Los Alamos National Laboratory (LANL), Lawrence Livermore National Laboratory (LLNL),more » and SNL. Additionally, the Red Storm Usage Model maps the provided capabilities to the Tri-Lab ASC Computing Environment (ACE) requirements. The ACE requirements reflect the high performance computing requirements for the ASC community and have been updated in FY05 to reflect the community's needs. For each section of the RSUM, Appendix I maps the ACE requirements to the Limited Availability User Environment capabilities and includes a description of ACE requirements met and those requirements that are not met in that particular section. The Red Storm Usage Model, along with the ACE mappings, has been issued and vetted throughout the Tri-Lab community.« less

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

Simon, Horst D.; Zorn, Manfred D.; Spengler, Sylvia J.

The pace of extraordinary advances in molecular biology has accelerated in the past decade due in large part to discoveries coming from genome projects on human and model organisms. The advances in the genome project so far, happening well ahead of schedule and under budget, have exceeded any dreams by its protagonists, let alone formal expectations. Biologists expect the next phase of the genome project to be even more startling in terms of dramatic breakthroughs in our understanding of human biology, the biology of health and of disease. Only today can biologists begin to envision the necessary experimental, computational andmore » theoretical steps necessary to exploit genome sequence information for its medical impact, its contribution to biotechnology and economic competitiveness, and its ultimate contribution to environmental quality. High performance computing has become one of the critical enabling technologies, which will help to translate this vision of future advances in biology into reality. Biologists are increasingly becoming aware of the potential of high performance computing. The goal of this tutorial is to introduce the exciting new developments in computational biology and genomics to the high performance computing community.« less

The GÉANT network: addressing current and future needs of the HEP community

NASA Astrophysics Data System (ADS)

Capone, Vincenzo; Usman, Mian

2015-12-01

The GÉANT infrastructure is the backbone that serves the scientific communities in Europe for their data movement needs and their access to international research and education networks. Using the extensive fibre footprint and infrastructure in Europe the GÉANT network delivers a portfolio of services aimed to best fit the specific needs of the users, including Authentication and Authorization Infrastructure, end-to-end performance monitoring, advanced network services (dynamic circuits, L2-L3VPN, MD-VPN). This talk will outline the factors that help the GÉANT network to respond to the needs of the High Energy Physics community, both in Europe and worldwide. The Pan-European network provides the connectivity between 40 European national research and education networks. In addition, GÉANT also connects the European NRENs to the R&E networks in other world region and has reach to over 110 NREN worldwide, making GÉANT the best connected Research and Education network, with its multiple intercontinental links to different continents e.g. North and South America, Africa and Asia-Pacific. The High Energy Physics computational needs have always had (and will keep having) a leading role among the scientific user groups of the GÉANT network: the LHCONE overlay network has been built, in collaboration with the other big world REN, specifically to address the peculiar needs of the LHC data movement. Recently, as a result of a series of coordinated efforts, the LHCONE network has been expanded to the Asia-Pacific area, and is going to include some of the main regional R&E network in the area. The LHC community is not the only one that is actively using a distributed computing model (hence the need for a high-performance network); new communities are arising, as BELLE II. GÉANT is deeply involved also with the BELLE II Experiment, to provide full support to their distributed computing model, along with a perfSONAR-based network monitoring system. GÉANT has also coordinated the setup of the network infrastructure to perform the BELLE II Trans-Atlantic Data Challenge, and has been active on helping the BELLE II community to sort out their end-to-end performance issues. In this talk we will provide information about the current GÉANT network architecture and of the international connectivity, along with the upcoming upgrades and the planned and foreseeable improvements. We will also describe the implementation of the solutions provided to support the LHC and BELLE II experiments.

Community Detection Algorithm Combining Stochastic Block Model and Attribute Data Clustering

NASA Astrophysics Data System (ADS)

Kataoka, Shun; Kobayashi, Takuto; Yasuda, Muneki; Tanaka, Kazuyuki

2016-11-01

We propose a new algorithm to detect the community structure in a network that utilizes both the network structure and vertex attribute data. Suppose we have the network structure together with the vertex attribute data, that is, the information assigned to each vertex associated with the community to which it belongs. The problem addressed this paper is the detection of the community structure from the information of both the network structure and the vertex attribute data. Our approach is based on the Bayesian approach that models the posterior probability distribution of the community labels. The detection of the community structure in our method is achieved by using belief propagation and an EM algorithm. We numerically verified the performance of our method using computer-generated networks and real-world networks.

High Performance Computing and Network Program. Hearing before the Subcommittee on Science of the Committee on Science, Space, and Technology, House of Representatives, One Hundred Third Congress, First Session.

ERIC Educational Resources Information Center

Congress of the U.S., Washington, DC. House Committee on Science, Space and Technology.

The purpose of the hearing transcribed in this document was to obtain the views of representatives of network user and provider communities regarding the path the National Science Foundation (NSF) is taking for recompetition of the NSFNET computer network. In particular the committee was interested in the consistency of the evolution of NSFNET…

Lewis Structures Technology, 1988. Volume 1: Structural Dynamics

NASA Technical Reports Server (NTRS)

1988-01-01

The specific purpose of the symposium was to familiarize the engineering structures community with the depth and range of research performed by the Structures Division of the Lewis Research Center and its academic and industrial partners. Sessions covered vibration control, fracture mechanics, ceramic component reliability, parallel computing, nondestructive testing, dynamical systems, fatigue and damage, wind turbines, hot section technology, structural mechanics codes, computational methods for dynamics, structural optimization, and applications of structural dynamics.

CyberShake: Running Seismic Hazard Workflows on Distributed HPC Resources

NASA Astrophysics Data System (ADS)

Callaghan, S.; Maechling, P. J.; Graves, R. W.; Gill, D.; Olsen, K. B.; Milner, K. R.; Yu, J.; Jordan, T. H.

2013-12-01

As part of its program of earthquake system science research, the Southern California Earthquake Center (SCEC) has developed a simulation platform, CyberShake, to perform physics-based probabilistic seismic hazard analysis (PSHA) using 3D deterministic wave propagation simulations. CyberShake performs PSHA by simulating a tensor-valued wavefield of Strain Green Tensors, and then using seismic reciprocity to calculate synthetic seismograms for about 415,000 events per site of interest. These seismograms are processed to compute ground motion intensity measures, which are then combined with probabilities from an earthquake rupture forecast to produce a site-specific hazard curve. Seismic hazard curves for hundreds of sites in a region can be used to calculate a seismic hazard map, representing the seismic hazard for a region. We present a recently completed PHSA study in which we calculated four CyberShake seismic hazard maps for the Southern California area to compare how CyberShake hazard results are affected by different SGT computational codes (AWP-ODC and AWP-RWG) and different community velocity models (Community Velocity Model - SCEC (CVM-S4) v11.11 and Community Velocity Model - Harvard (CVM-H) v11.9). We present our approach to running workflow applications on distributed HPC resources, including systems without support for remote job submission. We show how our approach extends the benefits of scientific workflows, such as job and data management, to large-scale applications on Track 1 and Leadership class open-science HPC resources. We used our distributed workflow approach to perform CyberShake Study 13.4 on two new NSF open-science HPC computing resources, Blue Waters and Stampede, executing over 470 million tasks to calculate physics-based hazard curves for 286 locations in the Southern California region. For each location, we calculated seismic hazard curves with two different community velocity models and two different SGT codes, resulting in over 1100 hazard curves. We will report on the performance of this CyberShake study, four times larger than previous studies. Additionally, we will examine the challenges we face applying these workflow techniques to additional open-science HPC systems and discuss whether our workflow solutions continue to provide value to our large-scale PSHA calculations.

Expanding the user base beyond HEP for the Ganga distributed analysis user interface

NASA Astrophysics Data System (ADS)

Currie, R.; Egede, U.; Richards, A.; Slater, M.; Williams, M.

2017-10-01

This document presents the result of recent developments within Ganga[1] project to support users from new communities outside of HEP. In particular I will examine the case of users from the Large Scale Survey Telescope (LSST) group looking to use resources provided by the UK based GridPP[2][3] DIRAC[4][5] instance. An example use case is work performed with users from the LSST Virtual Organisation (VO) to distribute the workflow used for galaxy shape identification analyses. This work highlighted some LSST specific challenges which could be well solved by common tools within the HEP community. As a result of this work the LSST community was able to take advantage of GridPP[2][3] resources to perform large computing tasks within the UK.

Students as Assets.

ERIC Educational Resources Information Center

Lipsky, Martin S.; Egan, Mari

1999-01-01

Lists ten ways in which having medical students in the community physician's office can be of value to preceptors, including providing valuable but time-consuming patient services, following up on phone calls, providing computer skills, performing minor office procedures, reviewing medical records, helping with paperwork, stimulating preceptor…

Teaching Computation/Shopping Skills to Mentally Retarded Adults.

ERIC Educational Resources Information Center

Matson, Johnny L.; Long, Sue

1986-01-01

Three moderately/mildly retarded adults were trained in adaptive community skills. Treatment involved instructions, performance feedback, social reinforcement, in-vivo modeling, self-evaluation, and social and tangible reinforcement. Rapid and dramatic improvements occurred soon after treatment began. Skills generalized to other shopping…

Predicting Microbial Fuel Cell Biofilm Communities and Bioreactor Performance using Artificial Neural Networks.

PubMed

Lesnik, Keaton Larson; Liu, Hong

2017-09-19

The complex interactions that occur in mixed-species bioelectrochemical reactors, like microbial fuel cells (MFCs), make accurate predictions of performance outcomes under untested conditions difficult. While direct correlations between any individual waste stream characteristic or microbial community structure and reactor performance have not been able to be directly established, the increase in sequencing data and readily available computational power enables the development of alternate approaches. In the current study, 33 MFCs were evaluated under a range of conditions including eight separate substrates and three different wastewaters. Artificial Neural Networks (ANNs) were used to establish mathematical relationships between wastewater/solution characteristics, biofilm communities, and reactor performance. ANN models that incorporated biotic interactions predicted reactor performance outcomes more accurately than those that did not. The average percent error of power density predictions was 16.01 ± 4.35%, while the average percent error of Coulombic efficiency and COD removal rate predictions were 1.77 ± 0.57% and 4.07 ± 1.06%, respectively. Predictions of power density improved to within 5.76 ± 3.16% percent error through classifying taxonomic data at the family versus class level. Results suggest that the microbial communities and performance of bioelectrochemical systems can be accurately predicted using data-mining, machine-learning techniques.

The computer-communication link for the innovative use of Space Station

NASA Technical Reports Server (NTRS)

Carroll, C. C.

1984-01-01

The potential capability of the computer-communications system link of space station is related to innovative utilization for industrial applications. Conceptual computer network architectures are presented and their respective accommodation of innovative industrial projects are discussed. To achieve maximum system availability for industrialization is a possible design goal, which would place the industrial community in an interactive mode with facilities in space. A worthy design goal would be to minimize the computer-communication management function and thereby optimize the system availability for industrial users. Quasi-autonomous modes and subnetworks are key design issues, since they would be the system elements directly effecting the system performance for industrial use.

Graphics processing unit based computation for NDE applications

NASA Astrophysics Data System (ADS)

Nahas, C. A.; Rajagopal, Prabhu; Balasubramaniam, Krishnan; Krishnamurthy, C. V.

2012-05-01

Advances in parallel processing in recent years are helping to improve the cost of numerical simulation. Breakthroughs in Graphical Processing Unit (GPU) based computation now offer the prospect of further drastic improvements. The introduction of 'compute unified device architecture' (CUDA) by NVIDIA (the global technology company based in Santa Clara, California, USA) has made programming GPUs for general purpose computing accessible to the average programmer. Here we use CUDA to develop parallel finite difference schemes as applicable to two problems of interest to NDE community, namely heat diffusion and elastic wave propagation. The implementations are for two-dimensions. Performance improvement of the GPU implementation against serial CPU implementation is then discussed.

Core Community Specifications for Electron Microprobe Operating Systems: Software, Quality Control, and Data Management Issues

NASA Technical Reports Server (NTRS)

Fournelle, John; Carpenter, Paul

2006-01-01

Modem electron microprobe systems have become increasingly sophisticated. These systems utilize either UNIX or PC computer systems for measurement, automation, and data reduction. These systems have undergone major improvements in processing, storage, display, and communications, due to increased capabilities of hardware and software. Instrument specifications are typically utilized at the time of purchase and concentrate on hardware performance. The microanalysis community includes analysts, researchers, software developers, and manufacturers, who could benefit from exchange of ideas and the ultimate development of core community specifications (CCS) for hardware and software components of microprobe instrumentation and operating systems.

plasmaFoam: An OpenFOAM framework for computational plasma physics and chemistry

NASA Astrophysics Data System (ADS)

Venkattraman, Ayyaswamy; Verma, Abhishek Kumar

2016-09-01

As emphasized in the 2012 Roadmap for low temperature plasmas (LTP), scientific computing has emerged as an essential tool for the investigation and prediction of the fundamental physical and chemical processes associated with these systems. While several in-house and commercial codes exist, with each having its own advantages and disadvantages, a common framework that can be developed by researchers from all over the world will likely accelerate the impact of computational studies on advances in low-temperature plasma physics and chemistry. In this regard, we present a finite volume computational toolbox to perform high-fidelity simulations of LTP systems. This framework, primarily based on the OpenFOAM solver suite, allows us to enhance our understanding of multiscale plasma phenomenon by performing massively parallel, three-dimensional simulations on unstructured meshes using well-established high performance computing tools that are widely used in the computational fluid dynamics community. In this talk, we will present preliminary results obtained using the OpenFOAM-based solver suite with benchmark three-dimensional simulations of microplasma devices including both dielectric and plasma regions. We will also discuss the future outlook for the solver suite.

Electronic Dental Records System Adoption.

PubMed

Abramovicz-Finkelsztain, Renata; Barsottini, Claudia G N; Marin, Heimar Fatima

2015-01-01

The use of Electronic Dental Records (EDRs) and management software has become more frequent, following the increase in prevelance of new technologies and computers in dental offices. The purpose of this study is to identify and evaluate the use of EDRs by the dental community in the São Paulo city area. A quantitative case study was performed using a survey on the phone. A total of 54 offices were contacted and only one declinedparticipation in this study. Only one office did not have a computer. EDRs were used in 28 offices and only four were paperless. The lack of studies in this area suggests the need for more usability and implementation studies on EDRs so that we can improve EDR adoption by the dental community.

Exploring new kinds of relationships using generative music-making software.

PubMed

Dillon, Steve; Jones, Anita

2009-08-01

This project focuses upon the use of jam2jam, a generative computer system, to increase access to improvization experiences for children and to facilitate new kinds of relationships with artists. The network jamming system uses visual and audio cultural materials to enable communities to be expressive with artistic materials that they value as a community. As the system is part of a network, performances can be shared between communities at great distances and recordings of performances can be uploaded to a digital social network (http://www.jam2jam.com/) and shared both locally and with the wider community. This paper examines a preliminary project where artwork made by Indigenous mental health clients in Far North Queensland was digitized and given to a group of 8-12-year-old urban Indigenous children to 'improvize' with and make music/video clips using the jam2jam instrument. It seeks to generate a discussion and identify applications within creative arts-led community health settings to facilitate new kinds of relationships with self, peers, local community, culture and artists through collaborative improvization.

Operation of Grid-tied 5 kWDC solar array to develop Laboratory Experiments for Solar PV Energy System courses

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

Ramos, Jaime

2012-12-14

To unlock the potential of micro grids we plan to build, commission and operate a 5 kWDC PV array and integrate it to the UTPA Engineering building low voltage network, as a micro grid; and promote community awareness. Assisted by a solar radiation tracker providing on-line information of its measurements and performing analysis for the use by the scientific and engineering community, we will write, perform and operate a set of Laboratory experiments and computer simulations supporting Electrical Engineering (graduate and undergraduate) courses on Renewable Energy, as well as Senior Design projects.

Generic Divide and Conquer Internet-Based Computing

NASA Technical Reports Server (NTRS)

Follen, Gregory J. (Technical Monitor); Radenski, Atanas

2003-01-01

The growth of Internet-based applications and the proliferation of networking technologies have been transforming traditional commercial application areas as well as computer and computational sciences and engineering. This growth stimulates the exploration of Peer to Peer (P2P) software technologies that can open new research and application opportunities not only for the commercial world, but also for the scientific and high-performance computing applications community. The general goal of this project is to achieve better understanding of the transition to Internet-based high-performance computing and to develop solutions for some of the technical challenges of this transition. In particular, we are interested in creating long-term motivation for end users to provide their idle processor time to support computationally intensive tasks. We believe that a practical P2P architecture should provide useful service to both clients with high-performance computing needs and contributors of lower-end computing resources. To achieve this, we are designing dual -service architecture for P2P high-performance divide-and conquer computing; we are also experimenting with a prototype implementation. Our proposed architecture incorporates a master server, utilizes dual satellite servers, and operates on the Internet in a dynamically changing large configuration of lower-end nodes provided by volunteer contributors. A dual satellite server comprises a high-performance computing engine and a lower-end contributor service engine. The computing engine provides generic support for divide and conquer computations. The service engine is intended to provide free useful HTTP-based services to contributors of lower-end computing resources. Our proposed architecture is complementary to and accessible from computational grids, such as Globus, Legion, and Condor. Grids provide remote access to existing higher-end computing resources; in contrast, our goal is to utilize idle processor time of lower-end Internet nodes. Our project is focused on a generic divide and conquer paradigm and on mobile applications of this paradigm that can operate on a loose and ever changing pool of lower-end Internet nodes.

The SGI/CRAY T3E: Experiences and Insights

NASA Technical Reports Server (NTRS)

Bernard, Lisa Hamet

1999-01-01

The focus of the HPCC Earth and Space Sciences (ESS) Project is capability computing - pushing highly scalable computing testbeds to their performance limits. The drivers of this focus are the Grand Challenge problems in Earth and space science: those that could not be addressed in a capacity computing environment where large jobs must continually compete for resources. These Grand Challenge codes require a high degree of communication, large memory, and very large I/O (throughout the duration of the processing, not just in loading initial conditions and saving final results). This set of parameters led to the selection of an SGI/Cray T3E as the current ESS Computing Testbed. The T3E at the Goddard Space Flight Center is a unique computational resource within NASA. As such, it must be managed to effectively support the diverse research efforts across the NASA research community yet still enable the ESS Grand Challenge Investigator teams to achieve their performance milestones, for which the system was intended. To date, all Grand Challenge Investigator teams have achieved the 10 GFLOPS milestone, eight of nine have achieved the 50 GFLOPS milestone, and three have achieved the 100 GFLOPS milestone. In addition, many technical papers have been published highlighting results achieved on the NASA T3E, including some at this Workshop. The successes enabled by the NASA T3E computing environment are best illustrated by the 512 PE upgrade funded by the NASA Earth Science Enterprise earlier this year. Never before has an HPCC computing testbed been so well received by the general NASA science community that it was deemed critical to the success of a core NASA science effort. NASA looks forward to many more success stories before the conclusion of the NASA-SGI/Cray cooperative agreement in June 1999.

Computers in Communications and Education at Coast Community College District.

ERIC Educational Resources Information Center

Luskin, Bernard J.; Ruth, Monty W.

Coast Community College District in Orange County, California is a leader among community colleges in the instructional use computers. The district's hardware consists of an IBM system 370 model 155 computer, over 80 typewriter terminals, 12 cathode ray tubes (CRT), and several microfiche image projection devices. Better than 700 computer-assisted…

QMC Goes BOINC: Using Public Resource Computing to Perform Quantum Monte Carlo Calculations

NASA Astrophysics Data System (ADS)

Rainey, Cameron; Engelhardt, Larry; Schröder, Christian; Hilbig, Thomas

2008-10-01

Theoretical modeling of magnetic molecules traditionally involves the diagonalization of quantum Hamiltonian matrices. However, as the complexity of these molecules increases, the matrices become so large that this process becomes unusable. An additional challenge to this modeling is that many repetitive calculations must be performed, further increasing the need for computing power. Both of these obstacles can be overcome by using a quantum Monte Carlo (QMC) method and a distributed computing project. We have recently implemented a QMC method within the Spinhenge@home project, which is a Public Resource Computing (PRC) project where private citizens allow part-time usage of their PCs for scientific computing. The use of PRC for scientific computing will be described in detail, as well as how you can contribute to the project. See, e.g., L. Engelhardt, et. al., Angew. Chem. Int. Ed. 47, 924 (2008). C. Schröoder, in Distributed & Grid Computing - Science Made Transparent for Everyone. Principles, Applications and Supporting Communities. (Weber, M.H.W., ed., 2008). Project URL: http://spin.fh-bielefeld.de

Cielo Computational Environment Usage Model With Mappings to ACE Requirements for the General Availability User Environment Capabilities Release Version 1.1

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

Vigil,Benny Manuel; Ballance, Robert; Haskell, Karen

Cielo is a massively parallel supercomputer funded by the DOE/NNSA Advanced Simulation and Computing (ASC) program, and operated by the Alliance for Computing at Extreme Scale (ACES), a partnership between Los Alamos National Laboratory (LANL) and Sandia National Laboratories (SNL). The primary Cielo compute platform is physically located at Los Alamos National Laboratory. This Cielo Computational Environment Usage Model documents the capabilities and the environment to be provided for the Q1 FY12 Level 2 Cielo Capability Computing (CCC) Platform Production Readiness Milestone. This document describes specific capabilities, tools, and procedures to support both local and remote users. The model ismore » focused on the needs of the ASC user working in the secure computing environments at Lawrence Livermore National Laboratory (LLNL), Los Alamos National Laboratory, or Sandia National Laboratories, but also addresses the needs of users working in the unclassified environment. The Cielo Computational Environment Usage Model maps the provided capabilities to the tri-Lab ASC Computing Environment (ACE) Version 8.0 requirements. The ACE requirements reflect the high performance computing requirements for the Production Readiness Milestone user environment capabilities of the ASC community. A description of ACE requirements met, and those requirements that are not met, are included in each section of this document. The Cielo Computing Environment, along with the ACE mappings, has been issued and reviewed throughout the tri-Lab community.« less

In Situ Methods, Infrastructures, and Applications on High Performance Computing Platforms, a State-of-the-art (STAR) Report

DOE PAGES

Bethel, EW; Bauer, A; Abbasi, H; ...

2016-06-10

The considerable interest in the high performance computing (HPC) community regarding analyzing and visualization data without first writing to disk, i.e., in situ processing, is due to several factors. First is an I/O cost savings, where data is analyzed /visualized while being generated, without first storing to a filesystem. Second is the potential for increased accuracy, where fine temporal sampling of transient analysis might expose some complex behavior missed in coarse temporal sampling. Third is the ability to use all available resources, CPU’s and accelerators, in the computation of analysis products. This STAR paper brings together researchers, developers and practitionersmore » using in situ methods in extreme-scale HPC with the goal to present existing methods, infrastructures, and a range of computational science and engineering applications using in situ analysis and visualization.« less

Generic Divide and Conquer Internet-Based Computing

NASA Technical Reports Server (NTRS)

Radenski, Atanas; Follen, Gregory J. (Technical Monitor)

2001-01-01

The rapid growth of internet-based applications and the proliferation of networking technologies have been transforming traditional commercial application areas as well as computer and computational sciences and engineering. This growth stimulates the exploration of new, internet-oriented software technologies that can open new research and application opportunities not only for the commercial world, but also for the scientific and high -performance computing applications community. The general goal of this research project is to contribute to better understanding of the transition to internet-based high -performance computing and to develop solutions for some of the difficulties of this transition. More specifically, our goal is to design an architecture for generic divide and conquer internet-based computing, to develop a portable implementation of this architecture, to create an example library of high-performance divide-and-conquer computing agents that run on top of this architecture, and to evaluate the performance of these agents. We have been designing an architecture that incorporates a master task-pool server and utilizes satellite computational servers that operate on the Internet in a dynamically changing large configuration of lower-end nodes provided by volunteer contributors. Our designed architecture is intended to be complementary to and accessible from computational grids such as Globus, Legion, and Condor. Grids provide remote access to existing high-end computing resources; in contrast, our goal is to utilize idle processor time of lower-end internet nodes. Our project is focused on a generic divide-and-conquer paradigm and its applications that operate on a loose and ever changing pool of lower-end internet nodes.

Improved Boundary Layer Module (BLM) for the Solid Performance Program (SPP)

NASA Astrophysics Data System (ADS)

Coats, D. E.; Cebeci, T.

1982-03-01

The requirements for a replacement to the Bartz boundary layer code, the standard method of computing the performance loss due to viscous effects by the solid performance program, were discussed by the propulsion community along with four nationally recognized boundary layer experts. A consensus was reached regarding the preferred features for the analysis of the replacement code. The major points that were agreed upon are: (1) finite difference methods are preferred over integral methods; (2) a single equation eddy viscosity model was considered to be adequate for the purpose of computing performance loss; (3) a variable grid capability in both coordinate directions would be required; (4) a proven finite difference algorithm which is not stability restricted should be used, that is, an implicit numerical scheme would be required; and (5) the replacement code should be able to compute both turbulent and laminar flows. The program should treat mass addition at the wall as well as being able to calculate a stagnation point starting line.

Enabling Diverse Software Stacks on Supercomputers using High Performance Virtual Clusters.

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

Younge, Andrew J.; Pedretti, Kevin; Grant, Ryan

While large-scale simulations have been the hallmark of the High Performance Computing (HPC) community for decades, Large Scale Data Analytics (LSDA) workloads are gaining attention within the scientific community not only as a processing component to large HPC simulations, but also as standalone scientific tools for knowledge discovery. With the path towards Exascale, new HPC runtime systems are also emerging in a way that differs from classical distributed com- puting models. However, system software for such capabilities on the latest extreme-scale DOE supercomputing needs to be enhanced to more appropriately support these types of emerging soft- ware ecosystems. In thismore » paper, we propose the use of Virtual Clusters on advanced supercomputing resources to enable systems to support not only HPC workloads, but also emerging big data stacks. Specifi- cally, we have deployed the KVM hypervisor within Cray's Compute Node Linux on a XC-series supercomputer testbed. We also use libvirt and QEMU to manage and provision VMs directly on compute nodes, leveraging Ethernet-over-Aries network emulation. To our knowledge, this is the first known use of KVM on a true MPP supercomputer. We investigate the overhead our solution using HPC benchmarks, both evaluating single-node performance as well as weak scaling of a 32-node virtual cluster. Overall, we find single node performance of our solution using KVM on a Cray is very efficient with near-native performance. However overhead increases by up to 20% as virtual cluster size increases, due to limitations of the Ethernet-over-Aries bridged network. Furthermore, we deploy Apache Spark with large data analysis workloads in a Virtual Cluster, ef- fectively demonstrating how diverse software ecosystems can be supported by High Performance Virtual Clusters.« less

NCI's Transdisciplinary High Performance Scientific Data Platform

NASA Astrophysics Data System (ADS)

Evans, Ben; Antony, Joseph; Bastrakova, Irina; Car, Nicholas; Cox, Simon; Druken, Kelsey; Evans, Bradley; Fraser, Ryan; Ip, Alex; Kemp, Carina; King, Edward; Minchin, Stuart; Larraondo, Pablo; Pugh, Tim; Richards, Clare; Santana, Fabiana; Smillie, Jon; Trenham, Claire; Wang, Jingbo; Wyborn, Lesley

2016-04-01

The Australian National Computational Infrastructure (NCI) manages Earth Systems data collections sourced from several domains and organisations onto a single High Performance Data (HPD) Node to further Australia's national priority research and innovation agenda. The NCI HPD Node has rapidly established its value, currently managing over 10 PBytes of datasets from collections that span a wide range of disciplines including climate, weather, environment, geoscience, geophysics, water resources and social sciences. Importantly, in order to facilitate broad user uptake, maximise reuse and enable transdisciplinary access through software and standardised interfaces, the datasets, associated information systems and processes have been incorporated into the design and operation of a unified platform that NCI has called, the National Environmental Research Data Interoperability Platform (NERDIP). The key goal of the NERDIP is to regularise data access so that it is easily discoverable, interoperable for different domains and enabled for high performance methods. It adopts and implements international standards and data conventions, and promotes scientific integrity within a high performance computing and data analysis environment. NCI has established a rich and flexible computing environment to access to this data, through the NCI supercomputer; a private cloud that supports both domain focused virtual laboratories and in-common interactive analysis interfaces; as well as remotely through scalable data services. Data collections of this importance must be managed with careful consideration of both their current use and the needs of the end-communities, as well as its future potential use, such as transitioning to more advanced software and improved methods. It is therefore critical that the data platform is both well-managed and trusted for stable production use (including transparency and reproducibility), agile enough to incorporate new technological advances and additional communities practices, and a foundation for new exploratory developments. To that end, NCI is already participating in numerous current and emerging collaborations internationally including the Earth System Grid Federation (ESGF); Climate and Weather Data from International agencies such as NASA, NOAA, and UK Met Office; Remotely Sensed Satellite Earth Imaging through collaborations through GEOS and CEOS; EU-led Ocean Data Interoperability Platform (ODIP) and Horizon2020 Earth Server2 project; as well as broader data infrastructure community activities such as Research Data Alliance (RDA). Each research community is heavily engaged in international standards such as ISO, OGC and W3C, adopting community-led conventions for data, supporting improved data organisation such as controlled vocabularies, and creating workflows that use mature APIs and data services. NCI is engaging with these communities on NERDIP to ensure that such standards are applied uniformly and tested in practice by working with the variety of data and technologies. This includes benchmarking exemplar cases from individual communities, documenting their use of standards, and evaluating their practical use of the different technologies. Such a process fully establishes the functionality and performance, and is required to safely transition when improvements or rationalisation is required. Work is now underway to extend the NERDIP platform for better utilisation in the subsurface geophysical community, including maximizing national uptake, as well as better integration with international science platforms.

Survey of Intelligent Computer-Aided Training

NASA Technical Reports Server (NTRS)

Loftin, R. B.; Savely, Robert T.

1992-01-01

Intelligent Computer-Aided Training (ICAT) systems integrate artificial intelligence and simulation technologies to deliver training for complex, procedural tasks in a distributed, workstation-based environment. Such systems embody both the knowledge of how to perform a task and how to train someone to perform that task. This paper briefly reviews the antecedents of ICAT systems and describes the approach to their creation developed at the NASA Lyndon B. Johnson Space Center. In addition to the general ICAT architecture, specific ICAT applications that have been or are currently under development are discussed. ICAT systems can offer effective solutions to a number of training problems of interest to the aerospace community.

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.

DOE High Performance Computing Operational Review (HPCOR): Enabling Data-Driven Scientific Discovery at HPC Facilities

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

Gerber, Richard; Allcock, William; Beggio, Chris

2014-10-17

U.S. Department of Energy (DOE) High Performance Computing (HPC) facilities are on the verge of a paradigm shift in the way they deliver systems and services to science and engineering teams. Research projects are producing a wide variety of data at unprecedented scale and level of complexity, with community-specific services that are part of the data collection and analysis workflow. On June 18-19, 2014 representatives from six DOE HPC centers met in Oakland, CA at the DOE High Performance Operational Review (HPCOR) to discuss how they can best provide facilities and services to enable large-scale data-driven scientific discovery at themore » DOE national laboratories. The report contains findings from that review.« less

Changing Community Health Behaviors with a Health Promotion Computer Network: Preliminary Findings from Stanford Health-Net

PubMed Central

Robinson, Thomas N.; Walters, Paul A.

1987-01-01

Computer-based health education has been employed in many settings. However, data on resultant behavior change are lacking. A randomized, controlled, prospective study was performed to test the efficacy of Stanford Health-Net in changing community health behaviors. Graduate and undergraduate students (N=1003) were randomly assigned to treatment and control conditions. The treatment group received access to Health-Net, a health promotion computer network emphasizing specific self-care and preventive strategies. Over a four month intervention period, 26% of the treatment group used Health-Net an average of 6.4 times each (range 1 to 97). Users rated Health-Net favorably. The mean number of ambulatory medical visits decreesed 22.5% more in the treatment group than in the control group (P<.05), while hospitalizations did not differ significantly between groups. In addition, perceived self-efficacy for preventing the acquisition of a STD and herpes increased 577% (P<.05) and 261% (P<.01) more, respectively, in the treatment group than in the control group. These findings suggest that access to Stanford Health-Net can result in significant health behavior change. The advantages of the network approach make it a potential model for other communities.

Meeting the computer technology needs of community faculty: building new models for faculty development.

PubMed

Baldwin, Constance D; Niebuhr, Virginia N; Sullivan, Brian

2004-01-01

We aimed to identify the evolving computer technology needs and interests of community faculty in order to design an effective faculty development program focused on computer skills: the Teaching and Learning Through Educational Technology (TeLeTET) program. Repeated surveys were conducted between 1994 and 2002 to assess computer resources and needs in a pool of over 800 primary care physician-educators in community practice in East Texas. Based on the results, we developed and evaluated several models to teach community preceptors about computer technologies that are useful for education. Before 1998, only half of our community faculty identified a strong interest in developing their technology skills. As the revolution in telecommunications advanced, however, preceptors' needs and interests changed, and the use of this technology to support community-based teaching became feasible. In 1998 and 1999, resource surveys showed that many of our community teaching sites had computers and Internet access. By 2001, the desire for teletechnology skills development was strong in a nucleus of community faculty, although lack of infrastructure, time, and skills were identified barriers. The TeLeTET project developed several innovative models for technology workshops and conferences, supplemented by online resources, that were well attended and positively evaluated by 181 community faculty over a 3-year period. We have identified the evolving needs of community faculty through iterative needs assessments, developed a flexible faculty development curriculum, and used open-ended, formative evaluation techniques to keep the TeLeTET program responsive to a rapidly changing environment for community-based education in computer technology.

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

Aurich, Maike K.; Fleming, Ronan M. T.; Thiele, Ines

Metabolomic data sets provide a direct read-out of cellular phenotypes and are increasingly generated to study biological questions. Previous work, by us and others, revealed the potential of analyzing extracellular metabolomic data in the context of the metabolic model using constraint-based modeling. With the MetaboTools, we make our methods available to the broader scientific community. The MetaboTools consist of a protocol, a toolbox, and tutorials of two use cases. The protocol describes, in a step-wise manner, the workflow of data integration, and computational analysis. The MetaboTools comprise the Matlab code required to complete the workflow described in the protocol. Tutorialsmore » explain the computational steps for integration of two different data sets and demonstrate a comprehensive set of methods for the computational analysis of metabolic models and stratification thereof into different phenotypes. The presented workflow supports integrative analysis of multiple omics data sets. Importantly, all analysis tools can be applied to metabolic models without performing the entire workflow. Taken together, the MetaboTools constitute a comprehensive guide to the intra-model analysis of extracellular metabolomic data from microbial, plant, or human cells. In conclusion, this computational modeling resource offers a broad set of computational analysis tools for a wide biomedical and non-biomedical research community.« less

Encapsulating model complexity and landscape-scale analyses of state-and-transition simulation models: an application of ecoinformatics and juniper encroachment in sagebrush steppe ecosystems

USGS Publications Warehouse

O'Donnell, Michael

2015-01-01

State-and-transition simulation modeling relies on knowledge of vegetation composition and structure (states) that describe community conditions, mechanistic feedbacks such as fire that can affect vegetation establishment, and ecological processes that drive community conditions as well as the transitions between these states. However, as the need for modeling larger and more complex landscapes increase, a more advanced awareness of computing resources becomes essential. The objectives of this study include identifying challenges of executing state-and-transition simulation models, identifying common bottlenecks of computing resources, developing a workflow and software that enable parallel processing of Monte Carlo simulations, and identifying the advantages and disadvantages of different computing resources. To address these objectives, this study used the ApexRMS® SyncroSim software and embarrassingly parallel tasks of Monte Carlo simulations on a single multicore computer and on distributed computing systems. The results demonstrated that state-and-transition simulation models scale best in distributed computing environments, such as high-throughput and high-performance computing, because these environments disseminate the workloads across many compute nodes, thereby supporting analysis of larger landscapes, higher spatial resolution vegetation products, and more complex models. Using a case study and five different computing environments, the top result (high-throughput computing versus serial computations) indicated an approximate 96.6% decrease of computing time. With a single, multicore compute node (bottom result), the computing time indicated an 81.8% decrease relative to using serial computations. These results provide insight into the tradeoffs of using different computing resources when research necessitates advanced integration of ecoinformatics incorporating large and complicated data inputs and models. - See more at: http://aimspress.com/aimses/ch/reader/view_abstract.aspx?file_no=Environ2015030&flag=1#sthash.p1XKDtF8.dpuf

Computational communities: African-American cultural capital in computer science education

NASA Astrophysics Data System (ADS)

Lachney, Michael

2017-10-01

Enrolling the cultural capital of underrepresented communities in PK-12 technology and curriculum design has been a primary strategy for broadening the participation of students of color in U.S. computer science (CS) fields. This article examines two ways that African-American cultural capital and computing can be bridged in CS education. The first is community representation, using cultural capital to highlight students' social identities and networks through computational thinking. The second, computational integration, locates computation in cultural capital itself. I survey two risks - the appearance of shallow computing and the reproduction of assimilationist logics - that may arise when constructing one bridge without the other. To avoid these risks, I introduce the concept of computational communities by exploring areas in CS education that employ both strategies. This concept is then grounded in qualitative data from an after school program that connected CS to African-American cosmetology.

A Plan for Community College Instructional Computing.

ERIC Educational Resources Information Center

Howard, Alan; And Others

This document presents a comprehensive plan for future growth in instructional computing in the Washington community colleges. Two chapters define the curriculum objectives and content recommended for instructional courses in the community colleges which require access to computing facilities. The courses described include data processing…

NASA's Participation in the National Computational Grid

NASA Technical Reports Server (NTRS)

Feiereisen, William J.; Zornetzer, Steve F. (Technical Monitor)

1998-01-01

Over the last several years it has become evident that the character of NASA's supercomputing needs has changed. One of the major missions of the agency is to support the design and manufacture of aero- and space-vehicles with technologies that will significantly reduce their cost. It is becoming clear that improvements in the process of aerospace design and manufacturing will require a high performance information infrastructure that allows geographically dispersed teams to draw upon resources that are broader than traditional supercomputing. A computational grid draws together our information resources into one system. We can foresee the time when a Grid will allow engineers and scientists to use the tools of supercomputers, databases and on line experimental devices in a virtual environment to collaborate with distant colleagues. The concept of a computational grid has been spoken of for many years, but several events in recent times are conspiring to allow us to actually build one. In late 1997 the National Science Foundation initiated the Partnerships for Advanced Computational Infrastructure (PACI) which is built around the idea of distributed high performance computing. The Alliance lead, by the National Computational Science Alliance (NCSA), and the National Partnership for Advanced Computational Infrastructure (NPACI), lead by the San Diego Supercomputing Center, have been instrumental in drawing together the "Grid Community" to identify the technology bottlenecks and propose a research agenda to address them. During the same period NASA has begun to reformulate parts of two major high performance computing research programs to concentrate on distributed high performance computing and has banded together with the PACI centers to address the research agenda in common.

Critical Assessment of Metagenome Interpretation – a benchmark of computational metagenomics software

PubMed Central

Sczyrba, Alexander; Hofmann, Peter; Belmann, Peter; Koslicki, David; Janssen, Stefan; Dröge, Johannes; Gregor, Ivan; Majda, Stephan; Fiedler, Jessika; Dahms, Eik; Bremges, Andreas; Fritz, Adrian; Garrido-Oter, Ruben; Jørgensen, Tue Sparholt; Shapiro, Nicole; Blood, Philip D.; Gurevich, Alexey; Bai, Yang; Turaev, Dmitrij; DeMaere, Matthew Z.; Chikhi, Rayan; Nagarajan, Niranjan; Quince, Christopher; Meyer, Fernando; Balvočiūtė, Monika; Hansen, Lars Hestbjerg; Sørensen, Søren J.; Chia, Burton K. H.; Denis, Bertrand; Froula, Jeff L.; Wang, Zhong; Egan, Robert; Kang, Dongwan Don; Cook, Jeffrey J.; Deltel, Charles; Beckstette, Michael; Lemaitre, Claire; Peterlongo, Pierre; Rizk, Guillaume; Lavenier, Dominique; Wu, Yu-Wei; Singer, Steven W.; Jain, Chirag; Strous, Marc; Klingenberg, Heiner; Meinicke, Peter; Barton, Michael; Lingner, Thomas; Lin, Hsin-Hung; Liao, Yu-Chieh; Silva, Genivaldo Gueiros Z.; Cuevas, Daniel A.; Edwards, Robert A.; Saha, Surya; Piro, Vitor C.; Renard, Bernhard Y.; Pop, Mihai; Klenk, Hans-Peter; Göker, Markus; Kyrpides, Nikos C.; Woyke, Tanja; Vorholt, Julia A.; Schulze-Lefert, Paul; Rubin, Edward M.; Darling, Aaron E.; Rattei, Thomas; McHardy, Alice C.

2018-01-01

In metagenome analysis, computational methods for assembly, taxonomic profiling and binning are key components facilitating downstream biological data interpretation. However, a lack of consensus about benchmarking datasets and evaluation metrics complicates proper performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on datasets of unprecedented complexity and realism. Benchmark metagenomes were generated from ~700 newly sequenced microorganisms and ~600 novel viruses and plasmids, including genomes with varying degrees of relatedness to each other and to publicly available ones and representing common experimental setups. Across all datasets, assembly and genome binning programs performed well for species represented by individual genomes, while performance was substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below the family level. Parameter settings substantially impacted performances, underscoring the importance of program reproducibility. While highlighting current challenges in computational metagenomics, the CAMI results provide a roadmap for software selection to answer specific research questions. PMID:28967888

Evaluating open-source cloud computing solutions for geosciences

NASA Astrophysics Data System (ADS)

Huang, Qunying; Yang, Chaowei; Liu, Kai; Xia, Jizhe; Xu, Chen; Li, Jing; Gui, Zhipeng; Sun, Min; Li, Zhenglong

2013-09-01

Many organizations start to adopt cloud computing for better utilizing computing resources by taking advantage of its scalability, cost reduction, and easy to access characteristics. Many private or community cloud computing platforms are being built using open-source cloud solutions. However, little has been done to systematically compare and evaluate the features and performance of open-source solutions in supporting Geosciences. This paper provides a comprehensive study of three open-source cloud solutions, including OpenNebula, Eucalyptus, and CloudStack. We compared a variety of features, capabilities, technologies and performances including: (1) general features and supported services for cloud resource creation and management, (2) advanced capabilities for networking and security, and (3) the performance of the cloud solutions in provisioning and operating the cloud resources as well as the performance of virtual machines initiated and managed by the cloud solutions in supporting selected geoscience applications. Our study found that: (1) no significant performance differences in central processing unit (CPU), memory and I/O of virtual machines created and managed by different solutions, (2) OpenNebula has the fastest internal network while both Eucalyptus and CloudStack have better virtual machine isolation and security strategies, (3) Cloudstack has the fastest operations in handling virtual machines, images, snapshots, volumes and networking, followed by OpenNebula, and (4) the selected cloud computing solutions are capable for supporting concurrent intensive web applications, computing intensive applications, and small-scale model simulations without intensive data communication.

Model-Invariant Hybrid Computations of Separated Flows for RCA Standard Test Cases

NASA Technical Reports Server (NTRS)

Woodruff, Stephen

2016-01-01

NASA's Revolutionary Computational Aerosciences (RCA) subproject has identified several smooth-body separated flows as standard test cases to emphasize the challenge these flows present for computational methods and their importance to the aerospace community. Results of computations of two of these test cases, the NASA hump and the FAITH experiment, are presented. The computations were performed with the model-invariant hybrid LES-RANS formulation, implemented in the NASA code VULCAN-CFD. The model- invariant formulation employs gradual LES-RANS transitions and compensation for model variation to provide more accurate and efficient hybrid computations. Comparisons revealed that the LES-RANS transitions employed in these computations were sufficiently gradual that the compensating terms were unnecessary. Agreement with experiment was achieved only after reducing the turbulent viscosity to mitigate the effect of numerical dissipation. The stream-wise evolution of peak Reynolds shear stress was employed as a measure of turbulence dynamics in separated flows useful for evaluating computations.

A Modular Environment for Geophysical Inversion and Run-time Autotuning using Heterogeneous Computing Systems

NASA Astrophysics Data System (ADS)

Myre, Joseph M.

Heterogeneous computing systems have recently come to the forefront of the High-Performance Computing (HPC) community's interest. HPC computer systems that incorporate special purpose accelerators, such as Graphics Processing Units (GPUs), are said to be heterogeneous. Large scale heterogeneous computing systems have consistently ranked highly on the Top500 list since the beginning of the heterogeneous computing trend. By using heterogeneous computing systems that consist of both general purpose processors and special- purpose accelerators, the speed and problem size of many simulations could be dramatically increased. Ultimately this results in enhanced simulation capabilities that allows, in some cases for the first time, the execution of parameter space and uncertainty analyses, model optimizations, and other inverse modeling techniques that are critical for scientific discovery and engineering analysis. However, simplifying the usage and optimization of codes for heterogeneous computing systems remains a challenge. This is particularly true for scientists and engineers for whom understanding HPC architectures and undertaking performance analysis may not be primary research objectives. To enable scientists and engineers to remain focused on their primary research objectives, a modular environment for geophysical inversion and run-time autotuning on heterogeneous computing systems is presented. This environment is composed of three major components: 1) CUSH---a framework for reducing the complexity of programming heterogeneous computer systems, 2) geophysical inversion routines which can be used to characterize physical systems, and 3) run-time autotuning routines designed to determine configurations of heterogeneous computing systems in an attempt to maximize the performance of scientific and engineering codes. Using three case studies, a lattice-Boltzmann method, a non-negative least squares inversion, and a finite-difference fluid flow method, it is shown that this environment provides scientists and engineers with means to reduce the programmatic complexity of their applications, to perform geophysical inversions for characterizing physical systems, and to determine high-performing run-time configurations of heterogeneous computing systems using a run-time autotuner.

Technology advances and market forces: Their impact on high performance architectures

NASA Technical Reports Server (NTRS)

Best, D. R.

1978-01-01

Reasonable projections into future supercomputer architectures and technology require an analysis of the computer industry market environment, the current capabilities and trends within the component industry, and the research activities on computer architecture in the industrial and academic communities. Management, programmer, architect, and user must cooperate to increase the efficiency of supercomputer development efforts. Care must be taken to match the funding, compiler, architecture and application with greater attention to testability, maintainability, reliability, and usability than supercomputer development programs of the past.

Application of infrared thermography in computer aided diagnosis

NASA Astrophysics Data System (ADS)

Faust, Oliver; Rajendra Acharya, U.; Ng, E. Y. K.; Hong, Tan Jen; Yu, Wenwei

2014-09-01

The invention of thermography, in the 1950s, posed a formidable problem to the research community: What is the relationship between disease and heat radiation captured with Infrared (IR) cameras? The research community responded with a continuous effort to find this crucial relationship. This effort was aided by advances in processing techniques, improved sensitivity and spatial resolution of thermal sensors. However, despite this progress fundamental issues with this imaging modality still remain. The main problem is that the link between disease and heat radiation is complex and in many cases even non-linear. Furthermore, the change in heat radiation as well as the change in radiation pattern, which indicate disease, is minute. On a technical level, this poses high requirements on image capturing and processing. On a more abstract level, these problems lead to inter-observer variability and on an even more abstract level they lead to a lack of trust in this imaging modality. In this review, we adopt the position that these problems can only be solved through a strict application of scientific principles and objective performance assessment. Computing machinery is inherently objective; this helps us to apply scientific principles in a transparent way and to assess the performance results. As a consequence, we aim to promote thermography based Computer-Aided Diagnosis (CAD) systems. Another benefit of CAD systems comes from the fact that the diagnostic accuracy is linked to the capability of the computing machinery and, in general, computers become ever more potent. We predict that a pervasive application of computers and networking technology in medicine will help us to overcome the shortcomings of any single imaging modality and this will pave the way for integrated health care systems which maximize the quality of patient care.

Java Performance for Scientific Applications on LLNL Computer Systems

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

Kapfer, C; Wissink, A

2002-05-10

Languages in use for high performance computing at the laboratory--Fortran (f77 and f90), C, and C++--have many years of development behind them and are generally considered the fastest available. However, Fortran and C do not readily extend to object-oriented programming models, limiting their capability for very complex simulation software. C++ facilitates object-oriented programming but is a very complex and error-prone language. Java offers a number of capabilities that these other languages do not. For instance it implements cleaner (i.e., easier to use and less prone to errors) object-oriented models than C++. It also offers networking and security as part ofmore » the language standard, and cross-platform executables that make it architecture neutral, to name a few. These features have made Java very popular for industrial computing applications. The aim of this paper is to explain the trade-offs in using Java for large-scale scientific applications at LLNL. Despite its advantages, the computational science community has been reluctant to write large-scale computationally intensive applications in Java due to concerns over its poor performance. However, considerable progress has been made over the last several years. The Java Grande Forum [1] has been promoting the use of Java for large-scale computing. Members have introduced efficient array libraries, developed fast just-in-time (JIT) compilers, and built links to existing packages used in high performance parallel computing.« less

Multi-threaded Sparse Matrix Sparse Matrix Multiplication for Many-Core and GPU Architectures.

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

Deveci, Mehmet; Trott, Christian Robert; Rajamanickam, Sivasankaran

Sparse Matrix-Matrix multiplication is a key kernel that has applications in several domains such as scientific computing and graph analysis. Several algorithms have been studied in the past for this foundational kernel. In this paper, we develop parallel algorithms for sparse matrix- matrix multiplication with a focus on performance portability across different high performance computing architectures. The performance of these algorithms depend on the data structures used in them. We compare different types of accumulators in these algorithms and demonstrate the performance difference between these data structures. Furthermore, we develop a meta-algorithm, kkSpGEMM, to choose the right algorithm and datamore » structure based on the characteristics of the problem. We show performance comparisons on three architectures and demonstrate the need for the community to develop two phase sparse matrix-matrix multiplication implementations for efficient reuse of the data structures involved.« less

Multi-threaded Sparse Matrix-Matrix Multiplication for Many-Core and GPU Architectures.

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

Deveci, Mehmet; Rajamanickam, Sivasankaran; Trott, Christian Robert

Sparse Matrix-Matrix multiplication is a key kernel that has applications in several domains such as scienti c computing and graph analysis. Several algorithms have been studied in the past for this foundational kernel. In this paper, we develop parallel algorithms for sparse matrix-matrix multiplication with a focus on performance portability across different high performance computing architectures. The performance of these algorithms depend on the data structures used in them. We compare different types of accumulators in these algorithms and demonstrate the performance difference between these data structures. Furthermore, we develop a meta-algorithm, kkSpGEMM, to choose the right algorithm and datamore » structure based on the characteristics of the problem. We show performance comparisons on three architectures and demonstrate the need for the community to develop two phase sparse matrix-matrix multiplication implementations for efficient reuse of the data structures involved.« less

Research Institute for Advanced Computer Science: Annual Report October 1998 through September 1999

NASA Technical Reports Server (NTRS)

Leiner, Barry M.; Gross, Anthony R. (Technical Monitor)

1999-01-01

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. RIACS is located at the NASA Ames Research Center (ARC). It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in the year 2002. ARC has been designated NASA's Center of Excellence in Information Technology. In this capacity, ARC is charged with the responsibility to build an Information Technology Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA ARC and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of information technology research necessary to meet the future challenges of NASA missions: (1) Automated Reasoning for Autonomous Systems. Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth. (2) Human-Centered Computing. Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities; (3) High Performance Computing and Networking Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to data analysis of large datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply information technology research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, and visiting scientist programs, designed to encourage and facilitate collaboration between the university and NASA information technology research communities.

Research Institute for Advanced Computer Science

NASA Technical Reports Server (NTRS)

Gross, Anthony R. (Technical Monitor); Leiner, Barry M.

2000-01-01

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. RIACS is located at the NASA Ames Research Center. It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in the year 2002. Ames has been designated NASA's Center of Excellence in Information Technology. In this capacity, Ames is charged with the responsibility to build an Information Technology Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA Ames and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of information technology research necessary to meet the future challenges of NASA missions: (1) Automated Reasoning for Autonomous Systems. Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth; (2) Human-Centered Computing. Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities; (3) High Performance Computing and Networking. Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to data analysis of large datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply information technology research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, and visiting scientist programs, designed to encourage and facilitate collaboration between the university and NASA information technology research communities.

An hierarchical approach to performance evaluation of expert systems

NASA Technical Reports Server (NTRS)

Dominick, Wayne D. (Editor); Kavi, Srinu

1985-01-01

The number and size of expert systems is growing rapidly. Formal evaluation of these systems - which is not performed for many systems - increases the acceptability by the user community and hence their success. Hierarchical evaluation that had been conducted for computer systems is applied for expert system performance evaluation. Expert systems are also evaluated by treating them as software systems (or programs). This paper reports many of the basic concepts and ideas in the Performance Evaluation of Expert Systems Study being conducted at the University of Southwestern Louisiana.

Software Engineering Support of the Third Round of Scientific Grand Challenge Investigations: An Earth Modeling System Software Framework Strawman Design that Integrates Cactus and UCLA/UCB Distributed Data Broker

NASA Technical Reports Server (NTRS)

Talbot, Bryan; Zhou, Shu-Jia; Higgins, Glenn

2002-01-01

One of the most significant challenges in large-scale climate modeling, as well as in high-performance computing in other scientific fields, is that of effectively integrating many software models from multiple contributors. A software framework facilitates the integration task. both in the development and runtime stages of the simulation. Effective software frameworks reduce the programming burden for the investigators, freeing them to focus more on the science and less on the parallel communication implementation, while maintaining high performance across numerous supercomputer and workstation architectures. This document proposes a strawman framework design for the climate community based on the integration of Cactus, from the relativistic physics community, and UCLA/UCB Distributed Data Broker (DDB) from the climate community. This design is the result of an extensive survey of climate models and frameworks in the climate community as well as frameworks from many other scientific communities. The design addresses fundamental development and runtime needs using Cactus, a framework with interfaces for FORTRAN and C-based languages, and high-performance model communication needs using DDB. This document also specifically explores object-oriented design issues in the context of climate modeling as well as climate modeling issues in terms of object-oriented design.

OASIS connections: results from an evaluation study.

PubMed

Czaja, Sara J; Lee, Chin Chin; Branham, Janice; Remis, Peggy

2012-10-01

The objectives of this study were to evaluate a community-based basic computer and Internet training program designed for older adults, provide recommendations for program refinement, and gather preliminary information on program sustainability. The program was developed by the OASIS Institute, a nonprofit agency serving older adults and implemented in 4 cities by community trainers across the United States. One hundred and ninety-six adults aged 40-90 years were assigned to the training or a wait-list control group. Knowledge of computers and the Internet, attitudes toward computers, and computer/Internet use were assessed at baseline, posttraining, and 3 months posttraining. The program was successful in increasing the computer/Internet skills of the trainees. The data indicated a significant increase in computer and Internet knowledge and comfort with computers among those who received the training. Further, those who completed the course reported an increase in both computer and Internet use 3 months posttraining. The findings indicate that a community-based computer and Internet training program delivered by community instructors can be effective in terms of increasing computer and Internet skills and comfort with computer technology among older adults.

Performance Characterization of Global Address Space Applications: A Case Study with NWChem

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

Hammond, Jeffrey R.; Krishnamoorthy, Sriram; Shende, Sameer

The use of global address space languages and one-sided communication for complex applications is gaining attention in the parallel computing community. However, lack of good evaluative methods to observe multiple levels of performance makes it difficult to isolate the cause of performance deficiencies and to understand the fundamental limitations of system and application design for future improvement. NWChem is a popular computational chemistry package which depends on the Global Arrays/ ARMCI suite for partitioned global address space functionality to deliver high-end molecular modeling capabilities. A workload characterization methodology was developed to support NWChem performance engineering on large-scale parallel platforms. Themore » research involved both the integration of performance instrumentation and measurement in the NWChem software, as well as the analysis of one-sided communication performance in the context of NWChem workloads. Scaling studies were conducted for NWChem on Blue Gene/P and on two large-scale clusters using different generation Infiniband interconnects and x86 processors. The performance analysis and results show how subtle changes in the runtime parameters related to the communication subsystem could have significant impact on performance behavior. The tool has successfully identified several algorithmic bottlenecks which are already being tackled by computational chemists to improve NWChem performance.« less

Scientific Services on the Cloud

NASA Astrophysics Data System (ADS)

Chapman, David; Joshi, Karuna P.; Yesha, Yelena; Halem, Milt; Yesha, Yaacov; Nguyen, Phuong

Scientific Computing was one of the first every applications for parallel and distributed computation. To this date, scientific applications remain some of the most compute intensive, and have inspired creation of petaflop compute infrastructure such as the Oak Ridge Jaguar and Los Alamos RoadRunner. Large dedicated hardware infrastructure has become both a blessing and a curse to the scientific community. Scientists are interested in cloud computing for much the same reason as businesses and other professionals. The hardware is provided, maintained, and administrated by a third party. Software abstraction and virtualization provide reliability, and fault tolerance. Graduated fees allow for multi-scale prototyping and execution. Cloud computing resources are only a few clicks away, and by far the easiest high performance distributed platform to gain access to. There may still be dedicated infrastructure for ultra-scale science, but the cloud can easily play a major part of the scientific computing initiative.

Development and Performance of the Modularized, High-performance Computing and Hybrid-architecture Capable GEOS-Chem Chemical Transport Model

NASA Astrophysics Data System (ADS)

Long, M. S.; Yantosca, R.; Nielsen, J.; Linford, J. C.; Keller, C. A.; Payer Sulprizio, M.; Jacob, D. J.

2014-12-01

The GEOS-Chem global chemical transport model (CTM), used by a large atmospheric chemistry research community, has been reengineered to serve as a platform for a range of computational atmospheric chemistry science foci and applications. Development included modularization for coupling to general circulation and Earth system models (ESMs) and the adoption of co-processor capable atmospheric chemistry solvers. This was done using an Earth System Modeling Framework (ESMF) interface that operates independently of GEOS-Chem scientific code to permit seamless transition from the GEOS-Chem stand-alone serial CTM to deployment as a coupled ESM module. In this manner, the continual stream of updates contributed by the CTM user community is automatically available for broader applications, which remain state-of-science and directly referenceable to the latest version of the standard GEOS-Chem CTM. These developments are now available as part of the standard version of the GEOS-Chem CTM. The system has been implemented as an atmospheric chemistry module within the NASA GEOS-5 ESM. The coupled GEOS-5/GEOS-Chem system was tested for weak and strong scalability and performance with a tropospheric oxidant-aerosol simulation. Results confirm that the GEOS-Chem chemical operator scales efficiently for any number of processes. Although inclusion of atmospheric chemistry in ESMs is computationally expensive, the excellent scalability of the chemical operator means that the relative cost goes down with increasing number of processes, making fine-scale resolution simulations possible.

NCI HPC Scaling and Optimisation in Climate, Weather, Earth system science and the Geosciences

NASA Astrophysics Data System (ADS)

Evans, B. J. K.; Bermous, I.; Freeman, J.; Roberts, D. S.; Ward, M. L.; Yang, R.

2016-12-01

The Australian National Computational Infrastructure (NCI) has a national focus in the Earth system sciences including climate, weather, ocean, water management, environment and geophysics. NCI leads a Program across its partners from the Australian science agencies and research communities to identify priority computational models to scale-up. Typically, these cases place a large overall demand on the available computer time, need to scale to higher resolutions, use excessive scarce resources such as large memory or bandwidth that limits, or in some cases, need to meet requirements for transition to a separate operational forecasting system, with set time-windows. The model codes include the UK Met Office Unified Model atmospheric model (UM), GFDL's Modular Ocean Model (MOM), both the UK Met Office's GC3 and Australian ACCESS coupled-climate systems (including sea ice), 4D-Var data assimilation and satellite processing, the Regional Ocean Model (ROMS), and WaveWatch3 as well as geophysics codes including hazards, magentuellerics, seismic inversions, and geodesy. Many of these codes use significant compute resources both for research applications as well as within the operational systems. Some of these models are particularly complex, and their behaviour had not been critically analysed for effective use of the NCI supercomputer or how they could be improved. As part of the Program, we have established a common profiling methodology that uses a suite of open source tools for performing scaling analyses. The most challenging cases are profiling multi-model coupled systems where the component models have their own complex algorithms and performance issues. We have also found issues within the current suite of profiling tools, and no single tool fully exposes the nature of the code performance. As a result of this work, international collaborations are now in place to ensure that improvements are incorporated within the community models, and our effort can be targeted in a coordinated way. The coordinations have involved user stakeholders, the model developer community, and dependent software libraries. For example, we have spent significant time characterising I/O scalability, and improving the use of libraries such as NetCDF and HDF5.

Accelerating the Mining of Influential Nodes in Complex Networks through Community Detection

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

Halappanavar, Mahantesh; Sathanur, Arun V.; Nandi, Apurba

Computing the set of influential nodes with a given size to ensure maximal spread of influence on a complex network is a challenging problem impacting multiple applications. A rigorous approach to influence maximization involves utilization of optimization routines that comes with a high computational cost. In this work, we propose to exploit the existence of communities in complex networks to accelerate the mining of influential seeds. We provide intuitive reasoning to explain why our approach should be able to provide speedups without significantly degrading the extent of the spread of influence when compared to the case of influence maximization withoutmore » using the community information. Additionally, we have parallelized the complete workflow by leveraging an existing parallel implementation of the Louvain community detection algorithm. We then conduct a series of experiments on a dataset with three representative graphs to first verify our implementation and then demonstrate the speedups. Our method achieves speedups ranging from 3x - 28x for graphs with small number of communities while nearly matching or even exceeding the activation performance on the entire graph. Complexity analysis reveals that dramatic speedups are possible for larger graphs that contain a correspondingly larger number of communities. In addition to the speedups obtained from the utilization of the community structure, scalability results show up to 6.3x speedup on 20 cores relative to the baseline run on 2 cores. Finally, current limitations of the approach are outlined along with the planned next steps.« less

2013 R&D 100 Award: ‘Miniapps’ Bolster High Performance Computing

ScienceCinema

Belak, Jim; Richards, David

2018-06-12

Two Livermore computer scientists served on a Sandia National Laboratories-led team that developed Mantevo Suite 1.0, the first integrated suite of small software programs, also called "miniapps," to be made available to the high performance computing (HPC) community. These miniapps facilitate the development of new HPC systems and the applications that run on them. Miniapps (miniature applications) serve as stripped down surrogates for complex, full-scale applications that can require a great deal of time and effort to port to a new HPC system because they often consist of hundreds of thousands of lines of code. The miniapps are a prototype that contains some or all of the essentials of the real application but with many fewer lines of code, making the miniapp more versatile for experimentation. This allows researchers to more rapidly explore options and optimize system design, greatly improving the chances the full-scale application will perform successfully. These miniapps have become essential tools for exploring complex design spaces because they can reliably predict the performance of full applications.

High performance hybrid functional Petri net simulations of biological pathway models on CUDA.

PubMed

Chalkidis, Georgios; Nagasaki, Masao; Miyano, Satoru

2011-01-01

Hybrid functional Petri nets are a wide-spread tool for representing and simulating biological models. Due to their potential of providing virtual drug testing environments, biological simulations have a growing impact on pharmaceutical research. Continuous research advancements in biology and medicine lead to exponentially increasing simulation times, thus raising the demand for performance accelerations by efficient and inexpensive parallel computation solutions. Recent developments in the field of general-purpose computation on graphics processing units (GPGPU) enabled the scientific community to port a variety of compute intensive algorithms onto the graphics processing unit (GPU). This work presents the first scheme for mapping biological hybrid functional Petri net models, which can handle both discrete and continuous entities, onto compute unified device architecture (CUDA) enabled GPUs. GPU accelerated simulations are observed to run up to 18 times faster than sequential implementations. Simulating the cell boundary formation by Delta-Notch signaling on a CUDA enabled GPU results in a speedup of approximately 7x for a model containing 1,600 cells.

Hopkinsville-Christian County Library, Final Performance Report for Library Services and Construction Act (LSCA) Title VI, Library Literacy Program.

ERIC Educational Resources Information Center

Nevels, Vada Germaine

The Hopkinsville-Christian County Library (Kentucky) conducted a project that involved recruitment, public awareness, basic literacy, collection development, tutoring, computer-assisted, other technology, and intergenerational/family programs. The project served a community of 50,000-100,000 people, and targeted the learning disabled,…

Columbia County Public Library, Final Performance Report for Library Services and Construction Act (LSCA) Title VI, Library Literacy Program.

ERIC Educational Resources Information Center

Cole, Lucy; Fraser, Ruth

The Columbia County Public Library (Lake City, Florida) conducted a project that involved recruitment, retention, public awareness, training, basic literacy, collection development, tutoring, computer- assisted, other technology, intergenerational/family, and English as a Second Language (ESL) programs. The project served a community of…

Peregrine Software Toolchains | High-Performance Computing | NREL

Science.gov Websites

toolchain is an open-source alternative against which many technical applications are natively developed and tested. The Portland Group compilers are not fully supported, but are available to the HPC community. Use Group (PGI) C/C++ and Fortran (partially supported) The PGI Accelerator compilers include NVIDIA GPU

Community Needs Assessment for an Electronics and Computer Engineering Technology Program at Maui, Molokai, and Lanai.

ERIC Educational Resources Information Center

Pezzoli, Jean A.

In June 1992, Maui Community College (MCC), in Hawaii, conducted a survey of the communities of Maui, Molokai, Lanai, and Hana to determine perceived needs for an associate degree and certificate program in electronics and computer engineering. Questionnaires were mailed to 500 firms utilizing electronic or computer services, seeking information…

Simulating Hydrologic Flow and Reactive Transport with PFLOTRAN and PETSc on Emerging Fine-Grained Parallel Computer Architectures

NASA Astrophysics Data System (ADS)

Mills, R. T.; Rupp, K.; Smith, B. F.; Brown, J.; Knepley, M.; Zhang, H.; Adams, M.; Hammond, G. E.

2017-12-01

As the high-performance computing community pushes towards the exascale horizon, power and heat considerations have driven the increasing importance and prevalence of fine-grained parallelism in new computer architectures. High-performance computing centers have become increasingly reliant on GPGPU accelerators and "manycore" processors such as the Intel Xeon Phi line, and 512-bit SIMD registers have even been introduced in the latest generation of Intel's mainstream Xeon server processors. The high degree of fine-grained parallelism and more complicated memory hierarchy considerations of such "manycore" processors present several challenges to existing scientific software. Here, we consider how the massively parallel, open-source hydrologic flow and reactive transport code PFLOTRAN - and the underlying Portable, Extensible Toolkit for Scientific Computation (PETSc) library on which it is built - can best take advantage of such architectures. We will discuss some key features of these novel architectures and our code optimizations and algorithmic developments targeted at them, and present experiences drawn from working with a wide range of PFLOTRAN benchmark problems on these architectures.

MetaboTools: A comprehensive toolbox for analysis of genome-scale metabolic models

DOE PAGES

Aurich, Maike K.; Fleming, Ronan M. T.; Thiele, Ines

2016-08-03

Metabolomic data sets provide a direct read-out of cellular phenotypes and are increasingly generated to study biological questions. Previous work, by us and others, revealed the potential of analyzing extracellular metabolomic data in the context of the metabolic model using constraint-based modeling. With the MetaboTools, we make our methods available to the broader scientific community. The MetaboTools consist of a protocol, a toolbox, and tutorials of two use cases. The protocol describes, in a step-wise manner, the workflow of data integration, and computational analysis. The MetaboTools comprise the Matlab code required to complete the workflow described in the protocol. Tutorialsmore » explain the computational steps for integration of two different data sets and demonstrate a comprehensive set of methods for the computational analysis of metabolic models and stratification thereof into different phenotypes. The presented workflow supports integrative analysis of multiple omics data sets. Importantly, all analysis tools can be applied to metabolic models without performing the entire workflow. Taken together, the MetaboTools constitute a comprehensive guide to the intra-model analysis of extracellular metabolomic data from microbial, plant, or human cells. In conclusion, this computational modeling resource offers a broad set of computational analysis tools for a wide biomedical and non-biomedical research community.« less

Use of an online survey during an outbreak of clostridium perfringens in a retirement community-Arizona, 2012.

PubMed

Yasmin, Seema; Pogreba-Brown, Kristen; Stewart, Jennifer; Sunenshine, Rebecca

2014-01-01

An outbreak of gastrointestinal (GI) illness among retirement community residents was reported to the Maricopa County Department of Public Health. Online surveys can be useful for rapid investigation of disease outbreaks, especially when local health departments lack time and resources to perform telephone interviews. Online survey utility among older populations, which may lack computer access or literacy, has not been defined. To investigate and implement prevention measures for a GI outbreak and assess the utility of an online survey among retirement community residents. A retrospective cohort investigation was conducted using an online survey distributed through the retirement community e-mail listserv; a follow-up telephone survey was conducted to assess computer literacy and Internet access. A case was defined as any GI illness occurring among residents during March 1-14, 2012. A barbecue in a retirement community of 3000 residents. Retirement community residents. Residents were directed to discard leftover food and seek health care for symptoms. A telephone survey was conducted to assess the utility of online surveys in this population. Computer literacy and Internet access of retirement community residents. Of 1000 residents on the listserv, 370 (37%) completed the online survey (mean age, 69.7 years; 60.6% women); 66 residents (17.8%) reported a GI illness after the barbecue, 63 (95.5%) reported diarrhea, and 5 (7.6%) reported vomiting. Leftover beef from an attendee's refrigerator grew Clostridium perfringens. Of 552 residents contacted by telephone, 113 completed the telephone survey (mean age, 71.3 years; 63.3% women), 101 (89.4%) reported the ability to send e-mail, 82 (81.2%) checked e-mail daily, and 28 (27.7%) checked e-mail on a handheld device. The attack rate was 17.8% for online versus 2.7% for telephone respondents (P < .001). This outbreak demonstrated the utility of an online survey to rapidly collect information and implement prevention measures among an older demographic.

It takes a village: supporting inquiry- and equity-oriented computer science pedagogy through a professional learning community

NASA Astrophysics Data System (ADS)

Ryoo, Jean; Goode, Joanna; Margolis, Jane

2015-10-01

This article describes the importance that high school computer science teachers place on a teachers' professional learning community designed around an inquiry- and equity-oriented approach for broadening participation in computing. Using grounded theory to analyze four years of teacher surveys and interviews from the Exploring Computer Science (ECS) program in the Los Angeles Unified School District, this article describes how participating in professional development activities purposefully aimed at fostering a teachers' professional learning community helps ECS teachers make the transition to an inquiry-based classroom culture and break professional isolation. This professional learning community also provides experiences that challenge prevalent deficit notions and stereotypes about which students can or cannot excel in computer science.

Dense and Sparse Matrix Operations on the Cell Processor

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

Williams, Samuel W.; Shalf, John; Oliker, Leonid

2005-05-01

The slowing pace of commodity microprocessor performance improvements combined with ever-increasing chip power demands has become of utmost concern to computational scientists. Therefore, the high performance computing community is examining alternative architectures that address the limitations of modern superscalar designs. In this work, we examine STI's forthcoming Cell processor: a novel, low-power architecture that combines a PowerPC core with eight independent SIMD processing units coupled with a software-controlled memory to offer high FLOP/s/Watt. Since neither Cell hardware nor cycle-accurate simulators are currently publicly available, we develop an analytic framework to predict Cell performance on dense and sparse matrix operations, usingmore » a variety of algorithmic approaches. Results demonstrate Cell's potential to deliver more than an order of magnitude better GFLOP/s per watt performance, when compared with the Intel Itanium2 and Cray X1 processors.« less

Affective medicine. A review of affective computing efforts in medical informatics.

PubMed

Luneski, A; Konstantinidis, E; Bamidis, P D

2010-01-01

Affective computing (AC) is concerned with emotional interactions performed with and through computers. It is defined as "computing that relates to, arises from, or deliberately influences emotions". AC enables investigation and understanding of the relation between human emotions and health as well as application of assistive and useful technologies in the medical domain. 1) To review the general state of the art in AC and its applications in medicine, and 2) to establish synergies between the research communities of AC and medical informatics. Aspects related to the human affective state as a determinant of the human health are discussed, coupled with an illustration of significant AC research and related literature output. Moreover, affective communication channels are described and their range of application fields is explored through illustrative examples. The presented conferences, European research projects and research publications illustrate the recent increase of interest in the AC area by the medical community. Tele-home healthcare, AmI, ubiquitous monitoring, e-learning and virtual communities with emotionally expressive characters for elderly or impaired people are few areas where the potential of AC has been realized and applications have emerged. A number of gaps can potentially be overcome through the synergy of AC and medical informatics. The application of AC technologies parallels the advancement of the existing state of the art and the introduction of new methods. The amount of work and projects reviewed in this paper witness an ambitious and optimistic synergetic future of the affective medicine field.

Communities for the New Century.

ERIC Educational Resources Information Center

Bishop, Ann Peterson

2000-01-01

Discusses making community networking a reality for all citizens, noting ways to reduce the digital divide that segments computer use along socioeconomic lines. Lists 4 insights that may help in the design and implementation of community services devoted to computer access and training. Notes a website on community networking, and recent…

Computers and the internet: tools for youth empowerment.

PubMed

Valaitis, Ruta K

2005-10-04

Youth are often disenfranchised in their communities and may feel they have little voice. Since computers are an important aspect of youth culture, they may offer solutions to increasing youth participation in communities. This qualitative case study investigated the perceptions of 19 (predominantly female) inner-city school youth about their use of computers and the Internet in a school-based community development project. Youth working with public health nurses in a school-based community development project communicated with local community members using computer-mediated communication, surveyed peers online, built websites, searched for information online, and prepared project materials using computers and the Internet. Participant observation, semistructured interviews, analysis of online messages, and online- and paper-based surveys were used to gather data about youth's and adults' perceptions and use of the technologies. Constant comparison method and between-method triangulation were used in the analysis to satisfy the existence of themes. Not all youth were interested in working with computers. Some electronic messages from adults were perceived to be critical, and writing to adults was intimidating for some youth. In addition, technical problems were experienced. Despite these barriers, most youth perceived that using computers and the Internet reduced their anxiety concerning communication with adults, increased their control when dealing with adults, raised their perception of their social status, increased participation within the community, supported reflective thought, increased efficiency, and improved their access to resources. Overall, youth perceived computers and the Internet to be empowering tools, and they should be encouraged to use such technology to support them in community initiatives.

Computers and the Internet: Tools for Youth Empowerment

PubMed Central

2005-01-01

Background Youth are often disenfranchised in their communities and may feel they have little voice. Since computers are an important aspect of youth culture, they may offer solutions to increasing youth participation in communities. Objective This qualitative case study investigated the perceptions of 19 (predominantly female) inner-city school youth about their use of computers and the Internet in a school-based community development project. Methods Youth working with public health nurses in a school-based community development project communicated with local community members using computer-mediated communication, surveyed peers online, built websites, searched for information online, and prepared project materials using computers and the Internet. Participant observation, semistructured interviews, analysis of online messages, and online- and paper-based surveys were used to gather data about youth’s and adults’ perceptions and use of the technologies. Constant comparison method and between-method triangulation were used in the analysis to satisfy the existence of themes. Results Not all youth were interested in working with computers. Some electronic messages from adults were perceived to be critical, and writing to adults was intimidating for some youth. In addition, technical problems were experienced. Despite these barriers, most youth perceived that using computers and the Internet reduced their anxiety concerning communication with adults, increased their control when dealing with adults, raised their perception of their social status, increased participation within the community, supported reflective thought, increased efficiency, and improved their access to resources. Conclusions Overall, youth perceived computers and the Internet to be empowering tools, and they should be encouraged to use such technology to support them in community initiatives. PMID:16403715

LXtoo: an integrated live Linux distribution for the bioinformatics community

PubMed Central

2012-01-01

Background Recent advances in high-throughput technologies dramatically increase biological data generation. However, many research groups lack computing facilities and specialists. This is an obstacle that remains to be addressed. Here, we present a Linux distribution, LXtoo, to provide a flexible computing platform for bioinformatics analysis. Findings Unlike most of the existing live Linux distributions for bioinformatics limiting their usage to sequence analysis and protein structure prediction, LXtoo incorporates a comprehensive collection of bioinformatics software, including data mining tools for microarray and proteomics, protein-protein interaction analysis, and computationally complex tasks like molecular dynamics. Moreover, most of the programs have been configured and optimized for high performance computing. Conclusions LXtoo aims to provide well-supported computing environment tailored for bioinformatics research, reducing duplication of efforts in building computing infrastructure. LXtoo is distributed as a Live DVD and freely available at http://bioinformatics.jnu.edu.cn/LXtoo. PMID:22813356

LXtoo: an integrated live Linux distribution for the bioinformatics community.

PubMed

Yu, Guangchuang; Wang, Li-Gen; Meng, Xiao-Hua; He, Qing-Yu

2012-07-19

Recent advances in high-throughput technologies dramatically increase biological data generation. However, many research groups lack computing facilities and specialists. This is an obstacle that remains to be addressed. Here, we present a Linux distribution, LXtoo, to provide a flexible computing platform for bioinformatics analysis. Unlike most of the existing live Linux distributions for bioinformatics limiting their usage to sequence analysis and protein structure prediction, LXtoo incorporates a comprehensive collection of bioinformatics software, including data mining tools for microarray and proteomics, protein-protein interaction analysis, and computationally complex tasks like molecular dynamics. Moreover, most of the programs have been configured and optimized for high performance computing. LXtoo aims to provide well-supported computing environment tailored for bioinformatics research, reducing duplication of efforts in building computing infrastructure. LXtoo is distributed as a Live DVD and freely available at http://bioinformatics.jnu.edu.cn/LXtoo.

Mesoscopic modelling and simulation of soft matter.

PubMed

Schiller, Ulf D; Krüger, Timm; Henrich, Oliver

2017-12-20

The deformability of soft condensed matter often requires modelling of hydrodynamical aspects to gain quantitative understanding. This, however, requires specialised methods that can resolve the multiscale nature of soft matter systems. We review a number of the most popular simulation methods that have emerged, such as Langevin dynamics, dissipative particle dynamics, multi-particle collision dynamics, sometimes also referred to as stochastic rotation dynamics, and the lattice-Boltzmann method. We conclude this review with a short glance at current compute architectures for high-performance computing and community codes for soft matter simulation.

Applied Computational Electromagnetics Society Journal (ACES); Special Issue on Electromagnetics and High Performance Computing. Vol. 13, No. 2

DTIC Science & Technology

1998-07-01

author’s responsibility to obtain written permission to reproduce such material. 1 " vssmwmato srÄmaöNfTT fWi««-ii|<.1iw »■■«. i-i...interesting to compare papers in the issue with previous special issues of other jour- nals and monographs, for example [ 1 , 2]. HPC issues first attracted...environment, in particular the Kendall Square Research KSR- 1 . Fast algorithms have attracted considerable atten- tion in the CEM community, since they

HPC Annual Report 2017

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

Dennig, Yasmin

Sandia National Laboratories has a long history of significant contributions to the high performance community and industry. Our innovative computer architectures allowed the United States to become the first to break the teraFLOP barrier—propelling us to the international spotlight. Our advanced simulation and modeling capabilities have been integral in high consequence US operations such as Operation Burnt Frost. Strong partnerships with industry leaders, such as Cray, Inc. and Goodyear, have enabled them to leverage our high performance computing (HPC) capabilities to gain a tremendous competitive edge in the marketplace. As part of our continuing commitment to providing modern computing infrastructuremore » and systems in support of Sandia missions, we made a major investment in expanding Building 725 to serve as the new home of HPC systems at Sandia. Work is expected to be completed in 2018 and will result in a modern facility of approximately 15,000 square feet of computer center space. The facility will be ready to house the newest National Nuclear Security Administration/Advanced Simulation and Computing (NNSA/ASC) Prototype platform being acquired by Sandia, with delivery in late 2019 or early 2020. This new system will enable continuing advances by Sandia science and engineering staff in the areas of operating system R&D, operation cost effectiveness (power and innovative cooling technologies), user environment and application code performance.« less

Instructional Computer Use in the Community College: A Discussion of the Research and Its Implications.

ERIC Educational Resources Information Center

Bower, Beverly L.

1998-01-01

Reviews research on the instructional benefits of computer technology. Discusses the computer readiness of students, faculty, and institutions, and suggests that despite mixed findings, political and organizational realities indicate computer-based instruction is a feasible alternative for community colleges. Therefore, educators should continue…

Instructional Computing in the Community Colleges of Washington State.

ERIC Educational Resources Information Center

Howard, Alan; And Others

A description of current activities in instructional computing in Washington State community colleges is presented, along with curriculum content guidelines and planning procedures to assist colleges which plan to initiate or upgrade their activities in instructional computing. The document provides an overview of computing activities in the…

Development of a clean optical telescope

NASA Technical Reports Server (NTRS)

Brown, R. A.

1983-01-01

Particulate contamination on astronomical mirrors degrades performance in two ways: by information loss by extinction of light; and background and noise from scattering, especially forward or Fraunhofer scattering. These effects were not generally understood, and an ambitious pilot program was outlined to measure particulate effects on telescope optical performance; develop prophylactic and cleaning procedures suitable for groundbased observatories; investigate by computational modelling the effects on telescopes in space; and communicate the results and concerns within the astronomical community.

Hibbing Community College's Community Computer Center.

ERIC Educational Resources Information Center

Regional Technology Strategies, Inc., Carrboro, NC.

This paper reports on the development of the Community Computer Center (CCC) at Hibbing Community College (HCC) in Minnesota. HCC is located in the largest U.S. iron mining area in the United States. Closures of steel-producing plants are affecting the Hibbing area. Outmigration, particularly of younger workers and their families, has been…

Twenty-First Century Learning: Communities, Interaction and Ubiquitous Computing

ERIC Educational Resources Information Center

Leh, Amy S.C.; Kouba, Barbara; Davis, Dirk

2005-01-01

Advanced technology makes 21st century learning, communities and interactions unique and leads people to an era of ubiquitous computing. The purpose of this article is to contribute to the discussion of learning in the 21st century. The paper will review literature on learning community, community learning, interaction, 21st century learning and…

Data handling and visualization for NASA's science programs

NASA Technical Reports Server (NTRS)

Bredekamp, Joseph H. (Editor)

1995-01-01

Advanced information systems capabilities are essential to conducting NASA's scientific research mission. Access to these capabilities is no longer a luxury for a select few within the science community, but rather an absolute necessity for carrying out scientific investigations. The dependence on high performance computing and networking, as well as ready and expedient access to science data, metadata, and analysis tools is the fundamental underpinning for the entire research endeavor. At the same time, advances in the whole range of information technologies continues on an almost explosive growth path, reaching beyond the research community to affect the population as a whole. Capitalizing on and exploiting these advances are critical to the continued success of space science investigations. NASA must remain abreast of developments in the field and strike an appropriate balance between being a smart buyer and a direct investor in the technology which serves its unique requirements. Another key theme deals with the need for the space and computer science communities to collaborate as partners to more fully realize the potential of information technology in the space science research environment.

Discontinuous Galerkin Methods and High-Speed Turbulent Flows

NASA Astrophysics Data System (ADS)

Atak, Muhammed; Larsson, Johan; Munz, Claus-Dieter

2014-11-01

Discontinuous Galerkin methods gain increasing importance within the CFD community as they combine arbitrary high order of accuracy in complex geometries with parallel efficiency. Particularly the discontinuous Galerkin spectral element method (DGSEM) is a promising candidate for both the direct numerical simulation (DNS) and large eddy simulation (LES) of turbulent flows due to its excellent scaling attributes. In this talk, we present a DNS of a compressible turbulent boundary layer along a flat plate at a free-stream Mach number of M = 2.67 and assess the computational efficiency of the DGSEM at performing high-fidelity simulations of both transitional and turbulent boundary layers. We compare the accuracy of the results as well as the computational performance to results using a high order finite difference method.

Bridging the digital divide by increasing computer and cancer literacy: community technology centers for head-start parents and families.

PubMed

Salovey, Peter; Williams-Piehota, Pamela; Mowad, Linda; Moret, Marta Elisa; Edlund, Denielle; Andersen, Judith

2009-01-01

This article describes the establishment of two community technology centers affiliated with Head Start early childhood education programs focused especially on Latino and African American parents of children enrolled in Head Start. A 6-hour course concerned with computer and cancer literacy was presented to 120 parents and other community residents who earned a free, refurbished, Internet-ready computer after completing the program. Focus groups provided the basis for designing the structure and content of the course and modifying it during the project period. An outcomes-based assessment comparing program participants with 70 nonparticipants at baseline, immediately after the course ended, and 3 months later suggested that the program increased knowledge about computers and their use, knowledge about cancer and its prevention, and computer use including health information-seeking via the Internet. The creation of community computer technology centers requires the availability of secure space, capacity of a community partner to oversee project implementation, and resources of this partner to ensure sustainability beyond core funding.

Community Petascale Project for Accelerator Science and Simulation: Advancing Computational Science for Future Accelerators and Accelerator Technologies

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

Spentzouris, P.; /Fermilab; Cary, J.

The design and performance optimization of particle accelerators are essential for the success of the DOE scientific program in the next decade. Particle accelerators are very complex systems whose accurate description involves a large number of degrees of freedom and requires the inclusion of many physics processes. Building on the success of the SciDAC-1 Accelerator Science and Technology project, the SciDAC-2 Community Petascale Project for Accelerator Science and Simulation (ComPASS) is developing a comprehensive set of interoperable components for beam dynamics, electromagnetics, electron cooling, and laser/plasma acceleration modelling. ComPASS is providing accelerator scientists the tools required to enable the necessarymore » accelerator simulation paradigm shift from high-fidelity single physics process modeling (covered under SciDAC1) to high-fidelity multiphysics modeling. Our computational frameworks have been used to model the behavior of a large number of accelerators and accelerator R&D experiments, assisting both their design and performance optimization. As parallel computational applications, the ComPASS codes have been shown to make effective use of thousands of processors. ComPASS is in the first year of executing its plan to develop the next-generation HPC accelerator modeling tools. ComPASS aims to develop an integrated simulation environment that will utilize existing and new accelerator physics modules with petascale capabilities, by employing modern computing and solver technologies. The ComPASS vision is to deliver to accelerator scientists a virtual accelerator and virtual prototyping modeling environment, with the necessary multiphysics, multiscale capabilities. The plan for this development includes delivering accelerator modeling applications appropriate for each stage of the ComPASS software evolution. Such applications are already being used to address challenging problems in accelerator design and optimization. The ComPASS organization for software development and applications accounts for the natural domain areas (beam dynamics, electromagnetics, and advanced acceleration), and all areas depend on the enabling technologies activities, such as solvers and component technology, to deliver the desired performance and integrated simulation environment. The ComPASS applications focus on computationally challenging problems important for design or performance optimization to all major HEP, NP, and BES accelerator facilities. With the cost and complexity of particle accelerators rising, the use of computation to optimize their designs and find improved operating regimes becomes essential, potentially leading to significant cost savings with modest investment.« less

Marin County Free Library, Final Performance Report for Library Services and Construction Act (LSCA) Title VI, Library Literacy Program.

ERIC Educational Resources Information Center

Mooney, Sharon Lopez

The West Marin Literacy Project, a project of the Marin County Free Library (San Rafael, California), involved recruitment, retention, coalition building, public awareness, training, rural oriented, tutoring, computer- assisted, intergenerational/family, and English as a Second Language (ESL) programs. The project served a community of under…

Modeling and Analysis Compute Environments, Utilizing Virtualization Technology in the Climate and Earth Systems Science domain

NASA Astrophysics Data System (ADS)

Michaelis, A.; Nemani, R. R.; Wang, W.; Votava, P.; Hashimoto, H.

2010-12-01

Given the increasing complexity of climate modeling and analysis tools, it is often difficult and expensive to build or recreate an exact replica of the software compute environment used in past experiments. With the recent development of new technologies for hardware virtualization, an opportunity exists to create full modeling, analysis and compute environments that are “archiveable”, transferable and may be easily shared amongst a scientific community or presented to a bureaucratic body if the need arises. By encapsulating and entire modeling and analysis environment in a virtual machine image, others may quickly gain access to the fully built system used in past experiments, potentially easing the task and reducing the costs of reproducing and verify past results produced by other researchers. Moreover, these virtual machine images may be used as a pedagogical tool for others that are interested in performing an academic exercise but don't yet possess the broad expertise required. We built two virtual machine images, one with the Community Earth System Model (CESM) and one with Weather Research Forecast Model (WRF), then ran several small experiments to assess the feasibility, performance overheads costs, reusability, and transferability. We present a list of the pros and cons as well as lessoned learned from utilizing virtualization technology in the climate and earth systems modeling domain.

Spatiotemporal Domain Decomposition for Massive Parallel Computation of Space-Time Kernel Density

NASA Astrophysics Data System (ADS)

Hohl, A.; Delmelle, E. M.; Tang, W.

2015-07-01

Accelerated processing capabilities are deemed critical when conducting analysis on spatiotemporal datasets of increasing size, diversity and availability. High-performance parallel computing offers the capacity to solve computationally demanding problems in a limited timeframe, but likewise poses the challenge of preventing processing inefficiency due to workload imbalance between computing resources. Therefore, when designing new algorithms capable of implementing parallel strategies, careful spatiotemporal domain decomposition is necessary to account for heterogeneity in the data. In this study, we perform octtree-based adaptive decomposition of the spatiotemporal domain for parallel computation of space-time kernel density. In order to avoid edge effects near subdomain boundaries, we establish spatiotemporal buffers to include adjacent data-points that are within the spatial and temporal kernel bandwidths. Then, we quantify computational intensity of each subdomain to balance workloads among processors. We illustrate the benefits of our methodology using a space-time epidemiological dataset of Dengue fever, an infectious vector-borne disease that poses a severe threat to communities in tropical climates. Our parallel implementation of kernel density reaches substantial speedup compared to sequential processing, and achieves high levels of workload balance among processors due to great accuracy in quantifying computational intensity. Our approach is portable of other space-time analytical tests.

The Technology Refresh Program: Affording State-of-the Art Personal Computing.

ERIC Educational Resources Information Center

Spiwak, Rand

2000-01-01

Describes the Florida Community College Technology Refresh Program in which 28 Florida community colleges refresh their personal computer technology on a three-year cyclical basis through negotiation of a contract with Dell Computer Corporation. Discusses the contract highlights (such as a 22.5 percent discount on personal computers and on-site…

The Materials Commons: A Collaboration Platform and Information Repository for the Global Materials Community

NASA Astrophysics Data System (ADS)

Puchala, Brian; Tarcea, Glenn; Marquis, Emmanuelle. A.; Hedstrom, Margaret; Jagadish, H. V.; Allison, John E.

2016-08-01

Accelerating the pace of materials discovery and development requires new approaches and means of collaborating and sharing information. To address this need, we are developing the Materials Commons, a collaboration platform and information repository for use by the structural materials community. The Materials Commons has been designed to be a continuous, seamless part of the scientific workflow process. Researchers upload the results of experiments and computations as they are performed, automatically where possible, along with the provenance information describing the experimental and computational processes. The Materials Commons website provides an easy-to-use interface for uploading and downloading data and data provenance, as well as for searching and sharing data. This paper provides an overview of the Materials Commons. Concepts are also outlined for integrating the Materials Commons with the broader Materials Information Infrastructure that is evolving to support the Materials Genome Initiative.

High Tech Programmers in Low-Income Communities: Creating a Computer Culture in a Community Technology Center

NASA Astrophysics Data System (ADS)

Kafai, Yasmin B.; Peppler, Kylie A.; Chiu, Grace M.

For the last twenty years, issues of the digital divide have driven efforts around the world to address the lack of access to computers and the Internet, pertinent and language appropriate content, and technical skills in low-income communities (Schuler & Day, 2004a and b). The title of our paper makes reference to a milestone publication (Schon, Sanyal, & Mitchell, 1998) that showcased some of the early work and thinking in this area. Schon, Sanyal and Mitchell's book edition included an article outlining the Computer Clubhouse, a type of community technology center model, which was developed to create opportunities for youth in low-income communities to become creators and designers of technologies by (1998). The model has been very successful scaling up, with over 110 Computer Clubhouses now in existence worldwide.

Computer Model Helps Communities Gauge Effects of New Industry.

ERIC Educational Resources Information Center

Long, Celeste; And Others

1987-01-01

Describes computer Industrial Impact Model used by Texas Agricultural Extension Service rural planners to assess potential benefits and costs of new firms on community private and public sectors. Presents selected data/results for two communities assessing impact of the same plant. (NEC)

The TeraShake Computational Platform for Large-Scale Earthquake Simulations

NASA Astrophysics Data System (ADS)

Cui, Yifeng; Olsen, Kim; Chourasia, Amit; Moore, Reagan; Maechling, Philip; Jordan, Thomas

Geoscientific and computer science researchers with the Southern California Earthquake Center (SCEC) are conducting a large-scale, physics-based, computationally demanding earthquake system science research program with the goal of developing predictive models of earthquake processes. The computational demands of this program continue to increase rapidly as these researchers seek to perform physics-based numerical simulations of earthquake processes for larger meet the needs of this research program, a multiple-institution team coordinated by SCEC has integrated several scientific codes into a numerical modeling-based research tool we call the TeraShake computational platform (TSCP). A central component in the TSCP is a highly scalable earthquake wave propagation simulation program called the TeraShake anelastic wave propagation (TS-AWP) code. In this chapter, we describe how we extended an existing, stand-alone, wellvalidated, finite-difference, anelastic wave propagation modeling code into the highly scalable and widely used TS-AWP and then integrated this code into the TeraShake computational platform that provides end-to-end (initialization to analysis) research capabilities. We also describe the techniques used to enhance the TS-AWP parallel performance on TeraGrid supercomputers, as well as the TeraShake simulations phases including input preparation, run time, data archive management, and visualization. As a result of our efforts to improve its parallel efficiency, the TS-AWP has now shown highly efficient strong scaling on over 40K processors on IBM’s BlueGene/L Watson computer. In addition, the TSCP has developed into a computational system that is useful to many members of the SCEC community for performing large-scale earthquake simulations.

Advanced Scientific Computing Research Exascale Requirements Review. An Office of Science review sponsored by Advanced Scientific Computing Research, September 27-29, 2016, Rockville, Maryland

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

Almgren, Ann; DeMar, Phil; Vetter, Jeffrey

The widespread use of computing in the American economy would not be possible without a thoughtful, exploratory research and development (R&D) community pushing the performance edge of operating systems, computer languages, and software libraries. These are the tools and building blocks — the hammers, chisels, bricks, and mortar — of the smartphone, the cloud, and the computing services on which we rely. Engineers and scientists need ever-more specialized computing tools to discover new material properties for manufacturing, make energy generation safer and more efficient, and provide insight into the fundamentals of the universe, for example. The research division of themore » U.S. Department of Energy’s (DOE’s) Office of Advanced Scientific Computing and Research (ASCR Research) ensures that these tools and building blocks are being developed and honed to meet the extreme needs of modern science. See also http://exascaleage.org/ascr/ for additional information.« less

The Chemistry Development Kit (CDK) v2.0: atom typing, depiction, molecular formulas, and substructure searching.

PubMed

Willighagen, Egon L; Mayfield, John W; Alvarsson, Jonathan; Berg, Arvid; Carlsson, Lars; Jeliazkova, Nina; Kuhn, Stefan; Pluskal, Tomáš; Rojas-Chertó, Miquel; Spjuth, Ola; Torrance, Gilleain; Evelo, Chris T; Guha, Rajarshi; Steinbeck, Christoph

2017-06-06

The Chemistry Development Kit (CDK) is a widely used open source cheminformatics toolkit, providing data structures to represent chemical concepts along with methods to manipulate such structures and perform computations on them. The library implements a wide variety of cheminformatics algorithms ranging from chemical structure canonicalization to molecular descriptor calculations and pharmacophore perception. It is used in drug discovery, metabolomics, and toxicology. Over the last 10 years, the code base has grown significantly, however, resulting in many complex interdependencies among components and poor performance of many algorithms. We report improvements to the CDK v2.0 since the v1.2 release series, specifically addressing the increased functional complexity and poor performance. We first summarize the addition of new functionality, such atom typing and molecular formula handling, and improvement to existing functionality that has led to significantly better performance for substructure searching, molecular fingerprints, and rendering of molecules. Second, we outline how the CDK has evolved with respect to quality control and the approaches we have adopted to ensure stability, including a code review mechanism. This paper highlights our continued efforts to provide a community driven, open source cheminformatics library, and shows that such collaborative projects can thrive over extended periods of time, resulting in a high-quality and performant library. By taking advantage of community support and contributions, we show that an open source cheminformatics project can act as a peer reviewed publishing platform for scientific computing software. Graphical abstract CDK 2.0 provides new features and improved performance.

Administrators' Perceptions of Community College Students' Computer Literacy Skills in Beginner Courses

ERIC Educational Resources Information Center

Ragin, Tracey B.

2013-01-01

Fundamental computer skills are vital in the current technology-driven society. The purpose of this study was to investigate the development needs of students at a rural community college in the Southeast who lacked the computer literacy skills required in a basic computer course. Guided by Greenwood's pragmatic approach as a reformative force in…

It Takes a Village: Supporting Inquiry- and Equity-Oriented Computer Science Pedagogy through a Professional Learning Community

ERIC Educational Resources Information Center

Ryoo, Jean; Goode, Joanna; Margolis, Jane

2015-01-01

This article describes the importance that high school computer science teachers place on a teachers' professional learning community designed around an inquiry- and equity-oriented approach for broadening participation in computing. Using grounded theory to analyze four years of teacher surveys and interviews from the Exploring Computer Science…

MIUS community conceptual design study

NASA Technical Reports Server (NTRS)

Fulbright, B. E.

1976-01-01

The feasibility, practicality, and applicability of the modular integrated utility systems (MIUS) concept to a satellite new-community development with a population of approximately 100,000 were analyzed. Two MIUS design options, the 29-MIUS-unit (option 1) and the 8-MIUS-unit (option 2) facilities were considered. Each resulted in considerable resource savings when compared to a conventional utility system. Economic analyses indicated that the total cash outlay and operations and maintenance costs for these two options were considerably less than for a conventional system. Computer analyses performed in support of this study provided corroborative data for the study group. An environmental impact assessment was performed to determine whether the MIUS meets or will meet necessary environmental standards. The MIUS can provide improved efficiency in the conservation of natural resources while not adversely affecting the physical environment.

Climate Modeling Computing Needs Assessment

NASA Astrophysics Data System (ADS)

Petraska, K. E.; McCabe, J. D.

2011-12-01

This paper discusses early findings of an assessment of computing needs for NASA science, engineering and flight communities. The purpose of this assessment is to document a comprehensive set of computing needs that will allow us to better evaluate whether our computing assets are adequately structured to meet evolving demand. The early results are interesting, already pointing out improvements we can make today to get more out of the computing capacity we have, as well as potential game changing innovations for the future in how we apply information technology to science computing. Our objective is to learn how to leverage our resources in the best way possible to do more science for less money. Our approach in this assessment is threefold: Development of use case studies for science workflows; Creating a taxonomy and structure for describing science computing requirements; and characterizing agency computing, analysis, and visualization resources. As projects evolve, science data sets increase in a number of ways: in size, scope, timelines, complexity, and fidelity. Generating, processing, moving, and analyzing these data sets places distinct and discernable requirements on underlying computing, analysis, storage, and visualization systems. The initial focus group for this assessment is the Earth Science modeling community within NASA's Science Mission Directorate (SMD). As the assessment evolves, this focus will expand to other science communities across the agency. We will discuss our use cases, our framework for requirements and our characterizations, as well as our interview process, what we learned and how we plan to improve our materials after using them in the first round of interviews in the Earth Science Modeling community. We will describe our plans for how to expand this assessment, first into the Earth Science data analysis and remote sensing communities, and then throughout the full community of science, engineering and flight at NASA.

Final report for Conference Support Grant "From Computational Biophysics to Systems Biology - CBSB12"

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

Hansmann, Ulrich H.E.

2012-07-02

This report summarizes the outcome of the international workshop From Computational Biophysics to Systems Biology (CBSB12) which was held June 3-5, 2012, at the University of Tennessee Conference Center in Knoxville, TN, and supported by DOE through the Conference Support Grant 120174. The purpose of CBSB12 was to provide a forum for the interaction between a data-mining interested systems biology community and a simulation and first-principle oriented computational biophysics/biochemistry community. CBSB12 was the sixth in a series of workshops of the same name organized in recent years, and the second that has been held in the USA. As in previousmore » years, it gave researchers from physics, biology, and computer science an opportunity to acquaint each other with current trends in computational biophysics and systems biology, to explore venues of cooperation, and to establish together a detailed understanding of cells at a molecular level. The conference grant of $10,000 was used to cover registration fees and provide travel fellowships to selected students and postdoctoral scientists. By educating graduate students and providing a forum for young scientists to perform research into the working of cells at a molecular level, the workshop adds to DOE's mission of paving the way to exploit the abilities of living systems to capture, store and utilize energy.« less

[Activities of Research Institute for Advanced Computer Science

NASA Technical Reports Server (NTRS)

Gross, Anthony R. (Technical Monitor); Leiner, Barry M.

2001-01-01

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administrations missions. RIACS is located at the NASA Ames Research Center, Moffett Field, California. RIACS research focuses on the three cornerstones of IT research necessary to meet the future challenges of NASA missions: 1. Automated Reasoning for Autonomous Systems Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth. 2. Human-Centered Computing Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities. 3. High Performance Computing and Networking Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to analysis of large scientific datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply IT research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, visiting scientist programs and student summer programs, designed to encourage and facilitate collaboration between the university and NASA IT research communities.

S-MART, a software toolbox to aid RNA-Seq data analysis.

PubMed

Zytnicki, Matthias; Quesneville, Hadi

2011-01-01

High-throughput sequencing is now routinely performed in many experiments. But the analysis of the millions of sequences generated, is often beyond the expertise of the wet labs who have no personnel specializing in bioinformatics. Whereas several tools are now available to map high-throughput sequencing data on a genome, few of these can extract biological knowledge from the mapped reads. We have developed a toolbox called S-MART, which handles mapped RNA-Seq data. S-MART is an intuitive and lightweight tool which performs many of the tasks usually required for the analysis of mapped RNA-Seq reads. S-MART does not require any computer science background and thus can be used by all of the biologist community through a graphical interface. S-MART can run on any personal computer, yielding results within an hour even for Gb of data for most queries. S-MART may perform the entire analysis of the mapped reads, without any need for other ad hoc scripts. With this tool, biologists can easily perform most of the analyses on their computer for their RNA-Seq data, from the mapped data to the discovery of important loci.

S-MART, A Software Toolbox to Aid RNA-seq Data Analysis

PubMed Central

Zytnicki, Matthias; Quesneville, Hadi

2011-01-01

High-throughput sequencing is now routinely performed in many experiments. But the analysis of the millions of sequences generated, is often beyond the expertise of the wet labs who have no personnel specializing in bioinformatics. Whereas several tools are now available to map high-throughput sequencing data on a genome, few of these can extract biological knowledge from the mapped reads. We have developed a toolbox called S-MART, which handles mapped RNA-Seq data. S-MART is an intuitive and lightweight tool which performs many of the tasks usually required for the analysis of mapped RNA-Seq reads. S-MART does not require any computer science background and thus can be used by all of the biologist community through a graphical interface. S-MART can run on any personal computer, yielding results within an hour even for Gb of data for most queries. S-MART may perform the entire analysis of the mapped reads, without any need for other ad hoc scripts. With this tool, biologists can easily perform most of the analyses on their computer for their RNA-Seq data, from the mapped data to the discovery of important loci. PMID:21998740

Lessons Learned in the Selection and Development of Test Cases for the Aeroelastic Prediction Workshop: Rectangular Supercritical Wing

NASA Technical Reports Server (NTRS)

Heeg, Jennifer; Chwalowski, Pawel; Wieseman, Carol D.; Florance, Jennifer P.; Schuster, David M.

2013-01-01

The Aeroelastic Prediction Workshop brought together an international community of computational fluid dynamicists as a step in defining the state of the art in computational aeroelasticity. The Rectangular Supercritical Wing (RSW) was chosen as the first configuration to study due to its geometric simplicity, perceived simple flow field at transonic conditions and availability of an experimental data set containing forced oscillation response data. Six teams performed analyses of the RSW; they used Reynolds-Averaged Navier-Stokes flow solvers exercised assuming that the wing had a rigid structure. Both steady-state and forced oscillation computations were performed by each team. The results of these calculations were compared with each other and with the experimental data. The steady-state results from the computations capture many of the flow features of a classical supercritical airfoil pressure distribution. The most dominant feature of the oscillatory results is the upper surface shock dynamics. Substantial variations were observed among the computational solutions as well as differences relative to the experimental data. Contributing issues to these differences include substantial wind tunnel wall effects and diverse choices in the analysis parameters.

Towards a Scalable and Adaptive Application Support Platform for Large-Scale Distributed E-Sciences in High-Performance Network Environments

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

Wu, Chase Qishi; Zhu, Michelle Mengxia

The advent of large-scale collaborative scientific applications has demonstrated the potential for broad scientific communities to pool globally distributed resources to produce unprecedented data acquisition, movement, and analysis. System resources including supercomputers, data repositories, computing facilities, network infrastructures, storage systems, and display devices have been increasingly deployed at national laboratories and academic institutes. These resources are typically shared by large communities of users over Internet or dedicated networks and hence exhibit an inherent dynamic nature in their availability, accessibility, capacity, and stability. Scientific applications using either experimental facilities or computation-based simulations with various physical, chemical, climatic, and biological models featuremore » diverse scientific workflows as simple as linear pipelines or as complex as a directed acyclic graphs, which must be executed and supported over wide-area networks with massively distributed resources. Application users oftentimes need to manually configure their computing tasks over networks in an ad hoc manner, hence significantly limiting the productivity of scientists and constraining the utilization of resources. The success of these large-scale distributed applications requires a highly adaptive and massively scalable workflow platform that provides automated and optimized computing and networking services. This project is to design and develop a generic Scientific Workflow Automation and Management Platform (SWAMP), which contains a web-based user interface specially tailored for a target application, a set of user libraries, and several easy-to-use computing and networking toolkits for application scientists to conveniently assemble, execute, monitor, and control complex computing workflows in heterogeneous high-performance network environments. SWAMP will enable the automation and management of the entire process of scientific workflows with the convenience of a few mouse clicks while hiding the implementation and technical details from end users. Particularly, we will consider two types of applications with distinct performance requirements: data-centric and service-centric applications. For data-centric applications, the main workflow task involves large-volume data generation, catalog, storage, and movement typically from supercomputers or experimental facilities to a team of geographically distributed users; while for service-centric applications, the main focus of workflow is on data archiving, preprocessing, filtering, synthesis, visualization, and other application-specific analysis. We will conduct a comprehensive comparison of existing workflow systems and choose the best suited one with open-source code, a flexible system structure, and a large user base as the starting point for our development. Based on the chosen system, we will develop and integrate new components including a black box design of computing modules, performance monitoring and prediction, and workflow optimization and reconfiguration, which are missing from existing workflow systems. A modular design for separating specification, execution, and monitoring aspects will be adopted to establish a common generic infrastructure suited for a wide spectrum of science applications. We will further design and develop efficient workflow mapping and scheduling algorithms to optimize the workflow performance in terms of minimum end-to-end delay, maximum frame rate, and highest reliability. We will develop and demonstrate the SWAMP system in a local environment, the grid network, and the 100Gpbs Advanced Network Initiative (ANI) testbed. The demonstration will target scientific applications in climate modeling and high energy physics and the functions to be demonstrated include workflow deployment, execution, steering, and reconfiguration. Throughout the project period, we will work closely with the science communities in the fields of climate modeling and high energy physics including Spallation Neutron Source (SNS) and Large Hadron Collider (LHC) projects to mature the system for production use.« less

Columbia Gorge Community College Business Survey.

ERIC Educational Resources Information Center

McKee, Jonathon V.

This is a report on a business survey conducted by Columbia Gorge Community College (CGCC) (Oregon) to review the success and quality of the college's degree and certificate programs in business administration, computer application systems, and computer information systems. The community college surveyed 104 local businesses to verify the…

WAERS: an application for Web-assisted estimation of relative survival.

PubMed

Clèries, Ramon; Valls, Joan; Esteban, Laura; Gálvez, Jordi; Pareja, Laura; Sanz, Xavier; Alliste, Luisa; Martínez, José Miguel; Moreno, Víctor; Bosch, Xavier; Borràs, Josep Maria; Ribes, Josepa Maria

2007-09-01

Net cancer survival estimation is usually performed by computing relative survival (RS), which is defined as the ratio between observed and expected survival rates. The mortality of a reference population is required in order to compute the expected survival rate, which can be performed using a variety of statistical packages. A new Web interface to compute RS, called WAERS, has been developed by the Catalan Institute of Oncology. The reference population is first selected, and then the RS of a cohort is computed. A remote server is used for this purpose. A mock example serves to illustrate the use of the tool with a hypothetical cohort, for which RS is estimated based on three different reference populations (a province of Spain, an autonomous community (Region), and the entire Spanish population). At present, only mortality tables for different areas of Spain are available. Future improvements of this application will include mortality tables of Latin American and European Union countries, and stratified (control variable) analysis. This application can be also useful for cohort mortality studies and for registries of several diseases.

COPEWELL: A Conceptual Framework and System Dynamics Model for Predicting Community Functioning and Resilience After Disasters.

PubMed

Links, Jonathan M; Schwartz, Brian S; Lin, Sen; Kanarek, Norma; Mitrani-Reiser, Judith; Sell, Tara Kirk; Watson, Crystal R; Ward, Doug; Slemp, Cathy; Burhans, Robert; Gill, Kimberly; Igusa, Tak; Zhao, Xilei; Aguirre, Benigno; Trainor, Joseph; Nigg, Joanne; Inglesby, Thomas; Carbone, Eric; Kendra, James M

2018-02-01

Policy-makers and practitioners have a need to assess community resilience in disasters. Prior efforts conflated resilience with community functioning, combined resistance and recovery (the components of resilience), and relied on a static model for what is inherently a dynamic process. We sought to develop linked conceptual and computational models of community functioning and resilience after a disaster. We developed a system dynamics computational model that predicts community functioning after a disaster. The computational model outputted the time course of community functioning before, during, and after a disaster, which was used to calculate resistance, recovery, and resilience for all US counties. The conceptual model explicitly separated resilience from community functioning and identified all key components for each, which were translated into a system dynamics computational model with connections and feedbacks. The components were represented by publicly available measures at the county level. Baseline community functioning, resistance, recovery, and resilience evidenced a range of values and geographic clustering, consistent with hypotheses based on the disaster literature. The work is transparent, motivates ongoing refinements, and identifies areas for improved measurements. After validation, such a model can be used to identify effective investments to enhance community resilience. (Disaster Med Public Health Preparedness. 2018;12:127-137).

Spontaneous Speech Events in Two Speech Databases of Human-Computer and Human-Human Dialogs in Spanish

ERIC Educational Resources Information Center

Rodriguez, Luis J.; Torres, M. Ines

2006-01-01

Previous works in English have revealed that disfluencies follow regular patterns and that incorporating them into the language model of a speech recognizer leads to lower perplexities and sometimes to a better performance. Although work on disfluency modeling has been applied outside the English community (e.g., in Japanese), as far as we know…

The HEPCloud Facility: elastic computing for High Energy Physics - The NOvA Use Case

NASA Astrophysics Data System (ADS)

Fuess, S.; Garzoglio, G.; Holzman, B.; Kennedy, R.; Norman, A.; Timm, S.; Tiradani, A.

2017-10-01

The need for computing in the HEP community follows cycles of peaks and valleys mainly driven by conference dates, accelerator shutdown, holiday schedules, and other factors. Because of this, the classical method of provisioning these resources at providing facilities has drawbacks such as potential overprovisioning. As the appetite for computing increases, however, so does the need to maximize cost efficiency by developing a model for dynamically provisioning resources only when needed. To address this issue, the HEPCloud project was launched by the Fermilab Scientific Computing Division in June 2015. Its goal is to develop a facility that provides a common interface to a variety of resources, including local clusters, grids, high performance computers, and community and commercial Clouds. Initially targeted experiments include CMS and NOvA, as well as other Fermilab stakeholders. In its first phase, the project has demonstrated the use of the “elastic” provisioning model offered by commercial clouds, such as Amazon Web Services. In this model, resources are rented and provisioned automatically over the Internet upon request. In January 2016, the project demonstrated the ability to increase the total amount of global CMS resources by 58,000 cores from 150,000 cores - a 38 percent increase - in preparation for the Recontres de Moriond. In March 2016, the NOvA experiment has also demonstrated resource burst capabilities with an additional 7,300 cores, achieving a scale almost four times as large as the local allocated resources and utilizing the local AWS s3 storage to optimize data handling operations and costs. NOvA was using the same familiar services used for local computations, such as data handling and job submission, in preparation for the Neutrino 2016 conference. In both cases, the cost was contained by the use of the Amazon Spot Instance Market and the Decision Engine, a HEPCloud component that aims at minimizing cost and job interruption. This paper describes the Fermilab HEPCloud Facility and the challenges overcome for the CMS and NOvA communities.

HEP Software Foundation Community White Paper Working Group - Detector Simulation

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

Apostolakis, J.

A working group on detector simulation was formed as part of the high-energy physics (HEP) Software Foundation's initiative to prepare a Community White Paper that describes the main software challenges and opportunities to be faced in the HEP field over the next decade. The working group met over a period of several months in order to review the current status of the Full and Fast simulation applications of HEP experiments and the improvements that will need to be made in order to meet the goals of future HEP experimental programmes. The scope of the topics covered includes the main componentsmore » of a HEP simulation application, such as MC truth handling, geometry modeling, particle propagation in materials and fields, physics modeling of the interactions of particles with matter, the treatment of pileup and other backgrounds, as well as signal processing and digitisation. The resulting work programme described in this document focuses on the need to improve both the software performance and the physics of detector simulation. The goals are to increase the accuracy of the physics models and expand their applicability to future physics programmes, while achieving large factors in computing performance gains consistent with projections on available computing resources.« less

Assessment of RANS and LES Turbulence Modeling for Buoyancy-Aided/Opposed Forced and Mixed Convection

NASA Astrophysics Data System (ADS)

Clifford, Corey; Kimber, Mark

2017-11-01

Over the last 30 years, an industry-wide shift within the nuclear community has led to increased utilization of computational fluid dynamics (CFD) to supplement nuclear reactor safety analyses. One such area that is of particular interest to the nuclear community, specifically to those performing loss-of-flow accident (LOFA) analyses for next-generation very-high temperature reactors (VHTR), is the capacity of current computational models to predict heat transfer across a wide range of buoyancy conditions. In the present investigation, a critical evaluation of Reynolds-averaged Navier-Stokes (RANS) and large-eddy simulation (LES) turbulence modeling techniques is conducted based on CFD validation data collected from the Rotatable Buoyancy Tunnel (RoBuT) at Utah State University. Four different experimental flow conditions are investigated: (1) buoyancy-aided forced convection; (2) buoyancy-opposed forced convection; (3) buoyancy-aided mixed convection; (4) buoyancy-opposed mixed convection. Overall, good agreement is found for both forced convection-dominated scenarios, but an overly-diffusive prediction of the normal Reynolds stress is observed for the RANS-based turbulence models. Low-Reynolds number RANS models perform adequately for mixed convection, while higher-order RANS approaches underestimate the influence of buoyancy on the production of turbulence.

Astronomy and Computing: A new journal for the astronomical computing community

NASA Astrophysics Data System (ADS)

Accomazzi, Alberto; Budavári, Tamás; Fluke, Christopher; Gray, Norman; Mann, Robert G.; O'Mullane, William; Wicenec, Andreas; Wise, Michael

2013-02-01

We introduce Astronomy and Computing, a new journal for the growing population of people working in the domain where astronomy overlaps with computer science and information technology. The journal aims to provide a new communication channel within that community, which is not well served by current journals, and to help secure recognition of its true importance within modern astronomy. In this inaugural editorial, we describe the rationale for creating the journal, outline its scope and ambitions, and seek input from the community in defining in detail how the journal should work towards its high-level goals.

Enhancing Children's Sense of Self and Community through Utilizing Computers.

ERIC Educational Resources Information Center

Haugland, Susan

1996-01-01

Argues that computers in early childhood classrooms serve to raise young children's self-esteem, self-concept, and place in the classroom community. Provides examples of specific computer exercises including storytelling, journals, autobiographies, classroom data collection and recording, and classroom activities. Notes that these computer…

A Student-Centered Perspective of Technology for Learning at California Community Colleges

ERIC Educational Resources Information Center

Regalado, Maria Carmen

2010-01-01

This study investigates how community college students' current levels of computer technology competence, confidence and attitudes toward technology in learning at a community college are affected by current access to technology and by demographic characteristics as well as by past experiences with computer technology. The research questions…

Some Thoughts Regarding Practical Quantum Computing

NASA Astrophysics Data System (ADS)

Ghoshal, Debabrata; Gomez, Richard; Lanzagorta, Marco; Uhlmann, Jeffrey

2006-03-01

Quantum computing has become an important area of research in computer science because of its potential to provide more efficient algorithmic solutions to certain problems than are possible with classical computing. The ability of performing parallel operations over an exponentially large computational space has proved to be the main advantage of the quantum computing model. In this regard, we are particularly interested in the potential applications of quantum computers to enhance real software systems of interest to the defense, industrial, scientific and financial communities. However, while much has been written in popular and scientific literature about the benefits of the quantum computational model, several of the problems associated to the practical implementation of real-life complex software systems in quantum computers are often ignored. In this presentation we will argue that practical quantum computation is not as straightforward as commonly advertised, even if the technological problems associated to the manufacturing and engineering of large-scale quantum registers were solved overnight. We will discuss some of the frequently overlooked difficulties that plague quantum computing in the areas of memories, I/O, addressing schemes, compilers, oracles, approximate information copying, logical debugging, error correction and fault-tolerant computing protocols.

Image Processor Electronics (IPE): The High-Performance Computing System for NASA SWIFT Mission

NASA Technical Reports Server (NTRS)

Nguyen, Quang H.; Settles, Beverly A.

2003-01-01

Gamma Ray Bursts (GRBs) are believed to be the most powerful explosions that have occurred in the Universe since the Big Bang and are a mystery to the scientific community. Swift, a NASA mission that includes international participation, was designed and built in preparation for a 2003 launch to help to determine the origin of Gamma Ray Bursts. Locating the position in the sky where a burst originates requires intensive computing, because the duration of a GRB can range between a few milliseconds up to approximately a minute. The instrument data system must constantly accept multiple images representing large regions of the sky that are generated by sixteen gamma ray detectors operating in parallel. It then must process the received images very quickly in order to determine the existence of possible gamma ray bursts and their locations. The high-performance instrument data computing system that accomplishes this is called the Image Processor Electronics (IPE). The IPE was designed, built and tested by NASA Goddard Space Flight Center (GSFC) in order to meet these challenging requirements. The IPE is a small size, low power and high performing computing system for space applications. This paper addresses the system implementation and the system hardware architecture of the IPE. The paper concludes with the IPE system performance that was measured during end-to-end system testing.

Research on private cloud computing based on analysis on typical opensource platform: a case study with Eucalyptus and Wavemaker

NASA Astrophysics Data System (ADS)

Yu, Xiaoyuan; Yuan, Jian; Chen, Shi

2013-03-01

Cloud computing is one of the most popular topics in the IT industry and is recently being adopted by many companies. It has four development models, as: public cloud, community cloud, hybrid cloud and private cloud. Except others, private cloud can be implemented in a private network, and delivers some benefits of cloud computing without pitfalls. This paper makes a comparison of typical open source platforms through which we can implement a private cloud. After this comparison, we choose Eucalyptus and Wavemaker to do a case study on the private cloud. We also do some performance estimation of cloud platform services and development of prototype software as cloud services.

Top-down network analysis characterizes hidden termite-termite interactions.

PubMed

Campbell, Colin; Russo, Laura; Marins, Alessandra; DeSouza, Og; Schönrogge, Karsten; Mortensen, David; Tooker, John; Albert, Réka; Shea, Katriona

2016-09-01

The analysis of ecological networks is generally bottom-up, where networks are established by observing interactions between individuals. Emergent network properties have been indicated to reflect the dominant mode of interactions in communities that might be mutualistic (e.g., pollination) or antagonistic (e.g., host-parasitoid communities). Many ecological communities, however, comprise species interactions that are difficult to observe directly. Here, we propose that a comparison of the emergent properties from detail-rich reference communities with known modes of interaction can inform our understanding of detail-sparse focal communities. With this top-down approach, we consider patterns of coexistence between termite species that live as guests in mounds built by other host termite species as a case in point. Termite societies are extremely sensitive to perturbations, which precludes determining the nature of their interactions through direct observations. We perform a literature review to construct two networks representing termite mound cohabitation in a Brazilian savanna and in the tropical forest of Cameroon. We contrast the properties of these cohabitation networks with a total of 197 geographically diverse mutualistic plant-pollinator and antagonistic host-parasitoid networks. We analyze network properties for the networks, perform a principal components analysis (PCA), and compute the Mahalanobis distance of the termite networks to the cloud of mutualistic and antagonistic networks to assess the extent to which the termite networks overlap with the properties of the reference networks. Both termite networks overlap more closely with the mutualistic plant-pollinator communities than the antagonistic host-parasitoid communities, although the Brazilian community overlap with mutualistic communities is stronger. The analysis raises the hypothesis that termite-termite cohabitation networks may be overall mutualistic. More broadly, this work provides support for the argument that cryptic communities may be analyzed via comparison to well-characterized communities.

Use of Computer Kiosks for Breast Cancer Education in Five Community Settings

ERIC Educational Resources Information Center

Kreuter, Matthew W.; Black, Wynona J.; Friend, LaBraunna; Booker, Angela C.; Klump, Paula; Bobra, Sonal; Holt, Cheryl L.

2006-01-01

Finding ways to bring effective computer-based behavioral interventions to those with limited access to technology is a continuing challenge for health educators. Computer kiosks placed in community settings may help reach such populations. The "Reflections of You" kiosk generates individually tailored magazines on breast cancer and…

Community Information Centers and the Computer.

ERIC Educational Resources Information Center

Carroll, John M.; Tague, Jean M.

Two computer data bases have been developed by the Computer Science Department at the University of Western Ontario for "Information London," the local community information center. One system, called LONDON, permits Boolean searches of a file of 5,000 records describing human service agencies in the London area. The second system,…

Parallel community climate model: Description and user`s guide

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

Drake, J.B.; Flanery, R.E.; Semeraro, B.D.

This report gives an overview of a parallel version of the NCAR Community Climate Model, CCM2, implemented for MIMD massively parallel computers using a message-passing programming paradigm. The parallel implementation was developed on an Intel iPSC/860 with 128 processors and on the Intel Delta with 512 processors, and the initial target platform for the production version of the code is the Intel Paragon with 2048 processors. Because the implementation uses a standard, portable message-passing libraries, the code has been easily ported to other multiprocessors supporting a message-passing programming paradigm. The parallelization strategy used is to decompose the problem domain intomore » geographical patches and assign each processor the computation associated with a distinct subset of the patches. With this decomposition, the physics calculations involve only grid points and data local to a processor and are performed in parallel. Using parallel algorithms developed for the semi-Lagrangian transport, the fast Fourier transform and the Legendre transform, both physics and dynamics are computed in parallel with minimal data movement and modest change to the original CCM2 source code. Sequential or parallel history tapes are written and input files (in history tape format) are read sequentially by the parallel code to promote compatibility with production use of the model on other computer systems. A validation exercise has been performed with the parallel code and is detailed along with some performance numbers on the Intel Paragon and the IBM SP2. A discussion of reproducibility of results is included. A user`s guide for the PCCM2 version 2.1 on the various parallel machines completes the report. Procedures for compilation, setup and execution are given. A discussion of code internals is included for those who may wish to modify and use the program in their own research.« less

PREPARING FOR EXASCALE: ORNL Leadership Computing Application Requirements and Strategy

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

Joubert, Wayne; Kothe, Douglas B; Nam, Hai Ah

2009-12-01

In 2009 the Oak Ridge Leadership Computing Facility (OLCF), a U.S. Department of Energy (DOE) facility at the Oak Ridge National Laboratory (ORNL) National Center for Computational Sciences (NCCS), elicited petascale computational science requirements from leading computational scientists in the international science community. This effort targeted science teams whose projects received large computer allocation awards on OLCF systems. A clear finding of this process was that in order to reach their science goals over the next several years, multiple projects will require computational resources in excess of an order of magnitude more powerful than those currently available. Additionally, for themore » longer term, next-generation science will require computing platforms of exascale capability in order to reach DOE science objectives over the next decade. It is generally recognized that achieving exascale in the proposed time frame will require disruptive changes in computer hardware and software. Processor hardware will become necessarily heterogeneous and will include accelerator technologies. Software must undergo the concomitant changes needed to extract the available performance from this heterogeneous hardware. This disruption portends to be substantial, not unlike the change to the message passing paradigm in the computational science community over 20 years ago. Since technological disruptions take time to assimilate, we must aggressively embark on this course of change now, to insure that science applications and their underlying programming models are mature and ready when exascale computing arrives. This includes initiation of application readiness efforts to adapt existing codes to heterogeneous architectures, support of relevant software tools, and procurement of next-generation hardware testbeds for porting and testing codes. The 2009 OLCF requirements process identified numerous actions necessary to meet this challenge: (1) Hardware capabilities must be advanced on multiple fronts, including peak flops, node memory capacity, interconnect latency, interconnect bandwidth, and memory bandwidth. (2) Effective parallel programming interfaces must be developed to exploit the power of emerging hardware. (3) Science application teams must now begin to adapt and reformulate application codes to the new hardware and software, typified by hierarchical and disparate layers of compute, memory and concurrency. (4) Algorithm research must be realigned to exploit this hierarchy. (5) When possible, mathematical libraries must be used to encapsulate the required operations in an efficient and useful way. (6) Software tools must be developed to make the new hardware more usable. (7) Science application software must be improved to cope with the increasing complexity of computing systems. (8) Data management efforts must be readied for the larger quantities of data generated by larger, more accurate science models. Requirements elicitation, analysis, validation, and management comprise a difficult and inexact process, particularly in periods of technological change. Nonetheless, the OLCF requirements modeling process is becoming increasingly quantitative and actionable, as the process becomes more developed and mature, and the process this year has identified clear and concrete steps to be taken. This report discloses (1) the fundamental science case driving the need for the next generation of computer hardware, (2) application usage trends that illustrate the science need, (3) application performance characteristics that drive the need for increased hardware capabilities, (4) resource and process requirements that make the development and deployment of science applications on next-generation hardware successful, and (5) summary recommendations for the required next steps within the computer and computational science communities.« less

Performance/price estimates for cortex-scale hardware: a design space exploration.

PubMed

Zaveri, Mazad S; Hammerstrom, Dan

2011-04-01

In this paper, we revisit the concept of virtualization. Virtualization is useful for understanding and investigating the performance/price and other trade-offs related to the hardware design space. Moreover, it is perhaps the most important aspect of a hardware design space exploration. Such a design space exploration is a necessary part of the study of hardware architectures for large-scale computational models for intelligent computing, including AI, Bayesian, bio-inspired and neural models. A methodical exploration is needed to identify potentially interesting regions in the design space, and to assess the relative performance/price points of these implementations. As an example, in this paper we investigate the performance/price of (digital and mixed-signal) CMOS and hypothetical CMOL (nanogrid) technology based hardware implementations of human cortex-scale spiking neural systems. Through this analysis, and the resulting performance/price points, we demonstrate, in general, the importance of virtualization, and of doing these kinds of design space explorations. The specific results suggest that hybrid nanotechnology such as CMOL is a promising candidate to implement very large-scale spiking neural systems, providing a more efficient utilization of the density and storage benefits of emerging nano-scale technologies. In general, we believe that the study of such hypothetical designs/architectures will guide the neuromorphic hardware community towards building large-scale systems, and help guide research trends in intelligent computing, and computer engineering. Copyright © 2010 Elsevier Ltd. All rights reserved.

MetaSort untangles metagenome assembly by reducing microbial community complexity

PubMed Central

Ji, Peifeng; Zhang, Yanming; Wang, Jinfeng; Zhao, Fangqing

2017-01-01

Most current approaches to analyse metagenomic data rely on reference genomes. Novel microbial communities extend far beyond the coverage of reference databases and de novo metagenome assembly from complex microbial communities remains a great challenge. Here we present a novel experimental and bioinformatic framework, metaSort, for effective construction of bacterial genomes from metagenomic samples. MetaSort provides a sorted mini-metagenome approach based on flow cytometry and single-cell sequencing methodologies, and employs new computational algorithms to efficiently recover high-quality genomes from the sorted mini-metagenome by the complementary of the original metagenome. Through extensive evaluations, we demonstrated that metaSort has an excellent and unbiased performance on genome recovery and assembly. Furthermore, we applied metaSort to an unexplored microflora colonized on the surface of marine kelp and successfully recovered 75 high-quality genomes at one time. This approach will greatly improve access to microbial genomes from complex or novel communities. PMID:28112173

Beating the tyranny of scale with a private cloud configured for Big Data

NASA Astrophysics Data System (ADS)

Lawrence, Bryan; Bennett, Victoria; Churchill, Jonathan; Juckes, Martin; Kershaw, Philip; Pepler, Sam; Pritchard, Matt; Stephens, Ag

2015-04-01

The Joint Analysis System, JASMIN, consists of a five significant hardware components: a batch computing cluster, a hypervisor cluster, bulk disk storage, high performance disk storage, and access to a tape robot. Each of the computing clusters consists of a heterogeneous set of servers, supporting a range of possible data analysis tasks - and a unique network environment makes it relatively trivial to migrate servers between the two clusters. The high performance disk storage will include the world's largest (publicly visible) deployment of the Panasas parallel disk system. Initially deployed in April 2012, JASMIN has already undergone two major upgrades, culminating in a system which by April 2015, will have in excess of 16 PB of disk and 4000 cores. Layered on the basic hardware are a range of services, ranging from managed services, such as the curated archives of the Centre for Environmental Data Archival or the data analysis environment for the National Centres for Atmospheric Science and Earth Observation, to a generic Infrastructure as a Service (IaaS) offering for the UK environmental science community. Here we present examples of some of the big data workloads being supported in this environment - ranging from data management tasks, such as checksumming 3 PB of data held in over one hundred million files, to science tasks, such as re-processing satellite observations with new algorithms, or calculating new diagnostics on petascale climate simulation outputs. We will demonstrate how the provision of a cloud environment closely coupled to a batch computing environment, all sharing the same high performance disk system allows massively parallel processing without the necessity to shuffle data excessively - even as it supports many different virtual communities, each with guaranteed performance. We will discuss the advantages of having a heterogeneous range of servers with available memory from tens of GB at the low end to (currently) two TB at the high end. There are some limitations of the JASMIN environment, the high performance disk environment is not fully available in the IaaS environment, and a planned ability to burst compute heavy jobs into the public cloud is not yet fully available. There are load balancing and performance issues that need to be understood. We will conclude with projections for future usage, and our plans to meet those requirements.

Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing.

PubMed

Shatil, Anwar S; Younas, Sohail; Pourreza, Hossein; Figley, Chase R

2015-01-01

With larger data sets and more sophisticated analyses, it is becoming increasingly common for neuroimaging researchers to push (or exceed) the limitations of standalone computer workstations. Nonetheless, although high-performance computing platforms such as clusters, grids and clouds are already in routine use by a small handful of neuroimaging researchers to increase their storage and/or computational power, the adoption of such resources by the broader neuroimaging community remains relatively uncommon. Therefore, the goal of the current manuscript is to: 1) inform prospective users about the similarities and differences between computing clusters, grids and clouds; 2) highlight their main advantages; 3) discuss when it may (and may not) be advisable to use them; 4) review some of their potential problems and barriers to access; and finally 5) give a few practical suggestions for how interested new users can start analyzing their neuroimaging data using cloud resources. Although the aim of cloud computing is to hide most of the complexity of the infrastructure management from end-users, we recognize that this can still be an intimidating area for cognitive neuroscientists, psychologists, neurologists, radiologists, and other neuroimaging researchers lacking a strong computational background. Therefore, with this in mind, we have aimed to provide a basic introduction to cloud computing in general (including some of the basic terminology, computer architectures, infrastructure and service models, etc.), a practical overview of the benefits and drawbacks, and a specific focus on how cloud resources can be used for various neuroimaging applications.

Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing

PubMed Central

Shatil, Anwar S.; Younas, Sohail; Pourreza, Hossein; Figley, Chase R.

2015-01-01

With larger data sets and more sophisticated analyses, it is becoming increasingly common for neuroimaging researchers to push (or exceed) the limitations of standalone computer workstations. Nonetheless, although high-performance computing platforms such as clusters, grids and clouds are already in routine use by a small handful of neuroimaging researchers to increase their storage and/or computational power, the adoption of such resources by the broader neuroimaging community remains relatively uncommon. Therefore, the goal of the current manuscript is to: 1) inform prospective users about the similarities and differences between computing clusters, grids and clouds; 2) highlight their main advantages; 3) discuss when it may (and may not) be advisable to use them; 4) review some of their potential problems and barriers to access; and finally 5) give a few practical suggestions for how interested new users can start analyzing their neuroimaging data using cloud resources. Although the aim of cloud computing is to hide most of the complexity of the infrastructure management from end-users, we recognize that this can still be an intimidating area for cognitive neuroscientists, psychologists, neurologists, radiologists, and other neuroimaging researchers lacking a strong computational background. Therefore, with this in mind, we have aimed to provide a basic introduction to cloud computing in general (including some of the basic terminology, computer architectures, infrastructure and service models, etc.), a practical overview of the benefits and drawbacks, and a specific focus on how cloud resources can be used for various neuroimaging applications. PMID:27279746

A computational workflow for designing silicon donor qubits

DOE PAGES

Humble, Travis S.; Ericson, M. Nance; Jakowski, Jacek; ...

2016-09-19

Developing devices that can reliably and accurately demonstrate the principles of superposition and entanglement is an on-going challenge for the quantum computing community. Modeling and simulation offer attractive means of testing early device designs and establishing expectations for operational performance. However, the complex integrated material systems required by quantum device designs are not captured by any single existing computational modeling method. We examine the development and analysis of a multi-staged computational workflow that can be used to design and characterize silicon donor qubit systems with modeling and simulation. Our approach integrates quantum chemistry calculations with electrostatic field solvers to performmore » detailed simulations of a phosphorus dopant in silicon. We show how atomistic details can be synthesized into an operational model for the logical gates that define quantum computation in this particular technology. In conclusion, the resulting computational workflow realizes a design tool for silicon donor qubits that can help verify and validate current and near-term experimental devices.« less

Association of unipedal standing time and bone mineral density in community-dwelling Japanese women.

PubMed

Sakai, A; Toba, N; Takeda, M; Suzuki, M; Abe, Y; Aoyagi, K; Nakamura, T

2009-05-01

Bone mineral density (BMD) and physical performance of the lower extremities decrease with age. In community-dwelling Japanese women, unipedal standing time, timed up and go test, and age are associated with BMD while in women aged 70 years and over, unipedal standing time is associated with BMD. The aim of this study was to clarify whether unipedal standing time is significantly associated with BMD in community-dwelling women. The subjects were 90 community-dwelling Japanese women aged 54.7 years. BMD of the second metacarpal bone was measured by computed X-ray densitometry. We measured unipedal standing time as well as timed up and go test to assess physical performance of the lower extremities. Unipedal standing time decreased with increased age. Timed up and go test significantly correlated with age. Low BMD was significantly associated with old age, short unipedal standing time, and long timed up and go test. Stepwise regression analysis revealed that age, unipedal standing time, and timed up and go test were significant factors associated with BMD. In 21 participants aged 70 years and over, body weight and unipedal standing time, but not age, were significantly associated with BMD. BMD and physical performance of the lower extremities decrease with older age. Unipedal standing time, timed up and go test, and age are associated with BMD in community-dwelling Japanese women. In women aged 70 years and over, unipedal standing time is significantly associated with BMD.

Planning for distributed workflows: constraint-based coscheduling of computational jobs and data placement in distributed environments

NASA Astrophysics Data System (ADS)

Makatun, Dzmitry; Lauret, Jérôme; Rudová, Hana; Šumbera, Michal

2015-05-01

When running data intensive applications on distributed computational resources long I/O overheads may be observed as access to remotely stored data is performed. Latencies and bandwidth can become the major limiting factor for the overall computation performance and can reduce the CPU/WallTime ratio to excessive IO wait. Reusing the knowledge of our previous research, we propose a constraint programming based planner that schedules computational jobs and data placements (transfers) in a distributed environment in order to optimize resource utilization and reduce the overall processing completion time. The optimization is achieved by ensuring that none of the resources (network links, data storages and CPUs) are oversaturated at any moment of time and either (a) that the data is pre-placed at the site where the job runs or (b) that the jobs are scheduled where the data is already present. Such an approach eliminates the idle CPU cycles occurring when the job is waiting for the I/O from a remote site and would have wide application in the community. Our planner was evaluated and simulated based on data extracted from log files of batch and data management systems of the STAR experiment. The results of evaluation and estimation of performance improvements are discussed in this paper.

EUROPLANET-RI modelling service for the planetary science community: European Modelling and Data Analysis Facility (EMDAF)

NASA Astrophysics Data System (ADS)

Khodachenko, Maxim; Miller, Steven; Stoeckler, Robert; Topf, Florian

2010-05-01

Computational modeling and observational data analysis are two major aspects of the modern scientific research. Both appear nowadays under extensive development and application. Many of the scientific goals of planetary space missions require robust models of planetary objects and environments as well as efficient data analysis algorithms, to predict conditions for mission planning and to interpret the experimental data. Europe has great strength in these areas, but it is insufficiently coordinated; individual groups, models, techniques and algorithms need to be coupled and integrated. Existing level of scientific cooperation and the technical capabilities for operative communication, allow considerable progress in the development of a distributed international Research Infrastructure (RI) which is based on the existing in Europe computational modelling and data analysis centers, providing the scientific community with dedicated services in the fields of their computational and data analysis expertise. These services will appear as a product of the collaborative communication and joint research efforts of the numerical and data analysis experts together with planetary scientists. The major goal of the EUROPLANET-RI / EMDAF is to make computational models and data analysis algorithms associated with particular national RIs and teams, as well as their outputs, more readily available to their potential user community and more tailored to scientific user requirements, without compromising front-line specialized research on model and data analysis algorithms development and software implementation. This objective will be met through four keys subdivisions/tasks of EMAF: 1) an Interactive Catalogue of Planetary Models; 2) a Distributed Planetary Modelling Laboratory; 3) a Distributed Data Analysis Laboratory, and 4) enabling Models and Routines for High Performance Computing Grids. Using the advantages of the coordinated operation and efficient communication between the involved computational modelling, research and data analysis expert teams and their related research infrastructures, EMDAF will provide a 1) flexible, 2) scientific user oriented, 3) continuously developing and fast upgrading computational and data analysis service to support and intensify the European planetary scientific research. At the beginning EMDAF will create a set of demonstrators and operational tests of this service in key areas of European planetary science. This work will aim at the following objectives: (a) Development and implementation of tools for distant interactive communication between the planetary scientists and computing experts (including related RIs); (b) Development of standard routine packages, and user-friendly interfaces for operation of the existing numerical codes and data analysis algorithms by the specialized planetary scientists; (c) Development of a prototype of numerical modelling services "on demand" for space missions and planetary researchers; (d) Development of a prototype of data analysis services "on demand" for space missions and planetary researchers; (e) Development of a prototype of coordinated interconnected simulations of planetary phenomena and objects (global multi-model simulators); (f) Providing the demonstrators of a coordinated use of high performance computing facilities (super-computer networks), done in cooperation with European HPC Grid DEISA.

A uniform approach for programming distributed heterogeneous computing systems

PubMed Central

Grasso, Ivan; Pellegrini, Simone; Cosenza, Biagio; Fahringer, Thomas

2014-01-01

Large-scale compute clusters of heterogeneous nodes equipped with multi-core CPUs and GPUs are getting increasingly popular in the scientific community. However, such systems require a combination of different programming paradigms making application development very challenging. In this article we introduce libWater, a library-based extension of the OpenCL programming model that simplifies the development of heterogeneous distributed applications. libWater consists of a simple interface, which is a transparent abstraction of the underlying distributed architecture, offering advanced features such as inter-context and inter-node device synchronization. It provides a runtime system which tracks dependency information enforced by event synchronization to dynamically build a DAG of commands, on which we automatically apply two optimizations: collective communication pattern detection and device-host-device copy removal. We assess libWater’s performance in three compute clusters available from the Vienna Scientific Cluster, the Barcelona Supercomputing Center and the University of Innsbruck, demonstrating improved performance and scaling with different test applications and configurations. PMID:25844015

A Secure Web Application Providing Public Access to High-Performance Data Intensive Scientific Resources - ScalaBLAST Web Application

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

Curtis, Darren S.; Peterson, Elena S.; Oehmen, Chris S.

2008-05-04

This work presents the ScalaBLAST Web Application (SWA), a web based application implemented using the PHP script language, MySQL DBMS, and Apache web server under a GNU/Linux platform. SWA is an application built as part of the Data Intensive Computer for Complex Biological Systems (DICCBS) project at the Pacific Northwest National Laboratory (PNNL). SWA delivers accelerated throughput of bioinformatics analysis via high-performance computing through a convenient, easy-to-use web interface. This approach greatly enhances emerging fields of study in biology such as ontology-based homology, and multiple whole genome comparisons which, in the absence of a tool like SWA, require a heroicmore » effort to overcome the computational bottleneck associated with genome analysis. The current version of SWA includes a user account management system, a web based user interface, and a backend process that generates the files necessary for the Internet scientific community to submit a ScalaBLAST parallel processing job on a dedicated cluster.« less

A uniform approach for programming distributed heterogeneous computing systems.

PubMed

Grasso, Ivan; Pellegrini, Simone; Cosenza, Biagio; Fahringer, Thomas

2014-12-01

Large-scale compute clusters of heterogeneous nodes equipped with multi-core CPUs and GPUs are getting increasingly popular in the scientific community. However, such systems require a combination of different programming paradigms making application development very challenging. In this article we introduce libWater, a library-based extension of the OpenCL programming model that simplifies the development of heterogeneous distributed applications. libWater consists of a simple interface, which is a transparent abstraction of the underlying distributed architecture, offering advanced features such as inter-context and inter-node device synchronization. It provides a runtime system which tracks dependency information enforced by event synchronization to dynamically build a DAG of commands, on which we automatically apply two optimizations: collective communication pattern detection and device-host-device copy removal. We assess libWater's performance in three compute clusters available from the Vienna Scientific Cluster, the Barcelona Supercomputing Center and the University of Innsbruck, demonstrating improved performance and scaling with different test applications and configurations.

PaleoMac: A Macintosh™ application for treating paleomagnetic data and making plate reconstructions

NASA Astrophysics Data System (ADS)

Cogné, J. P.

2003-01-01

This brief note provides an overview of a new Macintosh™ application, PaleoMac, (MacOS 8.0 or later, 15Mb RAM required) which permits rapid processing of paleomagnetic data, from the demagnetization data acquired in the laboratory, to the treatment of paleomagnetic poles, plate reconstructions, finite rotation computations on a sphere, and characterization of relative plate motions. Capabilities of PaleoMac include (1) high interactivity between the user and data displayed on screen which provides a fast and easy way to handle, add and remove data or contours, perform computations on subsets of points, change projections, sizes, etc.; (2) performance of all standard principal component analysis and statistical processing on a sphere [, 1953] etc.); (3) output of high quality plots, compatible with graphic programs such as Adobe Illustrator, and output of numerical results as ASCII files. Beyond its usefulness in treating paleomagnetic data, its ability to handle plate motion computations should be of large interest to the Earth science community.

Soldiers in the Blogosphere Using New Media to Help Win the War for Public Opinion

DTIC Science & Technology

2009-04-01

relaxed its policy on blogging, but still bans the use of community networking sites such as MySpace on government computers . The Army has practically...of community networking sites such as MySpace on government computers . The Army has practically ignored these new media sources to get its story...its policy on blogging, but still bans the use of community networking sites such as MySpace on government computers . The Army has practically

OpenTopography: Addressing Big Data Challenges Using Cloud Computing, HPC, and Data Analytics

NASA Astrophysics Data System (ADS)

Crosby, C. J.; Nandigam, V.; Phan, M.; Youn, C.; Baru, C.; Arrowsmith, R.

2014-12-01

OpenTopography (OT) is a geoinformatics-based data facility initiated in 2009 for democratizing access to high-resolution topographic data, derived products, and tools. Hosted at the San Diego Supercomputer Center (SDSC), OT utilizes cyberinfrastructure, including large-scale data management, high-performance computing, and service-oriented architectures to provide efficient Web based access to large, high-resolution topographic datasets. OT collocates data with processing tools to enable users to quickly access custom data and derived products for their application. OT's ongoing R&D efforts aim to solve emerging technical challenges associated with exponential growth in data, higher order data products, as well as user base. Optimization of data management strategies can be informed by a comprehensive set of OT user access metrics that allows us to better understand usage patterns with respect to the data. By analyzing the spatiotemporal access patterns within the datasets, we can map areas of the data archive that are highly active (hot) versus the ones that are rarely accessed (cold). This enables us to architect a tiered storage environment consisting of high performance disk storage (SSD) for the hot areas and less expensive slower disk for the cold ones, thereby optimizing price to performance. From a compute perspective, OT is looking at cloud based solutions such as the Microsoft Azure platform to handle sudden increases in load. An OT virtual machine image in Microsoft's VM Depot can be invoked and deployed quickly in response to increased system demand. OT has also integrated SDSC HPC systems like the Gordon supercomputer into our infrastructure tier to enable compute intensive workloads like parallel computation of hydrologic routing on high resolution topography. This capability also allows OT to scale to HPC resources during high loads to meet user demand and provide more efficient processing. With a growing user base and maturing scientific user community comes new requests for algorithms and processing capabilities. To address this demand, OT is developing an extensible service based architecture for integrating community-developed software. This "plugable" approach to Web service deployment will enable new processing and analysis tools to run collocated with OT hosted data.

Exploring the Strategies for a Community College Transition into a Cloud-Computing Environment

ERIC Educational Resources Information Center

DeBary, Narges

2017-01-01

The use of the Internet has resulted in the birth of an innovative virtualization technology called cloud computing. Virtualization can tremendously improve the instructional and operational systems of a community college. Although the incidental adoption of the cloud solutions in the community colleges of higher education has been increased,…

Education and Library Services for Community Information Utilities.

ERIC Educational Resources Information Center

Farquhar, John A.

The concept of "computer utility"--the provision of computing and information service by a utility in the form of a national network to which any person desiring information could gain access--has been gaining interest among the public and among the technical community. This report on planning community information utilities discusses the…

Benchmark problems for numerical implementations of phase field models

DOE PAGES

Jokisaari, A. M.; Voorhees, P. W.; Guyer, J. E.; ...

2016-10-01

Here, we present the first set of benchmark problems for phase field models that are being developed by the Center for Hierarchical Materials Design (CHiMaD) and the National Institute of Standards and Technology (NIST). While many scientific research areas use a limited set of well-established software, the growing phase field community continues to develop a wide variety of codes and lacks benchmark problems to consistently evaluate the numerical performance of new implementations. Phase field modeling has become significantly more popular as computational power has increased and is now becoming mainstream, driving the need for benchmark problems to validate and verifymore » new implementations. We follow the example set by the micromagnetics community to develop an evolving set of benchmark problems that test the usability, computational resources, numerical capabilities and physical scope of phase field simulation codes. In this paper, we propose two benchmark problems that cover the physics of solute diffusion and growth and coarsening of a second phase via a simple spinodal decomposition model and a more complex Ostwald ripening model. We demonstrate the utility of benchmark problems by comparing the results of simulations performed with two different adaptive time stepping techniques, and we discuss the needs of future benchmark problems. The development of benchmark problems will enable the results of quantitative phase field models to be confidently incorporated into integrated computational materials science and engineering (ICME), an important goal of the Materials Genome Initiative.« less

Particle Identification on an FPGA Accelerated Compute Platform for the LHCb Upgrade

NASA Astrophysics Data System (ADS)

Fäerber, Christian; Schwemmer, Rainer; Machen, Jonathan; Neufeld, Niko

2017-07-01

The current LHCb readout system will be upgraded in 2018 to a “triggerless” readout of the entire detector at the Large Hadron Collider collision rate of 40 MHz. The corresponding bandwidth from the detector down to the foreseen dedicated computing farm (event filter farm), which acts as the trigger, has to be increased by a factor of almost 100 from currently 500 Gb/s up to 40 Tb/s. The event filter farm will preanalyze the data and will select the events on an event by event basis. This will reduce the bandwidth down to a manageable size to write the interesting physics data to tape. The design of such a system is a challenging task, and the reason why different new technologies are considered and have to be investigated for the different parts of the system. For the usage in the event building farm or in the event filter farm (trigger), an experimental field programmable gate array (FPGA) accelerated computing platform is considered and, therefore, tested. FPGA compute accelerators are used more and more in standard servers such as for Microsoft Bing search or Baidu search. The platform we use hosts a general Intel CPU and a high-performance FPGA linked via the high-speed Intel QuickPath Interconnect. An accelerator is implemented on the FPGA. It is very likely that these platforms, which are built, in general, for high-performance computing, are also very interesting for the high-energy physics community. First, the performance results of smaller test cases performed at the beginning are presented. Afterward, a part of the existing LHCb RICH particle identification is tested and is ported to the experimental FPGA accelerated platform. We have compared the performance of the LHCb RICH particle identification running on a normal CPU with the performance of the same algorithm, which is running on the Xeon-FPGA compute accelerator platform.

The Effects of Social Environments on Time Spent Gaming: Focusing on the Effects of Communities and Neighborhoods.

PubMed

Lim, Tee Teng; Jung, Sun Young; Kim, Eunyi

2018-04-01

This study examined the impact of community and neighborhood on time spent computer gaming. Computer gaming for over 20 hours a week was set as the cutoff line for "engaged use" of computer games. For the analysis, this study analyzed data for about 1,800 subjects who participated in the Korean Children and Youth Panel Survey. The main findings are as follows: first, structural community characteristics and neighborhood social capital affected the engaged use of computer games. Second, adolescents who reside in regions with a higher divorce rate or higher residential mobility were likely to exhibit engaged use of computer games. Third, adolescents who highly perceive neighborhood social capital exhibited lower possibility of engaged use of computer games. Based on these findings, practical implications and directions for further study are suggested.

Students' Attitudes toward Computers at the College of Nursing at King Saud University (KSU)

ERIC Educational Resources Information Center

Samarkandi, Osama Abdulhaleem

2011-01-01

Computer knowledge and skills are becoming essential components technology in nursing education. Saudi nurses must be prepared to utilize these technologies for the advancement of science and nursing practice in local and global communities. Little attention has been directed to students' attitudes about computer usage in academic communities in…

Designing a Curriculum for Computer Students in the Community College.

ERIC Educational Resources Information Center

Kolatis, Maria

An overview is provided of the institutional and technological factors to be considered in designing or updating a computer science curriculum at the community college level. After underscoring the importance of the computer in today's society, the paper identifies and discusses the following considerations in curriculum design: (1) the mission of…

Providing Elementary Students Equitable Access to Notebook Computers by Empowering Three School Communities in Shared Decision Making.

ERIC Educational Resources Information Center

Despot, Paula C.

This practicum was designed to provide elementary students from low-socioeconomic school communities equitable opportunities to use notebook computer technology in the communication process. A multi-dimensional staff development program was designed and conducted to integrate computer technology in the classroom. Students and their families were…

Cloud Computing Applications in Support of Earth Science Activities at Marshall Space Flight Center

NASA Astrophysics Data System (ADS)

Molthan, A.; Limaye, A. S.

2011-12-01

Currently, the NASA Nebula Cloud Computing Platform is available to Agency personnel in a pre-release status as the system undergoes a formal operational readiness review. Over the past year, two projects within the Earth Science Office at NASA Marshall Space Flight Center have been investigating the performance and value of Nebula's "Infrastructure as a Service", or "IaaS" concept and applying cloud computing concepts to advance their respective mission goals. The Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique NASA satellite observations and weather forecasting capabilities for use within the operational forecasting community through partnerships with NOAA's National Weather Service (NWS). SPoRT has evaluated the performance of the Weather Research and Forecasting (WRF) model on virtual machines deployed within Nebula and used Nebula instances to simulate local forecasts in support of regional forecast studies of interest to select NWS forecast offices. In addition to weather forecasting applications, rapidly deployable Nebula virtual machines have supported the processing of high resolution NASA satellite imagery to support disaster assessment following the historic severe weather and tornado outbreak of April 27, 2011. Other modeling and satellite analysis activities are underway in support of NASA's SERVIR program, which integrates satellite observations, ground-based data and forecast models to monitor environmental change and improve disaster response in Central America, the Caribbean, Africa, and the Himalayas. Leveraging SPoRT's experience, SERVIR is working to establish a real-time weather forecasting model for Central America. Other modeling efforts include hydrologic forecasts for Kenya, driven by NASA satellite observations and reanalysis data sets provided by the broader meteorological community. Forecast modeling efforts are supplemented by short-term forecasts of convective initiation, determined by geostationary satellite observations processed on virtual machines powered by Nebula. This presentation will provide an overview of these activities from a scientific and cloud computing applications perspective, identifying the strengths and weaknesses for deploying each project within an IaaS environment, and ways to collaborate with the Nebula or other cloud-user communities to collaborate on projects as they go forward.

Community Cloud Computing

NASA Astrophysics Data System (ADS)

Marinos, Alexandros; Briscoe, Gerard

Cloud Computing is rising fast, with its data centres growing at an unprecedented rate. However, this has come with concerns over privacy, efficiency at the expense of resilience, and environmental sustainability, because of the dependence on Cloud vendors such as Google, Amazon and Microsoft. Our response is an alternative model for the Cloud conceptualisation, providing a paradigm for Clouds in the community, utilising networked personal computers for liberation from the centralised vendor model. Community Cloud Computing (C3) offers an alternative architecture, created by combing the Cloud with paradigms from Grid Computing, principles from Digital Ecosystems, and sustainability from Green Computing, while remaining true to the original vision of the Internet. It is more technically challenging than Cloud Computing, having to deal with distributed computing issues, including heterogeneous nodes, varying quality of service, and additional security constraints. However, these are not insurmountable challenges, and with the need to retain control over our digital lives and the potential environmental consequences, it is a challenge we must pursue.

Just for Fun: Using Programming Games in Software Programming Training and Education--A Field Study of IBM Robocode Community

ERIC Educational Resources Information Center

Long, Ju

2007-01-01

Improving learning effectiveness has always been a constant challenge in software education and training. One of the primary tasks educators face is to motivate learners to perform to their best abilities. Using computer games is one means to encourage learners to learn (Klawe, 1994). When games are used in general education, they could enhance…

Network community-detection enhancement by proper weighting

NASA Astrophysics Data System (ADS)

Khadivi, Alireza; Ajdari Rad, Ali; Hasler, Martin

2011-04-01

In this paper, we show how proper assignment of weights to the edges of a complex network can enhance the detection of communities and how it can circumvent the resolution limit and the extreme degeneracy problems associated with modularity. Our general weighting scheme takes advantage of graph theoretic measures and it introduces two heuristics for tuning its parameters. We use this weighting as a preprocessing step for the greedy modularity optimization algorithm of Newman to improve its performance. The result of the experiments of our approach on computer-generated and real-world data networks confirm that the proposed approach not only mitigates the problems of modularity but also improves the modularity optimization.

Opportunities for Computational Discovery in Basic Energy Sciences

NASA Astrophysics Data System (ADS)

Pederson, Mark

2011-03-01

An overview of the broad-ranging support of computational physics and computational science within the Department of Energy Office of Science will be provided. Computation as the third branch of physics is supported by all six offices (Advanced Scientific Computing, Basic Energy, Biological and Environmental, Fusion Energy, High-Energy Physics, and Nuclear Physics). Support focuses on hardware, software and applications. Most opportunities within the fields of~condensed-matter physics, chemical-physics and materials sciences are supported by the Officeof Basic Energy Science (BES) or through partnerships between BES and the Office for Advanced Scientific Computing. Activities include radiation sciences, catalysis, combustion, materials in extreme environments, energy-storage materials, light-harvesting and photovoltaics, solid-state lighting and superconductivity.~ A summary of two recent reports by the computational materials and chemical communities on the role of computation during the next decade will be provided. ~In addition to materials and chemistry challenges specific to energy sciences, issues identified~include a focus on the role of the domain scientist in integrating, expanding and sustaining applications-oriented capabilities on evolving high-performance computing platforms and on the role of computation in accelerating the development of innovative technologies. ~~

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.

Scalable Static and Dynamic Community Detection Using Grappolo

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

Halappanavar, Mahantesh; Lu, Hao; Kalyanaraman, Anantharaman

Graph clustering, popularly known as community detection, is a fundamental kernel for several applications of relevance to the Defense Advanced Research Projects Agency’s (DARPA) Hierarchical Identify Verify Exploit (HIVE) Pro- gram. Clusters or communities represent natural divisions within a network that are densely connected within a cluster and sparsely connected to the rest of the network. The need to compute clustering on large scale data necessitates the development of efficient algorithms that can exploit modern architectures that are fundamentally parallel in nature. How- ever, due to their irregular and inherently sequential nature, many of the current algorithms for community detectionmore » are challenging to parallelize. In response to the HIVE Graph Challenge, we present several parallelization heuristics for fast community detection using the Louvain method as the serial template. We implement all the heuristics in a software library called Grappolo. Using the inputs from the HIVE Challenge, we demonstrate superior performance and high quality solutions based on four parallelization heuristics. We use Grappolo on static graphs as the first step towards community detection on streaming graphs.« less

Information dynamics algorithm for detecting communities in networks

NASA Astrophysics Data System (ADS)

Massaro, Emanuele; Bagnoli, Franco; Guazzini, Andrea; Lió, Pietro

2012-11-01

The problem of community detection is relevant in many scientific disciplines, from social science to statistical physics. Given the impact of community detection in many areas, such as psychology and social sciences, we have addressed the issue of modifying existing well performing algorithms by incorporating elements of the domain application fields, i.e. domain-inspired. We have focused on a psychology and social network-inspired approach which may be useful for further strengthening the link between social network studies and mathematics of community detection. Here we introduce a community-detection algorithm derived from the van Dongen's Markov Cluster algorithm (MCL) method [4] by considering networks' nodes as agents capable to take decisions. In this framework we have introduced a memory factor to mimic a typical human behavior such as the oblivion effect. The method is based on information diffusion and it includes a non-linear processing phase. We test our method on two classical community benchmark and on computer generated networks with known community structure. Our approach has three important features: the capacity of detecting overlapping communities, the capability of identifying communities from an individual point of view and the fine tuning the community detectability with respect to prior knowledge of the data. Finally we discuss how to use a Shannon entropy measure for parameter estimation in complex networks.

Bionimbus: a cloud for managing, analyzing and sharing large genomics datasets

PubMed Central

Heath, Allison P; Greenway, Matthew; Powell, Raymond; Spring, Jonathan; Suarez, Rafael; Hanley, David; Bandlamudi, Chai; McNerney, Megan E; White, Kevin P; Grossman, Robert L

2014-01-01

Background As large genomics and phenotypic datasets are becoming more common, it is increasingly difficult for most researchers to access, manage, and analyze them. One possible approach is to provide the research community with several petabyte-scale cloud-based computing platforms containing these data, along with tools and resources to analyze it. Methods Bionimbus is an open source cloud-computing platform that is based primarily upon OpenStack, which manages on-demand virtual machines that provide the required computational resources, and GlusterFS, which is a high-performance clustered file system. Bionimbus also includes Tukey, which is a portal, and associated middleware that provides a single entry point and a single sign on for the various Bionimbus resources; and Yates, which automates the installation, configuration, and maintenance of the software infrastructure required. Results Bionimbus is used by a variety of projects to process genomics and phenotypic data. For example, it is used by an acute myeloid leukemia resequencing project at the University of Chicago. The project requires several computational pipelines, including pipelines for quality control, alignment, variant calling, and annotation. For each sample, the alignment step requires eight CPUs for about 12 h. BAM file sizes ranged from 5 GB to 10 GB for each sample. Conclusions Most members of the research community have difficulty downloading large genomics datasets and obtaining sufficient storage and computer resources to manage and analyze the data. Cloud computing platforms, such as Bionimbus, with data commons that contain large genomics datasets, are one choice for broadening access to research data in genomics. PMID:24464852

Climate Models

NASA Technical Reports Server (NTRS)

Druyan, Leonard M.

2012-01-01

Climate models is a very broad topic, so a single volume can only offer a small sampling of relevant research activities. This volume of 14 chapters includes descriptions of a variety of modeling studies for a variety of geographic regions by an international roster of authors. The climate research community generally uses the rubric climate models to refer to organized sets of computer instructions that produce simulations of climate evolution. The code is based on physical relationships that describe the shared variability of meteorological parameters such as temperature, humidity, precipitation rate, circulation, radiation fluxes, etc. Three-dimensional climate models are integrated over time in order to compute the temporal and spatial variations of these parameters. Model domains can be global or regional and the horizontal and vertical resolutions of the computational grid vary from model to model. Considering the entire climate system requires accounting for interactions between solar insolation, atmospheric, oceanic and continental processes, the latter including land hydrology and vegetation. Model simulations may concentrate on one or more of these components, but the most sophisticated models will estimate the mutual interactions of all of these environments. Advances in computer technology have prompted investments in more complex model configurations that consider more phenomena interactions than were possible with yesterday s computers. However, not every attempt to add to the computational layers is rewarded by better model performance. Extensive research is required to test and document any advantages gained by greater sophistication in model formulation. One purpose for publishing climate model research results is to present purported advances for evaluation by the scientific community.

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.

Crops in silico: A community wide multi-scale computational modeling framework of plant canopies

NASA Astrophysics Data System (ADS)

Srinivasan, V.; Christensen, A.; Borkiewic, K.; Yiwen, X.; Ellis, A.; Panneerselvam, B.; Kannan, K.; Shrivastava, S.; Cox, D.; Hart, J.; Marshall-Colon, A.; Long, S.

2016-12-01

Current crop models predict a looming gap between supply and demand for primary foodstuffs over the next 100 years. While significant yield increases were achieved in major food crops during the early years of the green revolution, the current rates of yield increases are insufficient to meet future projected food demand. Furthermore, with projected reduction in arable land, decrease in water availability, and increasing impacts of climate change on future food production, innovative technologies are required to sustainably improve crop yield. To meet these challenges, we are developing Crops in silico (Cis), a biologically informed, multi-scale, computational modeling framework that can facilitate whole plant simulations of crop systems. The Cis framework is capable of linking models of gene networks, protein synthesis, metabolic pathways, physiology, growth, and development in order to investigate crop response to different climate scenarios and resource constraints. This modeling framework will provide the mechanistic details to generate testable hypotheses toward accelerating directed breeding and engineering efforts to increase future food security. A primary objective for building such a framework is to create synergy among an inter-connected community of biologists and modelers to create a realistic virtual plant. This framework advantageously casts the detailed mechanistic understanding of individual plant processes across various scales in a common scalable framework that makes use of current advances in high performance and parallel computing. We are currently designing a user friendly interface that will make this tool equally accessible to biologists and computer scientists. Critically, this framework will provide the community with much needed tools for guiding future crop breeding and engineering, understanding the emergent implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment.

Architectural Aspects of Grid Computing and its Global Prospects for E-Science Community

NASA Astrophysics Data System (ADS)

Ahmad, Mushtaq

2008-05-01

The paper reviews the imminent Architectural Aspects of Grid Computing for e-Science community for scientific research and business/commercial collaboration beyond physical boundaries. Grid Computing provides all the needed facilities; hardware, software, communication interfaces, high speed internet, safe authentication and secure environment for collaboration of research projects around the globe. It provides highly fast compute engine for those scientific and engineering research projects and business/commercial applications which are heavily compute intensive and/or require humongous amounts of data. It also makes possible the use of very advanced methodologies, simulation models, expert systems and treasure of knowledge available around the globe under the umbrella of knowledge sharing. Thus it makes possible one of the dreams of global village for the benefit of e-Science community across the globe.

GPU-Accelerated Molecular Modeling Coming Of Age

PubMed Central

Stone, John E.; Hardy, David J.; Ufimtsev, Ivan S.

2010-01-01

Graphics processing units (GPUs) have traditionally been used in molecular modeling solely for visualization of molecular structures and animation of trajectories resulting from molecular dynamics simulations. Modern GPUs have evolved into fully programmable, massively parallel co-processors that can now be exploited to accelerate many scientific computations, typically providing about one order of magnitude speedup over CPU code and in special cases providing speedups of two orders of magnitude. This paper surveys the development of molecular modeling algorithms that leverage GPU computing, the advances already made and remaining issues to be resolved, and the continuing evolution of GPU technology that promises to become even more useful to molecular modeling. Hardware acceleration with commodity GPUs is expected to benefit the overall computational biology community by bringing teraflops performance to desktop workstations and in some cases potentially changing what were formerly batch-mode computational jobs into interactive tasks. PMID:20675161

Extended Operating Configuration 2 (EOC-2) Design Document

NASA Technical Reports Server (NTRS)

Barkai, David; Blaylock, Bruce T. (Technical Monitor)

1994-01-01

This document describes the design and plan of the Extended Operating Configuration 2 (EOC-2) for the Numerical Aerodynamic Simulation division (NAS). It covers the changes in the computing environment for the period of '93-'94. During this period the computation capability at NAS will have quadrupled. The first section summarizes this paper: the NAS mission is to provide, by the year 2000, a computing system capable of simulating an entire aerospace vehicle in a few hours. This will require 100 GigaFlops sustained performance. The second section contains information about the NAS user community and the computational model used for projecting future requirements. In the third section, the overall requirements are presented, followed by a summary of the target EOC-2 system. The following sections cover, in more detail, each major component that will have undergone change during EOC-2: the high speed processor, mass storage, workstations, and networks.

A Gateway for Phylogenetic Analysis Powered by Grid Computing Featuring GARLI 2.0

PubMed Central

Bazinet, Adam L.; Zwickl, Derrick J.; Cummings, Michael P.

2014-01-01

We introduce molecularevolution.org, a publicly available gateway for high-throughput, maximum-likelihood phylogenetic analysis powered by grid computing. The gateway features a garli 2.0 web service that enables a user to quickly and easily submit thousands of maximum likelihood tree searches or bootstrap searches that are executed in parallel on distributed computing resources. The garli web service allows one to easily specify partitioned substitution models using a graphical interface, and it performs sophisticated post-processing of phylogenetic results. Although the garli web service has been used by the research community for over three years, here we formally announce the availability of the service, describe its capabilities, highlight new features and recent improvements, and provide details about how the grid system efficiently delivers high-quality phylogenetic results. [garli, gateway, grid computing, maximum likelihood, molecular evolution portal, phylogenetics, web service.] PMID:24789072

A GPU accelerated and error-controlled solver for the unbounded Poisson equation in three dimensions

NASA Astrophysics Data System (ADS)

Exl, Lukas

2017-12-01

An efficient solver for the three dimensional free-space Poisson equation is presented. The underlying numerical method is based on finite Fourier series approximation. While the error of all involved approximations can be fully controlled, the overall computation error is driven by the convergence of the finite Fourier series of the density. For smooth and fast-decaying densities the proposed method will be spectrally accurate. The method scales with O(N log N) operations, where N is the total number of discretization points in the Cartesian grid. The majority of the computational costs come from fast Fourier transforms (FFT), which makes it ideal for GPU computation. Several numerical computations on CPU and GPU validate the method and show efficiency and convergence behavior. Tests are performed using the Vienna Scientific Cluster 3 (VSC3). A free MATLAB implementation for CPU and GPU is provided to the interested community.

GPU-accelerated molecular modeling coming of age.

PubMed

Stone, John E; Hardy, David J; Ufimtsev, Ivan S; Schulten, Klaus

2010-09-01

Graphics processing units (GPUs) have traditionally been used in molecular modeling solely for visualization of molecular structures and animation of trajectories resulting from molecular dynamics simulations. Modern GPUs have evolved into fully programmable, massively parallel co-processors that can now be exploited to accelerate many scientific computations, typically providing about one order of magnitude speedup over CPU code and in special cases providing speedups of two orders of magnitude. This paper surveys the development of molecular modeling algorithms that leverage GPU computing, the advances already made and remaining issues to be resolved, and the continuing evolution of GPU technology that promises to become even more useful to molecular modeling. Hardware acceleration with commodity GPUs is expected to benefit the overall computational biology community by bringing teraflops performance to desktop workstations and in some cases potentially changing what were formerly batch-mode computational jobs into interactive tasks. (c) 2010 Elsevier Inc. All rights reserved.

Distributed Damage Estimation for Prognostics based on Structural Model Decomposition

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Bregon, Anibal; Roychoudhury, Indranil

2011-01-01

Model-based prognostics approaches capture system knowledge in the form of physics-based models of components, and how they fail. These methods consist of a damage estimation phase, in which the health state of a component is estimated, and a prediction phase, in which the health state is projected forward in time to determine end of life. However, the damage estimation problem is often multi-dimensional and computationally intensive. We propose a model decomposition approach adapted from the diagnosis community, called possible conflicts, in order to both improve the computational efficiency of damage estimation, and formulate a damage estimation approach that is inherently distributed. Local state estimates are combined into a global state estimate from which prediction is performed. Using a centrifugal pump as a case study, we perform a number of simulation-based experiments to demonstrate the approach.

Optical Eigenvector.

DTIC Science & Technology

1984-10-01

it necessary and identify by blckci -. mbrr, ’At tile bneginninp, of this contract , bot], -,-j- .lc the rest of the optical community imagined * that...simple analog optical computer,, could produce satisfactory solutions to elgenproblems. Earl’ - in this contract we improved optical computing... contract both we and the rest of the optical community imagined that simple analog optical computers could produce . satisfactory solutions to

The Intersection of Community-Based Writing and Computer-Based Writing: A Cyberliteracy Case Study.

ERIC Educational Resources Information Center

Gabor, Catherine

The learning goals that inform service learning as a whole can contribute to the computers and writing field significantly. This paper demonstrates how two lines of inquiry can be furthered, community-based writing and computers and writing, through new data and critical reflection on learning goals and communication tools. The paper presents a…

Fundamental Aeronautics Program: Overview of Project Work in Supersonic Cruise Efficiency

NASA Technical Reports Server (NTRS)

Castner, Raymond

2011-01-01

The Supersonics Project, part of NASA?s Fundamental Aeronautics Program, contains a number of technical challenge areas which include sonic boom community response, airport noise, high altitude emissions, cruise efficiency, light weight durable engines/airframes, and integrated multi-discipline system design. This presentation provides an overview of the current (2011) activities in the supersonic cruise efficiency technical challenge, and is focused specifically on propulsion technologies. The intent is to develop and validate high-performance supersonic inlet and nozzle technologies. Additional work is planned for design and analysis tools for highly-integrated low-noise, low-boom applications. If successful, the payoffs include improved technologies and tools for optimized propulsion systems, propulsion technologies for a minimized sonic boom signature, and a balanced approach to meeting efficiency and community noise goals. In this propulsion area, the work is divided into advanced supersonic inlet concepts, advanced supersonic nozzle concepts, low fidelity computational tool development, high fidelity computational tools, and improved sensors and measurement capability. The current work in each area is summarized.

Cloud Computing Services for Seismic Networks

NASA Astrophysics Data System (ADS)

Olson, Michael

This thesis describes a compositional framework for developing situation awareness applications: applications that provide ongoing information about a user's changing environment. The thesis describes how the framework is used to develop a situation awareness application for earthquakes. The applications are implemented as Cloud computing services connected to sensors and actuators. The architecture and design of the Cloud services are described and measurements of performance metrics are provided. The thesis includes results of experiments on earthquake monitoring conducted over a year. The applications developed by the framework are (1) the CSN---the Community Seismic Network---which uses relatively low-cost sensors deployed by members of the community, and (2) SAF---the Situation Awareness Framework---which integrates data from multiple sources, including the CSN, CISN---the California Integrated Seismic Network, a network consisting of high-quality seismometers deployed carefully by professionals in the CISN organization and spread across Southern California---and prototypes of multi-sensor platforms that include carbon monoxide, methane, dust and radiation sensors.

Web-based analysis and publication of flow cytometry experiments.

PubMed

Kotecha, Nikesh; Krutzik, Peter O; Irish, Jonathan M

2010-07-01

Cytobank is a Web-based application for storage, analysis, and sharing of flow cytometry experiments. Researchers use a Web browser to log in and use a wide range of tools developed for basic and advanced flow cytometry. In addition to providing access to standard cytometry tools from any computer, Cytobank creates a platform and community for developing new analysis and publication tools. Figure layouts created on Cytobank are designed to allow transparent access to the underlying experiment annotation and data processing steps. Since all flow cytometry files and analysis data are stored on a central server, experiments and figures can be viewed or edited by anyone with the proper permission, from any computer with Internet access. Once a primary researcher has performed the initial analysis of the data, collaborators can engage in experiment analysis and make their own figure layouts using the gated, compensated experiment files. Cytobank is available to the scientific community at http://www.cytobank.org. (c) 2010 by John Wiley & Sons, Inc.

Web-Based Analysis and Publication of Flow Cytometry Experiments

PubMed Central

Kotecha, Nikesh; Krutzik, Peter O.; Irish, Jonathan M.

2014-01-01

Cytobank is a web-based application for storage, analysis, and sharing of flow cytometry experiments. Researchers use a web browser to log in and use a wide range of tools developed for basic and advanced flow cytometry. In addition to providing access to standard cytometry tools from any computer, Cytobank creates a platform and community for developing new analysis and publication tools. Figure layouts created on Cytobank are designed to allow transparent access to the underlying experiment annotation and data processing steps. Since all flow cytometry files and analysis data are stored on a central server, experiments and figures can be viewed or edited by anyone with the proper permissions from any computer with Internet access. Once a primary researcher has performed the initial analysis of the data, collaborators can engage in experiment analysis and make their own figure layouts using the gated, compensated experiment files. Cytobank is available to the scientific community at www.cytobank.org PMID:20578106

Fundamental Aeronautics Program: Overview of Propulsion Work in the Supersonic Cruise Efficiency Technical Challenge

NASA Technical Reports Server (NTRS)

Castner, Ray

2012-01-01

The Supersonics Project, part of NASA's Fundamental Aeronautics Program, contains a number of technical challenge areas which include sonic boom community response, airport noise, high altitude emissions, cruise efficiency, light weight durable engines/airframes, and integrated multi-discipline system design. This presentation provides an overview of the current (2012) activities in the supersonic cruise efficiency technical challenge, and is focused specifically on propulsion technologies. The intent is to develop and validate high-performance supersonic inlet and nozzle technologies. Additional work is planned for design and analysis tools for highly-integrated low-noise, low-boom applications. If successful, the payoffs include improved technologies and tools for optimized propulsion systems, propulsion technologies for a minimized sonic boom signature, and a balanced approach to meeting efficiency and community noise goals. In this propulsion area, the work is divided into advanced supersonic inlet concepts, advanced supersonic nozzle concepts, low fidelity computational tool development, high fidelity computational tools, and improved sensors and measurement capability. The current work in each area is summarized.

The NCI High Performance Computing (HPC) and High Performance Data (HPD) Platform to Support the Analysis of Petascale Environmental Data Collections

NASA Astrophysics Data System (ADS)

Evans, B. J. K.; Pugh, T.; Wyborn, L. A.; Porter, D.; Allen, C.; Smillie, J.; Antony, J.; Trenham, C.; Evans, B. J.; Beckett, D.; Erwin, T.; King, E.; Hodge, J.; Woodcock, R.; Fraser, R.; Lescinsky, D. T.

2014-12-01

The National Computational Infrastructure (NCI) has co-located a priority set of national data assets within a HPC research platform. This powerful in-situ computational platform has been created to help serve and analyse the massive amounts of data across the spectrum of environmental collections - in particular the climate, observational data and geoscientific domains. This paper examines the infrastructure, innovation and opportunity for this significant research platform. NCI currently manages nationally significant data collections (10+ PB) categorised as 1) earth system sciences, climate and weather model data assets and products, 2) earth and marine observations and products, 3) geosciences, 4) terrestrial ecosystem, 5) water management and hydrology, and 6) astronomy, social science and biosciences. The data is largely sourced from the NCI partners (who include the custodians of many of the national scientific records), major research communities, and collaborating overseas organisations. By co-locating these large valuable data assets, new opportunities have arisen by harmonising the data collections, making a powerful transdisciplinary research platformThe data is accessible within an integrated HPC-HPD environment - a 1.2 PFlop supercomputer (Raijin), a HPC class 3000 core OpenStack cloud system and several highly connected large scale and high-bandwidth Lustre filesystems. New scientific software, cloud-scale techniques, server-side visualisation and data services have been harnessed and integrated into the platform, so that analysis is performed seamlessly across the traditional boundaries of the underlying data domains. Characterisation of the techniques along with performance profiling ensures scalability of each software component, all of which can either be enhanced or replaced through future improvements. A Development-to-Operations (DevOps) framework has also been implemented to manage the scale of the software complexity alone. This ensures that software is both upgradable and maintainable, and can be readily reused with complexly integrated systems and become part of the growing global trusted community tools for cross-disciplinary research.

HPC-NMF: A High-Performance Parallel Algorithm for Nonnegative Matrix Factorization

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

Kannan, Ramakrishnan; Sukumar, Sreenivas R.; Ballard, Grey M.

NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of efficient distributed algorithms to solve the problem for big data sets. We propose a high-performance distributed-memory parallel algorithm that computes the factorization by iteratively solving alternating non-negative least squares (NLS) subproblems formore » $$\\WW$$ and $$\\HH$$. It maintains the data and factor matrices in memory (distributed across processors), uses MPI for interprocessor communication, and, in the dense case, provably minimizes communication costs (under mild assumptions). As opposed to previous implementation, our algorithm is also flexible: It performs well for both dense and sparse matrices, and allows the user to choose any one of the multiple algorithms for solving the updates to low rank factors $$\\WW$$ and $$\\HH$$ within the alternating iterations.« less

Tutorial: Asteroseismic Stellar Modelling with AIMS

NASA Astrophysics Data System (ADS)

Lund, Mikkel N.; Reese, Daniel R.

The goal of aims (Asteroseismic Inference on a Massive Scale) is to estimate stellar parameters and credible intervals/error bars in a Bayesian manner from a set of asteroseismic frequency data and so-called classical constraints. To achieve reliable parameter estimates and computational efficiency, it searches through a grid of pre-computed models using an MCMC algorithm—interpolation within the grid of models is performed by first tessellating the grid using a Delaunay triangulation and then doing a linear barycentric interpolation on matching simplexes. Inputs for the modelling consist of individual frequencies from peak-bagging, which can be complemented with classical spectroscopic constraints. aims is mostly written in Python with a modular structure to facilitate contributions from the community. Only a few computationally intensive parts have been rewritten in Fortran in order to speed up calculations.

Acceleration of Cherenkov angle reconstruction with the new Intel Xeon/FPGA compute platform for the particle identification in the LHCb Upgrade

NASA Astrophysics Data System (ADS)

Faerber, Christian

2017-10-01

The LHCb experiment at the LHC will upgrade its detector by 2018/2019 to a ‘triggerless’ readout scheme, where all the readout electronics and several sub-detector parts will be replaced. The new readout electronics will be able to readout the detector at 40 MHz. This increases the data bandwidth from the detector down to the Event Filter farm to 40 TBit/s, which also has to be processed to select the interesting proton-proton collision for later storage. The architecture of such a computing farm, which can process this amount of data as efficiently as possible, is a challenging task and several compute accelerator technologies are being considered for use inside the new Event Filter farm. In the high performance computing sector more and more FPGA compute accelerators are used to improve the compute performance and reduce the power consumption (e.g. in the Microsoft Catapult project and Bing search engine). Also for the LHCb upgrade the usage of an experimental FPGA accelerated computing platform in the Event Building or in the Event Filter farm is being considered and therefore tested. This platform from Intel hosts a general CPU and a high performance FPGA linked via a high speed link which is for this platform a QPI link. On the FPGA an accelerator is implemented. The used system is a two socket platform from Intel with a Xeon CPU and an FPGA. The FPGA has cache-coherent memory access to the main memory of the server and can collaborate with the CPU. As a first step, a computing intensive algorithm to reconstruct Cherenkov angles for the LHCb RICH particle identification was successfully ported in Verilog to the Intel Xeon/FPGA platform and accelerated by a factor of 35. The same algorithm was ported to the Intel Xeon/FPGA platform with OpenCL. The implementation work and the performance will be compared. Also another FPGA accelerator the Nallatech 385 PCIe accelerator with the same Stratix V FPGA were tested for performance. The results show that the Intel Xeon/FPGA platforms, which are built in general for high performance computing, are also very interesting for the High Energy Physics community.

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

Bailey, David H.

The NAS Parallel Benchmarks (NPB) are a suite of parallel computer performance benchmarks. They were originally developed at the NASA Ames Research Center in 1991 to assess high-end parallel supercomputers. Although they are no longer used as widely as they once were for comparing high-end system performance, they continue to be studied and analyzed a great deal in the high-performance computing community. The acronym 'NAS' originally stood for the Numerical Aeronautical Simulation Program at NASA Ames. The name of this organization was subsequently changed to the Numerical Aerospace Simulation Program, and more recently to the NASA Advanced Supercomputing Center, althoughmore » the acronym remains 'NAS.' The developers of the original NPB suite were David H. Bailey, Eric Barszcz, John Barton, David Browning, Russell Carter, LeoDagum, Rod Fatoohi, Samuel Fineberg, Paul Frederickson, Thomas Lasinski, Rob Schreiber, Horst Simon, V. Venkatakrishnan and Sisira Weeratunga. The original NAS Parallel Benchmarks consisted of eight individual benchmark problems, each of which focused on some aspect of scientific computing. The principal focus was in computational aerophysics, although most of these benchmarks have much broader relevance, since in a much larger sense they are typical of many real-world scientific computing applications. The NPB suite grew out of the need for a more rational procedure to select new supercomputers for acquisition by NASA. The emergence of commercially available highly parallel computer systems in the late 1980s offered an attractive alternative to parallel vector supercomputers that had been the mainstay of high-end scientific computing. However, the introduction of highly parallel systems was accompanied by a regrettable level of hype, not only on the part of the commercial vendors but even, in some cases, by scientists using the systems. As a result, it was difficult to discern whether the new systems offered any fundamental performance advantage over vector supercomputers, and, if so, which of the parallel offerings would be most useful in real-world scientific computation. In part to draw attention to some of the performance reporting abuses prevalent at the time, the present author wrote a humorous essay 'Twelve Ways to Fool the Masses,' which described in a light-hearted way a number of the questionable ways in which both vendor marketing people and scientists were inflating and distorting their performance results. All of this underscored the need for an objective and scientifically defensible measure to compare performance on these systems.« less

Virtual rehabilitation in an activity centre for community-dwelling persons with stroke. The possibilities of 3-dimensional computer games.

PubMed

Broeren, Jurgen; Claesson, Lisbeth; Goude, Daniel; Rydmark, Martin; Sunnerhagen, Katharina S

2008-01-01

The main purpose of this study was to place a virtual reality (VR) system, designed to assess and to promote motor performance in the affected upper extremity in subjects after stroke, in a nonhospital environment. We also wanted to investigate if playing computer games resulted in improved motor function in persons with prior stroke. The intervention involved 11 patients after stroke who received extra rehabilitation by training on a computer 3 times a week during a 4-week period. The control group involved 11 patients after stroke who continued their previous rehabilitation (no extra computer training) during this period. The mean age of all was 68 years (range = 47-85) and the average time after stroke 66 months (range = 15-140). The VR training consisted of challenging games, which provided a range of difficulty levels that allow practice to be fun and motivating. An additional group of 11 right-handed aged matched individuals without history of neurological or psychiatric illnesses served as reference subjects. All the participants reported that they were novel computer game players. After an initial introduction they learned to use the VR system quickly. The treatment group demonstrated improvements in motor outcome for the trained upper extremity, but this was not detected in real-life activities. The results of this research suggest the usefulness of computer games in training motor performance. VR can be used beneficially not only by younger participants but also by older persons to enhance their motor performance after stroke. Copyright 2008 S. Karger AG, Basel.

Computer and internet use in a community health clinic population.

PubMed

Peterson, Neeraja B; Dwyer, Kathleen A; Mulvaney, Shelagh A

2009-01-01

To determine if patients from a community health clinic have access to computers and/or the Internet and if they believe a computer is useful in their medical care. A convenience sample of 100 subjects, aged 50 years and older, from a community health clinic in Nashville, Tennessee, completed a structured interview and a health literacy assessment. Of the 100 participants, 40 did not have any computer access, 27 had computer but not Internet access, and 33 had Internet access. Participants with computer access (with or without Internet) had higher incomes, higher educational status, and higher literacy status than those without computer access. Of participants reporting current computer use (n = 54), 33% reported never using their computer to look up health and medical information. Of those who "never'' used their computer for this activity, 54% reported they did not have Internet connectivity, whereas 31% reported they did not know how to use the Internet. Although this group of individuals reported that they were comfortable using a computer (77%), they reported being uncomfortable with accessing the Internet (53%). Not only does access to computers and the Internet need to be improved before widespread use by patients, but computer users will need to be instructed on how to navigate the Internet.

Significantly reducing the processing times of high-speed photometry data sets using a distributed computing model

NASA Astrophysics Data System (ADS)

Doyle, Paul; Mtenzi, Fred; Smith, Niall; Collins, Adrian; O'Shea, Brendan

2012-09-01

The scientific community is in the midst of a data analysis crisis. The increasing capacity of scientific CCD instrumentation and their falling costs is contributing to an explosive generation of raw photometric data. This data must go through a process of cleaning and reduction before it can be used for high precision photometric analysis. Many existing data processing pipelines either assume a relatively small dataset or are batch processed by a High Performance Computing centre. A radical overhaul of these processing pipelines is required to allow reduction and cleaning rates to process terabyte sized datasets at near capture rates using an elastic processing architecture. The ability to access computing resources and to allow them to grow and shrink as demand fluctuates is essential, as is exploiting the parallel nature of the datasets. A distributed data processing pipeline is required. It should incorporate lossless data compression, allow for data segmentation and support processing of data segments in parallel. Academic institutes can collaborate and provide an elastic computing model without the requirement for large centralized high performance computing data centers. This paper demonstrates how a base 10 order of magnitude improvement in overall processing time has been achieved using the "ACN pipeline", a distributed pipeline spanning multiple academic institutes.

Simulating realistic predator signatures in quantitative fatty acid signature analysis

USGS Publications Warehouse

Bromaghin, Jeffrey F.

2015-01-01

Diet estimation is an important field within quantitative ecology, providing critical insights into many aspects of ecology and community dynamics. Quantitative fatty acid signature analysis (QFASA) is a prominent method of diet estimation, particularly for marine mammal and bird species. Investigators using QFASA commonly use computer simulation to evaluate statistical characteristics of diet estimators for the populations they study. Similar computer simulations have been used to explore and compare the performance of different variations of the original QFASA diet estimator. In both cases, computer simulations involve bootstrap sampling prey signature data to construct pseudo-predator signatures with known properties. However, bootstrap sample sizes have been selected arbitrarily and pseudo-predator signatures therefore may not have realistic properties. I develop an algorithm to objectively establish bootstrap sample sizes that generates pseudo-predator signatures with realistic properties, thereby enhancing the utility of computer simulation for assessing QFASA estimator performance. The algorithm also appears to be computationally efficient, resulting in bootstrap sample sizes that are smaller than those commonly used. I illustrate the algorithm with an example using data from Chukchi Sea polar bears (Ursus maritimus) and their marine mammal prey. The concepts underlying the approach may have value in other areas of quantitative ecology in which bootstrap samples are post-processed prior to their use.

Improving geolocation and spatial accuracies with the modular integrated avionics group (MIAG)

NASA Astrophysics Data System (ADS)

Johnson, Einar; Souter, Keith

1996-05-01

The modular integrated avionics group (MIAG) is a single unit approach to combining position, inertial and baro-altitude/air data sensors to provide optimized navigation, guidance and control performance. Lear Astronics Corporation is currently working within the navigation community to upgrade existing MIAG performance with precise GPS positioning mechanization tightly integrated with inertial, baro and other sensors. Among the immediate benefits are the following: (1) accurate target location in dynamic conditions; (2) autonomous launch and recovery using airborne avionics only; (3) precise flight path guidance; and (4) improved aircraft and payload stability information. This paper will focus on the impact of using the MIAG with its multimode navigation accuracies on the UAV targeting mission. Gimbaled electro-optical sensors mounted on a UAV can be used to determine ground coordinates of a target at the center of the field of view by a series of vector rotation and scaling computations. The accuracy of the computed target coordinates is dependent on knowing the UAV position and the UAV-to-target offset computation. Astronics performed a series of simulations to evaluate the effects that the improved angular and position data available from the MIAG have on target coordinate accuracy.

(Re)engineering Earth System Models to Expose Greater Concurrency for Ultrascale Computing: Practice, Experience, and Musings

NASA Astrophysics Data System (ADS)

Mills, R. T.

2014-12-01

As the high performance computing (HPC) community pushes towards the exascale horizon, the importance and prevalence of fine-grained parallelism in new computer architectures is increasing. This is perhaps most apparent in the proliferation of so-called "accelerators" such as the Intel Xeon Phi or NVIDIA GPGPUs, but the trend also holds for CPUs, where serial performance has grown slowly and effective use of hardware threads and vector units are becoming increasingly important to realizing high performance. This has significant implications for weather, climate, and Earth system modeling codes, many of which display impressive scalability across MPI ranks but take relatively little advantage of threading and vector processing. In addition to increasing parallelism, next generation codes will also need to address increasingly deep hierarchies for data movement: NUMA/cache levels, on node vs. off node, local vs. wide neighborhoods on the interconnect, and even in the I/O system. We will discuss some approaches (grounded in experiences with the Intel Xeon Phi architecture) for restructuring Earth science codes to maximize concurrency across multiple levels (vectors, threads, MPI ranks), and also discuss some novel approaches for minimizing expensive data movement/communication.

Neuromorphic Computing, Architectures, Models, and Applications. A Beyond-CMOS Approach to Future Computing, June 29-July 1, 2016, Oak Ridge, TN

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

Potok, Thomas; Schuman, Catherine; Patton, Robert

The White House and Department of Energy have been instrumental in driving the development of a neuromorphic computing program to help the United States continue its lead in basic research into (1) Beyond Exascale—high performance computing beyond Moore’s Law and von Neumann architectures, (2) Scientific Discovery—new paradigms for understanding increasingly large and complex scientific data, and (3) Emerging Architectures—assessing the potential of neuromorphic and quantum architectures. Neuromorphic computing spans a broad range of scientific disciplines from materials science to devices, to computer science, to neuroscience, all of which are required to solve the neuromorphic computing grand challenge. In our workshopmore » we focus on the computer science aspects, specifically from a neuromorphic device through an application. Neuromorphic devices present a very different paradigm to the computer science community from traditional von Neumann architectures, which raises six major questions about building a neuromorphic application from the device level. We used these fundamental questions to organize the workshop program and to direct the workshop panels and discussions. From the white papers, presentations, panels, and discussions, there emerged several recommendations on how to proceed.« less

EPA CHEMICAL PRIORITIZATION COMMUNITY OF PRACTICE.

EPA Science Inventory

IN 2005 THE NATIONAL CENTER FOR COMPUTATIONAL TOXICOLOGY (NCCT) ORGANIZED EPA CHEMICAL PRIORITIATION COMMUNITY OF PRACTICE (CPCP) TO PROVIDE A FORUM FOR DISCUSSING THE UTILITY OF COMPUTATIONAL CHEMISTRY, HIGH-THROUGHPUT SCREENIG (HTS) AND VARIOUS TOXICOGENOMIC TECHNOLOGIES FOR CH...

The Changing Role of Data Stewardship in Creating Trustworthy, Interdisciplinary High Performance Data Platforms for the Future.

NASA Astrophysics Data System (ADS)

Richards, C. J.; Evans, B. J. K.; Wyborn, L. A.; Wang, J.; Trenham, C. E.; Druken, K. A.

2016-12-01

The Australian National Computational Infrastructure (NCI) has ingested over 10PB of national and international environmental, Earth systems science and geophysics reference data onto a single platform to advance high performance data (HPD) techniques that enable interdisciplinary Data-intensive Science. Improved Data Stewardship is critical to evolve both data and data services that support the increasing need for programmatic usability and that prioritises interoperability rather than just traditional data download or portal access. A data platform designed for programmatic access requires quality checked collections that better utilise interoperable data formats and standards. Achieving this involves strategies to meet both the technical and `social' challenges. Aggregating datasets used by different communities and organisations requires satisfying multiple use cases for the broader research community, whilst addressing existing BAU requirements. For NCI, this requires working with data stewards to manage the process of replicating data to the common platform, community representatives and developers to confirm their requirements, and with international peers to better enable globally integrated data communities. It is particularly important to engage with representatives from each community who can work collaboratively to a common goal, as well as capture their community needs, apply quality assurance, determine any barriers to change and to understand priorities. This is critical when managing the aggregation of data collections from multiple producers with different levels of stewardship maturity, technologies and standards, and where organisational barriers can impact the transformation to interoperable and performant data access. To facilitate the management, development and operation of the HPD platform, NCI coordinates technical and domain committees made up of user representatives, data stewards and informatics experts to provide a forum to discuss, learn and advise NCI's management. This experience has been a useful collaboration and suggests that in the age of interdisciplinary HPD research, Data Stewardship is evolving from a focus on the needs of a single community to one which helps balance priorities and navigates change for multiple communities.

A Computer Simulation of Community Pharmacy Practice for Educational Use.

PubMed

Bindoff, Ivan; Ling, Tristan; Bereznicki, Luke; Westbury, Juanita; Chalmers, Leanne; Peterson, Gregory; Ollington, Robert

2014-11-15

To provide a computer-based learning method for pharmacy practice that is as effective as paper-based scenarios, but more engaging and less labor-intensive. We developed a flexible and customizable computer simulation of community pharmacy. Using it, the students would be able to work through scenarios which encapsulate the entirety of a patient presentation. We compared the traditional paper-based teaching method to our computer-based approach using equivalent scenarios. The paper-based group had 2 tutors while the computer group had none. Both groups were given a prescenario and postscenario clinical knowledge quiz and survey. Students in the computer-based group had generally greater improvements in their clinical knowledge score, and third-year students using the computer-based method also showed more improvements in history taking and counseling competencies. Third-year students also found the simulation fun and engaging. Our simulation of community pharmacy provided an educational experience as effective as the paper-based alternative, despite the lack of a human tutor.

A Comprehensive Review of Computer Science and Data Processing Education in Community Colleges and Area Vocational-Technical Centers.

ERIC Educational Resources Information Center

Florida State Community Coll. Coordinating Board, Tallahassee.

In 1987-88, the Florida State Board of Community Colleges and the Division of Vocational, Adult, and Community Education jointly conducted a review of instructional programs in computer science and data processing in order to determine needs for state policy changes and funding priorities. The process involved a review of printed resources on…

The Role of Perceived Learning and Communities of Inquiry in Predicting International Students' Course Grades in Computer-Mediated Graduate Courses

ERIC Educational Resources Information Center

Wendt, Jillian L.; Nisbet, Deanna L.

2017-01-01

This study examined the predictive relationship among international students' sense of community, perceived learning, and end-of-course grades in computer-mediated, U.S. graduate-level courses. The community of inquiry (CoI) framework served as the theoretical foundation for the study. Step-wise hierarchical multiple regression showed no…

Building a Digital Library from the Ground Up: an Examination of Emergent Information Resources in the Machine Learning Community

NASA Astrophysics Data System (ADS)

Cunningham, Sally Jo

The current crop of digital libraries for the computing community are strongly grounded in the conventional library paradigm: they provide indexes to support searching of collections of research papers. As such, these digital libraries are relatively impoverished; the present computing digital libraries omit many of the documents and resources that are currently available to computing researchers, and offer few browsing structures. These computing digital libraries were built 'top down': the resources and collection contents are forced to fit an existing digital library architecture. A 'bottom up' approach to digital library development would begin with an investigation of a community's information needs and available documents, and then design a library to organize those documents in such a way as to fulfill the community's needs. The 'home grown', informal information resources developed by and for the machine learning community are examined as a case study, to determine the types of information and document organizations 'native' to this group of researchers. The insights gained in this type of case study can be used to inform construction of a digital library tailored to this community.

Objective comparison of particle tracking methods.

PubMed

Chenouard, Nicolas; Smal, Ihor; de Chaumont, Fabrice; Maška, Martin; Sbalzarini, Ivo F; Gong, Yuanhao; Cardinale, Janick; Carthel, Craig; Coraluppi, Stefano; Winter, Mark; Cohen, Andrew R; Godinez, William J; Rohr, Karl; Kalaidzidis, Yannis; Liang, Liang; Duncan, James; Shen, Hongying; Xu, Yingke; Magnusson, Klas E G; Jaldén, Joakim; Blau, Helen M; Paul-Gilloteaux, Perrine; Roudot, Philippe; Kervrann, Charles; Waharte, François; Tinevez, Jean-Yves; Shorte, Spencer L; Willemse, Joost; Celler, Katherine; van Wezel, Gilles P; Dan, Han-Wei; Tsai, Yuh-Show; Ortiz de Solórzano, Carlos; Olivo-Marin, Jean-Christophe; Meijering, Erik

2014-03-01

Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy image data. Because manually detecting and following large numbers of individual particles is not feasible, automated computational methods have been developed for these tasks by many groups. Aiming to perform an objective comparison of methods, we gathered the community and organized an open competition in which participating teams applied their own methods independently to a commonly defined data set including diverse scenarios. Performance was assessed using commonly defined measures. Although no single method performed best across all scenarios, the results revealed clear differences between the various approaches, leading to notable practical conclusions for users and developers.

An ant colony based algorithm for overlapping community detection in complex networks

NASA Astrophysics Data System (ADS)

Zhou, Xu; Liu, Yanheng; Zhang, Jindong; Liu, Tuming; Zhang, Di

2015-06-01

Community detection is of great importance to understand the structures and functions of networks. Overlap is a significant feature of networks and overlapping community detection has attracted an increasing attention. Many algorithms have been presented to detect overlapping communities. In this paper, we present an ant colony based overlapping community detection algorithm which mainly includes ants' location initialization, ants' movement and post processing phases. An ants' location initialization strategy is designed to identify initial location of ants and initialize label list stored in each node. During the ants' movement phase, the entire ants move according to the transition probability matrix, and a new heuristic information computation approach is redefined to measure similarity between two nodes. Every node keeps a label list through the cooperation made by ants until a termination criterion is reached. A post processing phase is executed on the label list to get final overlapping community structure naturally. We illustrate the capability of our algorithm by making experiments on both synthetic networks and real world networks. The results demonstrate that our algorithm will have better performance in finding overlapping communities and overlapping nodes in synthetic datasets and real world datasets comparing with state-of-the-art algorithms.

Factors influencing use of an e-health website in a community sample of older adults.

PubMed

Czaja, Sara J; Sharit, Joseph; Lee, Chin Chin; Nair, Sankaran N; Hernández, Mario A; Arana, Neysarí; Fu, Shih Hua

2013-01-01

The use of the internet as a source of health information and link to healthcare services has raised concerns about the ability of consumers, especially vulnerable populations such as older adults, to access these applications. This study examined the influence of training on the ability of adults (aged 45+ years) to use the Medicare.gov website to solve problems related to health management. The influence of computer experience and cognitive abilities on performance was also examined. Seventy-one participants, aged 47-92, were randomized into a Multimedia training, Unimodal training, or Cold Start condition and completed three healthcare management problems. MEASUREMENT AND ANALYSES: Computer/internet experience was measured via questionnaire, and cognitive abilities were assessed using standard neuropsychological tests. Performance metrics included measures of navigation, accuracy and efficiency. Data were analyzed using analysis of variance, χ(2) and regression techniques. The data indicate that there was no difference among the three conditions on measures of accuracy, efficiency, or navigation. However, results of the regression analyses showed that, overall, people who received training performed better on the tasks, as evidenced by greater accuracy and efficiency. Performance was also significantly influenced by prior computer experience and cognitive abilities. Participants with more computer experience and higher cognitive abilities performed better. The findings indicate that training, experience, and abilities are important when using complex health websites. However, training alone is not sufficient. The complexity of web content needs to be considered to ensure successful use of these websites by those with lower abilities.

Factors influencing use of an e-health website in a community sample of older adults

PubMed Central

Sharit, Joseph; Lee, Chin Chin; Nair, Sankaran N; Hernández, Mario A; Arana, Neysarí; Fu, Shih Hua

2013-01-01

Objective The use of the internet as a source of health information and link to healthcare services has raised concerns about the ability of consumers, especially vulnerable populations such as older adults, to access these applications. This study examined the influence of training on the ability of adults (aged 45+ years) to use the Medicare.gov website to solve problems related to health management. The influence of computer experience and cognitive abilities on performance was also examined. Design Seventy-one participants, aged 47–92, were randomized into a Multimedia training, Unimodal training, or Cold Start condition and completed three healthcare management problems. Measurement and analyses Computer/internet experience was measured via questionnaire, and cognitive abilities were assessed using standard neuropsychological tests. Performance metrics included measures of navigation, accuracy and efficiency. Data were analyzed using analysis of variance, χ2 and regression techniques. Results The data indicate that there was no difference among the three conditions on measures of accuracy, efficiency, or navigation. However, results of the regression analyses showed that, overall, people who received training performed better on the tasks, as evidenced by greater accuracy and efficiency. Performance was also significantly influenced by prior computer experience and cognitive abilities. Participants with more computer experience and higher cognitive abilities performed better. Conclusions The findings indicate that training, experience, and abilities are important when using complex health websites. However, training alone is not sufficient. The complexity of web content needs to be considered to ensure successful use of these websites by those with lower abilities. PMID:22802269

Big Data Clustering via Community Detection and Hyperbolic Network Embedding in IoT Applications.

PubMed

Karyotis, Vasileios; Tsitseklis, Konstantinos; Sotiropoulos, Konstantinos; Papavassiliou, Symeon

2018-04-15

In this paper, we present a novel data clustering framework for big sensory data produced by IoT applications. Based on a network representation of the relations among multi-dimensional data, data clustering is mapped to node clustering over the produced data graphs. To address the potential very large scale of such datasets/graphs that test the limits of state-of-the-art approaches, we map the problem of data clustering to a community detection one over the corresponding data graphs. Specifically, we propose a novel computational approach for enhancing the traditional Girvan-Newman (GN) community detection algorithm via hyperbolic network embedding. The data dependency graph is embedded in the hyperbolic space via Rigel embedding, allowing more efficient computation of edge-betweenness centrality needed in the GN algorithm. This allows for more efficient clustering of the nodes of the data graph in terms of modularity, without sacrificing considerable accuracy. In order to study the operation of our approach with respect to enhancing GN community detection, we employ various representative types of artificial complex networks, such as scale-free, small-world and random geometric topologies, and frequently-employed benchmark datasets for demonstrating its efficacy in terms of data clustering via community detection. Furthermore, we provide a proof-of-concept evaluation by applying the proposed framework over multi-dimensional datasets obtained from an operational smart-city/building IoT infrastructure provided by the Federated Interoperable Semantic IoT/cloud Testbeds and Applications (FIESTA-IoT) testbed federation. It is shown that the proposed framework can be indeed used for community detection/data clustering and exploited in various other IoT applications, such as performing more energy-efficient smart-city/building sensing.

Big Data Clustering via Community Detection and Hyperbolic Network Embedding in IoT Applications

PubMed Central

Sotiropoulos, Konstantinos

2018-01-01

In this paper, we present a novel data clustering framework for big sensory data produced by IoT applications. Based on a network representation of the relations among multi-dimensional data, data clustering is mapped to node clustering over the produced data graphs. To address the potential very large scale of such datasets/graphs that test the limits of state-of-the-art approaches, we map the problem of data clustering to a community detection one over the corresponding data graphs. Specifically, we propose a novel computational approach for enhancing the traditional Girvan–Newman (GN) community detection algorithm via hyperbolic network embedding. The data dependency graph is embedded in the hyperbolic space via Rigel embedding, allowing more efficient computation of edge-betweenness centrality needed in the GN algorithm. This allows for more efficient clustering of the nodes of the data graph in terms of modularity, without sacrificing considerable accuracy. In order to study the operation of our approach with respect to enhancing GN community detection, we employ various representative types of artificial complex networks, such as scale-free, small-world and random geometric topologies, and frequently-employed benchmark datasets for demonstrating its efficacy in terms of data clustering via community detection. Furthermore, we provide a proof-of-concept evaluation by applying the proposed framework over multi-dimensional datasets obtained from an operational smart-city/building IoT infrastructure provided by the Federated Interoperable Semantic IoT/cloud Testbeds and Applications (FIESTA-IoT) testbed federation. It is shown that the proposed framework can be indeed used for community detection/data clustering and exploited in various other IoT applications, such as performing more energy-efficient smart-city/building sensing. PMID:29662043

Intuitive Space Weather Displays to Improve Space Situational Awareness (SSA)

DTIC Science & Technology

2011-09-01

parsimonious offering. After engaging several mathematicians and space physicists to devise valid computational formulas for aggregating the four hazard... PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Aptima, Inc.,12 Gill Street Ste 200,Woburn,MA... physicists , the operational users find little use in receiving particle fluxes or magnetometer readings collected by the scientific community. Fortunately

Acquisition of a High Performance Computing Instrument for Big Data Research and Education

DTIC Science & Technology

2015-12-03

Security and Privacy , University of Texas at Dallas, TX, September 16-17, 2014. • Chopade, P., Zhan, J., Community Detection in Large Scale Big Data...Security and Privacy in Communication Networks, Beijing, China, September 24-26, 2014. • Pravin Chopade, Kenneth Flurchick, Justin Zhan and Marwan...Balkirat Kaur, Malcolm Blow, and Justin Zhan, Digital Image Authentication in Social Media, The Sixth ASE International Conference on Privacy

Data Serving Climate Simulation Science at the NASA Center for Climate Simulation

NASA Technical Reports Server (NTRS)

Salmon, Ellen M.

2011-01-01

The NASA Center for Climate Simulation (NCCS) provides high performance computational resources, a multi-petabyte archive, and data services in support of climate simulation research and other NASA-sponsored science. This talk describes the NCCS's data-centric architecture and processing, which are evolving in anticipation of researchers' growing requirements for higher resolution simulations and increased data sharing among NCCS users and the external science community.

The JASMIN Cloud: specialised and hybrid to meet the needs of the Environmental Sciences Community

NASA Astrophysics Data System (ADS)

Kershaw, Philip; Lawrence, Bryan; Churchill, Jonathan; Pritchard, Matt

2014-05-01

Cloud computing provides enormous opportunities for the research community. The large public cloud providers provide near-limitless scaling capability. However, adapting Cloud to scientific workloads is not without its problems. The commodity nature of the public cloud infrastructure can be at odds with the specialist requirements of the research community. Issues such as trust, ownership of data, WAN bandwidth and costing models make additional barriers to more widespread adoption. Alongside the application of public cloud for scientific applications, a number of private cloud initiatives are underway in the research community of which the JASMIN Cloud is one example. Here, cloud service models are being effectively super-imposed over more established services such as data centres, compute cluster facilities and Grids. These have the potential to deliver the specialist infrastructure needed for the science community coupled with the benefits of a Cloud service model. The JASMIN facility based at the Rutherford Appleton Laboratory was established in 2012 to support the data analysis requirements of the climate and Earth Observation community. In its first year of operation, the 5PB of available storage capacity was filled and the hosted compute capability used extensively. JASMIN has modelled the concept of a centralised large-volume data analysis facility. Key characteristics have enabled success: peta-scale fast disk connected via low latency networks to compute resources and the use of virtualisation for effective management of the resources for a range of users. A second phase is now underway funded through NERC's (Natural Environment Research Council) Big Data initiative. This will see significant expansion to the resources available with a doubling of disk-based storage to 12PB and an increase of compute capacity by a factor of ten to over 3000 processing cores. This expansion is accompanied by a broadening in the scope for JASMIN, as a service available to the entire UK environmental science community. Experience with the first phase demonstrated the range of user needs. A trade-off is needed between access privileges to resources, flexibility of use and security. This has influenced the form and types of service under development for the new phase. JASMIN will deploy a specialised private cloud organised into "Managed" and "Unmanaged" components. In the Managed Cloud, users have direct access to the storage and compute resources for optimal performance but for reasons of security, via a more restrictive PaaS (Platform-as-a-Service) interface. The Unmanaged Cloud is deployed in an isolated part of the network but co-located with the rest of the infrastructure. This enables greater liberty to tenants - full IaaS (Infrastructure-as-a-Service) capability to provision customised infrastructure - whilst at the same time protecting more sensitive parts of the system from direct access using these elevated privileges. The private cloud will be augmented with cloud-bursting capability so that it can exploit the resources available from public clouds, making it effectively a hybrid solution. A single interface will overlay the functionality of both the private cloud and external interfaces to public cloud providers giving users the flexibility to migrate resources between infrastructures as requirements dictate.

Benchmarking infrastructure for mutation text mining

PubMed Central

2014-01-01

Background Experimental research on the automatic extraction of information about mutations from texts is greatly hindered by the lack of consensus evaluation infrastructure for the testing and benchmarking of mutation text mining systems. Results We propose a community-oriented annotation and benchmarking infrastructure to support development, testing, benchmarking, and comparison of mutation text mining systems. The design is based on semantic standards, where RDF is used to represent annotations, an OWL ontology provides an extensible schema for the data and SPARQL is used to compute various performance metrics, so that in many cases no programming is needed to analyze results from a text mining system. While large benchmark corpora for biological entity and relation extraction are focused mostly on genes, proteins, diseases, and species, our benchmarking infrastructure fills the gap for mutation information. The core infrastructure comprises (1) an ontology for modelling annotations, (2) SPARQL queries for computing performance metrics, and (3) a sizeable collection of manually curated documents, that can support mutation grounding and mutation impact extraction experiments. Conclusion We have developed the principal infrastructure for the benchmarking of mutation text mining tasks. The use of RDF and OWL as the representation for corpora ensures extensibility. The infrastructure is suitable for out-of-the-box use in several important scenarios and is ready, in its current state, for initial community adoption. PMID:24568600

Benchmarking infrastructure for mutation text mining.

PubMed

Klein, Artjom; Riazanov, Alexandre; Hindle, Matthew M; Baker, Christopher Jo

2014-02-25

Experimental research on the automatic extraction of information about mutations from texts is greatly hindered by the lack of consensus evaluation infrastructure for the testing and benchmarking of mutation text mining systems. We propose a community-oriented annotation and benchmarking infrastructure to support development, testing, benchmarking, and comparison of mutation text mining systems. The design is based on semantic standards, where RDF is used to represent annotations, an OWL ontology provides an extensible schema for the data and SPARQL is used to compute various performance metrics, so that in many cases no programming is needed to analyze results from a text mining system. While large benchmark corpora for biological entity and relation extraction are focused mostly on genes, proteins, diseases, and species, our benchmarking infrastructure fills the gap for mutation information. The core infrastructure comprises (1) an ontology for modelling annotations, (2) SPARQL queries for computing performance metrics, and (3) a sizeable collection of manually curated documents, that can support mutation grounding and mutation impact extraction experiments. We have developed the principal infrastructure for the benchmarking of mutation text mining tasks. The use of RDF and OWL as the representation for corpora ensures extensibility. The infrastructure is suitable for out-of-the-box use in several important scenarios and is ready, in its current state, for initial community adoption.

IN13B-1660: Analytics and Visualization Pipelines for Big Data on the NASA Earth Exchange (NEX) and OpenNEX

NASA Technical Reports Server (NTRS)

Chaudhary, Aashish; Votava, Petr; Nemani, Ramakrishna R.; Michaelis, Andrew; Kotfila, Chris

2016-01-01

We are developing capabilities for an integrated petabyte-scale Earth science collaborative analysis and visualization environment. The ultimate goal is to deploy this environment within the NASA Earth Exchange (NEX) and OpenNEX in order to enhance existing science data production pipelines in both high-performance computing (HPC) and cloud environments. Bridging of HPC and cloud is a fairly new concept under active research and this system significantly enhances the ability of the scientific community to accelerate analysis and visualization of Earth science data from NASA missions, model outputs and other sources. We have developed a web-based system that seamlessly interfaces with both high-performance computing (HPC) and cloud environments, providing tools that enable science teams to develop and deploy large-scale analysis, visualization and QA pipelines of both the production process and the data products, and enable sharing results with the community. Our project is developed in several stages each addressing separate challenge - workflow integration, parallel execution in either cloud or HPC environments and big-data analytics or visualization. This work benefits a number of existing and upcoming projects supported by NEX, such as the Web Enabled Landsat Data (WELD), where we are developing a new QA pipeline for the 25PB system.

Analytics and Visualization Pipelines for Big ­Data on the NASA Earth Exchange (NEX) and OpenNEX

NASA Astrophysics Data System (ADS)

Chaudhary, A.; Votava, P.; Nemani, R. R.; Michaelis, A.; Kotfila, C.

2016-12-01

We are developing capabilities for an integrated petabyte-scale Earth science collaborative analysis and visualization environment. The ultimate goal is to deploy this environment within the NASA Earth Exchange (NEX) and OpenNEX in order to enhance existing science data production pipelines in both high-performance computing (HPC) and cloud environments. Bridging of HPC and cloud is a fairly new concept under active research and this system significantly enhances the ability of the scientific community to accelerate analysis and visualization of Earth science data from NASA missions, model outputs and other sources. We have developed a web-based system that seamlessly interfaces with both high-performance computing (HPC) and cloud environments, providing tools that enable science teams to develop and deploy large-scale analysis, visualization and QA pipelines of both the production process and the data products, and enable sharing results with the community. Our project is developed in several stages each addressing separate challenge - workflow integration, parallel execution in either cloud or HPC environments and big-data analytics or visualization. This work benefits a number of existing and upcoming projects supported by NEX, such as the Web Enabled Landsat Data (WELD), where we are developing a new QA pipeline for the 25PB system.

A Rural Community's Involvement in the Design and Usability Testing of a Computer-Based Informed Consent Process for the Personalized Medicine Research Project

PubMed Central

Mahnke, Andrea N; Plasek, Joseph M; Hoffman, David G; Partridge, Nathan S; Foth, Wendy S; Waudby, Carol J; Rasmussen, Luke V; McManus, Valerie D; McCarty, Catherine A

2014-01-01

Many informed consent studies demonstrate that research subjects poorly retain and understand information in written consent documents. Previous research in multimedia consent is mixed in terms of success for improving participants’ understanding, satisfaction, and retention. This failure may be due to a lack of a community-centered design approach to building the interventions. The goal of this study was to gather information from the community to determine the best way to undertake the consent process. Community perceptions regarding different computer-based consenting approaches were evaluated, and a computer-based consent was developed and tested. A second goal was to evaluate whether participants make truly informed decisions to participate in research. Simulations of an informed consent process were videotaped to document the process. Focus groups were conducted to determine community attitudes towards a computer-based informed consent process. Hybrid focus groups were conducted to determine the most acceptable hardware device. Usability testing was conducted on a computer-based consent prototype using a touch-screen kiosk. Based on feedback, a computer-based consent was developed. Representative study participants were able to easily complete the consent, and all were able to correctly answer the comprehension check questions. Community involvement in developing a computer-based consent proved valuable for a population-based genetic study. These findings may translate to other types of informed consents, such as genetic clinical trials consents. A computer-based consent may serve to better communicate consistent, clear, accurate, and complete information regarding the risks and benefits of study participation. Additional analysis is necessary to measure the level of comprehension of the check-question answers by larger numbers of participants. The next step will involve contacting participants to measure whether understanding of what they consented to is retained over time. PMID:24273095

A rural community's involvement in the design and usability testing of a computer-based informed consent process for the Personalized Medicine Research Project.

PubMed

Mahnke, Andrea N; Plasek, Joseph M; Hoffman, David G; Partridge, Nathan S; Foth, Wendy S; Waudby, Carol J; Rasmussen, Luke V; McManus, Valerie D; McCarty, Catherine A

2014-01-01

Many informed consent studies demonstrate that research subjects poorly retain and understand information in written consent documents. Previous research in multimedia consent is mixed in terms of success for improving participants' understanding, satisfaction, and retention. This failure may be due to a lack of a community-centered design approach to building the interventions. The goal of this study was to gather information from the community to determine the best way to undertake the consent process. Community perceptions regarding different computer-based consenting approaches were evaluated, and a computer-based consent was developed and tested. A second goal was to evaluate whether participants make truly informed decisions to participate in research. Simulations of an informed consent process were videotaped to document the process. Focus groups were conducted to determine community attitudes towards a computer-based informed consent process. Hybrid focus groups were conducted to determine the most acceptable hardware device. Usability testing was conducted on a computer-based consent prototype using a touch-screen kiosk. Based on feedback, a computer-based consent was developed. Representative study participants were able to easily complete the consent, and all were able to correctly answer the comprehension check questions. Community involvement in developing a computer-based consent proved valuable for a population-based genetic study. These findings may translate to other types of informed consents, including those for trials involving treatment of genetic disorders. A computer-based consent may serve to better communicate consistent, clear, accurate, and complete information regarding the risks and benefits of study participation. Additional analysis is necessary to measure the level of comprehension of the check-question answers by larger numbers of participants. The next step will involve contacting participants to measure whether understanding of what they consented to is retained over time. © 2013 Wiley Periodicals, Inc.

The Montage architecture for grid-enabled science processing of large, distributed datasets

NASA Technical Reports Server (NTRS)

Jacob, Joseph C.; Katz, Daniel S .; Prince, Thomas; Berriman, Bruce G.; Good, John C.; Laity, Anastasia C.; Deelman, Ewa; Singh, Gurmeet; Su, Mei-Hui

2004-01-01

Montage is an Earth Science Technology Office (ESTO) Computational Technologies (CT) Round III Grand Challenge investigation to deploy a portable, compute-intensive, custom astronomical image mosaicking service for the National Virtual Observatory (NVO). Although Montage is developing a compute- and data-intensive service for the astronomy community, we are also helping to address a problem that spans both Earth and Space science, namely how to efficiently access and process multi-terabyte, distributed datasets. In both communities, the datasets are massive, and are stored in distributed archives that are, in most cases, remote from the available Computational resources. Therefore, state of the art computational grid technologies are a key element of the Montage portal architecture. This paper describes the aspects of the Montage design that are applicable to both the Earth and Space science communities.

Incidence and clinical characteristics of interstitial cystitis in the community.

PubMed

Patel, Ronak; Calhoun, Elizabeth A; Meenan, Richard T; O'Keeffe Rosetti, Maureen C; Kimes, Terry; Clemens, J Quentin

2008-08-01

We utilized physician-coded diagnoses and chart reviews to estimate the incidence of interstitial cystitis (IC) in women. A computer search of the Kaiser Permanente database was performed to identify newly coded diagnoses of IC (ICD-9 code 595.1) between May 2002 and May 2005. Chart reviews were performed and patient demographics, diagnosing physicians, and symptom characteristics were recorded. The IC incidence rate was 15 per 100,000 women per year. The mean age of the patients was 51 years (range 31-81 years). The most common presenting symptoms were frequency (70%), dysuria (52%), urgency (50%), suprapubic pain (50%), nocturia (35%), and dyspareunia (13%). Cases diagnosed by primary care physicians had a shorter median symptom duration (9 months) compared with those diagnosed by urologists (1 year) and gynecologists (3 years). IC is an uncommon diagnosis in the community setting, with an incidence rate of 15 per 100,000 women per year.

CFD: A Castle in the Sand?

NASA Technical Reports Server (NTRS)

Kleb, William L.; Wood, William A.

2004-01-01

The computational simulation community is not routinely publishing independently verifiable tests to accompany new models or algorithms. A survey reveals that only 22% of new models published are accompanied by tests suitable for independently verifying the new model. As the community develops larger codes with increased functionality, and hence increased complexity in terms of the number of building block components and their interactions, it becomes prohibitively expensive for each development group to derive the appropriate tests for each component. Therefore, the computational simulation community is building its collective castle on a very shaky foundation of components with unpublished and unrepeatable verification tests. The computational simulation community needs to begin publishing component level verification tests before the tide of complexity undermines its foundation.

Programming for 1.6 Millon cores: Early experiences with IBM's BG/Q SMP architecture

NASA Astrophysics Data System (ADS)

Glosli, James

2013-03-01

With the stall in clock cycle improvements a decade ago, the drive for computational performance has continues along a path of increasing core counts on a processor. The multi-core evolution has been expressed in both a symmetric multi processor (SMP) architecture and cpu/GPU architecture. Debates rage in the high performance computing (HPC) community which architecture best serves HPC. In this talk I will not attempt to resolve that debate but perhaps fuel it. I will discuss the experience of exploiting Sequoia, a 98304 node IBM Blue Gene/Q SMP at Lawrence Livermore National Laboratory. The advantages and challenges of leveraging the computational power BG/Q will be detailed through the discussion of two applications. The first application is a Molecular Dynamics code called ddcMD. This is a code developed over the last decade at LLNL and ported to BG/Q. The second application is a cardiac modeling code called Cardioid. This is a code that was recently designed and developed at LLNL to exploit the fine scale parallelism of BG/Q's SMP architecture. Through the lenses of these efforts I'll illustrate the need to rethink how we express and implement our computational approaches. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Internet end-to-end performance monitoring for the High Energy Nuclear and Particle Physics community

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

Matthews, W.

2000-02-22

Modern High Energy Nuclear and Particle Physics (HENP) experiments at Laboratories around the world present a significant challenge to wide area networks. Petabytes (1015) or exabytes (1018) of data will be generated during the lifetime of the experiment. Much of this data will be distributed via the Internet to the experiment's collaborators at Universities and Institutes throughout the world for analysis. In order to assess the feasibility of the computing goals of these and future experiments, the HENP networking community is actively monitoring performance across a large part of the Internet used by its collaborators. Since 1995, the pingER projectmore » has been collecting data on ping packet loss and round trip times. In January 2000, there are 28 monitoring sites in 15 countries gathering data on over 2,000 end-to-end pairs. HENP labs such as SLAC, Fermi Lab and CERN are using Advanced Network's Surveyor project and monitoring performance from one-way delay of UDP packets. More recently several HENP sites have become involved with NLANR's active measurement program (AMP). In addition SLAC and CERN are part of the RIPE test-traffic project and SLAC is home for a NIMI machine. The large End-to-end performance monitoring infrastructure allows the HENP networking community to chart long term trends and closely examine short term glitches across a wide range of networks and connections. The different methodologies provide opportunities to compare results based on different protocols and statistical samples. Understanding agreement and discrepancies between results provides particular insight into the nature of the network. This paper will highlight the practical side of monitoring by reviewing the special needs of High Energy Nuclear and Particle Physics experiments and provide an overview of the experience of measuring performance across a large number of interconnected networks throughout the world with various methodologies. In particular, results from each project will be compared and disagreement will be analyzed. The goal is to address issues for improving understanding for gathering and analysis of accurate monitoring data, but the outlook for the computing goals of HENP will also be examined.« less

Blueprint for a microwave trapped ion quantum computer.

PubMed

Lekitsch, Bjoern; Weidt, Sebastian; Fowler, Austin G; Mølmer, Klaus; Devitt, Simon J; Wunderlich, Christof; Hensinger, Winfried K

2017-02-01

The availability of a universal quantum computer may have a fundamental impact on a vast number of research fields and on society as a whole. An increasingly large scientific and industrial community is working toward the realization of such a device. An arbitrarily large quantum computer may best be constructed using a modular approach. We present a blueprint for a trapped ion-based scalable quantum computer module, making it possible to create a scalable quantum computer architecture based on long-wavelength radiation quantum gates. The modules control all operations as stand-alone units, are constructed using silicon microfabrication techniques, and are within reach of current technology. To perform the required quantum computations, the modules make use of long-wavelength radiation-based quantum gate technology. To scale this microwave quantum computer architecture to a large size, we present a fully scalable design that makes use of ion transport between different modules, thereby allowing arbitrarily many modules to be connected to construct a large-scale device. A high error-threshold surface error correction code can be implemented in the proposed architecture to execute fault-tolerant operations. With appropriate adjustments, the proposed modules are also suitable for alternative trapped ion quantum computer architectures, such as schemes using photonic interconnects.

Computational Science in Armenia (Invited Talk)

NASA Astrophysics Data System (ADS)

Marandjian, H.; Shoukourian, Yu.

This survey is devoted to the development of informatics and computer science in Armenia. The results in theoretical computer science (algebraic models, solutions to systems of general form recursive equations, the methods of coding theory, pattern recognition and image processing), constitute the theoretical basis for developing problem-solving-oriented environments. As examples can be mentioned: a synthesizer of optimized distributed recursive programs, software tools for cluster-oriented implementations of two-dimensional cellular automata, a grid-aware web interface with advanced service trading for linear algebra calculations. In the direction of solving scientific problems that require high-performance computing resources, examples of completed projects include the field of physics (parallel computing of complex quantum systems), astrophysics (Armenian virtual laboratory), biology (molecular dynamics study of human red blood cell membrane), meteorology (implementing and evaluating the Weather Research and Forecast Model for the territory of Armenia). The overview also notes that the Institute for Informatics and Automation Problems of the National Academy of Sciences of Armenia has established a scientific and educational infrastructure, uniting computing clusters of scientific and educational institutions of the country and provides the scientific community with access to local and international computational resources, that is a strong support for computational science in Armenia.

Software for Brain Network Simulations: A Comparative Study

PubMed Central

Tikidji-Hamburyan, Ruben A.; Narayana, Vikram; Bozkus, Zeki; El-Ghazawi, Tarek A.

2017-01-01

Numerical simulations of brain networks are a critical part of our efforts in understanding brain functions under pathological and normal conditions. For several decades, the community has developed many software packages and simulators to accelerate research in computational neuroscience. In this article, we select the three most popular simulators, as determined by the number of models in the ModelDB database, such as NEURON, GENESIS, and BRIAN, and perform an independent evaluation of these simulators. In addition, we study NEST, one of the lead simulators of the Human Brain Project. First, we study them based on one of the most important characteristics, the range of supported models. Our investigation reveals that brain network simulators may be biased toward supporting a specific set of models. However, all simulators tend to expand the supported range of models by providing a universal environment for the computational study of individual neurons and brain networks. Next, our investigations on the characteristics of computational architecture and efficiency indicate that all simulators compile the most computationally intensive procedures into binary code, with the aim of maximizing their computational performance. However, not all simulators provide the simplest method for module development and/or guarantee efficient binary code. Third, a study of their amenability for high-performance computing reveals that NEST can almost transparently map an existing model on a cluster or multicore computer, while NEURON requires code modification if the model developed for a single computer has to be mapped on a computational cluster. Interestingly, parallelization is the weakest characteristic of BRIAN, which provides no support for cluster computations and limited support for multicore computers. Fourth, we identify the level of user support and frequency of usage for all simulators. Finally, we carry out an evaluation using two case studies: a large network with simplified neural and synaptic models and a small network with detailed models. These two case studies allow us to avoid any bias toward a particular software package. The results indicate that BRIAN provides the most concise language for both cases considered. Furthermore, as expected, NEST mostly favors large network models, while NEURON is better suited for detailed models. Overall, the case studies reinforce our general observation that simulators have a bias in the computational performance toward specific types of the brain network models. PMID:28775687

ISCR Annual Report: Fical Year 2004

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

McGraw, J R

2005-03-03

Large-scale scientific computation and all of the disciplines that support and help to validate it have been placed at the focus of Lawrence Livermore National Laboratory (LLNL) by the Advanced Simulation and Computing (ASC) program of the National Nuclear Security Administration (NNSA) and the Scientific Discovery through Advanced Computing (SciDAC) initiative of the Office of Science of the Department of Energy (DOE). The maturation of computational simulation as a tool of scientific and engineering research is underscored in the November 2004 statement of the Secretary of Energy that, ''high performance computing is the backbone of the nation's science and technologymore » enterprise''. LLNL operates several of the world's most powerful computers--including today's single most powerful--and has undertaken some of the largest and most compute-intensive simulations ever performed. Ultrascale simulation has been identified as one of the highest priorities in DOE's facilities planning for the next two decades. However, computers at architectural extremes are notoriously difficult to use efficiently. Furthermore, each successful terascale simulation only points out the need for much better ways of interacting with the resulting avalanche of data. Advances in scientific computing research have, therefore, never been more vital to LLNL's core missions than at present. Computational science is evolving so rapidly along every one of its research fronts that to remain on the leading edge, LLNL must engage researchers at many academic centers of excellence. In Fiscal Year 2004, the Institute for Scientific Computing Research (ISCR) served as one of LLNL's main bridges to the academic community with a program of collaborative subcontracts, visiting faculty, student internships, workshops, and an active seminar series. The ISCR identifies researchers from the academic community for computer science and computational science collaborations with LLNL and hosts them for short- and long-term visits with the aim of encouraging long-term academic research agendas that address LLNL's research priorities. Through such collaborations, ideas and software flow in both directions, and LLNL cultivates its future workforce. The Institute strives to be LLNL's ''eyes and ears'' in the computer and information sciences, keeping the Laboratory aware of and connected to important external advances. It also attempts to be the ''feet and hands'' that carry those advances into the Laboratory and incorporates them into practice. ISCR research participants are integrated into LLNL's Computing and Applied Research (CAR) Department, especially into its Center for Applied Scientific Computing (CASC). In turn, these organizations address computational challenges arising throughout the rest of the Laboratory. Administratively, the ISCR flourishes under LLNL's University Relations Program (URP). Together with the other five institutes of the URP, it navigates a course that allows LLNL to benefit from academic exchanges while preserving national security. While it is difficult to operate an academic-like research enterprise within the context of a national security laboratory, the results declare the challenges well met and worth the continued effort.« less

The HEPCloud Facility: elastic computing for High Energy Physics – The NOvA Use Case

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

Fuess, S.; Garzoglio, G.; Holzman, B.

The need for computing in the HEP community follows cycles of peaks and valleys mainly driven by conference dates, accelerator shutdown, holiday schedules, and other factors. Because of this, the classical method of provisioning these resources at providing facilities has drawbacks such as potential overprovisioning. As the appetite for computing increases, however, so does the need to maximize cost efficiency by developing a model for dynamically provisioning resources only when needed. To address this issue, the HEPCloud project was launched by the Fermilab Scientific Computing Division in June 2015. Its goal is to develop a facility that provides a commonmore » interface to a variety of resources, including local clusters, grids, high performance computers, and community and commercial Clouds. Initially targeted experiments include CMS and NOvA, as well as other Fermilab stakeholders. In its first phase, the project has demonstrated the use of the “elastic” provisioning model offered by commercial clouds, such as Amazon Web Services. In this model, resources are rented and provisioned automatically over the Internet upon request. In January 2016, the project demonstrated the ability to increase the total amount of global CMS resources by 58,000 cores from 150,000 cores - a 25 percent increase - in preparation for the Recontres de Moriond. In March 2016, the NOvA experiment has also demonstrated resource burst capabilities with an additional 7,300 cores, achieving a scale almost four times as large as the local allocated resources and utilizing the local AWS s3 storage to optimize data handling operations and costs. NOvA was using the same familiar services used for local computations, such as data handling and job submission, in preparation for the Neutrino 2016 conference. In both cases, the cost was contained by the use of the Amazon Spot Instance Market and the Decision Engine, a HEPCloud component that aims at minimizing cost and job interruption. This paper describes the Fermilab HEPCloud Facility and the challenges overcome for the CMS and NOvA communities.« less

CyVerse Data Commons: lessons learned in cyberinfrastructure management and data hosting from the Life Sciences

NASA Astrophysics Data System (ADS)

Swetnam, T. L.; Walls, R.; Merchant, N.

2017-12-01

CyVerse, is a US National Science Foundation funded initiative "to design, deploy, and expand a national cyberinfrastructure for life sciences research, and to train scientists in its use," supporting and enabling cross disciplinary collaborations across institutions. CyVerse' free, open-source, cyberinfrastructure is being adopted into biogeoscience and space sciences research. CyVerse data-science agnostic platforms provide shared data storage, high performance computing, and cloud computing that allow analysis of very large data sets (including incomplete or work-in-progress data sets). Part of CyVerse success has been in addressing the handling of data through its entire lifecycle, from creation to final publication in a digital data repository to reuse in new analyses. CyVerse developers and user communities have learned many lessons that are germane to Earth and Environmental Science. We present an overview of the tools and services available through CyVerse including: interactive computing with the Discovery Environment (https://de.cyverse.org/), an interactive data science workbench featuring data storage and transfer via the Data Store; cloud computing with Atmosphere (https://atmo.cyverse.org); and access to HPC via Agave API (https://agaveapi.co/). Each CyVerse service emphasizes access to long term data storage, including our own Data Commons (http://datacommons.cyverse.org), as well as external repositories. The Data Commons service manages, organizes, preserves, publishes, allows for discovery and reuse of data. All data published to CyVerse's Curated Data receive a permanent identifier (PID) in the form of a DOI (Digital Object Identifier) or ARK (Archival Resource Key). Data that is more fluid can also be published in the Data commons through Community Collaborated data. The Data Commons provides landing pages, permanent DOIs or ARKs, and supports data reuse and citation through features such as open data licenses and downloadable citations. The ability to access and do computing on data within the CyVerse framework or with external compute resources when necessary, has proven highly beneficial to our user community, which has continuously grown since the inception of CyVerse nine years ago.

A Community-acquired Lung Abscess Attributable to Streptococcus pneumoniae which Extended Directly into the Chest Wall

PubMed Central

Ko, Yuki; Tobino, Kazunori; Yasuda, Yuichiro; Sueyasu, Takuto; Nishizawa, Saori; Yoshimine, Kouhei; Munechika, Miyuki; Asaji, Mina; Yamaji, Yoshikazu; Tsuruno, Kosuke; Miyajima, Hiroyuki; Mukasa, Yosuke; Ebi, Noriyuki

2017-01-01

We herein report the case of 75-year-old Japanese female with a community-acquired lung abscess attributable to Streptococcus pneumoniae (S. penumoniae) which extended into the chest wall. The patient was admitted to our hospital with a painful mass on the left anterior chest wall. A contrast-enhanced chest computed tomography scan showed a lung abscess in the left upper lobe which extended into the chest wall. Surgical debridement of the chest wall abscess and percutaneous transthoracic tube drainage of the lung abscess were performed. A culture of the drainage specimen yielded S. pneumoniae. The patient showed a remarkable improvement after the initiation of intravenous antibiotic therapy. PMID:28049987

A Community-acquired Lung Abscess Attributable to Streptococcus pneumoniae which Extended Directly into the Chest Wall.

PubMed

Ko, Yuki; Tobino, Kazunori; Yasuda, Yuichiro; Sueyasu, Takuto; Nishizawa, Saori; Yoshimine, Kouhei; Munechika, Miyuki; Asaji, Mina; Yamaji, Yoshikazu; Tsuruno, Kosuke; Miyajima, Hiroyuki; Mukasa, Yosuke; Ebi, Noriyuki

We herein report the case of 75-year-old Japanese female with a community-acquired lung abscess attributable to Streptococcus pneumoniae (S. penumoniae) which extended into the chest wall. The patient was admitted to our hospital with a painful mass on the left anterior chest wall. A contrast-enhanced chest computed tomography scan showed a lung abscess in the left upper lobe which extended into the chest wall. Surgical debridement of the chest wall abscess and percutaneous transthoracic tube drainage of the lung abscess were performed. A culture of the drainage specimen yielded S. pneumoniae. The patient showed a remarkable improvement after the initiation of intravenous antibiotic therapy.

An Analysis of Community Health Nurses Documentation: The Best Approach to Computerization

PubMed Central

Chalmers, M.

1988-01-01

The study explored and analyzed the actual patient-related documentation performed by a sample of community health nurses working in voluntary home health agencies. The outcome of the study was a system flow chart of that documentation and included: common components of the documentation, where in the existing systems they are recorded, when they are recorded by the nurse and why they are used by the nurses and administrative personnel in the agencies. The flow chart is suitable for use as a prototype for the development of a computer software package for the computerization of the patient-related documentation by community health nurses. General System and communication theories were used as a framework for this study. A thorough analysis of the documenation resulted in a complete and exhaustive explication of the documentation by community health nurses, as well as the identification of what parts of that documentation lend themselves most readily to computerization and what areas, if any, may not readily adapt to computerization.

Development of the ARISTOTLE webware for cloud-based rarefied gas flow modeling

NASA Astrophysics Data System (ADS)

Deschenes, Timothy R.; Grot, Jonathan; Cline, Jason A.

2016-11-01

Rarefied gas dynamics are important for a wide variety of applications. An improvement in the ability of general users to predict these gas flows will enable optimization of current, and discovery of future processes. Despite this potential, most rarefied simulation software is designed by and for experts in the community. This has resulted in low adoption of the methods outside of the immediate RGD community. This paper outlines an ongoing effort to create a rarefied gas dynamics simulation tool that can be used by a general audience. The tool leverages a direct simulation Monte Carlo (DSMC) library that is available to the entire community and a web-based simulation process that will enable all users to take advantage of high performance computing capabilities. First, the DSMC library and simulation architecture are described. Then the DSMC library is used to predict a number of representative transient gas flows that are applicable to the rarefied gas dynamics community. The paper closes with a summary and future direction.

Using Adaptive Mesh Refinment to Simulate Storm Surge

NASA Astrophysics Data System (ADS)

Mandli, K. T.; Dawson, C.

2012-12-01

Coastal hazards related to strong storms such as hurricanes and typhoons are one of the most frequently recurring and wide spread hazards to coastal communities. Storm surges are among the most devastating effects of these storms, and their prediction and mitigation through numerical simulations is of great interest to coastal communities that need to plan for the subsequent rise in sea level during these storms. Unfortunately these simulations require a large amount of resolution in regions of interest to capture relevant effects resulting in a computational cost that may be intractable. This problem is exacerbated in situations where a large number of similar runs is needed such as in design of infrastructure or forecasting with ensembles of probable storms. One solution to address the problem of computational cost is to employ adaptive mesh refinement (AMR) algorithms. AMR functions by decomposing the computational domain into regions which may vary in resolution as time proceeds. Decomposing the domain as the flow evolves makes this class of methods effective at ensuring that computational effort is spent only where it is needed. AMR also allows for placement of computational resolution independent of user interaction and expectation of the dynamics of the flow as well as particular regions of interest such as harbors. The simulation of many different applications have only been made possible by using AMR-type algorithms, which have allowed otherwise impractical simulations to be performed for much less computational expense. Our work involves studying how storm surge simulations can be improved with AMR algorithms. We have implemented relevant storm surge physics in the GeoClaw package and tested how Hurricane Ike's surge into Galveston Bay and up the Houston Ship Channel compares to available tide gauge data. We will also discuss issues dealing with refinement criteria, optimal resolution and refinement ratios, and inundation.

Bionimbus: a cloud for managing, analyzing and sharing large genomics datasets.

PubMed

Heath, Allison P; Greenway, Matthew; Powell, Raymond; Spring, Jonathan; Suarez, Rafael; Hanley, David; Bandlamudi, Chai; McNerney, Megan E; White, Kevin P; Grossman, Robert L

2014-01-01

As large genomics and phenotypic datasets are becoming more common, it is increasingly difficult for most researchers to access, manage, and analyze them. One possible approach is to provide the research community with several petabyte-scale cloud-based computing platforms containing these data, along with tools and resources to analyze it. Bionimbus is an open source cloud-computing platform that is based primarily upon OpenStack, which manages on-demand virtual machines that provide the required computational resources, and GlusterFS, which is a high-performance clustered file system. Bionimbus also includes Tukey, which is a portal, and associated middleware that provides a single entry point and a single sign on for the various Bionimbus resources; and Yates, which automates the installation, configuration, and maintenance of the software infrastructure required. Bionimbus is used by a variety of projects to process genomics and phenotypic data. For example, it is used by an acute myeloid leukemia resequencing project at the University of Chicago. The project requires several computational pipelines, including pipelines for quality control, alignment, variant calling, and annotation. For each sample, the alignment step requires eight CPUs for about 12 h. BAM file sizes ranged from 5 GB to 10 GB for each sample. Most members of the research community have difficulty downloading large genomics datasets and obtaining sufficient storage and computer resources to manage and analyze the data. Cloud computing platforms, such as Bionimbus, with data commons that contain large genomics datasets, are one choice for broadening access to research data in genomics. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Youpi: YOUr processing PIpeline

NASA Astrophysics Data System (ADS)

Monnerville, Mathias; Sémah, Gregory

2012-03-01

Youpi is a portable, easy to use web application providing high level functionalities to perform data reduction on scientific FITS images. Built on top of various open source reduction tools released to the community by TERAPIX (http://terapix.iap.fr), Youpi can help organize data, manage processing jobs on a computer cluster in real time (using Condor) and facilitate teamwork by allowing fine-grain sharing of results and data. Youpi is modular and comes with plugins which perform, from within a browser, various processing tasks such as evaluating the quality of incoming images (using the QualityFITS software package), computing astrometric and photometric solutions (using SCAMP), resampling and co-adding FITS images (using SWarp) and extracting sources and building source catalogues from astronomical images (using SExtractor). Youpi is useful for small to medium-sized data reduction projects; it is free and is published under the GNU General Public License.

Social significance of community structure: Statistical view

NASA Astrophysics Data System (ADS)

Li, Hui-Jia; Daniels, Jasmine J.

2015-01-01

Community structure analysis is a powerful tool for social networks that can simplify their topological and functional analysis considerably. However, since community detection methods have random factors and real social networks obtained from complex systems always contain error edges, evaluating the significance of a partitioned community structure is an urgent and important question. In this paper, integrating the specific characteristics of real society, we present a framework to analyze the significance of a social community. The dynamics of social interactions are modeled by identifying social leaders and corresponding hierarchical structures. Instead of a direct comparison with the average outcome of a random model, we compute the similarity of a given node with the leader by the number of common neighbors. To determine the membership vector, an efficient community detection algorithm is proposed based on the position of the nodes and their corresponding leaders. Then, using a log-likelihood score, the tightness of the community can be derived. Based on the distribution of community tightness, we establish a connection between p -value theory and network analysis, and then we obtain a significance measure of statistical form . Finally, the framework is applied to both benchmark networks and real social networks. Experimental results show that our work can be used in many fields, such as determining the optimal number of communities, analyzing the social significance of a given community, comparing the performance among various algorithms, etc.

Commnity Petascale Project for Accelerator Science And Simulation: Advancing Computational Science for Future Accelerators And Accelerator Technologies

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

Spentzouris, Panagiotis; /Fermilab; Cary, John

The design and performance optimization of particle accelerators are essential for the success of the DOE scientific program in the next decade. Particle accelerators are very complex systems whose accurate description involves a large number of degrees of freedom and requires the inclusion of many physics processes. Building on the success of the SciDAC-1 Accelerator Science and Technology project, the SciDAC-2 Community Petascale Project for Accelerator Science and Simulation (ComPASS) is developing a comprehensive set of interoperable components for beam dynamics, electromagnetics, electron cooling, and laser/plasma acceleration modelling. ComPASS is providing accelerator scientists the tools required to enable the necessarymore » accelerator simulation paradigm shift from high-fidelity single physics process modeling (covered under SciDAC1) to high-fidelity multiphysics modeling. Our computational frameworks have been used to model the behavior of a large number of accelerators and accelerator R&D experiments, assisting both their design and performance optimization. As parallel computational applications, the ComPASS codes have been shown to make effective use of thousands of processors.« less

SNAVA-A real-time multi-FPGA multi-model spiking neural network simulation architecture.

PubMed

Sripad, Athul; Sanchez, Giovanny; Zapata, Mireya; Pirrone, Vito; Dorta, Taho; Cambria, Salvatore; Marti, Albert; Krishnamourthy, Karthikeyan; Madrenas, Jordi

2018-01-01

Spiking Neural Networks (SNN) for Versatile Applications (SNAVA) simulation platform is a scalable and programmable parallel architecture that supports real-time, large-scale, multi-model SNN computation. This parallel architecture is implemented in modern Field-Programmable Gate Arrays (FPGAs) devices to provide high performance execution and flexibility to support large-scale SNN models. Flexibility is defined in terms of programmability, which allows easy synapse and neuron implementation. This has been achieved by using a special-purpose Processing Elements (PEs) for computing SNNs, and analyzing and customizing the instruction set according to the processing needs to achieve maximum performance with minimum resources. The parallel architecture is interfaced with customized Graphical User Interfaces (GUIs) to configure the SNN's connectivity, to compile the neuron-synapse model and to monitor SNN's activity. Our contribution intends to provide a tool that allows to prototype SNNs faster than on CPU/GPU architectures but significantly cheaper than fabricating a customized neuromorphic chip. This could be potentially valuable to the computational neuroscience and neuromorphic engineering communities. Copyright © 2017 Elsevier Ltd. All rights reserved.

LUNGx Challenge for computerized lung nodule classification

DOE PAGES

Armato, Samuel G.; Drukker, Karen; Li, Feng; ...

2016-12-19

The purpose of this work is to describe the LUNGx Challenge for the computerized classification of lung nodules on diagnostic computed tomography (CT) scans as benign or malignant and report the performance of participants’ computerized methods along with that of six radiologists who participated in an observer study performing the same Challenge task on the same dataset. The Challenge provided sets of calibration and testing scans, established a performance assessment process, and created an infrastructure for case dissemination and result submission. We present ten groups that applied their own methods to 73 lung nodules (37 benign and 36 malignant) thatmore » were selected to achieve approximate size matching between the two cohorts. Area under the receiver operating characteristic curve (AUC) values for these methods ranged from 0.50 to 0.68; only three methods performed statistically better than random guessing. The radiologists’ AUC values ranged from 0.70 to 0.85; three radiologists performed statistically better than the best-performing computer method. The LUNGx Challenge compared the performance of computerized methods in the task of differentiating benign from malignant lung nodules on CT scans, placed in the context of the performance of radiologists on the same task. Lastly, the continued public availability of the Challenge cases will provide a valuable resource for the medical imaging research community.« less

LUNGx Challenge for computerized lung nodule classification

PubMed Central

Armato, Samuel G.; Drukker, Karen; Li, Feng; Hadjiiski, Lubomir; Tourassi, Georgia D.; Engelmann, Roger M.; Giger, Maryellen L.; Redmond, George; Farahani, Keyvan; Kirby, Justin S.; Clarke, Laurence P.

2016-01-01

Abstract. The purpose of this work is to describe the LUNGx Challenge for the computerized classification of lung nodules on diagnostic computed tomography (CT) scans as benign or malignant and report the performance of participants’ computerized methods along with that of six radiologists who participated in an observer study performing the same Challenge task on the same dataset. The Challenge provided sets of calibration and testing scans, established a performance assessment process, and created an infrastructure for case dissemination and result submission. Ten groups applied their own methods to 73 lung nodules (37 benign and 36 malignant) that were selected to achieve approximate size matching between the two cohorts. Area under the receiver operating characteristic curve (AUC) values for these methods ranged from 0.50 to 0.68; only three methods performed statistically better than random guessing. The radiologists’ AUC values ranged from 0.70 to 0.85; three radiologists performed statistically better than the best-performing computer method. The LUNGx Challenge compared the performance of computerized methods in the task of differentiating benign from malignant lung nodules on CT scans, placed in the context of the performance of radiologists on the same task. The continued public availability of the Challenge cases will provide a valuable resource for the medical imaging research community. PMID:28018939

LUNGx Challenge for computerized lung nodule classification

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

Armato, Samuel G.; Drukker, Karen; Li, Feng

The purpose of this work is to describe the LUNGx Challenge for the computerized classification of lung nodules on diagnostic computed tomography (CT) scans as benign or malignant and report the performance of participants’ computerized methods along with that of six radiologists who participated in an observer study performing the same Challenge task on the same dataset. The Challenge provided sets of calibration and testing scans, established a performance assessment process, and created an infrastructure for case dissemination and result submission. We present ten groups that applied their own methods to 73 lung nodules (37 benign and 36 malignant) thatmore » were selected to achieve approximate size matching between the two cohorts. Area under the receiver operating characteristic curve (AUC) values for these methods ranged from 0.50 to 0.68; only three methods performed statistically better than random guessing. The radiologists’ AUC values ranged from 0.70 to 0.85; three radiologists performed statistically better than the best-performing computer method. The LUNGx Challenge compared the performance of computerized methods in the task of differentiating benign from malignant lung nodules on CT scans, placed in the context of the performance of radiologists on the same task. Lastly, the continued public availability of the Challenge cases will provide a valuable resource for the medical imaging research community.« less

Information system needs in health promotion: a case study of the Safe Community programme using requirements engineering methods.

PubMed

Timpka, Toomas; Olvander, Christina; Hallberg, Niklas

2008-09-01

The international Safe Community programme was used as the setting for a case study to explore the need for information system support in health promotion programmes. The 14 Safe Communities active in Sweden during 2002 were invited to participate and 13 accepted. A questionnaire on computer usage and a critical incident technique instrument were distributed. Sharing of management information, creating social capital for safety promotion, and injury data recording were found to be key areas that need to be further supported by computer-based information systems. Most respondents reported having access to a personal computer workstation with standard office software. Interest in using more advanced computer applications was low, and there was considerable need for technical user support. Areas where information systems can be used to make health promotion practice more efficient were identified, and patterns of computers usage were described.

Web Services Provide Access to SCEC Scientific Research Application Software

NASA Astrophysics Data System (ADS)

Gupta, N.; Gupta, V.; Okaya, D.; Kamb, L.; Maechling, P.

2003-12-01

Web services offer scientific communities a new paradigm for sharing research codes and communicating results. While there are formal technical definitions of what constitutes a web service, for a user community such as the Southern California Earthquake Center (SCEC), we may conceptually consider a web service to be functionality provided on-demand by an application which is run on a remote computer located elsewhere on the Internet. The value of a web service is that it can (1) run a scientific code without the user needing to install and learn the intricacies of running the code; (2) provide the technical framework which allows a user's computer to talk to the remote computer which performs the service; (3) provide the computational resources to run the code; and (4) bundle several analysis steps and provide the end results in digital or (post-processed) graphical form. Within an NSF-sponsored ITR project coordinated by SCEC, we are constructing web services using architectural protocols and programming languages (e.g., Java). However, because the SCEC community has a rich pool of scientific research software (written in traditional languages such as C and FORTRAN), we also emphasize making existing scientific codes available by constructing web service frameworks which wrap around and directly run these codes. In doing so we attempt to broaden community usage of these codes. Web service wrapping of a scientific code can be done using a "web servlet" construction or by using a SOAP/WSDL-based framework. This latter approach is widely adopted in IT circles although it is subject to rapid evolution. Our wrapping framework attempts to "honor" the original codes with as little modification as is possible. For versatility we identify three methods of user access: (A) a web-based GUI (written in HTML and/or Java applets); (B) a Linux/OSX/UNIX command line "initiator" utility (shell-scriptable); and (C) direct access from within any Java application (and with the correct API interface from within C++ and/or C/Fortran). This poster presentation will provide descriptions of the following selected web services and their origin as scientific application codes: 3D community velocity models for Southern California, geocoordinate conversions (latitude/longitude to UTM), execution of GMT graphical scripts, data format conversions (Gocad to Matlab format), and implementation of Seismic Hazard Analysis application programs that calculate hazard curve and hazard map data sets.

e-Infrastructures for Astronomy: An Integrated View

NASA Astrophysics Data System (ADS)

Pasian, F.; Longo, G.

2010-12-01

As for other disciplines, the capability of performing “Big Science” in astrophysics requires the availability of large facilities. In the field of ICT, computational resources (e.g. HPC) are important, but are far from being enough for the community: as a matter of fact, the whole set of e-infrastructures (network, computing nodes, data repositories, applications) need to work in an interoperable way. This implies the development of common (or at least compatible) user interfaces to computing resources, transparent access to observations and numerical simulations through the Virtual Observatory, integrated data processing pipelines, data mining and semantic web applications. Achieving this interoperability goal is a must to build a real “Knowledge Infrastructure” in the astrophysical domain. Also, the emergence of new professional profiles (e.g. the “astro-informatician”) is necessary to allow defining and implementing properly this conceptual schema.

Multiple-Swarm Ensembles: Improving the Predictive Power and Robustness of Predictive Models and Its Use in Computational Biology.

PubMed

Alves, Pedro; Liu, Shuang; Wang, Daifeng; Gerstein, Mark

2018-01-01

Machine learning is an integral part of computational biology, and has already shown its use in various applications, such as prognostic tests. In the last few years in the non-biological machine learning community, ensembling techniques have shown their power in data mining competitions such as the Netflix challenge; however, such methods have not found wide use in computational biology. In this work, we endeavor to show how ensembling techniques can be applied to practical problems, including problems in the field of bioinformatics, and how they often outperform other machine learning techniques in both predictive power and robustness. Furthermore, we develop a methodology of ensembling, Multi-Swarm Ensemble (MSWE) by using multiple particle swarm optimizations and demonstrate its ability to further enhance the performance of ensembles.

A Component-based Programming Model for Composite, Distributed Applications

NASA Technical Reports Server (NTRS)

Eidson, Thomas M.; Bushnell, Dennis M. (Technical Monitor)

2001-01-01

The nature of scientific programming is evolving to larger, composite applications that are composed of smaller element applications. These composite applications are more frequently being targeted for distributed, heterogeneous networks of computers. They are most likely programmed by a group of developers. Software component technology and computational frameworks are being proposed and developed to meet the programming requirements of these new applications. Historically, programming systems have had a hard time being accepted by the scientific programming community. In this paper, a programming model is outlined that attempts to organize the software component concepts and fundamental programming entities into programming abstractions that will be better understood by the application developers. The programming model is designed to support computational frameworks that manage many of the tedious programming details, but also that allow sufficient programmer control to design an accurate, high-performance application.

The Gain of Resource Delegation in Distributed Computing Environments

NASA Astrophysics Data System (ADS)

Fölling, Alexander; Grimme, Christian; Lepping, Joachim; Papaspyrou, Alexander

In this paper, we address job scheduling in Distributed Computing Infrastructures, that is a loosely coupled network of autonomous acting High Performance Computing systems. In contrast to the common approach of mutual workload exchange, we consider the more intuitive operator's viewpoint of load-dependent resource reconfiguration. In case of a site's over-utilization, the scheduling system is able to lease resources from other sites to keep up service quality for its local user community. Contrary, the granting of idle resources can increase utilization in times of low local workload and thus ensure higher efficiency. The evaluation considers real workload data and is done with respect to common service quality indicators. For two simple resource exchange policies and three basic setups we show the possible gain of this approach and analyze the dynamics in workload-adaptive reconfiguration behavior.

Forecasting techno-social systems: how physics and computing help to fight off global pandemics

NASA Astrophysics Data System (ADS)

Vespignani, Alessandro

2010-03-01

The crucial issue when planning for adequate public health interventions to mitigate the spread and impact of epidemics is risk evaluation and forecast. This amount to the anticipation of where, when and how strong the epidemic will strike. In the last decade advances in performance in computer technology, data acquisition, statistical physics and complex networks theory allow the generation of sophisticated simulations on supercomputer infrastructures to anticipate the spreading pattern of a pandemic. For the first time we are in the position of generating real time forecast of epidemic spreading. I will review the history of the current H1N1 pandemic, the major road-blocks the community has faced in its containment and mitigation and how physics and computing provide predictive tools that help us to battle epidemics.

A large-scale evaluation of computational protein function prediction

PubMed Central

Radivojac, Predrag; Clark, Wyatt T; Ronnen Oron, Tal; Schnoes, Alexandra M; Wittkop, Tobias; Sokolov, Artem; Graim, Kiley; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa; Pandey, Gaurav; Yunes, Jeffrey M; Talwalkar, Ameet S; Repo, Susanna; Souza, Michael L; Piovesan, Damiano; Casadio, Rita; Wang, Zheng; Cheng, Jianlin; Fang, Hai; Gough, Julian; Koskinen, Patrik; Törönen, Petri; Nokso-Koivisto, Jussi; Holm, Liisa; Cozzetto, Domenico; Buchan, Daniel W A; Bryson, Kevin; Jones, David T; Limaye, Bhakti; Inamdar, Harshal; Datta, Avik; Manjari, Sunitha K; Joshi, Rajendra; Chitale, Meghana; Kihara, Daisuke; Lisewski, Andreas M; Erdin, Serkan; Venner, Eric; Lichtarge, Olivier; Rentzsch, Robert; Yang, Haixuan; Romero, Alfonso E; Bhat, Prajwal; Paccanaro, Alberto; Hamp, Tobias; Kassner, Rebecca; Seemayer, Stefan; Vicedo, Esmeralda; Schaefer, Christian; Achten, Dominik; Auer, Florian; Böhm, Ariane; Braun, Tatjana; Hecht, Maximilian; Heron, Mark; Hönigschmid, Peter; Hopf, Thomas; Kaufmann, Stefanie; Kiening, Michael; Krompass, Denis; Landerer, Cedric; Mahlich, Yannick; Roos, Manfred; Björne, Jari; Salakoski, Tapio; Wong, Andrew; Shatkay, Hagit; Gatzmann, Fanny; Sommer, Ingolf; Wass, Mark N; Sternberg, Michael J E; Škunca, Nives; Supek, Fran; Bošnjak, Matko; Panov, Panče; Džeroski, Sašo; Šmuc, Tomislav; Kourmpetis, Yiannis A I; van Dijk, Aalt D J; ter Braak, Cajo J F; Zhou, Yuanpeng; Gong, Qingtian; Dong, Xinran; Tian, Weidong; Falda, Marco; Fontana, Paolo; Lavezzo, Enrico; Di Camillo, Barbara; Toppo, Stefano; Lan, Liang; Djuric, Nemanja; Guo, Yuhong; Vucetic, Slobodan; Bairoch, Amos; Linial, Michal; Babbitt, Patricia C; Brenner, Steven E; Orengo, Christine; Rost, Burkhard; Mooney, Sean D; Friedberg, Iddo

2013-01-01

Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based Critical Assessment of protein Function Annotation (CAFA) experiment. Fifty-four methods representing the state-of-the-art for protein function prediction were evaluated on a target set of 866 proteins from eleven organisms. Two findings stand out: (i) today’s best protein function prediction algorithms significantly outperformed widely-used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is significant need for improvement of currently available tools. PMID:23353650

Real-time seismic monitoring and functionality assessment of a building

USGS Publications Warehouse

Celebi, M.; ,

2005-01-01

This paper presents recent developments and approaches (using GPS technology and real-time double-integration) to obtain displacements and, in turn, drift ratios, in real-time or near real-time to meet the needs of the engineering and user community in seismic monitoring and assessing the functionality and damage condition of structures. Drift ratios computed in near real-time allow technical assessment of the damage condition of a building. Relevant parameters, such as the type of connections and story structural characteristics (including geometry) are used in computing drifts corresponding to several pre-selected threshold stages of damage. Thus, drift ratios determined from real-time monitoring can be compared to pre-computed threshold drift ratios. The approaches described herein can be used for performance evaluation of structures and can be considered as building health-monitoring applications.

Recent advances to obtain real - Time displacements for engineering applications

USGS Publications Warehouse

Celebi, M.

2005-01-01

This paper presents recent developments and approaches (using GPS technology and real-time double-integration) to obtain displacements and, in turn, drift ratios, in real-time or near real-time to meet the needs of the engineering and user community in seismic monitoring and assessing the functionality and damage condition of structures. Drift ratios computed in near real-time allow technical assessment of the damage condition of a building. Relevant parameters, such as the type of connections and story structural characteristics (including geometry) are used in computing drifts corresponding to several pre-selected threshold stages of damage. Thus, drift ratios determined from real-time monitoring can be compared to pre-computed threshold drift ratios. The approaches described herein can be used for performance evaluation of structures and can be considered as building health-monitoring applications.

The International Symposium on Grids and Clouds

NASA Astrophysics Data System (ADS)

The International Symposium on Grids and Clouds (ISGC) 2012 will be held at Academia Sinica in Taipei from 26 February to 2 March 2012, with co-located events and workshops. The conference is hosted by the Academia Sinica Grid Computing Centre (ASGC). 2012 is the decennium anniversary of the ISGC which over the last decade has tracked the convergence, collaboration and innovation of individual researchers across the Asia Pacific region to a coherent community. With the continuous support and dedication from the delegates, ISGC has provided the primary international distributed computing platform where distinguished researchers and collaboration partners from around the world share their knowledge and experiences. The last decade has seen the wide-scale emergence of e-Infrastructure as a critical asset for the modern e-Scientist. The emergence of large-scale research infrastructures and instruments that has produced a torrent of electronic data is forcing a generational change in the scientific process and the mechanisms used to analyse the resulting data deluge. No longer can the processing of these vast amounts of data and production of relevant scientific results be undertaken by a single scientist. Virtual Research Communities that span organisations around the world, through an integrated digital infrastructure that connects the trust and administrative domains of multiple resource providers, have become critical in supporting these analyses. Topics covered in ISGC 2012 include: High Energy Physics, Biomedicine & Life Sciences, Earth Science, Environmental Changes and Natural Disaster Mitigation, Humanities & Social Sciences, Operations & Management, Middleware & Interoperability, Security and Networking, Infrastructure Clouds & Virtualisation, Business Models & Sustainability, Data Management, Distributed Volunteer & Desktop Grid Computing, High Throughput Computing, and High Performance, Manycore & GPU Computing.

ENES the European Network for Earth System modelling and its infrastructure projects IS-ENES

NASA Astrophysics Data System (ADS)

Guglielmo, Francesca; Joussaume, Sylvie; Parinet, Marie

2016-04-01

The scientific community working on climate modelling is organized within the European Network for Earth System modelling (ENES). In the past decade, several European university departments, research centres, meteorological services, computer centres, and industrial partners engaged in the creation of ENES with the purpose of working together and cooperating towards the further development of the network, by signing a Memorandum of Understanding. As of 2015, the consortium counts 47 partners. The climate modelling community, and thus ENES, faces challenges which are both science-driven, i.e. analysing of the full complexity of the Earth System to improve our understanding and prediction of climate changes, and have multi-faceted societal implications, as a better representation of climate change on regional scales leads to improved understanding and prediction of impacts and to the development and provision of climate services. ENES, promoting and endorsing projects and initiatives, helps in developing and evaluating of state-of-the-art climate and Earth system models, facilitates model inter-comparison studies, encourages exchanges of software and model results, and fosters the use of high performance computing facilities dedicated to high-resolution multi-model experiments. ENES brings together public and private partners, integrates countries underrepresented in climate modelling studies, and reaches out to different user communities, thus enhancing European expertise and competitiveness. In this need of sophisticated models, world-class, high-performance computers, and state-of-the-art software solutions to make efficient use of models, data and hardware, a key role is played by the constitution and maintenance of a solid infrastructure, developing and providing services to the different user communities. ENES has investigated the infrastructural needs and has received funding from the EU FP7 program for the IS-ENES (InfraStructure for ENES) phase I and II projects. We present here the case study of an existing network of institutions brought together toward common goals by a non-binding agreement, ENES, and of its two IS-ENES projects. These latter will be discussed in their double role as a means to provide and/or maintain the actual infrastructure (hardware, software, skilled human resources, services) to achieve ENES scientific goals -fulfilling the aims set in a strategy document-, but also to inform and provide to the network a structured way of working and of interacting with the extended community. The genesis and evolution of the network and the interaction network/projects will also be analysed in terms of long-term sustainability.

Tuning In: Challenging Design for Communities through a Field Study of Radio Amateurs

NASA Astrophysics Data System (ADS)

Bogdan, Cristian; Bowers, John

As illustrated by the emerging field of Communities and Technologies, the topic of community, whether further qualified by ‘virtual' (Rheingold 1993), ‘on line' or ‘networked' (Schuler 1996), has become a major focus for field study, design, technical infrastructural provision, as well as social, psychological and economic theorising. Let us review some early examples of this ‘turn to community'. (1999) discuss the ‘network communities of SeniorNet', an organisation that supports people over the age of 50 in the use of computer networking technologies. The SeniorNet study highlights the complex ‘collage' of participation and interaction styles that community members sustain, many of which go beyond conventional understandings of older people, their practices and relations to technology. While the members of SeniorNet are geographically dispersed, (1996) describe the ‘Blacksburg Electronic Village', a local community computing initiative centred around Blacksburg, Virginia, USA. As long ago as 1994, (1994) claimed the existence of over 100 such projects in the US with very diverse aims and experiences but all concerned to be responsive to a community's needs while exploiting the Internet and the technical developments it has made possible. For their part, (2001) offer some generic infrastructural tools for community computing, including support for ‘identity management'.

Developing Models for Predictive Climate Science

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

Drake, John B; Jones, Philip W

2007-01-01

The Community Climate System Model results from a multi-agency collaboration designed to construct cutting-edge climate science simulation models for a broad research community. Predictive climate simulations are currently being prepared for the petascale computers of the near future. Modeling capabilities are continuously being improved in order to provide better answers to critical questions about Earth's climate. Climate change and its implications are front page news in today's world. Could global warming be responsible for the July 2006 heat waves in Europe and the United States? Should more resources be devoted to preparing for an increase in the frequency of strongmore » tropical storms and hurricanes like Katrina? Will coastal cities be flooded due to a rise in sea level? The National Climatic Data Center (NCDC), which archives all weather data for the nation, reports that global surface temperatures have increased over the last century, and that the rate of increase is three times greater since 1976. Will temperatures continue to climb at this rate, will they decline again, or will the rate of increase become even steeper? To address such a flurry of questions, scientists must adopt a systematic approach and develop a predictive framework. With responsibility for advising on energy and technology strategies, the DOE is dedicated to advancing climate research in order to elucidate the causes of climate change, including the role of carbon loading from fossil fuel use. Thus, climate science--which by nature involves advanced computing technology and methods--has been the focus of a number of DOE's SciDAC research projects. Dr. John Drake (ORNL) and Dr. Philip Jones (LANL) served as principal investigators on the SciDAC project, 'Collaborative Design and Development of the Community Climate System Model for Terascale Computers.' The Community Climate System Model (CCSM) is a fully-coupled global system that provides state-of-the-art computer simulations of the Earth's past, present, and future climate states. The collaborative SciDAC team--including over a dozen researchers at institutions around the country--developed, validated, documented, and optimized the performance of CCSM using the latest software engineering approaches, computational technology, and scientific knowledge. Many of the factors that must be accounted for in a comprehensive model of the climate system are illustrated in figure 1.« less

Public Domain Microcomputer Software for Forestry.

ERIC Educational Resources Information Center

Martin, Les

A project was conducted to develop a computer forestry/forest products bibliography applicable to high school and community college vocational/technical programs. The project director contacted curriculum clearinghouses, computer companies, and high school and community college instructors in order to obtain listings of public domain programs for…

Recent Enhancements to the Community Multiscale Air Quality Modeling System (CMAQ)

EPA Science Inventory

EPA’s Office of Research and Development, Computational Exposure Division held a webinar on January 31, 2017 to present the recent scientific and computational updates made by EPA to the Community Multi-Scale Air Quality Model (CMAQ). Topics covered included: (1) Improveme...

The Power of Computer-aided Tomography to Investigate Marine Benthic Communities

EPA Science Inventory

Utilization of Computer-aided-Tomography (CT) technology is a powerful tool to investigate benthic communities in aquatic systems. In this presentation, we will attempt to summarize our 15 years of experience in developing specific CT methods and applications to marine benthic co...

Towards a precise test for malaria diagnosis in the Brazilian Amazon: comparison among field microscopy, a rapid diagnostic test, nested PCR, and a computational expert system based on artificial neural networks

PubMed Central

2010-01-01

Background Accurate malaria diagnosis is mandatory for the treatment and management of severe cases. Moreover, individuals with asymptomatic malaria are not usually screened by health care facilities, which further complicates disease control efforts. The present study compared the performances of a malaria rapid diagnosis test (RDT), the thick blood smear method and nested PCR for the diagnosis of symptomatic malaria in the Brazilian Amazon. In addition, an innovative computational approach was tested for the diagnosis of asymptomatic malaria. Methods The study was divided in two parts. For the first part, passive case detection was performed in 311 individuals with malaria-related symptoms from a recently urbanized community in the Brazilian Amazon. A cross-sectional investigation compared the diagnostic performance of the RDT Optimal-IT, nested PCR and light microscopy. The second part of the study involved active case detection of asymptomatic malaria in 380 individuals from riverine communities in Rondônia, Brazil. The performances of microscopy, nested PCR and an expert computational system based on artificial neural networks (MalDANN) using epidemiological data were compared. Results Nested PCR was shown to be the gold standard for diagnosis of both symptomatic and asymptomatic malaria because it detected the major number of cases and presented the maximum specificity. Surprisingly, the RDT was superior to microscopy in the diagnosis of cases with low parasitaemia. Nevertheless, RDT could not discriminate the Plasmodium species in 12 cases of mixed infections (Plasmodium vivax + Plasmodium falciparum). Moreover, the microscopy presented low performance in the detection of asymptomatic cases (61.25% of correct diagnoses). The MalDANN system using epidemiological data was worse that the light microscopy (56% of correct diagnoses). However, when information regarding plasma levels of interleukin-10 and interferon-gamma were inputted, the MalDANN performance sensibly increased (80% correct diagnoses). Conclusions An RDT for malaria diagnosis may find a promising use in the Brazilian Amazon integrating a rational diagnostic approach. Despite the low performance of the MalDANN test using solely epidemiological data, an approach based on neural networks may be feasible in cases where simpler methods for discriminating individuals below and above threshold cytokine levels are available. PMID:20459613

Towards a precise test for malaria diagnosis in the Brazilian Amazon: comparison among field microscopy, a rapid diagnostic test, nested PCR, and a computational expert system based on artificial neural networks.

PubMed

Andrade, Bruno B; Reis-Filho, Antonio; Barros, Austeclino M; Souza-Neto, Sebastião M; Nogueira, Lucas L; Fukutani, Kiyoshi F; Camargo, Erney P; Camargo, Luís M A; Barral, Aldina; Duarte, Angelo; Barral-Netto, Manoel

2010-05-06

Accurate malaria diagnosis is mandatory for the treatment and management of severe cases. Moreover, individuals with asymptomatic malaria are not usually screened by health care facilities, which further complicates disease control efforts. The present study compared the performances of a malaria rapid diagnosis test (RDT), the thick blood smear method and nested PCR for the diagnosis of symptomatic malaria in the Brazilian Amazon. In addition, an innovative computational approach was tested for the diagnosis of asymptomatic malaria. The study was divided in two parts. For the first part, passive case detection was performed in 311 individuals with malaria-related symptoms from a recently urbanized community in the Brazilian Amazon. A cross-sectional investigation compared the diagnostic performance of the RDT Optimal-IT, nested PCR and light microscopy. The second part of the study involved active case detection of asymptomatic malaria in 380 individuals from riverine communities in Rondônia, Brazil. The performances of microscopy, nested PCR and an expert computational system based on artificial neural networks (MalDANN) using epidemiological data were compared. Nested PCR was shown to be the gold standard for diagnosis of both symptomatic and asymptomatic malaria because it detected the major number of cases and presented the maximum specificity. Surprisingly, the RDT was superior to microscopy in the diagnosis of cases with low parasitaemia. Nevertheless, RDT could not discriminate the Plasmodium species in 12 cases of mixed infections (Plasmodium vivax + Plasmodium falciparum). Moreover, the microscopy presented low performance in the detection of asymptomatic cases (61.25% of correct diagnoses). The MalDANN system using epidemiological data was worse that the light microscopy (56% of correct diagnoses). However, when information regarding plasma levels of interleukin-10 and interferon-gamma were inputted, the MalDANN performance sensibly increased (80% correct diagnoses). An RDT for malaria diagnosis may find a promising use in the Brazilian Amazon integrating a rational diagnostic approach. Despite the low performance of the MalDANN test using solely epidemiological data, an approach based on neural networks may be feasible in cases where simpler methods for discriminating individuals below and above threshold cytokine levels are available.

NASA-OAI HPCCP K-12 Program

NASA Technical Reports Server (NTRS)

1994-01-01

The NASA-OAI High Performance Communication and Computing K- 12 School Partnership program has been completed. Cleveland School of the Arts, Empire Computech Center, Grafton Local Schools and the Bug O Nay Ge Shig School have all received network equipment and connections. Each school is working toward integrating computer and communications technology into their classroom curriculum. Cleveland School of the Arts students are creating computer software. Empire Computech Center is a magnet school for technology education at the elementary school level. Grafton Local schools is located in a rural community and is using communications technology to bring to their students some of the same benefits students from suburban and urban areas receive. The Bug O Nay Ge Shig School is located on an Indian Reservation in Cass Lake, MN. The students at this school are using the computer to help them with geological studies. A grant has been issued to the friends of the Nashville Library. Nashville is a small township in Holmes County, Ohio. A community organization has been formed to turn their library into a state of the art Media Center. Their goal is to have a place where rural students can learn about different career options and how to go about pursuing those careers. Taylor High School in Cincinnati, Ohio was added to the schools involved in the Wind Tunnel Project. A mini grant has been awarded to Taylor High School for computer equipment. The computer equipment is utilized in the school's geometry class to computationally design objects which will be tested for their aerodynamic properties in the Barberton Wind Tunnel. The students who create the models can view the test in the wind tunnel via desk top conferencing. Two teachers received stipends for helping with the Regional Summer Computer Workshop. Both teachers were brought in to teach a session within the workshop. They were selected to teach the session based on their expertise in particular software applications.

The roles of 'subjective computer training' and management support in the use of computers in community health centres.

PubMed

Yaghmaie, Farideh; Jayasuriya, Rohan

2004-01-01

There have been many changes made to information systems in the last decade. Changes in information systems require users constantly to update their computer knowledge and skills. Computer training is a critical issue for any user because it offers them considerable new skills. The purpose of this study was to measure the effects of 'subjective computer training' and management support on attitudes to computers, computer anxiety and subjective norms to use computers. The data were collected from community health centre staff. The results of the study showed that health staff trained in computer use had more favourable attitudes to computers, less computer anxiety and more awareness of others' expectations about computer use than untrained users. However, there was no relationship between management support and computer attitude, computer anxiety or subjective norms. Lack of computer training for the majority of healthcare staff confirmed the need for more attention to this issue, particularly in health centres.

Automated design of image operators that detect interest points.

PubMed

Trujillo, Leonardo; Olague, Gustavo

2008-01-01

This work describes how evolutionary computation can be used to synthesize low-level image operators that detect interesting points on digital images. Interest point detection is an essential part of many modern computer vision systems that solve tasks such as object recognition, stereo correspondence, and image indexing, to name but a few. The design of the specialized operators is posed as an optimization/search problem that is solved with genetic programming (GP), a strategy still mostly unexplored by the computer vision community. The proposed approach automatically synthesizes operators that are competitive with state-of-the-art designs, taking into account an operator's geometric stability and the global separability of detected points during fitness evaluation. The GP search space is defined using simple primitive operations that are commonly found in point detectors proposed by the vision community. The experiments described in this paper extend previous results (Trujillo and Olague, 2006a,b) by presenting 15 new operators that were synthesized through the GP-based search. Some of the synthesized operators can be regarded as improved manmade designs because they employ well-known image processing techniques and achieve highly competitive performance. On the other hand, since the GP search also generates what can be considered as unconventional operators for point detection, these results provide a new perspective to feature extraction research.

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.

WPS mediation: An approach to process geospatial data on different computing backends

NASA Astrophysics Data System (ADS)

Giuliani, Gregory; Nativi, Stefano; Lehmann, Anthony; Ray, Nicolas

2012-10-01

The OGC Web Processing Service (WPS) specification allows generating information by processing distributed geospatial data made available through Spatial Data Infrastructures (SDIs). However, current SDIs have limited analytical capacities and various problems emerge when trying to use them in data and computing-intensive domains such as environmental sciences. These problems are usually not or only partially solvable using single computing resources. Therefore, the Geographic Information (GI) community is trying to benefit from the superior storage and computing capabilities offered by distributed computing (e.g., Grids, Clouds) related methods and technologies. Currently, there is no commonly agreed approach to grid-enable WPS. No implementation allows one to seamlessly execute a geoprocessing calculation following user requirements on different computing backends, ranging from a stand-alone GIS server up to computer clusters and large Grid infrastructures. Considering this issue, this paper presents a proof of concept by mediating different geospatial and Grid software packages, and by proposing an extension of WPS specification through two optional parameters. The applicability of this approach will be demonstrated using a Normalized Difference Vegetation Index (NDVI) mediated WPS process, highlighting benefits, and issues that need to be further investigated to improve performances.

Energy. Application of solar energy in dwellings: A technical and economical analysis for the European community

NASA Astrophysics Data System (ADS)

1980-03-01

The technical possibilities and economical limitations of solar heating systems for the application in swimming pools, hot water preparation, space heating and air conditioning were investigated. This analysis was performed for dwellings with special consideration of the climatic differences in each community. The computer program, which was used for solar system calculations, and all mathematical models, for technical and economical analysis were elucidated. In the technical and economical analysis, the most suitable solar system sizes for each community was determined. Four types of solar collectors were investigated. The single glass selective collector proved to be the most cost effective collector in all the above applications, provided the the additional cost for the selective coating is not more than 20DM/cu. From the results of the analysis certain recommendations were derived, which can improve the rapid implementation of solar heating systems into the market.

Mining Consumer Health Vocabulary from Community-Generated Text

PubMed Central

Vydiswaran, V.G. Vinod; Mei, Qiaozhu; Hanauer, David A.; Zheng, Kai

2014-01-01

Community-generated text corpora can be a valuable resource to extract consumer health vocabulary (CHV) and link them to professional terminologies and alternative variants. In this research, we propose a pattern-based text-mining approach to identify pairs of CHV and professional terms from Wikipedia, a large text corpus created and maintained by the community. A novel measure, leveraging the ratio of frequency of occurrence, was used to differentiate consumer terms from professional terms. We empirically evaluated the applicability of this approach using a large data sample consisting of MedLine abstracts and all posts from an online health forum, MedHelp. The results show that the proposed approach is able to identify synonymous pairs and label the terms as either consumer or professional term with high accuracy. We conclude that the proposed approach provides great potential to produce a high quality CHV to improve the performance of computational applications in processing consumer-generated health text. PMID:25954426

Objective comparison of particle tracking methods

PubMed Central

Chenouard, Nicolas; Smal, Ihor; de Chaumont, Fabrice; Maška, Martin; Sbalzarini, Ivo F.; Gong, Yuanhao; Cardinale, Janick; Carthel, Craig; Coraluppi, Stefano; Winter, Mark; Cohen, Andrew R.; Godinez, William J.; Rohr, Karl; Kalaidzidis, Yannis; Liang, Liang; Duncan, James; Shen, Hongying; Xu, Yingke; Magnusson, Klas E. G.; Jaldén, Joakim; Blau, Helen M.; Paul-Gilloteaux, Perrine; Roudot, Philippe; Kervrann, Charles; Waharte, François; Tinevez, Jean-Yves; Shorte, Spencer L.; Willemse, Joost; Celler, Katherine; van Wezel, Gilles P.; Dan, Han-Wei; Tsai, Yuh-Show; de Solórzano, Carlos Ortiz; Olivo-Marin, Jean-Christophe; Meijering, Erik

2014-01-01

Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy image data. Since manually detecting and following large numbers of individual particles is not feasible, automated computational methods have been developed for these tasks by many groups. Aiming to perform an objective comparison of methods, we gathered the community and organized, for the first time, an open competition, in which participating teams applied their own methods independently to a commonly defined data set including diverse scenarios. Performance was assessed using commonly defined measures. Although no single method performed best across all scenarios, the results revealed clear differences between the various approaches, leading to important practical conclusions for users and developers. PMID:24441936

Engaging Students in a Service-Learning Community through Computer-Mediated Communication

ERIC Educational Resources Information Center

Bair, Beth Teagarden

2017-01-01

In 2015, a university in rural Maryland offered an undergraduate service-learning leadership course, which collaborated with a service-learning community of practice. This interdisciplinary leadership course initiated and sustained personal and critical reflection and social interactions by integrating Computer-Medicated Communication (CMC)…

A Prototype of CAD/CAM Education in the Community College.

ERIC Educational Resources Information Center

Kimmey, James R.

Drawing upon Elgin Community College's (ECC's) 7-year history of program development and operation, this paper demonstrates how ECC, in cooperation with Northern Illinois Industries, Computervision Corporation, Mazak Corporation, and the Society of Manufacturing Engineers, established a Computer-Aided Design and Drafting/Computer-Aided Machining…

Mathematics and Computer Science: Exploring a Symbiotic Relationship

ERIC Educational Resources Information Center

Bravaco, Ralph; Simonson, Shai

2004-01-01

This paper describes a "learning community" designed for sophomore computer science majors who are simultaneously studying discrete mathematics. The learning community consists of three courses: Discrete Mathematics, Data Structures and an Integrative Seminar/Lab. The seminar functions as a link that integrates the two disciplines. Participation…

Validation of the Kp Geomagnetic Index Forecast at CCMC

NASA Astrophysics Data System (ADS)

Frechette, B. P.; Mays, M. L.

2017-12-01

The Community Coordinated Modeling Center (CCMC) Space Weather Research Center (SWRC) sub-team provides space weather services to NASA robotic mission operators and science campaigns and prototypes new models, forecasting techniques, and procedures. The Kp index is a measure of geomagnetic disturbances for space weather in the magnetosphere such as geomagnetic storms and substorms. In this study, we performed validation on the Newell et al. (2007) Kp prediction equation from December 2010 to July 2017. The purpose of this research is to understand the Kp forecast performance because it's critical for NASA missions to have confidence in the space weather forecast. This research was done by computing the Kp error for each forecast (average, minimum, maximum) and each synoptic period. Then to quantify forecast performance we computed the mean error, mean absolute error, root mean square error, multiplicative bias and correlation coefficient. A contingency table was made for each forecast and skill scores were computed. The results are compared to the perfect score and reference forecast skill score. In conclusion, the skill score and error results show that the minimum of the predicted Kp over each synoptic period from the Newell et al. (2007) Kp prediction equation performed better than the maximum or average of the prediction. However, persistence (reference forecast) outperformed all of the Kp forecasts (minimum, maximum, and average). Overall, the Newell Kp prediction still predicts within a range of 1, even though persistence beats it.

RIACS FY2002 Annual Report

NASA Technical Reports Server (NTRS)

Leiner, Barry M.; Gross, Anthony R. (Technical Monitor)

2002-01-01

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. Operated by the Universities Space Research Association (a non-profit university consortium), RIACS is located at the NASA Ames Research Center, Moffett Field, California. It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in September 2003. Ames has been designated NASA's Center of Excellence in Information Technology. In this capacity, Ames is charged with the responsibility to build an Information Technology (IT) Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA Ames and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of IT research necessary to meet the future challenges of NASA missions: 1) Automated Reasoning for Autonomous Systems; 2) Human-Centered Computing; and 3) High Performance Computing and Networking. In addition, RIACS collaborates with NASA scientists to apply IT research to a variety of NASA application domains including aerospace technology, earth science, life sciences, and astrobiology. RIACS also engages in other activities, such as workshops, seminars, visiting scientist programs and student summer programs, designed to encourage and facilitate collaboration between the university and NASA IT research communities.

Metadata Management on the SCEC PetaSHA Project: Helping Users Describe, Discover, Understand, and Use Simulation Data in a Large-Scale Scientific Collaboration

NASA Astrophysics Data System (ADS)

Okaya, D.; Deelman, E.; Maechling, P.; Wong-Barnum, M.; Jordan, T. H.; Meyers, D.

2007-12-01

Large scientific collaborations, such as the SCEC Petascale Cyberfacility for Physics-based Seismic Hazard Analysis (PetaSHA) Project, involve interactions between many scientists who exchange ideas and research results. These groups must organize, manage, and make accessible their community materials of observational data, derivative (research) results, computational products, and community software. The integration of scientific workflows as a paradigm to solve complex computations provides advantages of efficiency, reliability, repeatability, choices, and ease of use. The underlying resource needed for a scientific workflow to function and create discoverable and exchangeable products is the construction, tracking, and preservation of metadata. In the scientific workflow environment there is a two-tier structure of metadata. Workflow-level metadata and provenance describe operational steps, identity of resources, execution status, and product locations and names. Domain-level metadata essentially define the scientific meaning of data, codes and products. To a large degree the metadata at these two levels are separate. However, between these two levels is a subset of metadata produced at one level but is needed by the other. This crossover metadata suggests that some commonality in metadata handling is needed. SCEC researchers are collaborating with computer scientists at SDSC, the USC Information Sciences Institute, and Carnegie Mellon Univ. in order to perform earthquake science using high-performance computational resources. A primary objective of the "PetaSHA" collaboration is to perform physics-based estimations of strong ground motion associated with real and hypothetical earthquakes located within Southern California. Construction of 3D earth models, earthquake representations, and numerical simulation of seismic waves are key components of these estimations. Scientific workflows are used to orchestrate the sequences of scientific tasks and to access distributed computational facilities such as the NSF TeraGrid. Different types of metadata are produced and captured within the scientific workflows. One workflow within PetaSHA ("Earthworks") performs a linear sequence of tasks with workflow and seismological metadata preserved. Downstream scientific codes ingest these metadata produced by upstream codes. The seismological metadata uses attribute-value pairing in plain text; an identified need is to use more advanced handling methods. Another workflow system within PetaSHA ("Cybershake") involves several complex workflows in order to perform statistical analysis of ground shaking due to thousands of hypothetical but plausible earthquakes. Metadata management has been challenging due to its construction around a number of legacy scientific codes. We describe difficulties arising in the scientific workflow due to the lack of this metadata and suggest corrective steps, which in some cases include the cultural shift of domain science programmers coding for metadata.

Information Poverty and the Latino Community: Implications for Social Work Practice and Social Work Education.

ERIC Educational Resources Information Center

McNutt, John G.; Queiro-Tajalli, Irene; Boland, Katherine M.; Campbell, Craig

2001-01-01

Education level, computer ownership, and technology and information access determine one's status in the new information economy. Interventions such as community computer networks, telecommuting centers, grassroots electronic commerce, and volunteer technology corps can help Latinos and other marginalized groups overcome continued disadvantage.…

Computer-Assisted Community Planning and Decision Making.

ERIC Educational Resources Information Center

College of the Atlantic, Bar Harbor, ME.

The College of the Atlantic (COA) developed a broad-based, interdisciplinary curriculum in ecological policy and community planning and decision-making that incorporates two primary computer-based tools: ARC/INFO Geographic Information System (GIS) and STELLA, a systems-dynamics modeling tool. Students learn how to use and apply these tools…

Wireless Computing in the Library: A Successful Model at St. Louis Community College.

ERIC Educational Resources Information Center

Patton, Janice K.

2001-01-01

Describes the St. Louis Community College (Missouri) library's use of laptop computers in the instruction lab as a way to save space and wiring costs. Discusses the pros and cons of wireless library instruction-advantages include its flexibility and its ability to eliminate cabling. (NB)

Imprinting Community College Computer Science Education with Software Engineering Principles

ERIC Educational Resources Information Center

Hundley, Jacqueline Holliday

2012-01-01

Although the two-year curriculum guide includes coverage of all eight software engineering core topics, the computer science courses taught in Alabama community colleges limit student exposure to the programming, or coding, phase of the software development lifecycle and offer little experience in requirements analysis, design, testing, and…

APPLICATION OF 3D COMPUTER-AIDED TOMOGRAPHY TO THE QUANTIFICATION OF MARINE SEDIMENT COMMUNITIES IN POLLUTION GRADIENTS

EPA Science Inventory

Computer-Aided Tomography (CT) has been demonstrated to be a cost efficient tool for the qualitative and quantitative study of estuarine benthic communities along pollution gradients.
Now we have advanced this technology to successfully visualize and discriminate three dimen...

[Realistic possibilities of utilization of a personal computer in the office of a general practitioner].

PubMed

Masopust, V

1991-04-01

In May 1990 work on the programme "Computer system of the health community doctor Mic DOKI was" completed which resolves more than 70 basic tasks pertaining to the keeping of health documentation by health community doctors; it resolves automatically the entire administrative work in the health community, makes it possible to evaluate the activity of doctors and nurses it will facilitate the work of control organs of future health insurance companies and contribute to investigations of the health status of the population. Despite some problems ensuing from the contemporary economic situation of the country, the validity of contemporary health regulations and minimal training of our health personnel in the use of personal computers computerization of the health community system can be considered an asset to the reform of the health services which is under way.

Parallel Computation of the Regional Ocean Modeling System (ROMS)

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

Wang, P; Song, Y T; Chao, Y

2005-04-05

The Regional Ocean Modeling System (ROMS) is a regional ocean general circulation modeling system solving the free surface, hydrostatic, primitive equations over varying topography. It is free software distributed world-wide for studying both complex coastal ocean problems and the basin-to-global scale ocean circulation. The original ROMS code could only be run on shared-memory systems. With the increasing need to simulate larger model domains with finer resolutions and on a variety of computer platforms, there is a need in the ocean-modeling community to have a ROMS code that can be run on any parallel computer ranging from 10 to hundreds ofmore » processors. Recently, we have explored parallelization for ROMS using the MPI programming model. In this paper, an efficient parallelization strategy for such a large-scale scientific software package, based on an existing shared-memory computing model, is presented. In addition, scientific applications and data-performance issues on a couple of SGI systems, including Columbia, the world's third-fastest supercomputer, are discussed.« less

Phase field benchmark problems for dendritic growth and linear elasticity

DOE PAGES

Jokisaari, Andrea M.; Voorhees, P. W.; Guyer, Jonathan E.; ...

2018-03-26

We present the second set of benchmark problems for phase field models that are being jointly developed by the Center for Hierarchical Materials Design (CHiMaD) and the National Institute of Standards and Technology (NIST) along with input from other members in the phase field community. As the integrated computational materials engineering (ICME) approach to materials design has gained traction, there is an increasing need for quantitative phase field results. New algorithms and numerical implementations increase computational capabilities, necessitating standard problems to evaluate their impact on simulated microstructure evolution as well as their computational performance. We propose one benchmark problem formore » solidifiication and dendritic growth in a single-component system, and one problem for linear elasticity via the shape evolution of an elastically constrained precipitate. We demonstrate the utility and sensitivity of the benchmark problems by comparing the results of 1) dendritic growth simulations performed with different time integrators and 2) elastically constrained precipitate simulations with different precipitate sizes, initial conditions, and elastic moduli. As a result, these numerical benchmark problems will provide a consistent basis for evaluating different algorithms, both existing and those to be developed in the future, for accuracy and computational efficiency when applied to simulate physics often incorporated in phase field models.« less

SCinet Architecture: Featured at the International Conference for High Performance Computing,Networking, Storage and Analysis 2016

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

Lyonnais, Marc; Smith, Matt; Mace, Kate P.

SCinet is the purpose-built network that operates during the International Conference for High Performance Computing,Networking, Storage and Analysis (Super Computing or SC). Created each year for the conference, SCinet brings to life a high-capacity network that supports applications and experiments that are a hallmark of the SC conference. The network links the convention center to research and commercial networks around the world. This resource serves as a platform for exhibitors to demonstrate the advanced computing resources of their home institutions and elsewhere by supporting a wide variety of applications. Volunteers from academia, government and industry work together to design andmore » deliver the SCinet infrastructure. Industry vendors and carriers donate millions of dollars in equipment and services needed to build and support the local and wide area networks. Planning begins more than a year in advance of each SC conference and culminates in a high intensity installation in the days leading up to the conference. The SCinet architecture for SC16 illustrates a dramatic increase in participation from the vendor community, particularly those that focus on network equipment. Software-Defined Networking (SDN) and Data Center Networking (DCN) are present in nearly all aspects of the design.« less

Phase field benchmark problems for dendritic growth and linear elasticity

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

Jokisaari, Andrea M.; Voorhees, P. W.; Guyer, Jonathan E.

We present the second set of benchmark problems for phase field models that are being jointly developed by the Center for Hierarchical Materials Design (CHiMaD) and the National Institute of Standards and Technology (NIST) along with input from other members in the phase field community. As the integrated computational materials engineering (ICME) approach to materials design has gained traction, there is an increasing need for quantitative phase field results. New algorithms and numerical implementations increase computational capabilities, necessitating standard problems to evaluate their impact on simulated microstructure evolution as well as their computational performance. We propose one benchmark problem formore » solidifiication and dendritic growth in a single-component system, and one problem for linear elasticity via the shape evolution of an elastically constrained precipitate. We demonstrate the utility and sensitivity of the benchmark problems by comparing the results of 1) dendritic growth simulations performed with different time integrators and 2) elastically constrained precipitate simulations with different precipitate sizes, initial conditions, and elastic moduli. As a result, these numerical benchmark problems will provide a consistent basis for evaluating different algorithms, both existing and those to be developed in the future, for accuracy and computational efficiency when applied to simulate physics often incorporated in phase field models.« less

Jenkins-CI, an Open-Source Continuous Integration System, as a Scientific Data and Image-Processing Platform.

PubMed

Moutsatsos, Ioannis K; Hossain, Imtiaz; Agarinis, Claudia; Harbinski, Fred; Abraham, Yann; Dobler, Luc; Zhang, Xian; Wilson, Christopher J; Jenkins, Jeremy L; Holway, Nicholas; Tallarico, John; Parker, Christian N

2017-03-01

High-throughput screening generates large volumes of heterogeneous data that require a diverse set of computational tools for management, processing, and analysis. Building integrated, scalable, and robust computational workflows for such applications is challenging but highly valuable. Scientific data integration and pipelining facilitate standardized data processing, collaboration, and reuse of best practices. We describe how Jenkins-CI, an "off-the-shelf," open-source, continuous integration system, is used to build pipelines for processing images and associated data from high-content screening (HCS). Jenkins-CI provides numerous plugins for standard compute tasks, and its design allows the quick integration of external scientific applications. Using Jenkins-CI, we integrated CellProfiler, an open-source image-processing platform, with various HCS utilities and a high-performance Linux cluster. The platform is web-accessible, facilitates access and sharing of high-performance compute resources, and automates previously cumbersome data and image-processing tasks. Imaging pipelines developed using the desktop CellProfiler client can be managed and shared through a centralized Jenkins-CI repository. Pipelines and managed data are annotated to facilitate collaboration and reuse. Limitations with Jenkins-CI (primarily around the user interface) were addressed through the selection of helper plugins from the Jenkins-CI community.

Jenkins-CI, an Open-Source Continuous Integration System, as a Scientific Data and Image-Processing Platform

PubMed Central

Moutsatsos, Ioannis K.; Hossain, Imtiaz; Agarinis, Claudia; Harbinski, Fred; Abraham, Yann; Dobler, Luc; Zhang, Xian; Wilson, Christopher J.; Jenkins, Jeremy L.; Holway, Nicholas; Tallarico, John; Parker, Christian N.

2016-01-01

High-throughput screening generates large volumes of heterogeneous data that require a diverse set of computational tools for management, processing, and analysis. Building integrated, scalable, and robust computational workflows for such applications is challenging but highly valuable. Scientific data integration and pipelining facilitate standardized data processing, collaboration, and reuse of best practices. We describe how Jenkins-CI, an “off-the-shelf,” open-source, continuous integration system, is used to build pipelines for processing images and associated data from high-content screening (HCS). Jenkins-CI provides numerous plugins for standard compute tasks, and its design allows the quick integration of external scientific applications. Using Jenkins-CI, we integrated CellProfiler, an open-source image-processing platform, with various HCS utilities and a high-performance Linux cluster. The platform is web-accessible, facilitates access and sharing of high-performance compute resources, and automates previously cumbersome data and image-processing tasks. Imaging pipelines developed using the desktop CellProfiler client can be managed and shared through a centralized Jenkins-CI repository. Pipelines and managed data are annotated to facilitate collaboration and reuse. Limitations with Jenkins-CI (primarily around the user interface) were addressed through the selection of helper plugins from the Jenkins-CI community. PMID:27899692

Physical modeling and high-performance GPU computing for characterization, interception, and disruption of hazardous near-Earth objects

NASA Astrophysics Data System (ADS)

Kaplinger, Brian Douglas

For the past few decades, both the scientific community and the general public have been becoming more aware that the Earth lives in a shooting gallery of small objects. We classify all of these asteroids and comets, known or unknown, that cross Earth's orbit as near-Earth objects (NEOs). A look at our geologic history tells us that NEOs have collided with Earth in the past, and we expect that they will continue to do so. With thousands of known NEOs crossing the orbit of Earth, there has been significant scientific interest in developing the capability to deflect an NEO from an impacting trajectory. This thesis applies the ideas of Smoothed Particle Hydrodynamics (SPH) theory to the NEO disruption problem. A simulation package was designed that allows efficacy simulation to be integrated into the mission planning and design process. This is done by applying ideas in high-performance computing (HPC) on the computer graphics processing unit (GPU). Rather than prove a concept through large standalone simulations on a supercomputer, a highly parallel structure allows for flexible, target dependent questions to be resolved. Built around nonclassified data and analysis, this computer package will allow academic institutions to better tackle the issue of NEO mitigation effectiveness.

Measuring cues for stand-off deception detection based on full-body nonverbal features in body-worn cameras

NASA Astrophysics Data System (ADS)

Bouma, Henri; Burghouts, Gertjan; den Hollander, Richard; van der Zee, Sophie; Baan, Jan; ten Hove, Johan-Martijn; van Diepen, Sjaak; van den Haak, Paul; van Rest, Jeroen

2016-10-01

Deception detection is valuable in the security domain to distinguish truth from lies. It is desirable in many security applications, such as suspect and witness interviews and airport passenger screening. Interviewers are constantly trying to assess the credibility of a statement, usually based on intuition without objective technical support. However, psychological research has shown that humans can hardly perform better than random guessing. Deception detection is a multi-disciplinary research area with an interest from different fields, such as psychology and computer science. In the last decade, several developments have helped to improve the accuracy of lie detection (e.g., with a concealed information test, increasing the cognitive load, or measurements with motion capture suits) and relevant cues have been discovered (e.g., eye blinking or fiddling with the fingers). With an increasing presence of mobile phones and bodycams in society, a mobile, stand-off, automatic deception detection methodology based on various cues from the whole body would create new application opportunities. In this paper, we study the feasibility of measuring these visual cues automatically on different parts of the body, laying the groundwork for stand-off deception detection in more flexible and mobile deployable sensors, such as body-worn cameras. We give an extensive overview of recent developments in two communities: in the behavioral-science community the developments that improve deception detection with a special attention to the observed relevant non-verbal cues, and in the computer-vision community the recent methods that are able to measure these cues. The cues are extracted from several body parts: the eyes, the mouth, the head and the fullbody pose. We performed an experiment using several state-of-the-art video-content-analysis (VCA) techniques to assess the quality of robustly measuring these visual cues.

Facilitation as Attenuating of Environmental Stress among Structured Microbial Populations.

PubMed

Martins, Suzana Cláudia Silveira; Santaella, Sandra Tédde; Martins, Claudia Miranda; Martins, Rogério Parentoni

2016-01-01

There is currently an intense debate in microbial societies on whether evolution in complex communities is driven by competition or cooperation. Since Darwin, competition for scarce food resources has been considered the main ecological interaction shaping population dynamics and community structure both in vivo and in vitro. However, facilitation may be widespread across several animal and plant species. This could also be true in microbial strains growing under environmental stress. Pure and mixed strains of Serratia marcescens and Candida rugosa were grown in mineral culture media containing phenol. Growth rates were estimated as the angular coefficients computed from linearized growth curves. Fitness index was estimated as the quotient between growth rates computed for lineages grown in isolation and in mixed cultures. The growth rates were significantly higher in associated cultures than in pure cultures and fitness index was greater than 1 for both microbial species showing that the interaction between Serratia marcescens and Candida rugosa yielded more efficient phenol utilization by both lineages. This result corroborates the hypothesis that facilitation between microbial strains can increase their fitness and performance in environmental bioremediation.

Additions and improvements to the high energy density physics capabilities in the FLASH code

NASA Astrophysics Data System (ADS)

Lamb, D. Q.; Flocke, N.; Graziani, C.; Tzeferacos, P.; Weide, K.

2016-10-01

FLASH is an open source, finite-volume Eulerian, spatially adaptive radiation magnetohydrodynamics code that has the capabilities to treat a broad range of physical processes. FLASH performs well on a wide range of computer architectures, and has a broad user base. Extensive high energy density physics (HEDP) capabilities have been added to FLASH to make it an open toolset for the academic HEDP community. We summarize these capabilities, emphasizing recent additions and improvements. In particular, we showcase the ability of FLASH to simulate the Faraday Rotation Measure produced by the presence of magnetic fields; and proton radiography, proton self-emission, and Thomson scattering diagnostics with and without the presence of magnetic fields. We also describe several collaborations with the academic HEDP community in which FLASH simulations were used to design and interpret HEDP experiments. This work was supported in part at the University of Chicago by the DOE NNSA ASC through the Argonne Institute for Computing in Science under field work proposal 57789; and the NSF under Grant PHY-0903997.

Aerospace Engineering Systems

NASA Technical Reports Server (NTRS)

VanDalsem, William R.; Livingston, Mary E.; Melton, John E.; Torres, Francisco J.; Stremel, Paul M.

1999-01-01

Continuous improvement of aerospace product development processes is a driving requirement across much of the aerospace community. As up to 90% of the cost of an aerospace product is committed during the first 10% of the development cycle, there is a strong emphasis on capturing, creating, and communicating better information (both requirements and performance) early in the product development process. The community has responded by pursuing the development of computer-based systems designed to enhance the decision-making capabilities of product development individuals and teams. Recently, the historical foci on sharing the geometrical representation and on configuration management are being augmented: Physics-based analysis tools for filling the design space database; Distributed computational resources to reduce response time and cost; Web-based technologies to relieve machine-dependence; and Artificial intelligence technologies to accelerate processes and reduce process variability. Activities such as the Advanced Design Technologies Testbed (ADTT) project at NASA Ames Research Center study the strengths and weaknesses of the technologies supporting each of these trends, as well as the overall impact of the combination of these trends on a product development event. Lessons learned and recommendations for future activities will be reported.

Facilitation as Attenuating of Environmental Stress among Structured Microbial Populations

PubMed Central

Santaella, Sandra Tédde; Martins, Claudia Miranda; Martins, Rogério Parentoni

2016-01-01

There is currently an intense debate in microbial societies on whether evolution in complex communities is driven by competition or cooperation. Since Darwin, competition for scarce food resources has been considered the main ecological interaction shaping population dynamics and community structure both in vivo and in vitro. However, facilitation may be widespread across several animal and plant species. This could also be true in microbial strains growing under environmental stress. Pure and mixed strains of Serratia marcescens and Candida rugosa were grown in mineral culture media containing phenol. Growth rates were estimated as the angular coefficients computed from linearized growth curves. Fitness index was estimated as the quotient between growth rates computed for lineages grown in isolation and in mixed cultures. The growth rates were significantly higher in associated cultures than in pure cultures and fitness index was greater than 1 for both microbial species showing that the interaction between Serratia marcescens and Candida rugosa yielded more efficient phenol utilization by both lineages. This result corroborates the hypothesis that facilitation between microbial strains can increase their fitness and performance in environmental bioremediation. PMID:26904719

Some Programs Should Not Run on Laptops - Providing Programmatic Access to Applications Via Web Services

NASA Astrophysics Data System (ADS)

Gupta, V.; Gupta, N.; Gupta, S.; Field, E.; Maechling, P.

2003-12-01

Modern laptop computers, and personal computers, can provide capabilities that are, in many ways, comparable to workstations or departmental servers. However, this doesn't mean we should run all computations on our local computers. We have identified several situations in which it preferable to implement our seismological application programs in a distributed, server-based, computing model. In this model, application programs on the user's laptop, or local computer, invoke programs that run on an organizational server, and the results are returned to the invoking system. Situations in which a server-based architecture may be preferred include: (a) a program is written in a language, or written for an operating environment, that is unsupported on the local computer, (b) software libraries or utilities required to execute a program are not available on the users computer, (c) a computational program is physically too large, or computationally too expensive, to run on a users computer, (d) a user community wants to enforce a consistent method of performing a computation by standardizing on a single implementation of a program, and (e) the computational program may require current information, that is not available to all client computers. Until recently, distributed, server-based, computational capabilities were implemented using client/server architectures. In these architectures, client programs were often written in the same language, and they executed in the same computing environment, as the servers. Recently, a new distributed computational model, called Web Services, has been developed. Web Services are based on Internet standards such as XML, SOAP, WDSL, and UDDI. Web Services offer the promise of platform, and language, independent distributed computing. To investigate this new computational model, and to provide useful services to the SCEC Community, we have implemented several computational and utility programs using a Web Service architecture. We have hosted these Web Services as a part of the SCEC Community Modeling Environment (SCEC/CME) ITR Project (http://www.scec.org/cme). We have implemented Web Services for several of the reasons sited previously. For example, we implemented a FORTRAN-based Earthquake Rupture Forecast (ERF) as a Web Service for use by client computers that don't support a FORTRAN runtime environment. We implemented a Generic Mapping Tool (GMT) Web Service for use by systems that don't have local access to GMT. We implemented a Hazard Map Calculator Web Service to execute Hazard calculations that are too computationally intensive to run on a local system. We implemented a Coordinate Conversion Web Service to enforce a standard and consistent method for converting between UTM and Lat/Lon. Our experience developing these services indicates both strengths and weakness in current Web Service technology. Client programs that utilize Web Services typically need network access, a significant disadvantage at times. Programs with simple input and output parameters were the easiest to implement as Web Services, while programs with complex parameter-types required a significant amount of additional development. We also noted that Web services are very data-oriented, and adapting object-oriented software into the Web Service model proved problematic. Also, the Web Service approach of converting data types into XML format for network transmission has significant inefficiencies for some data sets.

Outcome assessment via handheld computer in community mental health: consumer satisfaction and reliability.

PubMed

Goldstein, Lizabeth A; Connolly Gibbons, Mary Beth; Thompson, Sarah M; Scott, Kelli; Heintz, Laura; Green, Patricia; Thompson, Donald; Crits-Christoph, Paul

2011-07-01

Computerized administration of mental health-related questionnaires has become relatively common, but little research has explored this mode of assessment in "real-world" settings. In the current study, 200 consumers at a community mental health center completed the BASIS-24 via handheld computer as well as paper and pen. Scores on the computerized BASIS-24 were compared with scores on the paper BASIS-24. Consumers also completed a questionnaire which assessed their level of satisfaction with the computerized BASIS-24. Results indicated that the BASIS-24 administered via handheld computer was highly correlated with pen and paper administration of the measure and was generally acceptable to consumers. Administration of the BASIS-24 via handheld computer may allow for efficient and sustainable outcomes assessment, adaptable research infrastructure, and maximization of clinical impact in community mental health agencies.

CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences

NASA Technical Reports Server (NTRS)

Slotnick, Jeffrey; Khodadoust, Abdollah; Alonso, Juan; Darmofal, David; Gropp, William; Lurie, Elizabeth; Mavriplis, Dimitri

2014-01-01

This report documents the results of a study to address the long range, strategic planning required by NASA's Revolutionary Computational Aerosciences (RCA) program in the area of computational fluid dynamics (CFD), including future software and hardware requirements for High Performance Computing (HPC). Specifically, the "Vision 2030" CFD study is to provide a knowledge-based forecast of the future computational capabilities required for turbulent, transitional, and reacting flow simulations across a broad Mach number regime, and to lay the foundation for the development of a future framework and/or environment where physics-based, accurate predictions of complex turbulent flows, including flow separation, can be accomplished routinely and efficiently in cooperation with other physics-based simulations to enable multi-physics analysis and design. Specific technical requirements from the aerospace industrial and scientific communities were obtained to determine critical capability gaps, anticipated technical challenges, and impediments to achieving the target CFD capability in 2030. A preliminary development plan and roadmap were created to help focus investments in technology development to help achieve the CFD vision in 2030.

Graphics processing units in bioinformatics, computational biology and systems biology.

PubMed

Nobile, Marco S; Cazzaniga, Paolo; Tangherloni, Andrea; Besozzi, Daniela

2017-09-01

Several studies in Bioinformatics, Computational Biology and Systems Biology rely on the definition of physico-chemical or mathematical models of biological systems at different scales and levels of complexity, ranging from the interaction of atoms in single molecules up to genome-wide interaction networks. Traditional computational methods and software tools developed in these research fields share a common trait: they can be computationally demanding on Central Processing Units (CPUs), therefore limiting their applicability in many circumstances. To overcome this issue, general-purpose Graphics Processing Units (GPUs) are gaining an increasing attention by the scientific community, as they can considerably reduce the running time required by standard CPU-based software, and allow more intensive investigations of biological systems. In this review, we present a collection of GPU tools recently developed to perform computational analyses in life science disciplines, emphasizing the advantages and the drawbacks in the use of these parallel architectures. The complete list of GPU-powered tools here reviewed is available at http://bit.ly/gputools. © The Author 2016. Published by Oxford University Press.

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

Evaluation of the Community Multi-scale Air Quality (CMAQ) ...

EPA Pesticide Factsheets

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Protection Agency develops the CMAQ model and periodically releases new versions of the model that include bug fixes and various other improvements to the modeling system. In the fall of 2015, CMAQ version 5.1 was released. This new version of CMAQ will contain important bug fixes to several issues that were identified in CMAQv5.0.2 and additionally include updates to other portions of the code. Several annual, and numerous episodic, CMAQv5.1 simulations were performed to assess the impact of these improvements on the model results. These results will be presented, along with a base evaluation of the performance of the CMAQv5.1 modeling system against available surface and upper-air measurements available during the time period simulated. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, proces

Towards a 'siliconeural computer': technological successes and challenges.

PubMed

Hughes, Mark A; Shipston, Mike J; Murray, Alan F

2015-07-28

Electronic signals govern the function of both nervous systems and computers, albeit in different ways. As such, hybridizing both systems to create an iono-electric brain-computer interface is a realistic goal; and one that promises exciting advances in both heterotic computing and neuroprosthetics capable of circumventing devastating neuropathology. 'Neural networks' were, in the 1980s, viewed naively as a potential panacea for all computational problems that did not fit well with conventional computing. The field bifurcated during the 1990s into a highly successful and much more realistic machine learning community and an equally pragmatic, biologically oriented 'neuromorphic computing' community. Algorithms found in nature that use the non-synchronous, spiking nature of neuronal signals have been found to be (i) implementable efficiently in silicon and (ii) computationally useful. As a result, interest has grown in techniques that could create mixed 'siliconeural' computers. Here, we discuss potential approaches and focus on one particular platform using parylene-patterned silicon dioxide.

HRP's Healthcare Spin-Offs Through Computational Modeling and Simulation Practice Methodologies

NASA Technical Reports Server (NTRS)

Mulugeta, Lealem; Walton, Marlei; Nelson, Emily; Peng, Grace; Morrison, Tina; Erdemir, Ahmet; Myers, Jerry

2014-01-01

Spaceflight missions expose astronauts to novel operational and environmental conditions that pose health risks that are currently not well understood, and perhaps unanticipated. Furthermore, given the limited number of humans that have flown in long duration missions and beyond low Earth-orbit, the amount of research and clinical data necessary to predict and mitigate these health and performance risks are limited. Consequently, NASA's Human Research Program (HRP) conducts research and develops advanced methods and tools to predict, assess, and mitigate potential hazards to the health of astronauts. In this light, NASA has explored the possibility of leveraging computational modeling since the 1970s as a means to elucidate the physiologic risks of spaceflight and develop countermeasures. Since that time, substantial progress has been realized in this arena through a number of HRP funded activates such as the Digital Astronaut Project (DAP) and the Integrated Medical Model (IMM). Much of this success can be attributed to HRP's endeavor to establish rigorous verification, validation, and credibility (VV&C) processes that ensure computational models and simulations (M&S) are sufficiently credible to address issues within their intended scope. This presentation summarizes HRP's activities in credibility of modeling and simulation, in particular through its outreach to the community of modeling and simulation practitioners. METHODS: The HRP requires all M&S that can have moderate to high impact on crew health or mission success must be vetted in accordance to NASA Standard for Models and Simulations, NASA-STD-7009 (7009) [5]. As this standard mostly focuses on engineering systems, the IMM and DAP have invested substantial efforts to adapt the processes established in this standard for their application to biological M&S, which is more prevalent in human health and performance (HHP) and space biomedical research and operations [6,7]. These methods have also generated substantial interest by the broader medical community though institutions like the National Institutes of Health (NIH) and the Food and Drug Administration (FDA) to develop similar standards and guidelines applicable to the larger medical operations and research community. DISCUSSION: Similar to NASA, many leading government agencies, health institutions and medical product developers around the world are recognizing the potential of computational M&S to support clinical research and decision making. In this light, substantial investments are being made in computational medicine and notable discoveries are being realized [8]. However, there is a lack of broadly applicable practice guidance for the development and implementation of M&S in clinical care and research in a manner that instills confidence among medical practitioners and biological researchers [9,10]. In this presentation, we will give an overview on how HRP is working with the NIH's Interagency Modeling and Analysis Group (IMAG), the FDA and the American Society of Mechanical Engineers (ASME) to leverage NASA's biomedical VV&C processes to establish a new regulatory standard for Verification and Validation in Computational Modeling of Medical Devices, and Guidelines for Credible Practice of Computational Modeling and Simulation in Healthcare.

Final Report Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale Knowledge Discovery

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

O'Leary, Patrick

The primary challenge motivating this project is the widening gap between the ability to compute information and to store it for subsequent analysis. This gap adversely impacts science code teams, who can perform analysis only on a small fraction of the data they calculate, resulting in the substantial likelihood of lost or missed science, when results are computed but not analyzed. Our approach is to perform as much analysis or visualization processing on data while it is still resident in memory, which is known as in situ processing. The idea in situ processing was not new at the time ofmore » the start of this effort in 2014, but efforts in that space were largely ad hoc, and there was no concerted effort within the research community that aimed to foster production-quality software tools suitable for use by Department of Energy (DOE) science projects. Our objective was to produce and enable the use of production-quality in situ methods and infrastructure, at scale, on DOE high-performance computing (HPC) facilities, though we expected to have an impact beyond DOE due to the widespread nature of the challenges, which affect virtually all large-scale computational science efforts. To achieve this objective, we engaged in software technology research and development (R&D), in close partnerships with DOE science code teams, to produce software technologies that were shown to run efficiently at scale on DOE HPC platforms.« less

A Standard Platform for Testing and Comparison of MDAO Architectures

NASA Technical Reports Server (NTRS)

Gray, Justin S.; Moore, Kenneth T.; Hearn, Tristan A.; Naylor, Bret A.

2012-01-01

The Multidisciplinary Design Analysis and Optimization (MDAO) community has developed a multitude of algorithms and techniques, called architectures, for performing optimizations on complex engineering systems which involve coupling between multiple discipline analyses. These architectures seek to efficiently handle optimizations with computationally expensive analyses including multiple disciplines. We propose a new testing procedure that can provide a quantitative and qualitative means of comparison among architectures. The proposed test procedure is implemented within the open source framework, OpenMDAO, and comparative results are presented for five well-known architectures: MDF, IDF, CO, BLISS, and BLISS-2000. We also demonstrate how using open source soft- ware development methods can allow the MDAO community to submit new problems and architectures to keep the test suite relevant.

Simulation of Fusion Plasmas

ScienceCinema

Holland, Chris [UC San Diego, San Diego, California, United States

2017-12-09

The upcoming ITER experiment (www.iter.org) represents the next major milestone in realizing the promise of using nuclear fusion as a commercial energy source, by moving into the “burning plasma” regime where the dominant heat source is the internal fusion reactions. As part of its support for the ITER mission, the US fusion community is actively developing validated predictive models of the behavior of magnetically confined plasmas. In this talk, I will describe how the plasma community is using the latest high performance computing facilities to develop and refine our models of the nonlinear, multiscale plasma dynamics, and how recent advances in experimental diagnostics are allowing us to directly test and validate these models at an unprecedented level.

HPC in a HEP lab: lessons learned from setting up cost-effective HPC clusters

NASA Astrophysics Data System (ADS)

Husejko, Michal; Agtzidis, Ioannis; Baehler, Pierre; Dul, Tadeusz; Evans, John; Himyr, Nils; Meinhard, Helge

2015-12-01

In this paper we present our findings gathered during the evaluation and testing of Windows Server High-Performance Computing (Windows HPC) in view of potentially using it as a production HPC system for engineering applications. The Windows HPC package, an extension of Microsofts Windows Server product, provides all essential interfaces, utilities and management functionality for creating, operating and monitoring a Windows-based HPC cluster infrastructure. The evaluation and test phase was focused on verifying the functionalities of Windows HPC, its performance, support of commercial tools and the integration with the users work environment. We describe constraints imposed by the way the CERN Data Centre is operated, licensing for engineering tools and scalability and behaviour of the HPC engineering applications used at CERN. We will present an initial set of requirements, which were created based on the above constraints and requests from the CERN engineering user community. We will explain how we have configured Windows HPC clusters to provide job scheduling functionalities required to support the CERN engineering user community, quality of service, user- and project-based priorities, and fair access to limited resources. Finally, we will present several performance tests we carried out to verify Windows HPC performance and scalability.

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.

Cloud computing approaches to accelerate drug discovery value chain.

PubMed

Garg, Vibhav; Arora, Suchir; Gupta, Chitra

2011-12-01

Continued advancements in the area of technology have helped high throughput screening (HTS) evolve from a linear to parallel approach by performing system level screening. Advanced experimental methods used for HTS at various steps of drug discovery (i.e. target identification, target validation, lead identification and lead validation) can generate data of the order of terabytes. As a consequence, there is pressing need to store, manage, mine and analyze this data to identify informational tags. This need is again posing challenges to computer scientists to offer the matching hardware and software infrastructure, while managing the varying degree of desired computational power. Therefore, the potential of "On-Demand Hardware" and "Software as a Service (SAAS)" delivery mechanisms cannot be denied. This on-demand computing, largely referred to as Cloud Computing, is now transforming the drug discovery research. Also, integration of Cloud computing with parallel computing is certainly expanding its footprint in the life sciences community. The speed, efficiency and cost effectiveness have made cloud computing a 'good to have tool' for researchers, providing them significant flexibility, allowing them to focus on the 'what' of science and not the 'how'. Once reached to its maturity, Discovery-Cloud would fit best to manage drug discovery and clinical development data, generated using advanced HTS techniques, hence supporting the vision of personalized medicine.

Blueprint for a microwave trapped ion quantum computer

PubMed Central

Lekitsch, Bjoern; Weidt, Sebastian; Fowler, Austin G.; Mølmer, Klaus; Devitt, Simon J.; Wunderlich, Christof; Hensinger, Winfried K.

2017-01-01

The availability of a universal quantum computer may have a fundamental impact on a vast number of research fields and on society as a whole. An increasingly large scientific and industrial community is working toward the realization of such a device. An arbitrarily large quantum computer may best be constructed using a modular approach. We present a blueprint for a trapped ion–based scalable quantum computer module, making it possible to create a scalable quantum computer architecture based on long-wavelength radiation quantum gates. The modules control all operations as stand-alone units, are constructed using silicon microfabrication techniques, and are within reach of current technology. To perform the required quantum computations, the modules make use of long-wavelength radiation–based quantum gate technology. To scale this microwave quantum computer architecture to a large size, we present a fully scalable design that makes use of ion transport between different modules, thereby allowing arbitrarily many modules to be connected to construct a large-scale device. A high error–threshold surface error correction code can be implemented in the proposed architecture to execute fault-tolerant operations. With appropriate adjustments, the proposed modules are also suitable for alternative trapped ion quantum computer architectures, such as schemes using photonic interconnects. PMID:28164154

Federated data storage system prototype for LHC experiments and data intensive science

NASA Astrophysics Data System (ADS)

Kiryanov, A.; Klimentov, A.; Krasnopevtsev, D.; Ryabinkin, E.; Zarochentsev, A.

2017-10-01

Rapid increase of data volume from the experiments running at the Large Hadron Collider (LHC) prompted physics computing community to evaluate new data handling and processing solutions. Russian grid sites and universities’ clusters scattered over a large area aim at the task of uniting their resources for future productive work, at the same time giving an opportunity to support large physics collaborations. In our project we address the fundamental problem of designing a computing architecture to integrate distributed storage resources for LHC experiments and other data-intensive science applications and to provide access to data from heterogeneous computing facilities. Studies include development and implementation of federated data storage prototype for Worldwide LHC Computing Grid (WLCG) centres of different levels and University clusters within one National Cloud. The prototype is based on computing resources located in Moscow, Dubna, Saint Petersburg, Gatchina and Geneva. This project intends to implement a federated distributed storage for all kind of operations such as read/write/transfer and access via WAN from Grid centres, university clusters, supercomputers, academic and commercial clouds. The efficiency and performance of the system are demonstrated using synthetic and experiment-specific tests including real data processing and analysis workflows from ATLAS and ALICE experiments, as well as compute-intensive bioinformatics applications (PALEOMIX) running on supercomputers. We present topology and architecture of the designed system, report performance and statistics for different access patterns and show how federated data storage can be used efficiently by physicists and biologists. We also describe how sharing data on a widely distributed storage system can lead to a new computing model and reformations of computing style, for instance how bioinformatics program running on supercomputers can read/write data from the federated storage.

Cloud Computing Applications in Support of Earth Science Activities at Marshall Space Flight Center

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Limaye, Ashutosh S.; Srikishen, Jayanthi

2011-01-01

Currently, the NASA Nebula Cloud Computing Platform is available to Agency personnel in a pre-release status as the system undergoes a formal operational readiness review. Over the past year, two projects within the Earth Science Office at NASA Marshall Space Flight Center have been investigating the performance and value of Nebula s "Infrastructure as a Service", or "IaaS" concept and applying cloud computing concepts to advance their respective mission goals. The Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique NASA satellite observations and weather forecasting capabilities for use within the operational forecasting community through partnerships with NOAA s National Weather Service (NWS). SPoRT has evaluated the performance of the Weather Research and Forecasting (WRF) model on virtual machines deployed within Nebula and used Nebula instances to simulate local forecasts in support of regional forecast studies of interest to select NWS forecast offices. In addition to weather forecasting applications, rapidly deployable Nebula virtual machines have supported the processing of high resolution NASA satellite imagery to support disaster assessment following the historic severe weather and tornado outbreak of April 27, 2011. Other modeling and satellite analysis activities are underway in support of NASA s SERVIR program, which integrates satellite observations, ground-based data and forecast models to monitor environmental change and improve disaster response in Central America, the Caribbean, Africa, and the Himalayas. Leveraging SPoRT s experience, SERVIR is working to establish a real-time weather forecasting model for Central America. Other modeling efforts include hydrologic forecasts for Kenya, driven by NASA satellite observations and reanalysis data sets provided by the broader meteorological community. Forecast modeling efforts are supplemented by short-term forecasts of convective initiation, determined by geostationary satellite observations processed on virtual machines powered by Nebula.

Intelligent Data Analysis in the 21st Century

NASA Astrophysics Data System (ADS)

Cohen, Paul; Adams, Niall

When IDA began, data sets were small and clean, data provenance and management were not significant issues, workflows and grid computing and cloud computing didn’t exist, and the world was not populated with billions of cellphone and computer users. The original conception of intelligent data analysis — automating some of the reasoning of skilled data analysts — has not been updated to account for the dramatic changes in what skilled data analysis means, today. IDA might update its mission to address pressing problems in areas such as climate change, habitat loss, education, and medicine. It might anticipate data analysis opportunities five to ten years out, such as customizing educational trajectories to individual students, and personalizing medical protocols. Such developments will elevate the conference and our community by shifting our focus from arbitrary measures of the performance of isolated algorithms to the practical, societal value of intelligent data analysis systems.

A gateway for phylogenetic analysis powered by grid computing featuring GARLI 2.0.

PubMed

Bazinet, Adam L; Zwickl, Derrick J; Cummings, Michael P

2014-09-01

We introduce molecularevolution.org, a publicly available gateway for high-throughput, maximum-likelihood phylogenetic analysis powered by grid computing. The gateway features a garli 2.0 web service that enables a user to quickly and easily submit thousands of maximum likelihood tree searches or bootstrap searches that are executed in parallel on distributed computing resources. The garli web service allows one to easily specify partitioned substitution models using a graphical interface, and it performs sophisticated post-processing of phylogenetic results. Although the garli web service has been used by the research community for over three years, here we formally announce the availability of the service, describe its capabilities, highlight new features and recent improvements, and provide details about how the grid system efficiently delivers high-quality phylogenetic results. © The Author(s) 2014. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

REVIEW OF THE GOVERNING EQUATIONS, COMPUTATIONAL ALGORITHMS, AND OTHER COMPONENTS OF THE MODELS-3 COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODELING SYSTEM

EPA Science Inventory

This article describes the governing equations, computational algorithms, and other components entering into the Community Multiscale Air Quality (CMAQ) modeling system. This system has been designed to approach air quality as a whole by including state-of-the-science capabiliti...

Evaluating How the Computer-Supported Collaborative Learning Community Fosters Critical Reflective Practices

ERIC Educational Resources Information Center

Ma, Ada W.W.

2013-01-01

In recent research, little attention has been paid to issues of methodology and analysis methods to evaluate the quality of the collaborative learning community. To address such issues, an attempt is made to adopt the Activity System Model as an analytical framework to examine the relationship between computer supported collaborative learning…

A Survey of Computer Use in Associate Degree Programs in Engineering Technology.

ERIC Educational Resources Information Center

Cunningham, Pearley

As part of its annual program review process, the Department of Engineering Technology at the Community College of Allegheny County, in Pennsylvania, conducted a study of computer usage in community college engineering technology programs across the nation. Specifically, the study sought to determine the types of software, Internet access, average…

The Reality of Computers at the Community College Level.

ERIC Educational Resources Information Center

Leone, Stephen J.

Writing teachers at the community college level who teach using a computer have come to accept the fact that it is more than "just teaching" composition. Such teaching often requires instructors to be as knowledgeable as some of the technicians. Two-year college students and faculty are typically given little support in using computers…

Negotiating Knowledge Contribution to Multiple Discourse Communities: A Doctoral Student of Computer Science Writing for Publication

ERIC Educational Resources Information Center

Li, Yongyan

2006-01-01

Despite the rich literature on disciplinary knowledge construction and multilingual scholars' academic literacy practices, little is known about how novice scholars are engaged in knowledge construction in negotiation with various target discourse communities. In this case study, with a focused analysis of a Chinese computer science doctoral…

Gifting Computers to a Poor School in Nepal: Beyond the Bling

ERIC Educational Resources Information Center

Raven, John

2013-01-01

Donating computers to schools in poorer communities with the altruistic hope of bridging some kind of "digital-divide" by providing access to modern technologies may seem commendable. Critics, however, would argue that these actions are ineffective, primarily serving the interests of the donators and may even damage the community. This…

A Survey of Current Computer Information Science (CIS) Students.

ERIC Educational Resources Information Center

Los Rios Community Coll. District, Sacramento, CA. Office of Institutional Research.

This document is a survey designed to be completed by current students of Computer Information Science (CIS) in the Los Rios Community College District (LRCCD), which consists of three community colleges: American River College, Cosumnes River College, and Sacramento City College. The students are asked about their educational goals and how…

A Database Training Module for Nassau Community College Staff and Faculty.

ERIC Educational Resources Information Center

Goodman, Harriett Ziskin

A training module developed following the Instructional System Design model was implemented at Nassau Community College (NCC) to teach its administration, faculty, and staff members computer skills that would enable them to use the available computer equipment more efficiently. Using this module, each trainee designed a file to be used for the…

Transnational Computer Use in Urban Latino Immigrant Communities: Implications for Schooling

ERIC Educational Resources Information Center

Sanchez, Patricia; Salazar, Malena

2012-01-01

This article examines the ways in which transnational Latino immigrants in urban communities use computer technology. Drawing from a 3-year ethnographic study, it focuses on three second-generation transnational female youth, their families, and members of their respective immigrant networks. Data were collected in both the United States and…

State College Scavenger: Evaluating the Perspectives of Mobile Computing Interactions within Community Spaces

ERIC Educational Resources Information Center

Hoffman, Blaine

2013-01-01

This work focuses on the impact of mobile computing on individuals' perspectives of places within their community. A technological intervention is designed and deployed to augment the user experience of visiting different locations around town, physically exploring them while also interacting with an online tool. The tool-supported activity serves…

Community Colleges in the Information Age: Gains Associated with Students' Use of Computer Technology

ERIC Educational Resources Information Center

Anderson, Bodi; Horn, Robert

2012-01-01

Computer literacy is increasingly important in higher education, and many educational technology experts propose a more prominent integration of technology into pedagogy. Empirical evidence is needed to support these theories. This study examined community college students planning to transfer to 4-year universities and estimated the relationship…

[Computer simulation of thyroid regulatory mechanisms in health and malignancy].

PubMed

Abduvaliev, A A; Gil'dieva, M S; Khidirov, B N; Saĭdalieva, M; Saatov, T S

2010-07-01

The paper describes a computer model for regulation of the number of thyroid follicular cells in health and malignancy. The authors'computer program for mathematical simulation of the regulatory mechanisms of a thyroid follicular cellular community cannot be now referred to as good commercial products. For commercialization of this product, it is necessary to draw up a direct relation of the introduced corrected values from the actually existing normal values, such as the peripheral blood concentrations of thyroid hormones or the mean values of endocrine tissue mitotic activity. However, the described computer program has been also used in researches by our scientific group in the study of thyroid cancer. The available biological experimental data and theoretical provisions on thyroid structural and functional organization at the cellular level allow one to construct mathematical models for quantitative analysis of the regulation of the size of a cellular community of a thyroid follicle in health and abnormalities, by using the method for simulation of the regulatory mechanisms of living systems and the equations of cellular community regulatory communities.

Introduction to computers: Reference guide

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

Ligon, F.V.

1995-04-01

The ``Introduction to Computers`` program establishes formal partnerships with local school districts and community-based organizations, introduces computer literacy to precollege students and their parents, and encourages students to pursue Scientific, Mathematical, Engineering, and Technical careers (SET). Hands-on assignments are given in each class, reinforcing the lesson taught. In addition, the program is designed to broaden the knowledge base of teachers in scientific/technical concepts, and Brookhaven National Laboratory continues to act as a liaison, offering educational outreach to diverse community organizations and groups. This manual contains the teacher`s lesson plans and the student documentation to this introduction to computer course.

New Trends in E-Science: Machine Learning and Knowledge Discovery in Databases

NASA Astrophysics Data System (ADS)

Brescia, Massimo

2012-11-01

Data mining, or Knowledge Discovery in Databases (KDD), while being the main methodology to extract the scientific information contained in Massive Data Sets (MDS), needs to tackle crucial problems since it has to orchestrate complex challenges posed by transparent access to different computing environments, scalability of algorithms, reusability of resources. To achieve a leap forward for the progress of e-science in the data avalanche era, the community needs to implement an infrastructure capable of performing data access, processing and mining in a distributed but integrated context. The increasing complexity of modern technologies carried out a huge production of data, whose related warehouse management and the need to optimize analysis and mining procedures lead to a change in concept on modern science. Classical data exploration, based on local user own data storage and limited computing infrastructures, is no more efficient in the case of MDS, worldwide spread over inhomogeneous data centres and requiring teraflop processing power. In this context modern experimental and observational science requires a good understanding of computer science, network infrastructures, Data Mining, etc. i.e. of all those techniques which fall into the domain of the so called e-science (recently assessed also by the Fourth Paradigm of Science). Such understanding is almost completely absent in the older generations of scientists and this reflects in the inadequacy of most academic and research programs. A paradigm shift is needed: statistical pattern recognition, object oriented programming, distributed computing, parallel programming need to become an essential part of scientific background. A possible practical solution is to provide the research community with easy-to understand, easy-to-use tools, based on the Web 2.0 technologies and Machine Learning methodology. Tools where almost all the complexity is hidden to the final user, but which are still flexible and able to produce efficient and reliable scientific results. All these considerations will be described in the detail in the chapter. Moreover, examples of modern applications offering to a wide variety of e-science communities a large spectrum of computational facilities to exploit the wealth of available massive data sets and powerful machine learning and statistical algorithms will be also introduced.

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

Taylor, Valerie

Given the significant impact of computing on society, it is important that all cultures, especially underrepresented cultures, are fully engaged in the field of computing to ensure that everyone benefits from the advances in computing. This proposal is focused on the field of high performance computing. The lack of cultural diversity in computing, in particular high performance computing, is especially evident with respect to the following ethnic groups – African Americans, Hispanics, and Native Americans – as well as People with Disabilities. The goal of this proposal is to organize and coordinate a National Laboratory Career Development Workshop focused onmore » underrepresented cultures (ethnic cultures and disability cultures) in high performance computing. It is expected that the proposed workshop will increase the engagement of underrepresented cultures in HPC through increased exposure to the excellent work at the national laboratories. The National Laboratory Workshops are focused on the recruitment of senior graduate students and the retention of junior lab staff through the various panels and discussions at the workshop. Further, the workshop will include a community building component that extends beyond the workshop. The workshop was held was held at the Lawrence Livermore National Laboratory campus in Livermore, CA. from June 14 - 15, 2012. The grant provided funding for 25 participants from underrepresented groups. The workshop also included another 25 local participants in the summer programs at Lawrence Livermore National Laboratory. Below are some key results from the assessment of the workshops: 86% of the participants indicated strongly agree or agree to the statement "I am more likely to consider/continue a career at a national laboratory as a result of participating in this workshop." 77% indicated strongly agree or agree to the statement "I plan to pursue a summer internship at a national laboratory." 100% of the participants indicated strongly agree or agree to the statement "The CMD-IT NLPDEV workshop was a valuable experience."« less

Computational Environments and Analysis methods available on the NCI High Performance Computing (HPC) and High Performance Data (HPD) Platform

NASA Astrophysics Data System (ADS)

Evans, B. J. K.; Foster, C.; Minchin, S. A.; Pugh, T.; Lewis, A.; Wyborn, L. A.; Evans, B. J.; Uhlherr, A.

2014-12-01

The National Computational Infrastructure (NCI) has established a powerful in-situ computational environment to enable both high performance computing and data-intensive science across a wide spectrum of national environmental data collections - in particular climate, observational data and geoscientific assets. This paper examines 1) the computational environments that supports the modelling and data processing pipelines, 2) the analysis environments and methods to support data analysis, and 3) the progress in addressing harmonisation of the underlying data collections for future transdisciplinary research that enable accurate climate projections. NCI makes available 10+ PB major data collections from both the government and research sectors based on six themes: 1) weather, climate, and earth system science model simulations, 2) marine and earth observations, 3) geosciences, 4) terrestrial ecosystems, 5) water and hydrology, and 6) astronomy, social and biosciences. Collectively they span the lithosphere, crust, biosphere, hydrosphere, troposphere, and stratosphere. The data is largely sourced from NCI's partners (which include the custodians of many of the national scientific records), major research communities, and collaborating overseas organisations. The data is accessible within an integrated HPC-HPD environment - a 1.2 PFlop supercomputer (Raijin), a HPC class 3000 core OpenStack cloud system and several highly connected large scale and high-bandwidth Lustre filesystems. This computational environment supports a catalogue of integrated reusable software and workflows from earth system and ecosystem modelling, weather research, satellite and other observed data processing and analysis. To enable transdisciplinary research on this scale, data needs to be harmonised so that researchers can readily apply techniques and software across the corpus of data available and not be constrained to work within artificial disciplinary boundaries. Future challenges will involve the further integration and analysis of this data across the social sciences to facilitate the impacts across the societal domain, including timely analysis to more accurately predict and forecast future climate and environmental state.

Perspectives on Sharing Models and Related Resources in Computational Biomechanics Research.

PubMed

Erdemir, Ahmet; Hunter, Peter J; Holzapfel, Gerhard A; Loew, Leslie M; Middleton, John; Jacobs, Christopher R; Nithiarasu, Perumal; Löhner, Rainlad; Wei, Guowei; Winkelstein, Beth A; Barocas, Victor H; Guilak, Farshid; Ku, Joy P; Hicks, Jennifer L; Delp, Scott L; Sacks, Michael; Weiss, Jeffrey A; Ateshian, Gerard A; Maas, Steve A; McCulloch, Andrew D; Peng, Grace C Y

2018-02-01

The role of computational modeling for biomechanics research and related clinical care will be increasingly prominent. The biomechanics community has been developing computational models routinely for exploration of the mechanics and mechanobiology of diverse biological structures. As a result, a large array of models, data, and discipline-specific simulation software has emerged to support endeavors in computational biomechanics. Sharing computational models and related data and simulation software has first become a utilitarian interest, and now, it is a necessity. Exchange of models, in support of knowledge exchange provided by scholarly publishing, has important implications. Specifically, model sharing can facilitate assessment of reproducibility in computational biomechanics and can provide an opportunity for repurposing and reuse, and a venue for medical training. The community's desire to investigate biological and biomechanical phenomena crossing multiple systems, scales, and physical domains, also motivates sharing of modeling resources as blending of models developed by domain experts will be a required step for comprehensive simulation studies as well as the enhancement of their rigor and reproducibility. The goal of this paper is to understand current perspectives in the biomechanics community for the sharing of computational models and related resources. Opinions on opportunities, challenges, and pathways to model sharing, particularly as part of the scholarly publishing workflow, were sought. A group of journal editors and a handful of investigators active in computational biomechanics were approached to collect short opinion pieces as a part of a larger effort of the IEEE EMBS Computational Biology and the Physiome Technical Committee to address model reproducibility through publications. A synthesis of these opinion pieces indicates that the community recognizes the necessity and usefulness of model sharing. There is a strong will to facilitate model sharing, and there are corresponding initiatives by the scientific journals. Outside the publishing enterprise, infrastructure to facilitate model sharing in biomechanics exists, and simulation software developers are interested in accommodating the community's needs for sharing of modeling resources. Encouragement for the use of standardized markups, concerns related to quality assurance, acknowledgement of increased burden, and importance of stewardship of resources are noted. In the short-term, it is advisable that the community builds upon recent strategies and experiments with new pathways for continued demonstration of model sharing, its promotion, and its utility. Nonetheless, the need for a long-term strategy to unify approaches in sharing computational models and related resources is acknowledged. Development of a sustainable platform supported by a culture of open model sharing will likely evolve through continued and inclusive discussions bringing all stakeholders at the table, e.g., by possibly establishing a consortium.

Algal bioassessment metrics for wadeable streams and rivers of Maine, USA

USGS Publications Warehouse

Danielson, Thomas J.; Loftin, Cynthia S.; Tsomides, Leonidas; DiFranco, Jeanne L.; Connors, Beth

2011-01-01

Many state water-quality agencies use biological assessment methods based on lotic fish and macroinvertebrate communities, but relatively few states have incorporated algal multimetric indices into monitoring programs. Algae are good indicators for monitoring water quality because they are sensitive to many environmental stressors. We evaluated benthic algal community attributes along a landuse gradient affecting wadeable streams and rivers in Maine, USA, to identify potential bioassessment metrics. We collected epilithic algal samples from 193 locations across the state. We computed weighted-average optima for common taxa for total P, total N, specific conductance, % impervious cover, and % developed watershed, which included all land use that is no longer forest or wetland. We assigned Maine stream tolerance values and categories (sensitive, intermediate, tolerant) to taxa based on their optima and responses to watershed disturbance. We evaluated performance of algal community metrics used in multimetric indices from other regions and novel metrics based on Maine data. Metrics specific to Maine data, such as the relative richness of species characterized as being sensitive in Maine, were more correlated with % developed watershed than most metrics used in other regions. Few community-structure attributes (e.g., species richness) were useful metrics in Maine. Performance of algal bioassessment models would be improved if metrics were evaluated with attributes of local data before inclusion in multimetric indices or statistical models. ?? 2011 by The North American Benthological Society.

A Position on a Computer Literacy Course.

ERIC Educational Resources Information Center

Self, Charles C.

A position is put forth on the appropriate content of a computer literacy course and the role of computer literacy in the community college. First, various definitions of computer literacy are examined, including the programming, computer awareness, and comprehensive approaches. Next, five essential components of a computer literacy course are…

Computer Training for Seniors: An Academic-Community Partnership

ERIC Educational Resources Information Center

Sanders, Martha J.; O'Sullivan, Beth; DeBurra, Katherine; Fedner, Alesha

2013-01-01

Computer technology is integral to information retrieval, social communication, and social interaction. However, only 47% of seniors aged 65 and older use computers. The purpose of this study was to determine the impact of a client-centered computer program on computer skills, attitudes toward computer use, and generativity in novice senior…

An Integrated Low-Speed Performance and Noise Prediction Methodology for Subsonic Aircraft

NASA Technical Reports Server (NTRS)

Olson, E. D.; Mavris, D. N.

2000-01-01

An integrated methodology has been assembled to compute the engine performance, takeoff and landing trajectories, and community noise levels for a subsonic commercial aircraft. Where feasible, physics-based noise analysis methods have been used to make the results more applicable to newer, revolutionary designs and to allow for a more direct evaluation of new technologies. The methodology is intended to be used with approximation methods and risk analysis techniques to allow for the analysis of a greater number of variable combinations while retaining the advantages of physics-based analysis. Details of the methodology are described and limited results are presented for a representative subsonic commercial aircraft.

SOA-based digital library services and composition in biomedical applications.

PubMed

Zhao, Xia; Liu, Enjie; Clapworthy, Gordon J; Viceconti, Marco; Testi, Debora

2012-06-01

Carefully collected, high-quality data are crucial in biomedical visualization, and it is important that the user community has ready access to both this data and the high-performance computing resources needed by the complex, computational algorithms that will process it. Biological researchers generally require data, tools and algorithms from multiple providers to achieve their goals. This paper illustrates our response to the problems that result from this. The Living Human Digital Library (LHDL) project presented in this paper has taken advantage of Web Services to build a biomedical digital library infrastructure that allows clinicians and researchers not only to preserve, trace and share data resources, but also to collaborate at the data-processing level. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Development and application of GASP 2.0

NASA Technical Reports Server (NTRS)

Mcgrory, W. D.; Huebner, L. D.; Slack, D. C.; Walters, R. W.

1992-01-01

GASP 2.0 represents a major new release of the computational fluid dynamics code in wide use by the aerospace community. The authors have spent the last two years analyzing the strengths and weaknesses of the previous version of the finite-rate chemistry, Navier Stokes solution algorithm. What has resulted is a completely redesigned computer code that offers two to four times the performance of previous versions while requiring as little as one quarter of the memory requirements. In addition to the improvements in efficiency over the original code, Version 2.0 contains many new features. A brief discussion of the improvements made to GASP, and an application using GASP 2.0 which demonstrates some of the new features are presented.

pFlogger: The Parallel Fortran Logging Utility

NASA Technical Reports Server (NTRS)

Clune, Tom; Cruz, Carlos A.

2017-01-01

In the context of high performance computing (HPC), software investments in support of text-based diagnostics, which monitor a running application, are typically limited compared to those for other types of IO. Examples of such diagnostics include reiteration of configuration parameters, progress indicators, simple metrics (e.g., mass conservation, convergence of solvers, etc.), and timers. To some degree, this difference in priority is justifiable as other forms of output are the primary products of a scientific model and, due to their large data volume, much more likely to be a significant performance concern. In contrast, text-based diagnostic content is generally not shared beyond the individual or group running an application and is most often used to troubleshoot when something goes wrong. We suggest that a more systematic approach enabled by a logging facility (or 'logger)' similar to those routinely used by many communities would provide significant value to complex scientific applications. In the context of high-performance computing, an appropriate logger would provide specialized support for distributed and shared-memory parallelism and have low performance overhead. In this paper, we present our prototype implementation of pFlogger - a parallel Fortran-based logging framework, and assess its suitability for use in a complex scientific application.

A Community-Based Participatory Approach to Personalized, Computer-Generated Nutrition Feedback Reports: The Healthy Environments Partnership

PubMed Central

Kannan, Srimathi; Schulz, Amy; Israel, Barbara; Ayra, Indira; Weir, Sheryl; Dvonch, Timothy J.; Rowe, Zachary; Miller, Patricia; Benjamin, Alison

2008-01-01

Background Computer tailoring and personalizing recommendations for dietary health-promoting behaviors are in accordance with community-based participatory research (CBPR) principles, which emphasizes research that benefits the participants and community involved. Objective To describe the CBPR process utilized to computer-generate and disseminate personalized nutrition feedback reports (NFRs) for Detroit Healthy Environments Partnership (HEP) study participants. METHODS The CBPR process included discussion and feedback from HEP partners on several draft personalized reports. The nutrition feedback process included defining the feedback objectives; prioritizing the nutrients; customizing the report design; reviewing and revising the NFR template and readability; producing and disseminating the report; and participant follow-up. Lessons Learned Application of CBPR principles in designing the NFR resulted in a reader-friendly product with useful recommendations to promote heart health. Conclusions A CBPR process can enhance computer tailoring of personalized NFRs to address racial and socioeconomic disparities in cardiovascular disease (CVD). PMID:19337572

Environmental computing compendium - background and motivation

NASA Astrophysics Data System (ADS)

Heikkurinen, Matti; Kranzlmüller, Dieter

2017-04-01

The emerging discipline of environmental computing brings together experts in applied, advanced environmental modelling. The application domains address several fundamental societal challenges, ranging from disaster risk reduction to sustainability issues (such as food security on the global scale). The community has used an Intuitive, pragmatic approach when determining which initiatives are considered to "belong to the discipline". The community's growth is based on sharing of experiences and tools provides opportunities for reusing solutions or applying knowledge in new settings. Thus, limiting possible synergies by applying an arbitrary, formal definition to exclude some of the sources of solutions and knowledge would be counterproductive. However, the number of individuals and initiatives involved has grown to the level where a survey of initiatives and sub-themes they focus on is of interest. By surveying the project landscape and identifying common themes and building a shared vocabulary to describe them we can both communicate the relevance of the new discipline to the general public more easily and make it easier for the new members of the community to find the most promising collaboration partners. This talk presents the methodology and initial findings of the initial survey of the environmental computing initiatives and organisations, as well as approaches that could lead to an environmental computing compendium that would be a collaborative maintained shared resource of the environmental computing community.

An Object-Oriented Approach to Writing Computational Electromagnetics Codes

NASA Technical Reports Server (NTRS)

Zimmerman, Martin; Mallasch, Paul G.

1996-01-01

Presently, most computer software development in the Computational Electromagnetics (CEM) community employs the structured programming paradigm, particularly using the Fortran language. Other segments of the software community began switching to an Object-Oriented Programming (OOP) paradigm in recent years to help ease design and development of highly complex codes. This paper examines design of a time-domain numerical analysis CEM code using the OOP paradigm, comparing OOP code and structured programming code in terms of software maintenance, portability, flexibility, and speed.

Community as client: environmental issues in the real world. A SimCity computer simulation.

PubMed

Bareford, C G

2001-01-01

The ability to think critically has become a crucial part of professional practice and education. SimCity, a popular computer simulation game, provides an opportunity to practice community assessment and interventions using a systems approach. SimCity is an interactive computer simulation game in which the player takes an active part in community planning. SimCity is supported on either a Windows 95/98 or a Macintosh platform and is available on CD-ROM at retail stores or at www.simcity.com. Students complete a tutorial and then apply a selected scenario in SimCity. Scenarios consist of hypothetical communities that have varying types and degrees of environmental problems, e.g., traffic, crime, nuclear meltdown, flooding, fire, and earthquakes. In problem solving with the simulated scenarios, students (a) identify systems and subsystems within the community that are critical factors impacting the environmental health of the community, (b) create changes in the systems and subsystems in an effort to solve the environmental health problem, and (c) evaluate the effectiveness of interventions based on the game score, demographic and fiscal data, and amount of community support. Because the consequences of planned intervention are part of the simulation, nursing students are able to develop critical-thinking skills. The simulation provides essential content in community planning in an interesting and interactive format.

Using the cloud to speed-up calibration of watershed-scale hydrologic models (Invited)

NASA Astrophysics Data System (ADS)

Goodall, J. L.; Ercan, M. B.; Castronova, A. M.; Humphrey, M.; Beekwilder, N.; Steele, J.; Kim, I.

2013-12-01

This research focuses on using the cloud to address computational challenges associated with hydrologic modeling. One example is calibration of a watershed-scale hydrologic model, which can take days of execution time on typical computers. While parallel algorithms for model calibration exist and some researchers have used multi-core computers or clusters to run these algorithms, these solutions do not fully address the challenge because (i) calibration can still be too time consuming even on multicore personal computers and (ii) few in the community have the time and expertise needed to manage a compute cluster. Given this, another option for addressing this challenge that we are exploring through this work is the use of the cloud for speeding-up calibration of watershed-scale hydrologic models. The cloud used in this capacity provides a means for renting a specific number and type of machines for only the time needed to perform a calibration model run. The cloud allows one to precisely balance the duration of the calibration with the financial costs so that, if the budget allows, the calibration can be performed more quickly by renting more machines. Focusing specifically on the SWAT hydrologic model and a parallel version of the DDS calibration algorithm, we show significant speed-up time across a range of watershed sizes using up to 256 cores to perform a model calibration. The tool provides a simple web-based user interface and the ability to monitor the calibration job submission process during the calibration process. Finally this talk concludes with initial work to leverage the cloud for other tasks associated with hydrologic modeling including tasks related to preparing inputs for constructing place-based hydrologic models.

PREDICTORS OF COMPUTER USE IN COMMUNITY-DWELLING ETHNICALLY DIVERSE OLDER ADULTS

PubMed Central

Werner, Julie M.; Carlson, Mike; Jordan-Marsh, Maryalice; Clark, Florence

2011-01-01

Objective In this study we analyzed self-reported computer use, demographic variables, psychosocial variables, and health and well-being variables collected from 460 ethnically diverse, community-dwelling elders in order to investigate the relationship computer use has with demographics, well-being and other key psychosocial variables in older adults. Background Although younger elders with more education, those who employ active coping strategies, or those who are low in anxiety levels are thought to use computers at higher rates than others, previous research has produced mixed or inconclusive results regarding ethnic, gender, and psychological factors, or has concentrated on computer-specific psychological factors only (e.g., computer anxiety). Few such studies have employed large sample sizes or have focused on ethnically diverse populations of community-dwelling elders. Method With a large number of overlapping predictors, zero-order analysis alone is poorly equipped to identify variables that are independently associated with computer use. Accordingly, both zero-order and stepwise logistic regression analyses were conducted to determine the correlates of two types of computer use: email and general computer use. Results Results indicate that younger age, greater level of education, non-Hispanic ethnicity, behaviorally active coping style, general physical health, and role-related emotional health each independently predicted computer usage. Conclusion Study findings highlight differences in computer usage, especially in regard to Hispanic ethnicity and specific health and well-being factors. Application Potential applications of this research include future intervention studies, individualized computer-based activity programming, or customizable software and user interface design for older adults responsive to a variety of personal characteristics and capabilities. PMID:22046718

Predictors of computer use in community-dwelling, ethnically diverse older adults.

PubMed

Werner, Julie M; Carlson, Mike; Jordan-Marsh, Maryalice; Clark, Florence

2011-10-01

In this study, we analyzed self-reported computer use, demographic variables, psychosocial variables, and health and well-being variables collected from 460 ethnically diverse, community-dwelling elders to investigate the relationship computer use has with demographics, well-being, and other key psychosocial variables in older adults. Although younger elders with more education, those who employ active coping strategies, or those who are low in anxiety levels are thought to use computers at higher rates than do others, previous research has produced mixed or inconclusive results regarding ethnic, gender, and psychological factors or has concentrated on computer-specific psychological factors only (e.g., computer anxiety). Few such studies have employed large sample sizes or have focused on ethnically diverse populations of community-dwelling elders. With a large number of overlapping predictors, zero-order analysis alone is poorly equipped to identify variables that are independently associated with computer use. Accordingly, both zero-order and stepwise logistic regression analyses were conducted to determine the correlates of two types of computer use: e-mail and general computer use. Results indicate that younger age, greater level of education, non-Hispanic ethnicity, behaviorally active coping style, general physical health, and role-related emotional health each independently predicted computer usage. Study findings highlight differences in computer usage, especially in regard to Hispanic ethnicity and specific health and well-being factors. Potential applications of this research include future intervention studies, individualized computer-based activity programming, or customizable software and user interface design for older adults responsive to a variety of personal characteristics and capabilities.

Maximal Neighbor Similarity Reveals Real Communities in Networks

PubMed Central

Žalik, Krista Rizman

2015-01-01

An important problem in the analysis of network data is the detection of groups of densely interconnected nodes also called modules or communities. Community structure reveals functions and organizations of networks. Currently used algorithms for community detection in large-scale real-world networks are computationally expensive or require a priori information such as the number or sizes of communities or are not able to give the same resulting partition in multiple runs. In this paper we investigate a simple and fast algorithm that uses the network structure alone and requires neither optimization of pre-defined objective function nor information about number of communities. We propose a bottom up community detection algorithm in which starting from communities consisting of adjacent pairs of nodes and their maximal similar neighbors we find real communities. We show that the overall advantage of the proposed algorithm compared to the other community detection algorithms is its simple nature, low computational cost and its very high accuracy in detection communities of different sizes also in networks with blurred modularity structure consisting of poorly separated communities. All communities identified by the proposed method for facebook network and E-Coli transcriptional regulatory network have strong structural and functional coherence. PMID:26680448

Addressing capability computing challenges of high-resolution global climate modelling at the Oak Ridge Leadership Computing Facility

NASA Astrophysics Data System (ADS)

Anantharaj, Valentine; Norman, Matthew; Evans, Katherine; Taylor, Mark; Worley, Patrick; Hack, James; Mayer, Benjamin

2014-05-01

During 2013, high-resolution climate model simulations accounted for over 100 million "core hours" using Titan at the Oak Ridge Leadership Computing Facility (OLCF). The suite of climate modeling experiments, primarily using the Community Earth System Model (CESM) at nearly 0.25 degree horizontal resolution, generated over a petabyte of data and nearly 100,000 files, ranging in sizes from 20 MB to over 100 GB. Effective utilization of leadership class resources requires careful planning and preparation. The application software, such as CESM, need to be ported, optimized and benchmarked for the target platform in order to meet the computational readiness requirements. The model configuration needs to be "tuned and balanced" for the experiments. This can be a complicated and resource intensive process, especially for high-resolution configurations using complex physics. The volume of I/O also increases with resolution; and new strategies may be required to manage I/O especially for large checkpoint and restart files that may require more frequent output for resiliency. It is also essential to monitor the application performance during the course of the simulation exercises. Finally, the large volume of data needs to be analyzed to derive the scientific results; and appropriate data and information delivered to the stakeholders. Titan is currently the largest supercomputer available for open science. The computational resources, in terms of "titan core hours" are allocated primarily via the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) and ASCR Leadership Computing Challenge (ALCC) programs, both sponsored by the U.S. Department of Energy (DOE) Office of Science. Titan is a Cray XK7 system, capable of a theoretical peak performance of over 27 PFlop/s, consists of 18,688 compute nodes, with a NVIDIA Kepler K20 GPU and a 16-core AMD Opteron CPU in every node, for a total of 299,008 Opteron cores and 18,688 GPUs offering a cumulative 560,640 equivalent cores. Scientific applications, such as CESM, are also required to demonstrate a "computational readiness capability" to efficiently scale across and utilize 20% of the entire system. The 0,25 deg configuration of the spectral element dynamical core of the Community Atmosphere Model (CAM-SE), the atmospheric component of CESM, has been demonstrated to scale efficiently across more than 5,000 nodes (80,000 CPU cores) on Titan. The tracer transport routines of CAM-SE have also been ported to take advantage of the hybrid many-core architecture of Titan using GPUs [see EGU2014-4233], yielding over 2X speedup when transporting over 100 tracers. The high throughput I/O in CESM, based on the Parallel IO Library (PIO), is being further augmented to support even higher resolutions and enhance resiliency. The application performance of the individual runs are archived in a database and routinely analyzed to identify and rectify performance degradation during the course of the experiments. The various resources available at the OLCF now support a scientific workflow to facilitate high-resolution climate modelling. A high-speed center-wide parallel file system, called ATLAS, capable of 1 TB/s, is available on Titan as well as on the clusters used for analysis (Rhea) and visualization (Lens/EVEREST). Long-term archive is facilitated by the HPSS storage system. The Earth System Grid (ESG), featuring search & discovery, is also used to deliver data. The end-to-end workflow allows OLCF users to efficiently share data and publish results in a timely manner.

An assessment technique for computer-socket manufacturing

PubMed Central

Sanders, Joan; Severance, Michael

2015-01-01

An assessment strategy is presented for testing the quality of carving and forming of individual computer aided manufacturing facilities. The strategy is potentially useful to facilities making sockets and companies marketing manufacturing equipment. To execute the strategy, an evaluator fabricates a collection of test models and sockets using the manufacturing suite under evaluation, and then measures their shapes using scanning equipment. Overall socket quality is assessed by comparing socket shapes with electronic file shapes. Then model shapes are compared with electronic file shapes to characterize carving performance. Socket shapes are compared with model shapes to characterize forming performance. The mean radial error (MRE), which is the average difference in radii between the two shapes being compared, provides insight into sizing quality. Inter-quartile range (IQR), the range of radial error for the best matched half of the points on the surfaces being compared, provides insight into shape quality. By determining MRE and IQR for carving and forming separately, the source(s) of socket shape error may be pinpointed. The developed strategy may provide a useful tool to the prosthetics community and industry to help identify problems and limitations in computer aided manufacturing and insight into appropriate modifications to overcome them. PMID:21938663

Efficient, graph-based white matter connectivity from orientation distribution functions via multi-directional graph propagation

NASA Astrophysics Data System (ADS)

Boucharin, Alexis; Oguz, Ipek; Vachet, Clement; Shi, Yundi; Sanchez, Mar; Styner, Martin

2011-03-01

The use of regional connectivity measurements derived from diffusion imaging datasets has become of considerable interest in the neuroimaging community in order to better understand cortical and subcortical white matter connectivity. Current connectivity assessment methods are based on streamline fiber tractography, usually applied in a Monte-Carlo fashion. In this work we present a novel, graph-based method that performs a fully deterministic, efficient and stable connectivity computation. The method handles crossing fibers and deals well with multiple seed regions. The computation is based on a multi-directional graph propagation method applied to sampled orientation distribution function (ODF), which can be computed directly from the original diffusion imaging data. We show early results of our method on synthetic and real datasets. The results illustrate the potential of our method towards subjectspecific connectivity measurements that are performed in an efficient, stable and reproducible manner. Such individual connectivity measurements would be well suited for application in population studies of neuropathology, such as Autism, Huntington's Disease, Multiple Sclerosis or leukodystrophies. The proposed method is generic and could easily be applied to non-diffusion data as long as local directional data can be derived.

Boston Community Information System 1986 Experimental Test Results.

DTIC Science & Technology

1987-08-01

self -selected participants have a strong technical orientation and high educational achievement. In addition, five visually impaired people use the...group. The experimental test of the system was performed on a self -selected population of computer literate volunteers. In order to simplify the test...for fat respose .’ - 1041 OI haven’t used it yet.’ - 1046 ’No modem yet. New version installed 11/2/86.0 - 1047 ’Not yet tried. Wil do so moon.’ - 1061

It's a River, Not a Lake: A Report on Instructional Technology for the Maricopa Community Colleges.

ERIC Educational Resources Information Center

Jacobs, Alan

This report examines the effects of technological change on Arizona's Maricopa County Community College District (MCCCD) and assesses changes and progress made since the publication of MCCCD's Master Plan for Instructional Computing in 1986. The first section views constant change in computer technology as a running stream and examines the need…

The Rise of Computing Research in East Africa: The Relationship between Funding, Capacity and Research Community in a Nascent Field

ERIC Educational Resources Information Center

Harsh, Matthew; Bal, Ravtosh; Wetmore, Jameson; Zachary, G. Pascal; Holden, Kerry

2018-01-01

The emergence of vibrant research communities of computer scientists in Kenya and Uganda has occurred in the context of neoliberal privatization, commercialization, and transnational capital flows from donors and corporations. We explore how this funding environment configures research culture and research practices, which are conceptualized as…

Women in Community College: Factors Related to Intentions to Pursue Computer Science

ERIC Educational Resources Information Center

Denner, Jill; Werner, Linda; O'Connor, Lisa

2015-01-01

Community colleges (CC) are obvious places to recruit more women into computer science. Enrollment at CCs has grown in response to a struggling economy, and students are more likely to be from underrepresented groups than students enrolled in 4-year universities (National Center for Education Statistics, 2008). However, we know little about why so…

Balancing Act: The Struggle between Orality and Linearity in Computer-Mediated Communication.

ERIC Educational Resources Information Center

Metz, J Michel

1996-01-01

Asks whether computer-mediated communication allows creation of isolated virtual communities for its interlocutors or brings closer the ideal of a global community. Examines the question from the standpoint of R. Cathcart and G. Gumpert's medium theory. Uses data derived from an ethnographic study to illustrate how a new approach is required. (PA)

Use of Standardized Test Scores to Predict Success in a Computer Applications Course

ERIC Educational Resources Information Center

Harris, Robert V.

2014-01-01

In this educational study, the research problem was that each semester a variable number of community college students are unable to complete an introductory computer applications course at a community college in the state of Mississippi with a successful course letter grade. Course failure, or non-success, at the collegiate level is a negative…

Computer-Assisted, Counselor-Delivered Smoking Cessation Counseling for Community College Students: Intervention Approach and Sample Characteristics

ERIC Educational Resources Information Center

Prokhorov, Alexander V.; Fouladi, Rachel T.; de Moor, Carl; Warneke, Carla L.; Luca, Mario; Jones, Mary Mullin; Rosenblum, Carol; Emmons, Karen M.; Hudmon, Karen Suchanek; Yost, Tracey E.; Gritz, Ellen R.

2007-01-01

This report presents the experimental approach and baseline findings from "Look at Your Health," an ongoing study to develop and evaluate a computer-assisted, counselor-delivered smoking cessation program for community college students. It describes the expert system software program used for data collection and for provision of tailored feedback,…

The Impact of Computer Assisted Instruction As It Relates to Learning Disabled Adults in California Community Colleges.

ERIC Educational Resources Information Center

Brower, Mary Jo

A study was conducted to determine the advantages and disadvantages of using computer-assisted instruction (CAI) with learning disabled (LD) adults attending California community colleges. A questionnaire survey of the directors of the LD programs solicited information on the availability of CAI for LD adults, methods of course advertisement,…

A Survey of Computer Usage in Adult Education Programs in Florida Report.

ERIC Educational Resources Information Center

Florida State Dept. of Education, Tallahassee. Div. of Vocational, Adult, and Community Education.

A study was conducted to identify the types and uses of computer hardware and software in adult and community education programs in Florida. Information was gathered through a survey instrument developed for the study and mailed to 100 adult and community education directors and adult literacy center coordinators (92 surveys were returned). The…

Decoding communities in networks

NASA Astrophysics Data System (ADS)

Radicchi, Filippo

2018-02-01

According to a recent information-theoretical proposal, the problem of defining and identifying communities in networks can be interpreted as a classical communication task over a noisy channel: memberships of nodes are information bits erased by the channel, edges and nonedges in the network are parity bits introduced by the encoder but degraded through the channel, and a community identification algorithm is a decoder. The interpretation is perfectly equivalent to the one at the basis of well-known statistical inference algorithms for community detection. The only difference in the interpretation is that a noisy channel replaces a stochastic network model. However, the different perspective gives the opportunity to take advantage of the rich set of tools of coding theory to generate novel insights on the problem of community detection. In this paper, we illustrate two main applications of standard coding-theoretical methods to community detection. First, we leverage a state-of-the-art decoding technique to generate a family of quasioptimal community detection algorithms. Second and more important, we show that the Shannon's noisy-channel coding theorem can be invoked to establish a lower bound, here named as decodability bound, for the maximum amount of noise tolerable by an ideal decoder to achieve perfect detection of communities. When computed for well-established synthetic benchmarks, the decodability bound explains accurately the performance achieved by the best community detection algorithms existing on the market, telling us that only little room for their improvement is still potentially left.

Decoding communities in networks.

PubMed

Radicchi, Filippo

2018-02-01

According to a recent information-theoretical proposal, the problem of defining and identifying communities in networks can be interpreted as a classical communication task over a noisy channel: memberships of nodes are information bits erased by the channel, edges and nonedges in the network are parity bits introduced by the encoder but degraded through the channel, and a community identification algorithm is a decoder. The interpretation is perfectly equivalent to the one at the basis of well-known statistical inference algorithms for community detection. The only difference in the interpretation is that a noisy channel replaces a stochastic network model. However, the different perspective gives the opportunity to take advantage of the rich set of tools of coding theory to generate novel insights on the problem of community detection. In this paper, we illustrate two main applications of standard coding-theoretical methods to community detection. First, we leverage a state-of-the-art decoding technique to generate a family of quasioptimal community detection algorithms. Second and more important, we show that the Shannon's noisy-channel coding theorem can be invoked to establish a lower bound, here named as decodability bound, for the maximum amount of noise tolerable by an ideal decoder to achieve perfect detection of communities. When computed for well-established synthetic benchmarks, the decodability bound explains accurately the performance achieved by the best community detection algorithms existing on the market, telling us that only little room for their improvement is still potentially left.

Breaking the computational barriers of pairwise genome comparison.

PubMed

Torreno, Oscar; Trelles, Oswaldo

2015-08-11

Conventional pairwise sequence comparison software algorithms are being used to process much larger datasets than they were originally designed for. This can result in processing bottlenecks that limit software capabilities or prevent full use of the available hardware resources. Overcoming the barriers that limit the efficient computational analysis of large biological sequence datasets by retrofitting existing algorithms or by creating new applications represents a major challenge for the bioinformatics community. We have developed C libraries for pairwise sequence comparison within diverse architectures, ranging from commodity systems to high performance and cloud computing environments. Exhaustive tests were performed using different datasets of closely- and distantly-related sequences that span from small viral genomes to large mammalian chromosomes. The tests demonstrated that our solution is capable of generating high quality results with a linear-time response and controlled memory consumption, being comparable or faster than the current state-of-the-art methods. We have addressed the problem of pairwise and all-versus-all comparison of large sequences in general, greatly increasing the limits on input data size. The approach described here is based on a modular out-of-core strategy that uses secondary storage to avoid reaching memory limits during the identification of High-scoring Segment Pairs (HSPs) between the sequences under comparison. Software engineering concepts were applied to avoid intermediate result re-calculation, to minimise the performance impact of input/output (I/O) operations and to modularise the process, thus enhancing application flexibility and extendibility. Our computationally-efficient approach allows tasks such as the massive comparison of complete genomes, evolutionary event detection, the identification of conserved synteny blocks and inter-genome distance calculations to be performed more effectively.

Building confidence and credibility amid growing model and computing complexity

NASA Astrophysics Data System (ADS)

Evans, K. J.; Mahajan, S.; Veneziani, C.; Kennedy, J. H.

2017-12-01

As global Earth system models are developed to answer an ever-wider range of science questions, software products that provide robust verification, validation, and evaluation must evolve in tandem. Measuring the degree to which these new models capture past behavior, predict the future, and provide the certainty of predictions is becoming ever more challenging for reasons that are generally well known, yet are still challenging to address. Two specific and divergent needs for analysis of the Accelerated Climate Model for Energy (ACME) model - but with a similar software philosophy - are presented to show how a model developer-based focus can address analysis needs during expansive model changes to provide greater fidelity and execute on multi-petascale computing facilities. A-PRIME is a python script-based quick-look overview of a fully-coupled global model configuration to determine quickly if it captures specific behavior before significant computer time and expense is invested. EVE is an ensemble-based software framework that focuses on verification of performance-based ACME model development, such as compiler or machine settings, to determine the equivalence of relevant climate statistics. The challenges and solutions for analysis of multi-petabyte output data are highlighted from the aspect of the scientist using the software, with the aim of fostering discussion and further input from the community about improving developer confidence and community credibility.

International Symposium on Grids and Clouds (ISGC) 2016

NASA Astrophysics Data System (ADS)

The International Symposium on Grids and Clouds (ISGC) 2016 will be held at Academia Sinica in Taipei, Taiwan from 13-18 March 2016, with co-located events and workshops. The conference is hosted by the Academia Sinica Grid Computing Centre (ASGC). The theme of ISGC 2016 focuses on“Ubiquitous e-infrastructures and Applications”. Contemporary research is impossible without a strong IT component - researchers rely on the existence of stable and widely available e-infrastructures and their higher level functions and properties. As a result of these expectations, e-Infrastructures are becoming ubiquitous, providing an environment that supports large scale collaborations that deal with global challenges as well as smaller and temporal research communities focusing on particular scientific problems. To support those diversified communities and their needs, the e-Infrastructures themselves are becoming more layered and multifaceted, supporting larger groups of applications. Following the call for the last year conference, ISGC 2016 continues its aim to bring together users and application developers with those responsible for the development and operation of multi-purpose ubiquitous e-Infrastructures. Topics of discussion include Physics (including HEP) and Engineering Applications, Biomedicine & Life Sciences Applications, Earth & Environmental Sciences & Biodiversity Applications, Humanities, Arts, and Social Sciences (HASS) Applications, Virtual Research Environment (including Middleware, tools, services, workflow, etc.), Data Management, Big Data, Networking & Security, Infrastructure & Operations, Infrastructure Clouds and Virtualisation, Interoperability, Business Models & Sustainability, Highly Distributed Computing Systems, and High Performance & Technical Computing (HPTC), etc.

BarraCUDA - a fast short read sequence aligner using graphics processing units

PubMed Central

2012-01-01

Background With the maturation of next-generation DNA sequencing (NGS) technologies, the throughput of DNA sequencing reads has soared to over 600 gigabases from a single instrument run. General purpose computing on graphics processing units (GPGPU), extracts the computing power from hundreds of parallel stream processors within graphics processing cores and provides a cost-effective and energy efficient alternative to traditional high-performance computing (HPC) clusters. In this article, we describe the implementation of BarraCUDA, a GPGPU sequence alignment software that is based on BWA, to accelerate the alignment of sequencing reads generated by these instruments to a reference DNA sequence. Findings Using the NVIDIA Compute Unified Device Architecture (CUDA) software development environment, we ported the most computational-intensive alignment component of BWA to GPU to take advantage of the massive parallelism. As a result, BarraCUDA offers a magnitude of performance boost in alignment throughput when compared to a CPU core while delivering the same level of alignment fidelity. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the alignment throughput. Conclusions BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the alignment of millions of sequencing reads generated by NGS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology. BarraCUDA is currently available from http://seqbarracuda.sf.net PMID:22244497

Integrated Exoplanet Modeling with the GSFC Exoplanet Modeling & Analysis Center (EMAC)

NASA Astrophysics Data System (ADS)

Mandell, Avi M.; Hostetter, Carl; Pulkkinen, Antti; Domagal-Goldman, Shawn David

2018-01-01

Our ability to characterize the atmospheres of extrasolar planets will be revolutionized by JWST, WFIRST and future ground- and space-based telescopes. In preparation, the exoplanet community must develop an integrated suite of tools with which we can comprehensively predict and analyze observations of exoplanets, in order to characterize the planetary environments and ultimately search them for signs of habitability and life.The GSFC Exoplanet Modeling and Analysis Center (EMAC) will be a web-accessible high-performance computing platform with science support for modelers and software developers to host and integrate their scientific software tools, with the goal of leveraging the scientific contributions from the entire exoplanet community to improve our interpretations of future exoplanet discoveries. Our suite of models will include stellar models, models for star-planet interactions, atmospheric models, planet system science models, telescope models, instrument models, and finally models for retrieving signals from observational data. By integrating this suite of models, the community will be able to self-consistently calculate the emergent spectra from the planet whether from emission, scattering, or in transmission, and use these simulations to model the performance of current and new telescopes and their instrumentation.The EMAC infrastructure will not only provide a repository for planetary and exoplanetary community models, modeling tools and intermodal comparisons, but it will include a "run-on-demand" portal with each software tool hosted on a separate virtual machine. The EMAC system will eventually include a means of running or “checking in” new model simulations that are in accordance with the community-derived standards. Additionally, the results of intermodal comparisons will be used to produce open source publications that quantify the model comparisons and provide an overview of community consensus on model uncertainties on the climates of various planetary targets.

Towards New Metrics for High-Performance Computing Resilience

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

Hukerikar, Saurabh; Ashraf, Rizwan A; Engelmann, Christian

Ensuring the reliability of applications is becoming an increasingly important challenge as high-performance computing (HPC) systems experience an ever-growing number of faults, errors and failures. While the HPC community has made substantial progress in developing various resilience solutions, it continues to rely on platform-based metrics to quantify application resiliency improvements. The resilience of an HPC application is concerned with the reliability of the application outcome as well as the fault handling efficiency. To understand the scope of impact, effective coverage and performance efficiency of existing and emerging resilience solutions, there is a need for new metrics. In this paper, wemore » develop new ways to quantify resilience that consider both the reliability and the performance characteristics of the solutions from the perspective of HPC applications. As HPC systems continue to evolve in terms of scale and complexity, it is expected that applications will experience various types of faults, errors and failures, which will require applications to apply multiple resilience solutions across the system stack. The proposed metrics are intended to be useful for understanding the combined impact of these solutions on an application's ability to produce correct results and to evaluate their overall impact on an application's performance in the presence of various modes of faults.« less

A Fast MHD Code for Gravitationally Stratified Media using Graphical Processing Units: SMAUG

NASA Astrophysics Data System (ADS)

Griffiths, M. K.; Fedun, V.; Erdélyi, R.

2015-03-01

Parallelization techniques have been exploited most successfully by the gaming/graphics industry with the adoption of graphical processing units (GPUs), possessing hundreds of processor cores. The opportunity has been recognized by the computational sciences and engineering communities, who have recently harnessed successfully the numerical performance of GPUs. For example, parallel magnetohydrodynamic (MHD) algorithms are important for numerical modelling of highly inhomogeneous solar, astrophysical and geophysical plasmas. Here, we describe the implementation of SMAUG, the Sheffield Magnetohydrodynamics Algorithm Using GPUs. SMAUG is a 1-3D MHD code capable of modelling magnetized and gravitationally stratified plasma. The objective of this paper is to present the numerical methods and techniques used for porting the code to this novel and highly parallel compute architecture. The methods employed are justified by the performance benchmarks and validation results demonstrating that the code successfully simulates the physics for a range of test scenarios including a full 3D realistic model of wave propagation in the solar atmosphere.

Equivalent Discrete-Time Channel Modeling for Molecular Communication With Emphasize on an Absorbing Receiver.

PubMed

Damrath, Martin; Korte, Sebastian; Hoeher, Peter Adam

2017-01-01

This paper introduces the equivalent discrete-time channel model (EDTCM) to the area of diffusion-based molecular communication (DBMC). Emphasis is on an absorbing receiver, which is based on the so-called first passage time concept. In the wireless communications community the EDTCM is well known. Therefore, it is anticipated that the EDTCM improves the accessibility of DBMC and supports the adaptation of classical wireless communication algorithms to the area of DBMC. Furthermore, the EDTCM has the capability to provide a remarkable reduction of computational complexity compared to random walk based DBMC simulators. Besides the exact EDTCM, three approximations thereof based on binomial, Gaussian, and Poisson approximation are proposed and analyzed in order to further reduce computational complexity. In addition, the Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm is adapted to all four channel models. Numerical results show the performance of the exact EDTCM, illustrate the performance of the adapted BCJR algorithm, and demonstrate the accuracy of the approximations.

Graph Matching: Relax at Your Own Risk.

PubMed

Lyzinski, Vince; Fishkind, Donniell E; Fiori, Marcelo; Vogelstein, Joshua T; Priebe, Carey E; Sapiro, Guillermo

2016-01-01

Graph matching-aligning a pair of graphs to minimize their edge disagreements-has received wide-spread attention from both theoretical and applied communities over the past several decades, including combinatorics, computer vision, and connectomics. Its attention can be partially attributed to its computational difficulty. Although many heuristics have previously been proposed in the literature to approximately solve graph matching, very few have any theoretical support for their performance. A common technique is to relax the discrete problem to a continuous problem, therefore enabling practitioners to bring gradient-descent-type algorithms to bear. We prove that an indefinite relaxation (when solved exactly) almost always discovers the optimal permutation, while a common convex relaxation almost always fails to discover the optimal permutation. These theoretical results suggest that initializing the indefinite algorithm with the convex optimum might yield improved practical performance. Indeed, experimental results illuminate and corroborate these theoretical findings, demonstrating that excellent results are achieved in both benchmark and real data problems by amalgamating the two approaches.

A Technical Survey on Optimization of Processing Geo Distributed Data

NASA Astrophysics Data System (ADS)

Naga Malleswari, T. Y. J.; Ushasukhanya, S.; Nithyakalyani, A.; Girija, S.

2018-04-01

With growing cloud services and technology, there is growth in some geographically distributed data centers to store large amounts of data. Analysis of geo-distributed data is required in various services for data processing, storage of essential information, etc., processing this geo-distributed data and performing analytics on this data is a challenging task. The distributed data processing is accompanied by issues in storage, computation and communication. The key issues to be dealt with are time efficiency, cost minimization, utility maximization. This paper describes various optimization methods like end-to-end multiphase, G-MR, etc., using the techniques like Map-Reduce, CDS (Community Detection based Scheduling), ROUT, Workload-Aware Scheduling, SAGE, AMP (Ant Colony Optimization) to handle these issues. In this paper various optimization methods and techniques used are analyzed. It has been observed that end-to end multiphase achieves time efficiency; Cost minimization concentrates to achieve Quality of Service, Computation and reduction of Communication cost. SAGE achieves performance improvisation in processing geo-distributed data sets.

A Constrained Genetic Algorithm with Adaptively Defined Fitness Function in MRS Quantification

NASA Astrophysics Data System (ADS)

Papakostas, G. A.; Karras, D. A.; Mertzios, B. G.; Graveron-Demilly, D.; van Ormondt, D.

MRS Signal quantification is a rather involved procedure and has attracted the interest of the medical engineering community, regarding the development of computationally efficient methodologies. Significant contributions based on Computational Intelligence tools, such as Neural Networks (NNs), demonstrated a good performance but not without drawbacks already discussed by the authors. On the other hand preliminary application of Genetic Algorithms (GA) has already been reported in the literature by the authors regarding the peak detection problem encountered in MRS quantification using the Voigt line shape model. This paper investigates a novel constrained genetic algorithm involving a generic and adaptively defined fitness function which extends the simple genetic algorithm methodology in case of noisy signals. The applicability of this new algorithm is scrutinized through experimentation in artificial MRS signals interleaved with noise, regarding its signal fitting capabilities. Although extensive experiments with real world MRS signals are necessary, the herein shown performance illustrates the method's potential to be established as a generic MRS metabolites quantification procedure.

Multiscale Computer Simulation of Failure in Aerogels

NASA Technical Reports Server (NTRS)

Good, Brian S.

2008-01-01

Aerogels have been of interest to the aerospace community primarily for their thermal properties, notably their low thermal conductivities. While such gels are typically fragile, recent advances in the application of conformal polymer layers to these gels has made them potentially useful as lightweight structural materials as well. We have previously performed computer simulations of aerogel thermal conductivity and tensile and compressive failure, with results that are in qualitative, and sometimes quantitative, agreement with experiment. However, recent experiments in our laboratory suggest that gels having similar densities may exhibit substantially different properties. In this work, we extend our original diffusion limited cluster aggregation (DLCA) model for gel structure to incorporate additional variation in DLCA simulation parameters, with the aim of producing DLCA clusters of similar densities that nevertheless have different fractal dimension and secondary particle coordination. We perform particle statics simulations of gel strain on these clusters, and consider the effects of differing DLCA simulation conditions, and the resultant differences in fractal dimension and coordination, on gel strain properties.

Current and anticipated uses of the thermal hydraulics codes at the NRC

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

Caruso, R.

1997-07-01

The focus of Thermal-Hydraulic computer code usage in nuclear regulatory organizations has undergone a considerable shift since the codes were originally conceived. Less work is being done in the area of {open_quotes}Design Basis Accidents,{close_quotes}, and much more emphasis is being placed on analysis of operational events, probabalistic risk/safety assessment, and maintenance practices. All of these areas need support from Thermal-Hydraulic computer codes to model the behavior of plant fluid systems, and they all need the ability to perform large numbers of analyses quickly. It is therefore important for the T/H codes of the future to be able to support thesemore » needs, by providing robust, easy-to-use, tools that produce easy-to understand results for a wider community of nuclear professionals. These tools need to take advantage of the great advances that have occurred recently in computer software, by providing users with graphical user interfaces for both input and output. In addition, reduced costs of computer memory and other hardware have removed the need for excessively complex data structures and numerical schemes, which make the codes more difficult and expensive to modify, maintain, and debug, and which increase problem run-times. Future versions of the T/H codes should also be structured in a modular fashion, to allow for the easy incorporation of new correlations, models, or features, and to simplify maintenance and testing. Finally, it is important that future T/H code developers work closely with the code user community, to ensure that the code meet the needs of those users.« less

Towards Test Driven Development for Computational Science with pFUnit

NASA Technical Reports Server (NTRS)

Rilee, Michael L.; Clune, Thomas L.

2014-01-01

Developers working in Computational Science & Engineering (CSE)/High Performance Computing (HPC) must contend with constant change due to advances in computing technology and science. Test Driven Development (TDD) is a methodology that mitigates software development risks due to change at the cost of adding comprehensive and continuous testing to the development process. Testing frameworks tailored for CSE/HPC, like pFUnit, can lower the barriers to such testing, yet CSE software faces unique constraints foreign to the broader software engineering community. Effective testing of numerical software requires a comprehensive suite of oracles, i.e., use cases with known answers, as well as robust estimates for the unavoidable numerical errors associated with implementation with finite-precision arithmetic. At first glance these concerns often seem exceedingly challenging or even insurmountable for real-world scientific applications. However, we argue that this common perception is incorrect and driven by (1) a conflation between model validation and software verification and (2) the general tendency in the scientific community to develop relatively coarse-grained, large procedures that compound numerous algorithmic steps.We believe TDD can be applied routinely to numerical software if developers pursue fine-grained implementations that permit testing, neatly side-stepping concerns about needing nontrivial oracles as well as the accumulation of errors. We present an example of a successful, complex legacy CSE/HPC code whose development process shares some aspects with TDD, which we contrast with current and potential capabilities. A mix of our proposed methodology and framework support should enable everyday use of TDD by CSE-expert developers.

Meshless collocation methods for the numerical solution of elliptic boundary valued problems the rotational shallow water equations on the sphere

NASA Astrophysics Data System (ADS)

Blakely, Christopher D.

This dissertation thesis has three main goals: (1) To explore the anatomy of meshless collocation approximation methods that have recently gained attention in the numerical analysis community; (2) Numerically demonstrate why the meshless collocation method should clearly become an attractive alternative to standard finite-element methods due to the simplicity of its implementation and its high-order convergence properties; (3) Propose a meshless collocation method for large scale computational geophysical fluid dynamics models. We provide numerical verification and validation of the meshless collocation scheme applied to the rotational shallow-water equations on the sphere and demonstrate computationally that the proposed model can compete with existing high performance methods for approximating the shallow-water equations such as the SEAM (spectral-element atmospheric model) developed at NCAR. A detailed analysis of the parallel implementation of the model, along with the introduction of parallel algorithmic routines for the high-performance simulation of the model will be given. We analyze the programming and computational aspects of the model using Fortran 90 and the message passing interface (mpi) library along with software and hardware specifications and performance tests. Details from many aspects of the implementation in regards to performance, optimization, and stabilization will be given. In order to verify the mathematical correctness of the algorithms presented and to validate the performance of the meshless collocation shallow-water model, we conclude the thesis with numerical experiments on some standardized test cases for the shallow-water equations on the sphere using the proposed method.

Marshal Wrubel and the Electronic Computer as an Astronomical Instrument

NASA Astrophysics Data System (ADS)

Mutschlecner, J. P.; Olsen, K. H.

1998-05-01

In 1960, Marshal H. Wrubel, professor of astrophysics at Indiana University, published an influential review paper under the title, "The Electronic Computer as an Astronomical Instrument." This essay pointed out the enormous potential of the electronic computer as an instrument of observational and theoretical research in astronomy, illustrated programming concepts, and made specific recommendations for the increased use of computers in astronomy. He noted that, with a few scattered exceptions, computer use by the astronomical community had heretofore been "timid and sporadic." This situation was to improve dramatically in the next few years. By the late 1950s, general-purpose, high-speed, "mainframe" computers were just emerging from the experimental, developmental stage, but few were affordable by or available to academic and research institutions not closely associated with large industrial or national defense programs. Yet by 1960 Wrubel had spent a decade actively pioneering and promoting the imaginative application of electronic computation within the astronomical community. Astronomy upper-level undergraduate and graduate students at Indiana were introduced to computing, and Ph.D. candidates who he supervised applied computer techniques to problems in theoretical astrophysics. He wrote an early textbook on programming, taught programming classes, and helped establish and direct the Research Computing Center at Indiana, later named the Wrubel Computing Center in his honor. He and his students created a variety of algorithms and subroutines and exchanged these throughout the astronomical community by distributing the Astronomical Computation News Letter. Nationally as well as internationally, Wrubel actively cooperated with other groups interested in computing applications for theoretical astrophysics, often through his position as secretary of the IAU commission on Stellar Constitution.

Acceptability of a Virtual Patient Educator for Hispanic Women.

PubMed

Wells, Kristen J; Vàzquez-Otero, Coralia; Bredice, Marissa; Meade, Cathy D; Chaet, Alexis; Rivera, Maria I; Arroyo, Gloria; Proctor, Sara K; Barnes, Laura E

2015-01-01

There are few Spanish language interactive, technology-driven health education programs. Objectives of this feasibility study were to (a) learn more about computer and technology usage among Hispanic women living in a rural community and (b) evaluate acceptability of the concept of using an embodied conversational agent (ECA) computer application among this population. A survey about computer usage history and interest in computers was administered to a convenience sample of 26 women. A sample video prototype of a hospital discharge ECA was administered followed by questions to gauge opinion about the ECA. Data indicate women exhibited both a high level of computer experience and enthusiasm for the ECA. Feedback from community is essential to ensure equity in state of the art dissemination of health information.

RayPlus: a Web-Based Platform for Medical Image Processing.

PubMed

Yuan, Rong; Luo, Ming; Sun, Zhi; Shi, Shuyue; Xiao, Peng; Xie, Qingguo

2017-04-01

Medical image can provide valuable information for preclinical research, clinical diagnosis, and treatment. As the widespread use of digital medical imaging, many researchers are currently developing medical image processing algorithms and systems in order to accommodate a better result to clinical community, including accurate clinical parameters or processed images from the original images. In this paper, we propose a web-based platform to present and process medical images. By using Internet and novel database technologies, authorized users can easily access to medical images and facilitate their workflows of processing with server-side powerful computing performance without any installation. We implement a series of algorithms of image processing and visualization in the initial version of Rayplus. Integration of our system allows much flexibility and convenience for both research and clinical communities.

Building a Community Infrastructure for Scalable On-Line Performance Analysis Tools around Open|Speedshop

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

Miller, Barton

2014-06-30

Peta-scale computing environments pose significant challenges for both system and application developers and addressing them required more than simply scaling up existing tera-scale solutions. Performance analysis tools play an important role in gaining this understanding, but previous monolithic tools with fixed feature sets have not sufficed. Instead, this project worked on the design, implementation, and evaluation of a general, flexible tool infrastructure supporting the construction of performance tools as “pipelines” of high-quality tool building blocks. These tool building blocks provide common performance tool functionality, and are designed for scalability, lightweight data acquisition and analysis, and interoperability. For this project, wemore » built on Open|SpeedShop, a modular and extensible open source performance analysis tool set. The design and implementation of such a general and reusable infrastructure targeted for petascale systems required us to address several challenging research issues. All components needed to be designed for scale, a task made more difficult by the need to provide general modules. The infrastructure needed to support online data aggregation to cope with the large amounts of performance and debugging data. We needed to be able to map any combination of tool components to each target architecture. And we needed to design interoperable tool APIs and workflows that were concrete enough to support the required functionality, yet provide the necessary flexibility to address a wide range of tools. A major result of this project is the ability to use this scalable infrastructure to quickly create tools that match with a machine architecture and a performance problem that needs to be understood. Another benefit is the ability for application engineers to use the highly scalable, interoperable version of Open|SpeedShop, which are reassembled from the tool building blocks into a flexible, multi-user interface set of tools. This set of tools targeted at Office of Science Leadership Class computer systems and selected Office of Science application codes. We describe the contributions made by the team at the University of Wisconsin. The project built on the efforts in Open|SpeedShop funded by DOE/NNSA and the DOE/NNSA Tri-Lab community, extended Open|Speedshop to the Office of Science Leadership Class Computing Facilities, and addressed new challenges found on these cutting edge systems. Work done under this project at Wisconsin can be divided into two categories, new algorithms and techniques for debugging, and foundation infrastructure work on our Dyninst binary analysis and instrumentation toolkits and MRNet scalability infrastructure.« less

Research in the Classroom: Talk, Texts, and Inquiry.

ERIC Educational Resources Information Center

Donoahue, Zoe, Ed.; And Others

This book presents nine studies conducted by teacher researchers who explore the oral and written discourse of learning communities--communities of students, communities of teachers, and communities in which students and teachers learn together. The studies focus on journal writing, conversation, story telling, geometry, computer technology, and…

Wyoming Community College Commission Agency Annual Report.

ERIC Educational Resources Information Center

Wyoming Community Coll. Commission, Cheyenne.

This paper reports on outcomes of community college programs monitored by the Wyoming Community College Commission (WCCC). The document covers the following WCCC objectives: (1) Study of tuition rates for the community colleges; (2) Negotiation of contracts and provision of financial support for administrative computing system components and…

GeoBrain Computational Cyber-laboratory for Earth Science Studies

NASA Astrophysics Data System (ADS)

Deng, M.; di, L.

2009-12-01

Computational approaches (e.g., computer-based data visualization, analysis and modeling) are critical for conducting increasingly data-intensive Earth science (ES) studies to understand functions and changes of the Earth system. However, currently Earth scientists, educators, and students have met two major barriers that prevent them from being effectively using computational approaches in their learning, research and application activities. The two barriers are: 1) difficulties in finding, obtaining, and using multi-source ES data; and 2) lack of analytic functions and computing resources (e.g., analysis software, computing models, and high performance computing systems) to analyze the data. Taking advantages of recent advances in cyberinfrastructure, Web service, and geospatial interoperability technologies, GeoBrain, a project funded by NASA, has developed a prototype computational cyber-laboratory to effectively remove the two barriers. The cyber-laboratory makes ES data and computational resources at large organizations in distributed locations available to and easily usable by the Earth science community through 1) enabling seamless discovery, access and retrieval of distributed data, 2) federating and enhancing data discovery with a catalogue federation service and a semantically-augmented catalogue service, 3) customizing data access and retrieval at user request with interoperable, personalized, and on-demand data access and services, 4) automating or semi-automating multi-source geospatial data integration, 5) developing a large number of analytic functions as value-added, interoperable, and dynamically chainable geospatial Web services and deploying them in high-performance computing facilities, 6) enabling the online geospatial process modeling and execution, and 7) building a user-friendly extensible web portal for users to access the cyber-laboratory resources. Users can interactively discover the needed data and perform on-demand data analysis and modeling through the web portal. The GeoBrain cyber-laboratory provides solutions to meet common needs of ES research and education, such as, distributed data access and analysis services, easy access to and use of ES data, and enhanced geoprocessing and geospatial modeling capability. It greatly facilitates ES research, education, and applications. The development of the cyber-laboratory provides insights, lessons-learned, and technology readiness to build more capable computing infrastructure for ES studies, which can meet wide-range needs of current and future generations of scientists, researchers, educators, and students for their formal or informal educational training, research projects, career development, and lifelong learning.

Using Java for distributed computing in the Gaia satellite data processing

NASA Astrophysics Data System (ADS)

O'Mullane, William; Luri, Xavier; Parsons, Paul; Lammers, Uwe; Hoar, John; Hernandez, Jose

2011-10-01

In recent years Java has matured to a stable easy-to-use language with the flexibility of an interpreter (for reflection etc.) but the performance and type checking of a compiled language. When we started using Java for astronomical applications around 1999 they were the first of their kind in astronomy. Now a great deal of astronomy software is written in Java as are many business applications. We discuss the current environment and trends concerning the language and present an actual example of scientific use of Java for high-performance distributed computing: ESA's mission Gaia. The Gaia scanning satellite will perform a galactic census of about 1,000 million objects in our galaxy. The Gaia community has chosen to write its processing software in Java. We explore the manifold reasons for choosing Java for this large science collaboration. Gaia processing is numerically complex but highly distributable, some parts being embarrassingly parallel. We describe the Gaia processing architecture and its realisation in Java. We delve into the astrometric solution which is the most advanced and most complex part of the processing. The Gaia simulator is also written in Java and is the most mature code in the system. This has been successfully running since about 2005 on the supercomputer "Marenostrum" in Barcelona. We relate experiences of using Java on a large shared machine. Finally we discuss Java, including some of its problems, for scientific computing.

ArrayBridge: Interweaving declarative array processing with high-performance computing

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

Xing, Haoyuan; Floratos, Sofoklis; Blanas, Spyros

Scientists are increasingly turning to datacenter-scale computers to produce and analyze massive arrays. Despite decades of database research that extols the virtues of declarative query processing, scientists still write, debug and parallelize imperative HPC kernels even for the most mundane queries. This impedance mismatch has been partly attributed to the cumbersome data loading process; in response, the database community has proposed in situ mechanisms to access data in scientific file formats. Scientists, however, desire more than a passive access method that reads arrays from files. This paper describes ArrayBridge, a bi-directional array view mechanism for scientific file formats, that aimsmore » to make declarative array manipulations interoperable with imperative file-centric analyses. Our prototype implementation of ArrayBridge uses HDF5 as the underlying array storage library and seamlessly integrates into the SciDB open-source array database system. In addition to fast querying over external array objects, ArrayBridge produces arrays in the HDF5 file format just as easily as it can read from it. ArrayBridge also supports time travel queries from imperative kernels through the unmodified HDF5 API, and automatically deduplicates between array versions for space efficiency. Our extensive performance evaluation in NERSC, a large-scale scientific computing facility, shows that ArrayBridge exhibits statistically indistinguishable performance and I/O scalability to the native SciDB storage engine.« less

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

Madduri, Kamesh; Im, Eun-Jin; Ibrahim, Khaled Z.

The next decade of high-performance computing (HPC) systems will see a rapid evolution and divergence of multi- and manycore architectures as power and cooling constraints limit increases in microprocessor clock speeds. Understanding efficient optimization methodologies on diverse multicore designs in the context of demanding numerical methods is one of the greatest challenges faced today by the HPC community. In this paper, we examine the efficient multicore optimization of GTC, a petascale gyrokinetic toroidal fusion code for studying plasma microturbulence in tokamak devices. For GTC’s key computational components (charge deposition and particle push), we explore efficient parallelization strategies across a broadmore » range of emerging multicore designs, including the recently-released Intel Nehalem-EX, the AMD Opteron Istanbul, and the highly multithreaded Sun UltraSparc T2+. We also present the first study on tuning gyrokinetic particle-in-cell (PIC) algorithms for graphics processors, using the NVIDIA C2050 (Fermi). Our work discusses several novel optimization approaches for gyrokinetic PIC, including mixed-precision computation, particle binning and decomposition strategies, grid replication, SIMDized atomic floating-point operations, and effective GPU texture memory utilization. Overall, we achieve significant performance improvements of 1.3–4.7× on these complex PIC kernels, despite the inherent challenges of data dependency and locality. Finally, our work also points to several architectural and programming features that could significantly enhance PIC performance and productivity on next-generation architectures.« less

Genre Analysis of Tax Computation Letters: How and Why Tax Accountants Write the Way They Do

ERIC Educational Resources Information Center

Flowerdew, John; Wan, Alina

2006-01-01

This study is a genre analysis which explores the specific discourse community of tax accountants. Tax computation letters from one international accounting firm in Hong Kong were analyzed and compared. To probe deeper into the tax accounting discourse community, a group of tax accountants from the same firm was observed and questioned. The texts…

Simulating the Dynamics of Subsistence Fishing Communities: REEFGAME as a Learning and Data-Gathering Computer-Assisted Role-Play Game

ERIC Educational Resources Information Center

Cleland, Deborah; Dray, Anne; Perez, Pascal; Cruz-Trinidad, Annabelle; Geronimo, Rollan

2012-01-01

REEFGAME is a computer-assisted role-playing game that explores the interactions among management strategies, livelihood options, and ecological degradation in subsistence fishing communities. The tool has been successfully used in the Philippines and a variety of student workshops. In the field, REEFGAME operated as a two-way learning tool,…

Using Computational Modeling to Assess the Impact of Clinical Decision Support on Cancer Screening within Community Health Centers

PubMed Central

Carney, Timothy Jay; Morgan, Geoffrey P.; Jones, Josette; McDaniel, Anna M.; Weaver, Michael; Weiner, Bryan; Haggstrom, David A.

2014-01-01

Our conceptual model demonstrates our goal to investigate the impact of clinical decision support (CDS) utilization on cancer screening improvement strategies in the community health care (CHC) setting. We employed a dual modeling technique using both statistical and computational modeling to evaluate impact. Our statistical model used the Spearman’s Rho test to evaluate the strength of relationship between our proximal outcome measures (CDS utilization) against our distal outcome measure (provider self-reported cancer screening improvement). Our computational model relied on network evolution theory and made use of a tool called Construct-TM to model the use of CDS measured by the rate of organizational learning. We employed the use of previously collected survey data from community health centers Cancer Health Disparities Collaborative (HDCC). Our intent is to demonstrate the added valued gained by using a computational modeling tool in conjunction with a statistical analysis when evaluating the impact a health information technology, in the form of CDS, on health care quality process outcomes such as facility-level screening improvement. Significant simulated disparities in organizational learning over time were observed between community health centers beginning the simulation with high and low clinical decision support capability. PMID:24953241

Computer Aided Manufacturing.

ERIC Educational Resources Information Center

Insolia, Gerard

This document contains course outlines in computer-aided manufacturing developed for a business-industry technology resource center for firms in eastern Pennsylvania by Northampton Community College. The four units of the course cover the following: (1) introduction to computer-assisted design (CAD)/computer-assisted manufacturing (CAM); (2) CAM…