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.

Performance Analysis of Cloud Computing Architectures Using Discrete Event Simulation

NASA Technical Reports Server (NTRS)

Stocker, John C.; Golomb, Andrew M.

2011-01-01

Cloud computing offers the economic benefit of on-demand resource allocation to meet changing enterprise computing needs. However, the flexibility of cloud computing is disadvantaged when compared to traditional hosting in providing predictable application and service performance. Cloud computing relies on resource scheduling in a virtualized network-centric server environment, which makes static performance analysis infeasible. We developed a discrete event simulation model to evaluate the overall effectiveness of organizations in executing their workflow in traditional and cloud computing architectures. The two part model framework characterizes both the demand using a probability distribution for each type of service request as well as enterprise computing resource constraints. Our simulations provide quantitative analysis to design and provision computing architectures that maximize overall mission effectiveness. We share our analysis of key resource constraints in cloud computing architectures and findings on the appropriateness of cloud computing in various applications.

Dynamic VM Provisioning for TORQUE in a Cloud Environment

NASA Astrophysics Data System (ADS)

Zhang, S.; Boland, L.; Coddington, P.; Sevior, M.

2014-06-01

Cloud computing, also known as an Infrastructure-as-a-Service (IaaS), is attracting more interest from the commercial and educational sectors as a way to provide cost-effective computational infrastructure. It is an ideal platform for researchers who must share common resources but need to be able to scale up to massive computational requirements for specific periods of time. This paper presents the tools and techniques developed to allow the open source TORQUE distributed resource manager and Maui cluster scheduler to dynamically integrate OpenStack cloud resources into existing high throughput computing clusters.

Self-guaranteed measurement-based quantum computation

NASA Astrophysics Data System (ADS)

Hayashi, Masahito; Hajdušek, Michal

2018-05-01

In order to guarantee the output of a quantum computation, we usually assume that the component devices are trusted. However, when the total computation process is large, it is not easy to guarantee the whole system when we have scaling effects, unexpected noise, or unaccounted for correlations between several subsystems. If we do not trust the measurement basis or the prepared entangled state, we do need to be worried about such uncertainties. To this end, we propose a self-guaranteed protocol for verification of quantum computation under the scheme of measurement-based quantum computation where no prior-trusted devices (measurement basis or entangled state) are needed. The approach we present enables the implementation of verifiable quantum computation using the measurement-based model in the context of a particular instance of delegated quantum computation where the server prepares the initial computational resource and sends it to the client, who drives the computation by single-qubit measurements. Applying self-testing procedures, we are able to verify the initial resource as well as the operation of the quantum devices and hence the computation itself. The overhead of our protocol scales with the size of the initial resource state to the power of 4 times the natural logarithm of the initial state's size.

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.

Exploring Cloud Computing for Large-scale Scientific Applications

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

Lin, Guang; Han, Binh; Yin, Jian

This paper explores cloud computing for large-scale data-intensive scientific applications. Cloud computing is attractive because it provides hardware and software resources on-demand, which relieves the burden of acquiring and maintaining a huge amount of resources that may be used only once by a scientific application. However, unlike typical commercial applications that often just requires a moderate amount of ordinary resources, large-scale scientific applications often need to process enormous amount of data in the terabyte or even petabyte range and require special high performance hardware with low latency connections to complete computation in a reasonable amount of time. To address thesemore » challenges, we build an infrastructure that can dynamically select high performance computing hardware across institutions and dynamically adapt the computation to the selected resources to achieve high performance. We have also demonstrated the effectiveness of our infrastructure by building a system biology application and an uncertainty quantification application for carbon sequestration, which can efficiently utilize data and computation resources across several institutions.« less

Functional requirements of computer systems for the U.S. Geological Survey, Water Resources Division, 1988-97

USGS Publications Warehouse

Hathaway, R.M.; McNellis, J.M.

1989-01-01

Investigating the occurrence, quantity, quality, distribution, and movement of the Nation 's water resources is the principal mission of the U.S. Geological Survey 's Water Resources Division. Reports of these investigations are published and available to the public. To accomplish this mission, the Division requires substantial computer technology to process, store, and analyze data from more than 57,000 hydrologic sites. The Division 's computer resources are organized through the Distributed Information System Program Office that manages the nationwide network of computers. The contract that provides the major computer components for the Water Resources Division 's Distributed information System expires in 1991. Five work groups were organized to collect the information needed to procure a new generation of computer systems for the U. S. Geological Survey, Water Resources Division. Each group was assigned a major Division activity and asked to describe its functional requirements of computer systems for the next decade. The work groups and major activities are: (1) hydrologic information; (2) hydrologic applications; (3) geographic information systems; (4) reports and electronic publishing; and (5) administrative. The work groups identified 42 functions and described their functional requirements for 1988, 1992, and 1997. A few new functions such as Decision Support Systems and Executive Information Systems, were identified, but most are the same as performed today. Although the number of functions will remain about the same, steady growth in the size, complexity, and frequency of many functions is predicted for the next decade. No compensating increase in the Division 's staff is anticipated during this period. To handle the increased workload and perform these functions, new approaches will be developed that use advanced computer technology. The advanced technology is required in a unified, tightly coupled system that will support all functions simultaneously. The new approaches and expanded use of computers will require substantial increases in the quantity and sophistication of the Division 's computer resources. The requirements presented in this report will be used to develop technical specifications that describe the computer resources needed during the 1990's. (USGS)

Desktop Computing Integration Project

NASA Technical Reports Server (NTRS)

Tureman, Robert L., Jr.

1992-01-01

The Desktop Computing Integration Project for the Human Resources Management Division (HRMD) of LaRC was designed to help division personnel use personal computing resources to perform job tasks. The three goals of the project were to involve HRMD personnel in desktop computing, link mainframe data to desktop capabilities, and to estimate training needs for the division. The project resulted in increased usage of personal computers by Awards specialists, an increased awareness of LaRC resources to help perform tasks, and personal computer output that was used in presentation of information to center personnel. In addition, the necessary skills for HRMD personal computer users were identified. The Awards Office was chosen for the project because of the consistency of their data requests and the desire of employees in that area to use the personal computer.

The Computing and Data Grid Approach: Infrastructure for Distributed Science Applications

NASA Technical Reports Server (NTRS)

Johnston, William E.

2002-01-01

With the advent of Grids - infrastructure for using and managing widely distributed computing and data resources in the science environment - there is now an opportunity to provide a standard, large-scale, computing, data, instrument, and collaboration environment for science that spans many different projects and provides the required infrastructure and services in a relatively uniform and supportable way. Grid technology has evolved over the past several years to provide the services and infrastructure needed for building 'virtual' systems and organizations. We argue that Grid technology provides an excellent basis for the creation of the integrated environments that can combine the resources needed to support the large- scale science projects located at multiple laboratories and universities. We present some science case studies that indicate that a paradigm shift in the process of science will come about as a result of Grids providing transparent and secure access to advanced and integrated information and technologies infrastructure: powerful computing systems, large-scale data archives, scientific instruments, and collaboration tools. These changes will be in the form of services that can be integrated with the user's work environment, and that enable uniform and highly capable access to these computers, data, and instruments, regardless of the location or exact nature of these resources. These services will integrate transient-use resources like computing systems, scientific instruments, and data caches (e.g., as they are needed to perform a simulation or analyze data from a single experiment); persistent-use resources. such as databases, data catalogues, and archives, and; collaborators, whose involvement will continue for the lifetime of a project or longer. While we largely address large-scale science in this paper, Grids, particularly when combined with Web Services, will address a broad spectrum of science scenarios. both large and small scale.

APL: An Alternative to the Multi-Language Environment for Education. Systems Research Memo Number Four.

ERIC Educational Resources Information Center

Lippert, Henry T.; Harris, Edward V.

The diverse requirements for computing facilities in education place heavy demands upon available resources. Although multiple or very large computers can supply such diverse needs, their cost makes them impractical for many institutions. Small computers which serve a few specific needs may be an economical answer. However, to serve operationally…

Galaxy CloudMan: delivering cloud compute clusters.

PubMed

Afgan, Enis; Baker, Dannon; Coraor, Nate; Chapman, Brad; Nekrutenko, Anton; Taylor, James

2010-12-21

Widespread adoption of high-throughput sequencing has greatly increased the scale and sophistication of computational infrastructure needed to perform genomic research. An alternative to building and maintaining local infrastructure is "cloud computing", which, in principle, offers on demand access to flexible computational infrastructure. However, cloud computing resources are not yet suitable for immediate "as is" use by experimental biologists. We present a cloud resource management system that makes it possible for individual researchers to compose and control an arbitrarily sized compute cluster on Amazon's EC2 cloud infrastructure without any informatics requirements. Within this system, an entire suite of biological tools packaged by the NERC Bio-Linux team (http://nebc.nerc.ac.uk/tools/bio-linux) is available for immediate consumption. The provided solution makes it possible, using only a web browser, to create a completely configured compute cluster ready to perform analysis in less than five minutes. Moreover, we provide an automated method for building custom deployments of cloud resources. This approach promotes reproducibility of results and, if desired, allows individuals and labs to add or customize an otherwise available cloud system to better meet their needs. The expected knowledge and associated effort with deploying a compute cluster in the Amazon EC2 cloud is not trivial. The solution presented in this paper eliminates these barriers, making it possible for researchers to deploy exactly the amount of computing power they need, combined with a wealth of existing analysis software, to handle the ongoing data deluge.

Natural Resource Information System. Volume I. Overall Description.

ERIC Educational Resources Information Center

Boeing Computer Services, Inc., Seattle, WA.

Recognizing the need for the development of a computer based information system which would handle remote sensing as well as conventional mapping data, the Bureau of Indian Affairs and the Bureau of Land Management contracted with Boeing Computer Services for the design and construction of a prototype Natural Resource Information System. The…

SCEAPI: A unified Restful Web API for High-Performance Computing

NASA Astrophysics Data System (ADS)

Rongqiang, Cao; Haili, Xiao; Shasha, Lu; Yining, Zhao; Xiaoning, Wang; Xuebin, Chi

2017-10-01

The development of scientific computing is increasingly moving to collaborative web and mobile applications. All these applications need high-quality programming interface for accessing heterogeneous computing resources consisting of clusters, grid computing or cloud computing. In this paper, we introduce our high-performance computing environment that integrates computing resources from 16 HPC centers across China. Then we present a bundle of web services called SCEAPI and describe how it can be used to access HPC resources with HTTP or HTTPs protocols. We discuss SCEAPI from several aspects including architecture, implementation and security, and address specific challenges in designing compatible interfaces and protecting sensitive data. We describe the functions of SCEAPI including authentication, file transfer and job management for creating, submitting and monitoring, and how to use SCEAPI in an easy-to-use way. Finally, we discuss how to exploit more HPC resources quickly for the ATLAS experiment by implementing the custom ARC compute element based on SCEAPI, and our work shows that SCEAPI is an easy-to-use and effective solution to extend opportunistic HPC resources.

ADP Analysis project for the Human Resources Management Division

NASA Technical Reports Server (NTRS)

Tureman, Robert L., Jr.

1993-01-01

The ADP (Automated Data Processing) Analysis Project was conducted for the Human Resources Management Division (HRMD) of NASA's Langley Research Center. The three major areas of work in the project were computer support, automated inventory analysis, and an ADP study for the Division. The goal of the computer support work was to determine automation needs of Division personnel and help them solve computing problems. The goal of automated inventory analysis was to find a way to analyze installed software and usage on a Macintosh. Finally, the ADP functional systems study for the Division was designed to assess future HRMD needs concerning ADP organization and activities.

Dynamically allocating sets of fine-grained processors to running computations

NASA Technical Reports Server (NTRS)

Middleton, David

1988-01-01

Researchers explore an approach to using general purpose parallel computers which involves mapping hardware resources onto computations instead of mapping computations onto hardware. Problems such as processor allocation, task scheduling and load balancing, which have traditionally proven to be challenging, change significantly under this approach and may become amenable to new attacks. Researchers describe the implementation of this approach used by the FFP Machine whose computation and communication resources are repeatedly partitioned into disjoint groups that match the needs of available tasks from moment to moment. Several consequences of this system are examined.

Galaxy CloudMan: delivering cloud compute clusters

PubMed Central

2010-01-01

Background Widespread adoption of high-throughput sequencing has greatly increased the scale and sophistication of computational infrastructure needed to perform genomic research. An alternative to building and maintaining local infrastructure is “cloud computing”, which, in principle, offers on demand access to flexible computational infrastructure. However, cloud computing resources are not yet suitable for immediate “as is” use by experimental biologists. Results We present a cloud resource management system that makes it possible for individual researchers to compose and control an arbitrarily sized compute cluster on Amazon’s EC2 cloud infrastructure without any informatics requirements. Within this system, an entire suite of biological tools packaged by the NERC Bio-Linux team (http://nebc.nerc.ac.uk/tools/bio-linux) is available for immediate consumption. The provided solution makes it possible, using only a web browser, to create a completely configured compute cluster ready to perform analysis in less than five minutes. Moreover, we provide an automated method for building custom deployments of cloud resources. This approach promotes reproducibility of results and, if desired, allows individuals and labs to add or customize an otherwise available cloud system to better meet their needs. Conclusions The expected knowledge and associated effort with deploying a compute cluster in the Amazon EC2 cloud is not trivial. The solution presented in this paper eliminates these barriers, making it possible for researchers to deploy exactly the amount of computing power they need, combined with a wealth of existing analysis software, to handle the ongoing data deluge. PMID:21210983

Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter

PubMed Central

Loganathan, Shyamala; Mukherjee, Saswati

2015-01-01

Cloud computing is an on-demand computing model, which uses virtualization technology to provide cloud resources to users in the form of virtual machines through internet. Being an adaptable technology, cloud computing is an excellent alternative for organizations for forming their own private cloud. Since the resources are limited in these private clouds maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. For that, efficient scheduling is needed. This research reports on an efficient data structure for resource management and resource scheduling technique in a private cloud environment and discusses a cloud model. The proposed scheduling algorithm considers the types of jobs and the resource availability in its scheduling decision. Finally, we conducted simulations using CloudSim and compared our algorithm with other existing methods, like V-MCT and priority scheduling algorithms. PMID:26473166

Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter.

PubMed

Loganathan, Shyamala; Mukherjee, Saswati

2015-01-01

Cloud computing is an on-demand computing model, which uses virtualization technology to provide cloud resources to users in the form of virtual machines through internet. Being an adaptable technology, cloud computing is an excellent alternative for organizations for forming their own private cloud. Since the resources are limited in these private clouds maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. For that, efficient scheduling is needed. This research reports on an efficient data structure for resource management and resource scheduling technique in a private cloud environment and discusses a cloud model. The proposed scheduling algorithm considers the types of jobs and the resource availability in its scheduling decision. Finally, we conducted simulations using CloudSim and compared our algorithm with other existing methods, like V-MCT and priority scheduling algorithms.

Computer Literacy and Societal Impact of Computers: Education and Manpower.

ERIC Educational Resources Information Center

Hamblen, John W.

The use of computers in education and general society is continually expanding, but the growing need for highly educated computer technologists will continue unless universities take major steps toward the reallocation of their resources in favor of the burgeoning computer science departments, and government and industry provide a significant…

LaRC local area networks to support distributed computing

NASA Technical Reports Server (NTRS)

Riddle, E. P.

1984-01-01

The Langley Research Center's (LaRC) Local Area Network (LAN) effort is discussed. LaRC initiated the development of a LAN to support a growing distributed computing environment at the Center. The purpose of the network is to provide an improved capability (over inteactive and RJE terminal access) for sharing multivendor computer resources. Specifically, the network will provide a data highway for the transfer of files between mainframe computers, minicomputers, work stations, and personal computers. An important influence on the overall network design was the vital need of LaRC researchers to efficiently utilize the large CDC mainframe computers in the central scientific computing facility. Although there was a steady migration from a centralized to a distributed computing environment at LaRC in recent years, the work load on the central resources increased. Major emphasis in the network design was on communication with the central resources within the distributed environment. The network to be implemented will allow researchers to utilize the central resources, distributed minicomputers, work stations, and personal computers to obtain the proper level of computing power to efficiently perform their jobs.

Cloud Computing in Support of Applied Learning: A Baseline Study of Infrastructure Design at Southern Polytechnic State University

ERIC Educational Resources Information Center

Conn, Samuel S.; Reichgelt, Han

2013-01-01

Cloud computing represents an architecture and paradigm of computing designed to deliver infrastructure, platforms, and software as constructible computing resources on demand to networked users. As campuses are challenged to better accommodate academic needs for applications and computing environments, cloud computing can provide an accommodating…

A new taxonomy for distributed computer systems based upon operating system structure

NASA Technical Reports Server (NTRS)

Foudriat, E. C.

1985-01-01

Characteristics of the resource structure found in the operating system are considered as a mechanism for classifying distributed computer systems. Since the operating system resources, themselves, are too diversified to provide a consistent classification, the structure upon which resources are built and shared are examined. The location and control character of this indivisibility provides the taxonomy for separating uniprocessors, computer networks, network computers (fully distributed processing systems or decentralized computers) and algorithm and/or data control multiprocessors. The taxonomy is important because it divides machines into a classification that is relevant or important to the client and not the hardware architect. It also defines the character of the kernel O/S structure needed for future computer systems. What constitutes an operating system for a fully distributed processor is discussed in detail.

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

Reconfigurable Computing Concepts for Space Missions: Universal Modular Spares

NASA Technical Reports Server (NTRS)

Patrick, M. Clinton

2007-01-01

Computing hardware for control, data collection, and other purposes will prove many times over crucial resources in NASA's upcoming space missions. Ability to provide these resources within mission payload requirements, with the hardiness to operate for extended periods under potentially harsh conditions in off-World environments, is daunting enough without considering the possibility of doing so with conventional electronics. This paper examines some ideas and options, and proposes some initial approaches, for logical design of reconfigurable computing resources offering true modularity, universal compatibility, and unprecedented flexibility to service all forms and needs of mission infrastructure.

Progress in Machine Learning Studies for the CMS Computing Infrastructure

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

Bonacorsi, Daniele; Kuznetsov, Valentin; Magini, Nicolo

Here, computing systems for LHC experiments developed together with Grids worldwide. While a complete description of the original Grid-based infrastructure and services for LHC experiments and its recent evolutions can be found elsewhere, it is worth to mention here the scale of the computing resources needed to fulfill the needs of LHC experiments in Run-1 and Run-2 so far.

Progress in Machine Learning Studies for the CMS Computing Infrastructure

DOE PAGES

Bonacorsi, Daniele; Kuznetsov, Valentin; Magini, Nicolo; ...

2017-12-06

Here, computing systems for LHC experiments developed together with Grids worldwide. While a complete description of the original Grid-based infrastructure and services for LHC experiments and its recent evolutions can be found elsewhere, it is worth to mention here the scale of the computing resources needed to fulfill the needs of LHC experiments in Run-1 and Run-2 so far.

Equity in health care in Namibia: developing a needs-based resource allocation formula using principal components analysis

PubMed Central

Zere, Eyob; Mandlhate, Custodia; Mbeeli, Thomas; Shangula, Kalumbi; Mutirua, Kauto; Kapenambili, William

2007-01-01

Background The pace of redressing inequities in the distribution of scarce health care resources in Namibia has been slow. This is due primarily to adherence to the historical incrementalist type of budgeting that has been used to allocate resources. Those regions with high levels of deprivation and relatively greater need for health care resources have been getting less than their fair share. To rectify this situation, which was inherited from the apartheid system, there is a need to develop a needs-based resource allocation mechanism. Methods Principal components analysis was employed to compute asset indices from asset based and health-related variables, using data from the Namibia demographic and health survey of 2000. The asset indices then formed the basis of proposals for regional weights for establishing a needs-based resource allocation formula. Results Comparing the current allocations of public sector health car resources with estimates using a needs based formula showed that regions with higher levels of need currently receive fewer resources than do regions with lower need. Conclusion To address the prevailing inequities in resource allocation, the Ministry of Health and Social Services should abandon the historical incrementalist method of budgeting/resource allocation and adopt a more appropriate allocation mechanism that incorporates measures of need for health care. PMID:17391533

Equity in health care in Namibia: developing a needs-based resource allocation formula using principal components analysis.

PubMed

Zere, Eyob; Mandlhate, Custodia; Mbeeli, Thomas; Shangula, Kalumbi; Mutirua, Kauto; Kapenambili, William

2007-03-29

The pace of redressing inequities in the distribution of scarce health care resources in Namibia has been slow. This is due primarily to adherence to the historical incrementalist type of budgeting that has been used to allocate resources. Those regions with high levels of deprivation and relatively greater need for health care resources have been getting less than their fair share. To rectify this situation, which was inherited from the apartheid system, there is a need to develop a needs-based resource allocation mechanism. Principal components analysis was employed to compute asset indices from asset based and health-related variables, using data from the Namibia demographic and health survey of 2000. The asset indices then formed the basis of proposals for regional weights for establishing a needs-based resource allocation formula. Comparing the current allocations of public sector health car resources with estimates using a needs based formula showed that regions with higher levels of need currently receive fewer resources than do regions with lower need. To address the prevailing inequities in resource allocation, the Ministry of Health and Social Services should abandon the historical incrementalist method of budgeting/resource allocation and adopt a more appropriate allocation mechanism that incorporates measures of need for health care.

Research on the digital education resources of sharing pattern in independent colleges based on cloud computing environment

NASA Astrophysics Data System (ADS)

Xiong, Ting; He, Zhiwen

2017-06-01

Cloud computing was first proposed by Google Company in the United States, which was based on the Internet center, providing a standard and open network sharing service approach. With the rapid development of the higher education in China, the educational resources provided by colleges and universities had greatly gap in the actual needs of teaching resources. therefore, Cloud computing of using the Internet technology to provide shared methods liked the timely rain, which had become an important means of the Digital Education on sharing applications in the current higher education. Based on Cloud computing environment, the paper analyzed the existing problems about the sharing of digital educational resources in Jiangxi Province Independent Colleges. According to the sharing characteristics of mass storage, efficient operation and low input about Cloud computing, the author explored and studied the design of the sharing model about the digital educational resources of higher education in Independent College. Finally, the design of the shared model was put into the practical applications.

The Need for Computer Science

ERIC Educational Resources Information Center

Margolis, Jane; Goode, Joanna; Bernier, David

2011-01-01

Broadening computer science learning to include more students is a crucial item on the United States' education agenda, these authors say. Although policymakers advocate more computer science expertise, computer science offerings in high schools are few--and actually shrinking. In addition, poorly resourced schools with a high percentage of…

Study on the application of mobile internet cloud computing platform

NASA Astrophysics Data System (ADS)

Gong, Songchun; Fu, Songyin; Chen, Zheng

2012-04-01

The innovative development of computer technology promotes the application of the cloud computing platform, which actually is the substitution and exchange of a sort of resource service models and meets the needs of users on the utilization of different resources after changes and adjustments of multiple aspects. "Cloud computing" owns advantages in many aspects which not merely reduce the difficulties to apply the operating system and also make it easy for users to search, acquire and process the resources. In accordance with this point, the author takes the management of digital libraries as the research focus in this paper, and analyzes the key technologies of the mobile internet cloud computing platform in the operation process. The popularization and promotion of computer technology drive people to create the digital library models, and its core idea is to strengthen the optimal management of the library resource information through computers and construct an inquiry and search platform with high performance, allowing the users to access to the necessary information resources at any time. However, the cloud computing is able to promote the computations within the computers to distribute in a large number of distributed computers, and hence implement the connection service of multiple computers. The digital libraries, as a typical representative of the applications of the cloud computing, can be used to carry out an analysis on the key technologies of the cloud computing.

Framework Resources Multiply Computing Power

NASA Technical Reports Server (NTRS)

2010-01-01

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

Infrastructure Systems for Advanced Computing in E-science applications

NASA Astrophysics Data System (ADS)

Terzo, Olivier

2013-04-01

In the e-science field are growing needs for having computing infrastructure more dynamic and customizable with a model of use "on demand" that follow the exact request in term of resources and storage capacities. The integration of grid and cloud infrastructure solutions allows us to offer services that can adapt the availability in terms of up scaling and downscaling resources. The main challenges for e-sciences domains will on implement infrastructure solutions for scientific computing that allow to adapt dynamically the demands of computing resources with a strong emphasis on optimizing the use of computing resources for reducing costs of investments. Instrumentation, data volumes, algorithms, analysis contribute to increase the complexity for applications who require high processing power and storage for a limited time and often exceeds the computational resources that equip the majority of laboratories, research Unit in an organization. Very often it is necessary to adapt or even tweak rethink tools, algorithms, and consolidate existing applications through a phase of reverse engineering in order to adapt them to a deployment on Cloud infrastructure. For example, in areas such as rainfall monitoring, meteorological analysis, Hydrometeorology, Climatology Bioinformatics Next Generation Sequencing, Computational Electromagnetic, Radio occultation, the complexity of the analysis raises several issues such as the processing time, the scheduling of tasks of processing, storage of results, a multi users environment. For these reasons, it is necessary to rethink the writing model of E-Science applications in order to be already adapted to exploit the potentiality of cloud computing services through the uses of IaaS, PaaS and SaaS layer. An other important focus is on create/use hybrid infrastructure typically a federation between Private and public cloud, in fact in this way when all resources owned by the organization are all used it will be easy with a federate cloud infrastructure to add some additional resources form the Public cloud for following the needs in term of computational and storage resources and release them where process are finished. Following the hybrid model, the scheduling approach is important for managing both cloud models. Thanks to this model infrastructure every time resources are available for additional request in term of IT capacities that can used "on demand" for a limited time without having to proceed to purchase additional servers.

Factors Influencing the Adoption of Cloud Computing by Decision Making Managers

ERIC Educational Resources Information Center

Ross, Virginia Watson

2010-01-01

Cloud computing is a growing field, addressing the market need for access to computing resources to meet organizational computing requirements. The purpose of this research is to evaluate the factors that influence an organization in their decision whether to adopt cloud computing as a part of their strategic information technology planning.…

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.

Interfacing HTCondor-CE with OpenStack

NASA Astrophysics Data System (ADS)

Bockelman, B.; Caballero Bejar, J.; Hover, J.

2017-10-01

Over the past few years, Grid Computing technologies have reached a high level of maturity. One key aspect of this success has been the development and adoption of newer Compute Elements to interface the external Grid users with local batch systems. These new Compute Elements allow for better handling of jobs requirements and a more precise management of diverse local resources. However, despite this level of maturity, the Grid Computing world is lacking diversity in local execution platforms. As Grid Computing technologies have historically been driven by the needs of the High Energy Physics community, most resource providers run the platform (operating system version and architecture) that best suits the needs of their particular users. In parallel, the development of virtualization and cloud technologies has accelerated recently, making available a variety of solutions, both commercial and academic, proprietary and open source. Virtualization facilitates performing computational tasks on platforms not available at most computing sites. This work attempts to join the technologies, allowing users to interact with computing sites through one of the standard Computing Elements, HTCondor-CE, but running their jobs within VMs on a local cloud platform, OpenStack, when needed. The system will re-route, in a transparent way, end user jobs into dynamically-launched VM worker nodes when they have requirements that cannot be satisfied by the static local batch system nodes. Also, once the automated mechanisms are in place, it becomes straightforward to allow an end user to invoke a custom Virtual Machine at the site. This will allow cloud resources to be used without requiring the user to establish a separate account. Both scenarios are described in this work.

Optimization of tomographic reconstruction workflows on geographically distributed resources

DOE PAGES

Bicer, Tekin; Gursoy, Doga; Kettimuthu, Rajkumar; ...

2016-01-01

New technological advancements in synchrotron light sources enable data acquisitions at unprecedented levels. This emergent trend affects not only the size of the generated data but also the need for larger computational resources. Although beamline scientists and users have access to local computational resources, these are typically limited and can result in extended execution times. Applications that are based on iterative processing as in tomographic reconstruction methods require high-performance compute clusters for timely analysis of data. Here, time-sensitive analysis and processing of Advanced Photon Source data on geographically distributed resources are focused on. Two main challenges are considered: (i) modelingmore » of the performance of tomographic reconstruction workflows and (ii) transparent execution of these workflows on distributed resources. For the former, three main stages are considered: (i) data transfer between storage and computational resources, (i) wait/queue time of reconstruction jobs at compute resources, and (iii) computation of reconstruction tasks. These performance models allow evaluation and estimation of the execution time of any given iterative tomographic reconstruction workflow that runs on geographically distributed resources. For the latter challenge, a workflow management system is built, which can automate the execution of workflows and minimize the user interaction with the underlying infrastructure. The system utilizes Globus to perform secure and efficient data transfer operations. The proposed models and the workflow management system are evaluated by using three high-performance computing and two storage resources, all of which are geographically distributed. Workflows were created with different computational requirements using two compute-intensive tomographic reconstruction algorithms. Experimental evaluation shows that the proposed models and system can be used for selecting the optimum resources, which in turn can provide up to 3.13× speedup (on experimented resources). Furthermore, the error rates of the models range between 2.1 and 23.3% (considering workflow execution times), where the accuracy of the model estimations increases with higher computational demands in reconstruction tasks.« less

Optimization of tomographic reconstruction workflows on geographically distributed resources

PubMed Central

Bicer, Tekin; Gürsoy, Doǧa; Kettimuthu, Rajkumar; De Carlo, Francesco; Foster, Ian T.

2016-01-01

New technological advancements in synchrotron light sources enable data acquisitions at unprecedented levels. This emergent trend affects not only the size of the generated data but also the need for larger computational resources. Although beamline scientists and users have access to local computational resources, these are typically limited and can result in extended execution times. Applications that are based on iterative processing as in tomographic reconstruction methods require high-performance compute clusters for timely analysis of data. Here, time-sensitive analysis and processing of Advanced Photon Source data on geographically distributed resources are focused on. Two main challenges are considered: (i) modeling of the performance of tomographic reconstruction workflows and (ii) transparent execution of these workflows on distributed resources. For the former, three main stages are considered: (i) data transfer between storage and computational resources, (i) wait/queue time of reconstruction jobs at compute resources, and (iii) computation of reconstruction tasks. These performance models allow evaluation and estimation of the execution time of any given iterative tomographic reconstruction workflow that runs on geographically distributed resources. For the latter challenge, a workflow management system is built, which can automate the execution of workflows and minimize the user interaction with the underlying infrastructure. The system utilizes Globus to perform secure and efficient data transfer operations. The proposed models and the workflow management system are evaluated by using three high-performance computing and two storage resources, all of which are geographically distributed. Workflows were created with different computational requirements using two compute-intensive tomographic reconstruction algorithms. Experimental evaluation shows that the proposed models and system can be used for selecting the optimum resources, which in turn can provide up to 3.13× speedup (on experimented resources). Moreover, the error rates of the models range between 2.1 and 23.3% (considering workflow execution times), where the accuracy of the model estimations increases with higher computational demands in reconstruction tasks. PMID:27359149

Optimization of tomographic reconstruction workflows on geographically distributed resources

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

Bicer, Tekin; Gursoy, Doga; Kettimuthu, Rajkumar

New technological advancements in synchrotron light sources enable data acquisitions at unprecedented levels. This emergent trend affects not only the size of the generated data but also the need for larger computational resources. Although beamline scientists and users have access to local computational resources, these are typically limited and can result in extended execution times. Applications that are based on iterative processing as in tomographic reconstruction methods require high-performance compute clusters for timely analysis of data. Here, time-sensitive analysis and processing of Advanced Photon Source data on geographically distributed resources are focused on. Two main challenges are considered: (i) modelingmore » of the performance of tomographic reconstruction workflows and (ii) transparent execution of these workflows on distributed resources. For the former, three main stages are considered: (i) data transfer between storage and computational resources, (i) wait/queue time of reconstruction jobs at compute resources, and (iii) computation of reconstruction tasks. These performance models allow evaluation and estimation of the execution time of any given iterative tomographic reconstruction workflow that runs on geographically distributed resources. For the latter challenge, a workflow management system is built, which can automate the execution of workflows and minimize the user interaction with the underlying infrastructure. The system utilizes Globus to perform secure and efficient data transfer operations. The proposed models and the workflow management system are evaluated by using three high-performance computing and two storage resources, all of which are geographically distributed. Workflows were created with different computational requirements using two compute-intensive tomographic reconstruction algorithms. Experimental evaluation shows that the proposed models and system can be used for selecting the optimum resources, which in turn can provide up to 3.13× speedup (on experimented resources). Furthermore, the error rates of the models range between 2.1 and 23.3% (considering workflow execution times), where the accuracy of the model estimations increases with higher computational demands in reconstruction tasks.« less

Goals and Objectives for Computing in the Associated Colleges of the St. Lawrence Valley.

ERIC Educational Resources Information Center

Grupe, Fritz H.

A forecast of the computing requirements of the Associated Colleges of the St. Lawrence Valley, an analysis of their needs, and specifications for a joint computer system are presented. Problems encountered included the lack of resources and computer sophistication at the member schools and a dearth of experience with long-term computer consortium…

Computer Operating System Maintenance.

DTIC Science & Technology

1982-06-01

FACILITY The Computer Management Information Facility ( CMIF ) system was developed by Rapp Systems to fulfill the need at the CRF to record and report on...computer center resource usage and utilization. The foundation of the CMIF system is a System 2000 data base (CRFMGMT) which stores and permits access

Surfer: An Extensible Pull-Based Framework for Resource Selection and Ranking

NASA Technical Reports Server (NTRS)

Zolano, Paul Z.

2004-01-01

Grid computing aims to connect large numbers of geographically and organizationally distributed resources to increase computational power; resource utilization, and resource accessibility. In order to effectively utilize grids, users need to be connected to the best available resources at any given time. As grids are in constant flux, users cannot be expected to keep up with the configuration and status of the grid, thus they must be provided with automatic resource brokering for selecting and ranking resources meeting constraints and preferences they specify. This paper presents a new OGSI-compliant resource selection and ranking framework called Surfer that has been implemented as part of NASA's Information Power Grid (IPG) project. Surfer is highly extensible and may be integrated into any grid environment by adding information providers knowledgeable about that environment.

The Changing Hardwood Export Market and Research to Keep the U.S. Competitive

Treesearch

Philip A. Araman

1988-01-01

Primary hardwood processors face many interrelated market, product, processing, and resource problems generated by the increasing export market. In processing, yields and quality must be increased and costs must be reduced to stay competitive. Computer-aided and computer-controlled automated processing is also needed. The industry needs to keep its products competitive...

Using Cloud Computing infrastructure with CloudBioLinux, CloudMan and Galaxy

PubMed Central

Afgan, Enis; Chapman, Brad; Jadan, Margita; Franke, Vedran; Taylor, James

2012-01-01

Cloud computing has revolutionized availability and access to computing and storage resources; making it possible to provision a large computational infrastructure with only a few clicks in a web browser. However, those resources are typically provided in the form of low-level infrastructure components that need to be procured and configured before use. In this protocol, we demonstrate how to utilize cloud computing resources to perform open-ended bioinformatics analyses, with fully automated management of the underlying cloud infrastructure. By combining three projects, CloudBioLinux, CloudMan, and Galaxy into a cohesive unit, we have enabled researchers to gain access to more than 100 preconfigured bioinformatics tools and gigabytes of reference genomes on top of the flexible cloud computing infrastructure. The protocol demonstrates how to setup the available infrastructure and how to use the tools via a graphical desktop interface, a parallel command line interface, and the web-based Galaxy interface. PMID:22700313

Using cloud computing infrastructure with CloudBioLinux, CloudMan, and Galaxy.

PubMed

Afgan, Enis; Chapman, Brad; Jadan, Margita; Franke, Vedran; Taylor, James

2012-06-01

Cloud computing has revolutionized availability and access to computing and storage resources, making it possible to provision a large computational infrastructure with only a few clicks in a Web browser. However, those resources are typically provided in the form of low-level infrastructure components that need to be procured and configured before use. In this unit, we demonstrate how to utilize cloud computing resources to perform open-ended bioinformatic analyses, with fully automated management of the underlying cloud infrastructure. By combining three projects, CloudBioLinux, CloudMan, and Galaxy, into a cohesive unit, we have enabled researchers to gain access to more than 100 preconfigured bioinformatics tools and gigabytes of reference genomes on top of the flexible cloud computing infrastructure. The protocol demonstrates how to set up the available infrastructure and how to use the tools via a graphical desktop interface, a parallel command-line interface, and the Web-based Galaxy interface.

Infrastructures for Distributed Computing: the case of BESIII

NASA Astrophysics Data System (ADS)

Pellegrino, J.

2018-05-01

The BESIII is an electron-positron collision experiment hosted at BEPCII in Beijing and aimed to investigate Tau-Charm physics. Now BESIII has been running for several years and gathered more than 1PB raw data. In order to analyze these data and perform massive Monte Carlo simulations, a large amount of computing and storage resources is needed. The distributed computing system is based up on DIRAC and it is in production since 2012. It integrates computing and storage resources from different institutes and a variety of resource types such as cluster, grid, cloud or volunteer computing. About 15 sites from BESIII Collaboration from all over the world joined this distributed computing infrastructure, giving a significant contribution to the IHEP computing facility. Nowadays cloud computing is playing a key role in the HEP computing field, due to its scalability and elasticity. Cloud infrastructures take advantages of several tools, such as VMDirac, to manage virtual machines through cloud managers according to the job requirements. With the virtually unlimited resources from commercial clouds, the computing capacity could scale accordingly in order to deal with any burst demands. General computing models have been discussed in the talk and are addressed herewith, with particular focus on the BESIII infrastructure. Moreover new computing tools and upcoming infrastructures will be addressed.

Workflow Management Systems for Molecular Dynamics on Leadership Computers

NASA Astrophysics Data System (ADS)

Wells, Jack; Panitkin, Sergey; Oleynik, Danila; Jha, Shantenu

Molecular Dynamics (MD) simulations play an important role in a range of disciplines from Material Science to Biophysical systems and account for a large fraction of cycles consumed on computing resources. Increasingly science problems require the successful execution of ''many'' MD simulations as opposed to a single MD simulation. There is a need to provide scalable and flexible approaches to the execution of the workload. We present preliminary results on the Titan computer at the Oak Ridge Leadership Computing Facility that demonstrate a general capability to manage workload execution agnostic of a specific MD simulation kernel or execution pattern, and in a manner that integrates disparate grid-based and supercomputing resources. Our results build upon our extensive experience of distributed workload management in the high-energy physics ATLAS project using PanDA (Production and Distributed Analysis System), coupled with recent conceptual advances in our understanding of workload management on heterogeneous resources. We will discuss how we will generalize these initial capabilities towards a more production level service on DOE leadership resources. This research is sponsored by US DOE/ASCR and used resources of the OLCF computing facility.

Now and next-generation sequencing techniques: future of sequence analysis using cloud computing.

PubMed

Thakur, Radhe Shyam; Bandopadhyay, Rajib; Chaudhary, Bratati; Chatterjee, Sourav

2012-01-01

Advances in the field of sequencing techniques have resulted in the greatly accelerated production of huge sequence datasets. This presents immediate challenges in database maintenance at datacenters. It provides additional computational challenges in data mining and sequence analysis. Together these represent a significant overburden on traditional stand-alone computer resources, and to reach effective conclusions quickly and efficiently, the virtualization of the resources and computation on a pay-as-you-go concept (together termed "cloud computing") has recently appeared. The collective resources of the datacenter, including both hardware and software, can be available publicly, being then termed a public cloud, the resources being provided in a virtual mode to the clients who pay according to the resources they employ. Examples of public companies providing these resources include Amazon, Google, and Joyent. The computational workload is shifted to the provider, which also implements required hardware and software upgrades over time. A virtual environment is created in the cloud corresponding to the computational and data storage needs of the user via the internet. The task is then performed, the results transmitted to the user, and the environment finally deleted after all tasks are completed. In this discussion, we focus on the basics of cloud computing, and go on to analyze the prerequisites and overall working of clouds. Finally, the applications of cloud computing in biological systems, particularly in comparative genomics, genome informatics, and SNP detection are discussed with reference to traditional workflows.

Administration of Computer Resources.

ERIC Educational Resources Information Center

Franklin, Gene F.

Computing at Stanford University has, until recently, been performed at one of five facilities. The Stanford hospital operates an IBM 370/135 mainly for administrative use. The university business office has an IBM 370/145 for its administrative needs and support of the medical clinic. Under the supervision of the Stanford Computation Center are…

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

NASA Astrophysics Data System (ADS)

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

2001-07-01

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

CERN Computing in Commercial Clouds

NASA Astrophysics Data System (ADS)

Cordeiro, C.; Field, L.; Garrido Bear, B.; Giordano, D.; Jones, B.; Keeble, O.; Manzi, A.; Martelli, E.; McCance, G.; Moreno-García, D.; Traylen, S.

2017-10-01

By the end of 2016 more than 10 Million core-hours of computing resources have been delivered by several commercial cloud providers to the four LHC experiments to run their production workloads, from simulation to full chain processing. In this paper we describe the experience gained at CERN in procuring and exploiting commercial cloud resources for the computing needs of the LHC experiments. The mechanisms used for provisioning, monitoring, accounting, alarming and benchmarking will be discussed, as well as the involvement of the LHC collaborations in terms of managing the workflows of the experiments within a multicloud environment.

AGIS: The ATLAS Grid Information System

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Resources for GCSE.

ERIC Educational Resources Information Center

Anderton, Alain

1987-01-01

Argues that new resources are needed to help teachers prepare students for the new General Certificate in Secondary Education (GCSE) examination. Compares previous examinations with new examinations to illustrate the problem. Presents textbooks, workbooks, computer programs, and other curriculum materials to demonstrate the gap between resources…

Energy sustainability: consumption, efficiency, and environmental impact

EPA Science Inventory

One of the critical challenges in achieving sustainability is finding a way to meet the energy consumption needs of a growing population in the face of increasing economic prosperity and finite resources. According to ecological footprint computations, the global resource consump...

Now and Next-Generation Sequencing Techniques: Future of Sequence Analysis Using Cloud Computing

PubMed Central

Thakur, Radhe Shyam; Bandopadhyay, Rajib; Chaudhary, Bratati; Chatterjee, Sourav

2012-01-01

Advances in the field of sequencing techniques have resulted in the greatly accelerated production of huge sequence datasets. This presents immediate challenges in database maintenance at datacenters. It provides additional computational challenges in data mining and sequence analysis. Together these represent a significant overburden on traditional stand-alone computer resources, and to reach effective conclusions quickly and efficiently, the virtualization of the resources and computation on a pay-as-you-go concept (together termed “cloud computing”) has recently appeared. The collective resources of the datacenter, including both hardware and software, can be available publicly, being then termed a public cloud, the resources being provided in a virtual mode to the clients who pay according to the resources they employ. Examples of public companies providing these resources include Amazon, Google, and Joyent. The computational workload is shifted to the provider, which also implements required hardware and software upgrades over time. A virtual environment is created in the cloud corresponding to the computational and data storage needs of the user via the internet. The task is then performed, the results transmitted to the user, and the environment finally deleted after all tasks are completed. In this discussion, we focus on the basics of cloud computing, and go on to analyze the prerequisites and overall working of clouds. Finally, the applications of cloud computing in biological systems, particularly in comparative genomics, genome informatics, and SNP detection are discussed with reference to traditional workflows. PMID:23248640

Managing competing elastic Grid and Cloud scientific computing applications using OpenNebula

NASA Astrophysics Data System (ADS)

Bagnasco, S.; Berzano, D.; Lusso, S.; Masera, M.; Vallero, S.

2015-12-01

Elastic cloud computing applications, i.e. applications that automatically scale according to computing needs, work on the ideal assumption of infinite resources. While large public cloud infrastructures may be a reasonable approximation of this condition, scientific computing centres like WLCG Grid sites usually work in a saturated regime, in which applications compete for scarce resources through queues, priorities and scheduling policies, and keeping a fraction of the computing cores idle to allow for headroom is usually not an option. In our particular environment one of the applications (a WLCG Tier-2 Grid site) is much larger than all the others and cannot autoscale easily. Nevertheless, other smaller applications can benefit of automatic elasticity; the implementation of this property in our infrastructure, based on the OpenNebula cloud stack, will be described and the very first operational experiences with a small number of strategies for timely allocation and release of resources will be discussed.

Identifying Key Features, Cutting Edge Cloud Resources, and Artificial Intelligence Tools to Achieve User-Friendly Water Science in the Cloud

NASA Astrophysics Data System (ADS)

Pierce, S. A.

2017-12-01

Decision making for groundwater systems is becoming increasingly important, as shifting water demands increasingly impact aquifers. As buffer systems, aquifers provide room for resilient responses and augment the actual timeframe for hydrological response. Yet the pace impacts, climate shifts, and degradation of water resources is accelerating. To meet these new drivers, groundwater science is transitioning toward the emerging field of Integrated Water Resources Management, or IWRM. IWRM incorporates a broad array of dimensions, methods, and tools to address problems that tend to be complex. Computational tools and accessible cyberinfrastructure (CI) are needed to cross the chasm between science and society. Fortunately cloud computing environments, such as the new Jetstream system, are evolving rapidly. While still targeting scientific user groups systems such as, Jetstream, offer configurable cyberinfrastructure to enable interactive computing and data analysis resources on demand. The web-based interfaces allow researchers to rapidly customize virtual machines, modify computing architecture and increase the usability and access for broader audiences to advanced compute environments. The result enables dexterous configurations and opening up opportunities for IWRM modelers to expand the reach of analyses, number of case studies, and quality of engagement with stakeholders and decision makers. The acute need to identify improved IWRM solutions paired with advanced computational resources refocuses the attention of IWRM researchers on applications, workflows, and intelligent systems that are capable of accelerating progress. IWRM must address key drivers of community concern, implement transdisciplinary methodologies, adapt and apply decision support tools in order to effectively support decisions about groundwater resource management. This presentation will provide an overview of advanced computing services in the cloud using integrated groundwater management case studies to highlight how Cloud CI streamlines the process for setting up an interactive decision support system. Moreover, advances in artificial intelligence offer new techniques for old problems from integrating data to adaptive sensing or from interactive dashboards to optimizing multi-attribute problems. The combination of scientific expertise, flexible cloud computing solutions, and intelligent systems opens new research horizons.

Computing Bounds on Resource Levels for Flexible Plans

NASA Technical Reports Server (NTRS)

Muscvettola, Nicola; Rijsman, David

2009-01-01

A new algorithm efficiently computes the tightest exact bound on the levels of resources induced by a flexible activity plan (see figure). Tightness of bounds is extremely important for computations involved in planning because tight bounds can save potentially exponential amounts of search (through early backtracking and detection of solutions), relative to looser bounds. The bound computed by the new algorithm, denoted the resource-level envelope, constitutes the measure of maximum and minimum consumption of resources at any time for all fixed-time schedules in the flexible plan. At each time, the envelope guarantees that there are two fixed-time instantiations one that produces the minimum level and one that produces the maximum level. Therefore, the resource-level envelope is the tightest possible resource-level bound for a flexible plan because any tighter bound would exclude the contribution of at least one fixed-time schedule. If the resource- level envelope can be computed efficiently, one could substitute looser bounds that are currently used in the inner cores of constraint-posting scheduling algorithms, with the potential for great improvements in performance. What is needed to reduce the cost of computation is an algorithm, the measure of complexity of which is no greater than a low-degree polynomial in N (where N is the number of activities). The new algorithm satisfies this need. In this algorithm, the computation of resource-level envelopes is based on a novel combination of (1) the theory of shortest paths in the temporal-constraint network for the flexible plan and (2) the theory of maximum flows for a flow network derived from the temporal and resource constraints. The measure of asymptotic complexity of the algorithm is O(N O(maxflow(N)), where O(x) denotes an amount of computing time or a number of arithmetic operations proportional to a number of the order of x and O(maxflow(N)) is the measure of complexity (and thus of cost) of a maximumflow algorithm applied to an auxiliary flow network of 2N nodes. The algorithm is believed to be efficient in practice; experimental analysis shows the practical cost of maxflow to be as low as O(N1.5). The algorithm could be enhanced following at least two approaches. In the first approach, incremental subalgorithms for the computation of the envelope could be developed. By use of temporal scanning of the events in the temporal network, it may be possible to significantly reduce the size of the networks on which it is necessary to run the maximum-flow subalgorithm, thereby significantly reducing the time required for envelope calculation. In the second approach, the practical effectiveness of resource envelopes in the inner loops of search algorithms could be tested for multi-capacity resource scheduling. This testing would include inner-loop backtracking and termination tests and variable and value-ordering heuristics that exploit the properties of resource envelopes more directly.

A cross-sectional evaluation of computer literacy among medical students at a tertiary care teaching hospital in Mumbai, Bombay.

PubMed

Panchabhai, T S; Dangayach, N S; Mehta, V S; Patankar, C V; Rege, N N

2011-01-01

Computer usage capabilities of medical students for introduction of computer-aided learning have not been adequately assessed. Cross-sectional study to evaluate computer literacy among medical students. Tertiary care teaching hospital in Mumbai, India. Participants were administered a 52-question questionnaire, designed to study their background, computer resources, computer usage, activities enhancing computer skills, and attitudes toward computer-aided learning (CAL). The data was classified on the basis of sex, native place, and year of medical school, and the computer resources were compared. The computer usage and attitudes toward computer-based learning were assessed on a five-point Likert scale, to calculate Computer usage score (CUS - maximum 55, minimum 11) and Attitude score (AS - maximum 60, minimum 12). The quartile distribution among the groups with respect to the CUS and AS was compared by chi-squared tests. The correlation between CUS and AS was then tested. Eight hundred and seventy-five students agreed to participate in the study and 832 completed the questionnaire. One hundred and twenty eight questionnaires were excluded and 704 were analyzed. Outstation students had significantly lesser computer resources as compared to local students (P<0.0001). The mean CUS for local students (27.0±9.2, Mean±SD) was significantly higher than outstation students (23.2±9.05). No such difference was observed for the AS. The means of CUS and AS did not differ between males and females. The CUS and AS had positive, but weak correlations for all subgroups. The weak correlation between AS and CUS for all students could be explained by the lack of computer resources or inadequate training to use computers for learning. Providing additional resources would benefit the subset of outstation students with lesser computer resources. This weak correlation between the attitudes and practices of all students needs to be investigated. We believe that this gap can be bridged with a structured computer learning program.

A Framework for Control and Observation in Distributed Environments

NASA Technical Reports Server (NTRS)

Smith, Warren

2001-01-01

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

Parallel computing method for simulating hydrological processesof large rivers under climate change

NASA Astrophysics Data System (ADS)

Wang, H.; Chen, Y.

2016-12-01

Climate change is one of the proverbial global environmental problems in the world.Climate change has altered the watershed hydrological processes in time and space distribution, especially in worldlarge rivers.Watershed hydrological process simulation based on physically based distributed hydrological model can could have better results compared with the lumped models.However, watershed hydrological process simulation includes large amount of calculations, especially in large rivers, thus needing huge computing resources that may not be steadily available for the researchers or at high expense, this seriously restricted the research and application. To solve this problem, the current parallel method are mostly parallel computing in space and time dimensions.They calculate the natural features orderly thatbased on distributed hydrological model by grid (unit, a basin) from upstream to downstream.This articleproposes ahigh-performancecomputing method of hydrological process simulation with high speedratio and parallel efficiency.It combinedthe runoff characteristics of time and space of distributed hydrological model withthe methods adopting distributed data storage, memory database, distributed computing, parallel computing based on computing power unit.The method has strong adaptability and extensibility,which means it canmake full use of the computing and storage resources under the condition of limited computing resources, and the computing efficiency can be improved linearly with the increase of computing resources .This method can satisfy the parallel computing requirements ofhydrological process simulation in small, medium and large rivers.

Extensible Computational Chemistry Environment

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

2012-08-09

ECCE provides a sophisticated graphical user interface, scientific visualization tools, and the underlying data management framework enabling scientists to efficiently set up calculations and store, retrieve, and analyze the rapidly growing volumes of data produced by computational chemistry studies. ECCE was conceived as part of the Environmental Molecular Sciences Laboratory construction to solve the problem of researchers being able to effectively utilize complex computational chemistry codes and massively parallel high performance compute resources. Bringing the power of these codes and resources to the desktops of researcher and thus enabling world class research without users needing a detailed understanding of themore » inner workings of either the theoretical codes or the supercomputers needed to run them was a grand challenge problem in the original version of the EMSL. ECCE allows collaboration among researchers using a web-based data repository where the inputs and results for all calculations done within ECCE are organized. ECCE is a first of kind end-to-end problem solving environment for all phases of computational chemistry research: setting up calculations with sophisticated GUI and direct manipulation visualization tools, submitting and monitoring calculations on remote high performance supercomputers without having to be familiar with the details of using these compute resources, and performing results visualization and analysis including creating publication quality images. ECCE is a suite of tightly integrated applications that are employed as the user moves through the modeling process.« less

Elucidating reaction mechanisms on quantum computers.

PubMed

Reiher, Markus; Wiebe, Nathan; Svore, Krysta M; Wecker, Dave; Troyer, Matthias

2017-07-18

With rapid recent advances in quantum technology, we are close to the threshold of quantum devices whose computational powers can exceed those of classical supercomputers. Here, we show that a quantum computer can be used to elucidate reaction mechanisms in complex chemical systems, using the open problem of biological nitrogen fixation in nitrogenase as an example. We discuss how quantum computers can augment classical computer simulations used to probe these reaction mechanisms, to significantly increase their accuracy and enable hitherto intractable simulations. Our resource estimates show that, even when taking into account the substantial overhead of quantum error correction, and the need to compile into discrete gate sets, the necessary computations can be performed in reasonable time on small quantum computers. Our results demonstrate that quantum computers will be able to tackle important problems in chemistry without requiring exorbitant resources.

Elucidating reaction mechanisms on quantum computers

PubMed Central

Reiher, Markus; Wiebe, Nathan; Svore, Krysta M.; Wecker, Dave; Troyer, Matthias

2017-01-01

With rapid recent advances in quantum technology, we are close to the threshold of quantum devices whose computational powers can exceed those of classical supercomputers. Here, we show that a quantum computer can be used to elucidate reaction mechanisms in complex chemical systems, using the open problem of biological nitrogen fixation in nitrogenase as an example. We discuss how quantum computers can augment classical computer simulations used to probe these reaction mechanisms, to significantly increase their accuracy and enable hitherto intractable simulations. Our resource estimates show that, even when taking into account the substantial overhead of quantum error correction, and the need to compile into discrete gate sets, the necessary computations can be performed in reasonable time on small quantum computers. Our results demonstrate that quantum computers will be able to tackle important problems in chemistry without requiring exorbitant resources. PMID:28674011

Elucidating reaction mechanisms on quantum computers

NASA Astrophysics Data System (ADS)

Reiher, Markus; Wiebe, Nathan; Svore, Krysta M.; Wecker, Dave; Troyer, Matthias

2017-07-01

With rapid recent advances in quantum technology, we are close to the threshold of quantum devices whose computational powers can exceed those of classical supercomputers. Here, we show that a quantum computer can be used to elucidate reaction mechanisms in complex chemical systems, using the open problem of biological nitrogen fixation in nitrogenase as an example. We discuss how quantum computers can augment classical computer simulations used to probe these reaction mechanisms, to significantly increase their accuracy and enable hitherto intractable simulations. Our resource estimates show that, even when taking into account the substantial overhead of quantum error correction, and the need to compile into discrete gate sets, the necessary computations can be performed in reasonable time on small quantum computers. Our results demonstrate that quantum computers will be able to tackle important problems in chemistry without requiring exorbitant resources.

Desktop supercomputer: what can it do?

NASA Astrophysics Data System (ADS)

Bogdanov, A.; Degtyarev, A.; Korkhov, V.

2017-12-01

The paper addresses the issues of solving complex problems that require using supercomputers or multiprocessor clusters available for most researchers nowadays. Efficient distribution of high performance computing resources according to actual application needs has been a major research topic since high-performance computing (HPC) technologies became widely introduced. At the same time, comfortable and transparent access to these resources was a key user requirement. In this paper we discuss approaches to build a virtual private supercomputer available at user's desktop: a virtual computing environment tailored specifically for a target user with a particular target application. We describe and evaluate possibilities to create the virtual supercomputer based on light-weight virtualization technologies, and analyze the efficiency of our approach compared to traditional methods of HPC resource management.

On-demand provisioning of HEP compute resources on cloud sites and shared HPC centers

NASA Astrophysics Data System (ADS)

Erli, G.; Fischer, F.; Fleig, G.; Giffels, M.; Hauth, T.; Quast, G.; Schnepf, M.; Heese, J.; Leppert, K.; Arnaez de Pedro, J.; Sträter, R.

2017-10-01

This contribution reports on solutions, experiences and recent developments with the dynamic, on-demand provisioning of remote computing resources for analysis and simulation workflows. Local resources of a physics institute are extended by private and commercial cloud sites, ranging from the inclusion of desktop clusters over institute clusters to HPC centers. Rather than relying on dedicated HEP computing centers, it is nowadays more reasonable and flexible to utilize remote computing capacity via virtualization techniques or container concepts. We report on recent experience from incorporating a remote HPC center (NEMO Cluster, Freiburg University) and resources dynamically requested from the commercial provider 1&1 Internet SE into our intitute’s computing infrastructure. The Freiburg HPC resources are requested via the standard batch system, allowing HPC and HEP applications to be executed simultaneously, such that regular batch jobs run side by side to virtual machines managed via OpenStack [1]. For the inclusion of the 1&1 commercial resources, a Python API and SDK as well as the possibility to upload images were available. Large scale tests prove the capability to serve the scientific use case in the European 1&1 datacenters. The described environment at the Institute of Experimental Nuclear Physics (IEKP) at KIT serves the needs of researchers participating in the CMS and Belle II experiments. In total, resources exceeding half a million CPU hours have been provided by remote sites.

A Proposal for a Computer Network for the Indonesian Air Force’s Remote Site Radar System

DTIC Science & Technology

1989-03-01

This thesis proposes two alternatives for a preliminary design of a computer network to support this need. It suggests how existing communication...suggests how existing communication resources such as telephones, microwave links and satellite systems can be used to support the network. The first...telephone, radio-link, microwave-link and satellite systems. The goal of this thesis is to suggest how to utilize or implement these resources to support

The "Terminology Market."

ERIC Educational Resources Information Center

Galinski, Christian

This paper examines needs, resources, and trends in the computer-based development of field-specific terminologies in varied languages. The range of special terminologies, their users, and their producers is noted, and the kinds of resources produced (data and tools) are outlined. Data types include: terminological information proper (information…

A Hierarchical Auction-Based Mechanism for Real-Time Resource Allocation in Cloud Robotic Systems.

PubMed

Wang, Lujia; Liu, Ming; Meng, Max Q-H

2017-02-01

Cloud computing enables users to share computing resources on-demand. The cloud computing framework cannot be directly mapped to cloud robotic systems with ad hoc networks since cloud robotic systems have additional constraints such as limited bandwidth and dynamic structure. However, most multirobotic applications with cooperative control adopt this decentralized approach to avoid a single point of failure. Robots need to continuously update intensive data to execute tasks in a coordinated manner, which implies real-time requirements. Thus, a resource allocation strategy is required, especially in such resource-constrained environments. This paper proposes a hierarchical auction-based mechanism, namely link quality matrix (LQM) auction, which is suitable for ad hoc networks by introducing a link quality indicator. The proposed algorithm produces a fast and robust method that is accurate and scalable. It reduces both global communication and unnecessary repeated computation. The proposed method is designed for firm real-time resource retrieval for physical multirobot systems. A joint surveillance scenario empirically validates the proposed mechanism by assessing several practical metrics. The results show that the proposed LQM auction outperforms state-of-the-art algorithms for resource allocation.

User's manual for BRI-STARS (BRIdge Stream Tube model for Alluvial River Simulation)

DOT National Transportation Integrated Search

1998-07-01

There is a need for a generalized water and sediment-routing computer model for solving complicated river engineering problems with limited data and resources. This program should have the following capabilities: to compute hydraulic parameters for o...

Implementation of DFT application on ternary optical computer

NASA Astrophysics Data System (ADS)

Junjie, Peng; Youyi, Fu; Xiaofeng, Zhang; Shuai, Kong; Xinyu, Wei

2018-03-01

As its characteristics of huge number of data bits and low energy consumption, optical computing may be used in the applications such as DFT etc. which needs a lot of computation and can be implemented in parallel. According to this, DFT implementation methods in full parallel as well as in partial parallel are presented. Based on resources ternary optical computer (TOC), extensive experiments were carried out. Experimental results show that the proposed schemes are correct and feasible. They provide a foundation for further exploration of the applications on TOC that needs a large amount calculation and can be processed in parallel.

Application of microarray analysis on computer cluster and cloud platforms.

PubMed

Bernau, C; Boulesteix, A-L; Knaus, J

2013-01-01

Analysis of recent high-dimensional biological data tends to be computationally intensive as many common approaches such as resampling or permutation tests require the basic statistical analysis to be repeated many times. A crucial advantage of these methods is that they can be easily parallelized due to the computational independence of the resampling or permutation iterations, which has induced many statistics departments to establish their own computer clusters. An alternative is to rent computing resources in the cloud, e.g. at Amazon Web Services. In this article we analyze whether a selection of statistical projects, recently implemented at our department, can be efficiently realized on these cloud resources. Moreover, we illustrate an opportunity to combine computer cluster and cloud resources. In order to compare the efficiency of computer cluster and cloud implementations and their respective parallelizations we use microarray analysis procedures and compare their runtimes on the different platforms. Amazon Web Services provide various instance types which meet the particular needs of the different statistical projects we analyzed in this paper. Moreover, the network capacity is sufficient and the parallelization is comparable in efficiency to standard computer cluster implementations. Our results suggest that many statistical projects can be efficiently realized on cloud resources. It is important to mention, however, that workflows can change substantially as a result of a shift from computer cluster to cloud computing.

AGIS: Integration of new technologies used in ATLAS Distributed Computing

NASA Astrophysics Data System (ADS)

Anisenkov, Alexey; Di Girolamo, Alessandro; Alandes Pradillo, Maria

2017-10-01

The variety of the ATLAS Distributed Computing infrastructure requires a central information system to define the topology of computing resources and to store different parameters and configuration data which are needed by various ATLAS software components. The ATLAS Grid Information System (AGIS) is the system designed to integrate configuration and status information about resources, services and topology of the computing infrastructure used by ATLAS Distributed Computing applications and services. Being an intermediate middleware system between clients and external information sources (like central BDII, GOCDB, MyOSG), AGIS defines the relations between experiment specific used resources and physical distributed computing capabilities. Being in production during LHC Runl AGIS became the central information system for Distributed Computing in ATLAS and it is continuously evolving to fulfil new user requests, enable enhanced operations and follow the extension of the ATLAS Computing model. The ATLAS Computing model and data structures used by Distributed Computing applications and services are continuously evolving and trend to fit newer requirements from ADC community. In this note, we describe the evolution and the recent developments of AGIS functionalities, related to integration of new technologies recently become widely used in ATLAS Computing, like flexible computing utilization of opportunistic Cloud and HPC resources, ObjectStore services integration for Distributed Data Management (Rucio) and ATLAS workload management (PanDA) systems, unified storage protocols declaration required for PandDA Pilot site movers and others. The improvements of information model and general updates are also shown, in particular we explain how other collaborations outside ATLAS could benefit the system as a computing resources information catalogue. AGIS is evolving towards a common information system, not coupled to a specific experiment.

Computer programs for forward and inverse modeling of acoustic and electromagnetic data

USGS Publications Warehouse

Ellefsen, Karl J.

2011-01-01

A suite of computer programs was developed by U.S. Geological Survey personnel for forward and inverse modeling of acoustic and electromagnetic data. This report describes the computer resources that are needed to execute the programs, the installation of the programs, the program designs, some tests of their accuracy, and some suggested improvements.

A Quantitative Risk Analysis Framework for Evaluating and Monitoring Operational Reliability of Cloud Computing

ERIC Educational Resources Information Center

Islam, Muhammad Faysal

2013-01-01

Cloud computing offers the advantage of on-demand, reliable and cost efficient computing solutions without the capital investment and management resources to build and maintain in-house data centers and network infrastructures. Scalability of cloud solutions enable consumers to upgrade or downsize their services as needed. In a cloud environment,…

Using an Interactive Computer Program to Communicate With the Wilderness Visitor

Treesearch

David W. Harmon

1992-01-01

The Bureau of Land Management, Oregon State Office, identified a need for a tool to communicate with wilderness visitors, managers, and decisionmakers regarding wilderness values and existing resource information in 87 wilderness study areas. An interactive computer program was developed using a portable Macintosh computer, a touch screen monitor, and laser disk player...

The Magellan Final Report on Cloud Computing

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

,; Coghlan, Susan; Yelick, Katherine

The goal of Magellan, a project funded through the U.S. Department of Energy (DOE) Office of Advanced Scientific Computing Research (ASCR), was to investigate the potential role of cloud computing in addressing the computing needs for the DOE Office of Science (SC), particularly related to serving the needs of mid- range computing and future data-intensive computing workloads. A set of research questions was formed to probe various aspects of cloud computing from performance, usability, and cost. To address these questions, a distributed testbed infrastructure was deployed at the Argonne Leadership Computing Facility (ALCF) and the National Energy Research Scientific Computingmore » Center (NERSC). The testbed was designed to be flexible and capable enough to explore a variety of computing models and hardware design points in order to understand the impact for various scientific applications. During the project, the testbed also served as a valuable resource to application scientists. Applications from a diverse set of projects such as MG-RAST (a metagenomics analysis server), the Joint Genome Institute, the STAR experiment at the Relativistic Heavy Ion Collider, and the Laser Interferometer Gravitational Wave Observatory (LIGO), were used by the Magellan project for benchmarking within the cloud, but the project teams were also able to accomplish important production science utilizing the Magellan cloud resources.« less

Information Power Grid Posters

NASA Technical Reports Server (NTRS)

Vaziri, Arsi

2003-01-01

This document is a summary of the accomplishments of the Information Power Grid (IPG). Grids are an emerging technology that provide seamless and uniform access to the geographically dispersed, computational, data storage, networking, instruments, and software resources needed for solving large-scale scientific and engineering problems. The goal of the NASA IPG is to use NASA's remotely located computing and data system resources to build distributed systems that can address problems that are too large or complex for a single site. The accomplishments outlined in this poster presentation are: access to distributed data, IPG heterogeneous computing, integration of large-scale computing node into distributed environment, remote access to high data rate instruments,and exploratory grid environment.

Efficient classical simulation of the Deutsch-Jozsa and Simon's algorithms

NASA Astrophysics Data System (ADS)

Johansson, Niklas; Larsson, Jan-Åke

2017-09-01

A long-standing aim of quantum information research is to understand what gives quantum computers their advantage. This requires separating problems that need genuinely quantum resources from those for which classical resources are enough. Two examples of quantum speed-up are the Deutsch-Jozsa and Simon's problem, both efficiently solvable on a quantum Turing machine, and both believed to lack efficient classical solutions. Here we present a framework that can simulate both quantum algorithms efficiently, solving the Deutsch-Jozsa problem with probability 1 using only one oracle query, and Simon's problem using linearly many oracle queries, just as expected of an ideal quantum computer. The presented simulation framework is in turn efficiently simulatable in a classical probabilistic Turing machine. This shows that the Deutsch-Jozsa and Simon's problem do not require any genuinely quantum resources, and that the quantum algorithms show no speed-up when compared with their corresponding classical simulation. Finally, this gives insight into what properties are needed in the two algorithms and calls for further study of oracle separation between quantum and classical computation.

Gravel resources, urbanization, and future land use, Front Range Urban Corridor, Colorado

USGS Publications Warehouse

Soule, James M.; Fitch, Harold R.

1974-01-01

An assessment of gravel needs in Front Range Urban Corridor markets to 2000 A.D., based on forecast population increases and urbanization, indicates that adequate resources to meet anticipated needs are potentially available, if future land use does not preclude their extraction. Because of urban encroachment onto gravel-bearing lands, this basic construction material is in short supply nationally and in the Front Range Urban Corridor. Longer hauls, increased prices, and use of alternatives, especially crushed rock aggregate, have resulted. An analysis of possible sequential land uses following gravel mining indicates that a desirable use is for 'real estate' ponds and small lakes. A method for computing gravel reserves, based on planimeter measurement of area of resource-bearing lands and statistical analysis of reliability of thickness and size distribution data, was developed to compute reserves in individual markets. A discussion of the qualitative 'usability' of these reserves is then made for the individual markets.

Proposal for grid computing for nuclear applications

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

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

2014-02-12

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

CMS Connect

NASA Astrophysics Data System (ADS)

Balcas, J.; Bockelman, B.; Gardner, R., Jr.; Hurtado Anampa, K.; Jayatilaka, B.; Aftab Khan, F.; Lannon, K.; Larson, K.; Letts, J.; Marra Da Silva, J.; Mascheroni, M.; Mason, D.; Perez-Calero Yzquierdo, A.; Tiradani, A.

2017-10-01

The CMS experiment collects and analyzes large amounts of data coming from high energy particle collisions produced by the Large Hadron Collider (LHC) at CERN. This involves a huge amount of real and simulated data processing that needs to be handled in batch-oriented platforms. The CMS Global Pool of computing resources provide +100K dedicated CPU cores and another 50K to 100K CPU cores from opportunistic resources for these kind of tasks and even though production and event processing analysis workflows are already managed by existing tools, there is still a lack of support to submit final stage condor-like analysis jobs familiar to Tier-3 or local Computing Facilities users into these distributed resources in an integrated (with other CMS services) and friendly way. CMS Connect is a set of computing tools and services designed to augment existing services in the CMS Physics community focusing on these kind of condor analysis jobs. It is based on the CI-Connect platform developed by the Open Science Grid and uses the CMS GlideInWMS infrastructure to transparently plug CMS global grid resources into a virtual pool accessed via a single submission machine. This paper describes the specific developments and deployment of CMS Connect beyond the CI-Connect platform in order to integrate the service with CMS specific needs, including specific Site submission, accounting of jobs and automated reporting to standard CMS monitoring resources in an effortless way to their users.

Requirements for fault-tolerant factoring on an atom-optics quantum computer.

PubMed

Devitt, Simon J; Stephens, Ashley M; Munro, William J; Nemoto, Kae

2013-01-01

Quantum information processing and its associated technologies have reached a pivotal stage in their development, with many experiments having established the basic building blocks. Moving forward, the challenge is to scale up to larger machines capable of performing computational tasks not possible today. This raises questions that need to be urgently addressed, such as what resources these machines will consume and how large will they be. Here we estimate the resources required to execute Shor's factoring algorithm on an atom-optics quantum computer architecture. We determine the runtime and size of the computer as a function of the problem size and physical error rate. Our results suggest that once the physical error rate is low enough to allow quantum error correction, optimization to reduce resources and increase performance will come mostly from integrating algorithms and circuits within the error correction environment, rather than from improving the physical hardware.

Reducing usage of the computational resources by event driven approach to model predictive control

NASA Astrophysics Data System (ADS)

Misik, Stefan; Bradac, Zdenek; Cela, Arben

2017-08-01

This paper deals with a real-time and optimal control of dynamic systems while also considers the constraints which these systems might be subject to. Main objective of this work is to propose a simple modification of the existing Model Predictive Control approach to better suit needs of computational resource-constrained real-time systems. An example using model of a mechanical system is presented and the performance of the proposed method is evaluated in a simulated environment.

Statistical, economic and other tools for assessing natural aggregate

USGS Publications Warehouse

Bliss, J.D.; Moyle, P.R.; Bolm, K.S.

2003-01-01

Quantitative aggregate resource assessment provides resource estimates useful for explorationists, land managers and those who make decisions about land allocation, which may have long-term implications concerning cost and the availability of aggregate resources. Aggregate assessment needs to be systematic and consistent, yet flexible enough to allow updating without invalidating other parts of the assessment. Evaluators need to use standard or consistent aggregate classification and statistic distributions or, in other words, models with geological, geotechnical and economic variables or interrelationships between these variables. These models can be used with subjective estimates, if needed, to estimate how much aggregate may be present in a region or country using distributions generated by Monte Carlo computer simulations.

Parallel computing for automated model calibration

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

Burke, John S.; Danielson, Gary R.; Schulz, Douglas A.

2002-07-29

Natural resources model calibration is a significant burden on computing and staff resources in modeling efforts. Most assessments must consider multiple calibration objectives (for example magnitude and timing of stream flow peak). An automated calibration process that allows real time updating of data/models, allowing scientists to focus effort on improving models is needed. We are in the process of building a fully featured multi objective calibration tool capable of processing multiple models cheaply and efficiently using null cycle computing. Our parallel processing and calibration software routines have been generically, but our focus has been on natural resources model calibration. Somore » far, the natural resources models have been friendly to parallel calibration efforts in that they require no inter-process communication, only need a small amount of input data and only output a small amount of statistical information for each calibration run. A typical auto calibration run might involve running a model 10,000 times with a variety of input parameters and summary statistical output. In the past model calibration has been done against individual models for each data set. The individual model runs are relatively fast, ranging from seconds to minutes. The process was run on a single computer using a simple iterative process. We have completed two Auto Calibration prototypes and are currently designing a more feature rich tool. Our prototypes have focused on running the calibration in a distributed computing cross platform environment. They allow incorporation of?smart? calibration parameter generation (using artificial intelligence processing techniques). Null cycle computing similar to SETI@Home has also been a focus of our efforts. This paper details the design of the latest prototype and discusses our plans for the next revision of the software.« less

Orchestrating Distributed Resource Ensembles for Petascale Science

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

Baldin, Ilya; Mandal, Anirban; Ruth, Paul

2014-04-24

Distributed, data-intensive computational science applications of interest to DOE scientific com- munities move large amounts of data for experiment data management, distributed analysis steps, remote visualization, and accessing scientific instruments. These applications need to orchestrate ensembles of resources from multiple resource pools and interconnect them with high-capacity multi- layered networks across multiple domains. It is highly desirable that mechanisms are designed that provide this type of resource provisioning capability to a broad class of applications. It is also important to have coherent monitoring capabilities for such complex distributed environments. In this project, we addressed these problems by designing an abstractmore » API, enabled by novel semantic resource descriptions, for provisioning complex and heterogeneous resources from multiple providers using their native provisioning mechanisms and control planes: computational, storage, and multi-layered high-speed network domains. We used an extensible resource representation based on semantic web technologies to afford maximum flexibility to applications in specifying their needs. We evaluated the effectiveness of provisioning using representative data-intensive ap- plications. We also developed mechanisms for providing feedback about resource performance to the application, to enable closed-loop feedback control and dynamic adjustments to resource allo- cations (elasticity). This was enabled through development of a novel persistent query framework that consumes disparate sources of monitoring data, including perfSONAR, and provides scalable distribution of asynchronous notifications.« less

Automation of the CFD Process on Distributed Computing Systems

NASA Technical Reports Server (NTRS)

Tejnil, Ed; Gee, Ken; Rizk, Yehia M.

2000-01-01

A script system was developed to automate and streamline portions of the CFD process. The system was designed to facilitate the use of CFD flow solvers on supercomputer and workstation platforms within a parametric design event. Integrating solver pre- and postprocessing phases, the fully automated ADTT script system marshalled the required input data, submitted the jobs to available computational resources, and processed the resulting output data. A number of codes were incorporated into the script system, which itself was part of a larger integrated design environment software package. The IDE and scripts were used in a design event involving a wind tunnel test. This experience highlighted the need for efficient data and resource management in all parts of the CFD process. To facilitate the use of CFD methods to perform parametric design studies, the script system was developed using UNIX shell and Perl languages. The goal of the work was to minimize the user interaction required to generate the data necessary to fill a parametric design space. The scripts wrote out the required input files for the user-specified flow solver, transferred all necessary input files to the computational resource, submitted and tracked the jobs using the resource queuing structure, and retrieved and post-processed the resulting dataset. For computational resources that did not run queueing software, the script system established its own simple first-in-first-out queueing structure to manage the workload. A variety of flow solvers were incorporated in the script system, including INS2D, PMARC, TIGER and GASP. Adapting the script system to a new flow solver was made easier through the use of object-oriented programming methods. The script system was incorporated into an ADTT integrated design environment and evaluated as part of a wind tunnel experiment. The system successfully generated the data required to fill the desired parametric design space. This stressed the computational resources required to compute and store the information. The scripts were continually modified to improve the utilization of the computational resources and reduce the likelihood of data loss due to failures. An ad-hoc file server was created to manage the large amount of data being generated as part of the design event. Files were stored and retrieved as needed to create new jobs and analyze the results. Additional information is contained in the original.

The transforming effect of handheld computers on nursing practice.

PubMed

Thompson, Brent W

2005-01-01

Handheld computers have the power to transform nursing care. The roots of this power are the shift to decentralization of communication, electronic health records, and nurses' greater need for information at the point of care. This article discusses the effects of handheld resources, calculators, databases, electronic health records, and communication devices on nursing practice. The US government has articulated the necessity of implementing the use of handheld computers in healthcare. Nurse administrators need to encourage and promote the diffusion of this technology, which can reduce costs and improve care.

The Eukaryotic Pathogen Databases: a functional genomic resource integrating data from human and veterinary parasites.

PubMed

Harb, Omar S; Roos, David S

2015-01-01

Over the past 20 years, advances in high-throughput biological techniques and the availability of computational resources including fast Internet access have resulted in an explosion of large genome-scale data sets "big data." While such data are readily available for download and personal use and analysis from a variety of repositories, often such analysis requires access to seldom-available computational skills. As a result a number of databases have emerged to provide scientists with online tools enabling the interrogation of data without the need for sophisticated computational skills beyond basic knowledge of Internet browser utility. This chapter focuses on the Eukaryotic Pathogen Databases (EuPathDB: http://eupathdb.org) Bioinformatic Resource Center (BRC) and illustrates some of the available tools and methods.

Adoption and implementation of a computer-delivered HIV/STD risk-reduction intervention for African American adolescent females seeking services at county health departments: implementation optimization is urgently needed.

PubMed

DiClemente, Ralph J; Bradley, Erin; Davis, Teaniese L; Brown, Jennifer L; Ukuku, Mary; Sales, Jessica M; Rose, Eve S; Wingood, Gina M

2013-06-01

Although group-delivered HIV/sexually transmitted disease (STD) risk-reduction interventions for African American adolescent females have proven efficacious, they require significant financial and staffing resources to implement and may not be feasible in personnel- and resource-constrained public health clinics. We conducted a study assessing adoption and implementation of an evidence-based HIV/STD risk-reduction intervention that was translated from a group-delivered modality to a computer-delivered modality to facilitate use in county public health departments. Usage of the computer-delivered intervention was low across 8 participating public health clinics. Further investigation is needed to optimize implementation by identifying, understanding, and surmounting barriers that hamper timely and efficient implementation of technology-delivered HIV/STD risk-reduction interventions in county public health clinics.

Adoption and Implementation of a Computer-delivered HIV/STD Risk-Reduction Intervention for African American Adolescent Females Seeking Services at County Health Departments: Implementation Optimization is Urgently Needed

PubMed Central

DiClemente, Ralph J.; Bradley, Erin; Davis, Teaniese L.; Brown, Jennifer L.; Ukuku, Mary; Sales, Jessica M.; Rose, Eve S.; Wingood, Gina M.

2013-01-01

Although group-delivered HIV/STD risk-reduction interventions for African American adolescent females have proven efficacious, they require significant financial and staffing resources to implement and may not be feasible in personnel- and resource-constrained public health clinics. We conducted a study assessing adoption and implementation of an evidence-based HIV/STD risk-reduction intervention that was translated from a group-delivered modality to a computer-delivered modality to facilitate use in county public health departments. Usage of the computer-delivered intervention was low across eight participating public health clinics. Further investigation is needed to optimize implementation by identifying, understanding and surmounting barriers that hamper timely and efficient implementation of technology-delivered HIV/STD risk-reduction interventions in county public health clinics. PMID:23673891

Optimisation of the usage of LHC and local computing resources in a multidisciplinary physics department hosting a WLCG Tier-2 centre

NASA Astrophysics Data System (ADS)

Barberis, Stefano; Carminati, Leonardo; Leveraro, Franco; Mazza, Simone Michele; Perini, Laura; Perlz, Francesco; Rebatto, David; Tura, Ruggero; Vaccarossa, Luca; Villaplana, Miguel

2015-12-01

We present the approach of the University of Milan Physics Department and the local unit of INFN to allow and encourage the sharing among different research areas of computing, storage and networking resources (the largest ones being those composing the Milan WLCG Tier-2 centre and tailored to the needs of the ATLAS experiment). Computing resources are organised as independent HTCondor pools, with a global master in charge of monitoring them and optimising their usage. The configuration has to provide satisfactory throughput for both serial and parallel (multicore, MPI) jobs. A combination of local, remote and cloud storage options are available. The experience of users from different research areas operating on this shared infrastructure is discussed. The promising direction of improving scientific computing throughput by federating access to distributed computing and storage also seems to fit very well with the objectives listed in the European Horizon 2020 framework for research and development.

Human face recognition using eigenface in cloud computing environment

NASA Astrophysics Data System (ADS)

Siregar, S. T. M.; Syahputra, M. F.; Rahmat, R. F.

2018-02-01

Doing a face recognition for one single face does not take a long time to process, but if we implement attendance system or security system on companies that have many faces to be recognized, it will take a long time. Cloud computing is a computing service that is done not on a local device, but on an internet connected to a data center infrastructure. The system of cloud computing also provides a scalability solution where cloud computing can increase the resources needed when doing larger data processing. This research is done by applying eigenface while collecting data as training data is also done by using REST concept to provide resource, then server can process the data according to existing stages. After doing research and development of this application, it can be concluded by implementing Eigenface, recognizing face by applying REST concept as endpoint in giving or receiving related information to be used as a resource in doing model formation to do face recognition.

High Energy Physics Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and High Energy Physics, June 10-12, 2015, Bethesda, Maryland

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

Habib, Salman; Roser, Robert; Gerber, Richard

The U.S. Department of Energy (DOE) Office of Science (SC) Offices of High Energy Physics (HEP) and Advanced Scientific Computing Research (ASCR) convened a programmatic Exascale Requirements Review on June 10–12, 2015, in Bethesda, Maryland. This report summarizes the findings, results, and recommendations derived from that meeting. The high-level findings and observations are as follows. Larger, more capable computing and data facilities are needed to support HEP science goals in all three frontiers: Energy, Intensity, and Cosmic. The expected scale of the demand at the 2025 timescale is at least two orders of magnitude — and in some cases greatermore » — than that available currently. The growth rate of data produced by simulations is overwhelming the current ability of both facilities and researchers to store and analyze it. Additional resources and new techniques for data analysis are urgently needed. Data rates and volumes from experimental facilities are also straining the current HEP infrastructure in its ability to store and analyze large and complex data volumes. Appropriately configured leadership-class facilities can play a transformational role in enabling scientific discovery from these datasets. A close integration of high-performance computing (HPC) simulation and data analysis will greatly aid in interpreting the results of HEP experiments. Such an integration will minimize data movement and facilitate interdependent workflows. Long-range planning between HEP and ASCR will be required to meet HEP’s research needs. To best use ASCR HPC resources, the experimental HEP program needs (1) an established, long-term plan for access to ASCR computational and data resources, (2) the ability to map workflows to HPC resources, (3) the ability for ASCR facilities to accommodate workflows run by collaborations potentially comprising thousands of individual members, (4) to transition codes to the next-generation HPC platforms that will be available at ASCR facilities, (5) to build up and train a workforce capable of developing and using simulations and analysis to support HEP scientific research on next-generation systems.« less

Budgeting and Funding School Technology: Essential Considerations

ERIC Educational Resources Information Center

Ireh, Maduakolam

2010-01-01

School districts need adequate financial resources to purchase hardware and software, wire their buildings to network computers and other information and communication devices, and connect to the Internet to provide students, teachers, and other school personnel with adequate access to technology. Computers and other peripherals, particularly,…

Interoperable PKI Data Distribution in Computational Grids

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

Pala, Massimiliano; Cholia, Shreyas; Rea, Scott A.

One of the most successful working examples of virtual organizations, computational grids need authentication mechanisms that inter-operate across domain boundaries. Public Key Infrastructures(PKIs) provide sufficient flexibility to allow resource managers to securely grant access to their systems in such distributed environments. However, as PKIs grow and services are added to enhance both security and usability, users and applications must struggle to discover available resources-particularly when the Certification Authority (CA) is alien to the relying party. This article presents how to overcome these limitations of the current grid authentication model by integrating the PKI Resource Query Protocol (PRQP) into the Gridmore » Security Infrastructure (GSI).« less

Reprocessing Multiyear GPS Data from Continuously Operating Reference Stations on Cloud Computing Platform

NASA Astrophysics Data System (ADS)

Yoon, S.

2016-12-01

To define geodetic reference frame using GPS data collected by Continuously Operating Reference Stations (CORS) network, historical GPS data needs to be reprocessed regularly. Reprocessing GPS data collected by upto 2000 CORS sites for the last two decades requires a lot of computational resource. At National Geodetic Survey (NGS), there has been one completed reprocessing in 2011, and currently, the second reprocessing is undergoing. For the first reprocessing effort, in-house computing resource was utilized. In the current second reprocessing effort, outsourced cloud computing platform is being utilized. In this presentation, the outline of data processing strategy at NGS is described as well as the effort to parallelize the data processing procedure in order to maximize the benefit of the cloud computing. The time and cost savings realized by utilizing cloud computing approach will also be discussed.

Computational Complexity and Human Decision-Making.

PubMed

Bossaerts, Peter; Murawski, Carsten

2017-12-01

The rationality principle postulates that decision-makers always choose the best action available to them. It underlies most modern theories of decision-making. The principle does not take into account the difficulty of finding the best option. Here, we propose that computational complexity theory (CCT) provides a framework for defining and quantifying the difficulty of decisions. We review evidence showing that human decision-making is affected by computational complexity. Building on this evidence, we argue that most models of decision-making, and metacognition, are intractable from a computational perspective. To be plausible, future theories of decision-making will need to take into account both the resources required for implementing the computations implied by the theory, and the resource constraints imposed on the decision-maker by biology. Copyright © 2017 Elsevier Ltd. All rights reserved.

Use of DHCP to provide essential information for care and management of HIV patients.

PubMed

Pfeil, C N; Ivey, J L; Hoffman, J D; Kuhn, I M

1991-01-01

The Department of Veterans' Affairs (VA) has reported over 10,000 Acquired Immune Deficiency Syndrome (AIDS) cases since the beginning of the epidemic. These cases were distributed throughout 152 of the VA's network of 172 medical centers and outpatient clinics. This network of health care facilities presents a unique opportunity to provide computer based information systems for clinical care and resource monitoring for these patients. The VA further facilitates such a venture through its commitment to the Decentralized Hospital Computer Program (DHCP). This paper describes a new application within DHCP known as the VA's HIV Registry. This project addresses the need to support clinical information as well as the added need to manage the resources necessary to care for HIV patients.

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.

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.

Grid site availability evaluation and monitoring at CMS

DOE PAGES

Lyons, Gaston; Maciulaitis, Rokas; Bagliesi, Giuseppe; ...

2017-10-01

The Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) uses distributed grid computing to store, process, and analyse the vast quantity of scientific data recorded every year. The computing resources are grouped into sites and organized in a tiered structure. Each site provides computing and storage to the CMS computing grid. Over a hundred sites worldwide contribute with resources from hundred to well over ten thousand computing cores and storage from tens of TBytes to tens of PBytes. In such a large computing setup scheduled and unscheduled outages occur continually and are not allowed to significantly impactmore » data handling, processing, and analysis. Unscheduled capacity and performance reductions need to be detected promptly and corrected. CMS developed a sophisticated site evaluation and monitoring system for Run 1 of the LHC based on tools of the Worldwide LHC Computing Grid. For Run 2 of the LHC the site evaluation and monitoring system is being overhauled to enable faster detection/reaction to failures and a more dynamic handling of computing resources. Furthermore, enhancements to better distinguish site from central service issues and to make evaluations more transparent and informative to site support staff are planned.« less

Grid site availability evaluation and monitoring at CMS

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

Lyons, Gaston; Maciulaitis, Rokas; Bagliesi, Giuseppe

The Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) uses distributed grid computing to store, process, and analyse the vast quantity of scientific data recorded every year. The computing resources are grouped into sites and organized in a tiered structure. Each site provides computing and storage to the CMS computing grid. Over a hundred sites worldwide contribute with resources from hundred to well over ten thousand computing cores and storage from tens of TBytes to tens of PBytes. In such a large computing setup scheduled and unscheduled outages occur continually and are not allowed to significantly impactmore » data handling, processing, and analysis. Unscheduled capacity and performance reductions need to be detected promptly and corrected. CMS developed a sophisticated site evaluation and monitoring system for Run 1 of the LHC based on tools of the Worldwide LHC Computing Grid. For Run 2 of the LHC the site evaluation and monitoring system is being overhauled to enable faster detection/reaction to failures and a more dynamic handling of computing resources. Furthermore, enhancements to better distinguish site from central service issues and to make evaluations more transparent and informative to site support staff are planned.« less

Grid site availability evaluation and monitoring at CMS

NASA Astrophysics Data System (ADS)

Lyons, Gaston; Maciulaitis, Rokas; Bagliesi, Giuseppe; Lammel, Stephan; Sciabà, Andrea

2017-10-01

The Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) uses distributed grid computing to store, process, and analyse the vast quantity of scientific data recorded every year. The computing resources are grouped into sites and organized in a tiered structure. Each site provides computing and storage to the CMS computing grid. Over a hundred sites worldwide contribute with resources from hundred to well over ten thousand computing cores and storage from tens of TBytes to tens of PBytes. In such a large computing setup scheduled and unscheduled outages occur continually and are not allowed to significantly impact data handling, processing, and analysis. Unscheduled capacity and performance reductions need to be detected promptly and corrected. CMS developed a sophisticated site evaluation and monitoring system for Run 1 of the LHC based on tools of the Worldwide LHC Computing Grid. For Run 2 of the LHC the site evaluation and monitoring system is being overhauled to enable faster detection/reaction to failures and a more dynamic handling of computing resources. Enhancements to better distinguish site from central service issues and to make evaluations more transparent and informative to site support staff are planned.

Integrating Computing Resources: A Shared Distributed Architecture for Academics and Administrators.

ERIC Educational Resources Information Center

Beltrametti, Monica; English, Will

1994-01-01

Development and implementation of a shared distributed computing architecture at the University of Alberta (Canada) are described. Aspects discussed include design of the architecture, users' views of the electronic environment, technical and managerial challenges, and the campuswide human infrastructures needed to manage such an integrated…

Exploring Cloud Computing for Distance Learning

ERIC Educational Resources Information Center

He, Wu; Cernusca, Dan; Abdous, M'hammed

2011-01-01

The use of distance courses in learning is growing exponentially. To better support faculty and students for teaching and learning, distance learning programs need to constantly innovate and optimize their IT infrastructures. The new IT paradigm called "cloud computing" has the potential to transform the way that IT resources are utilized and…

SOCR: Statistics Online Computational Resource

ERIC Educational Resources Information Center

Dinov, Ivo D.

2006-01-01

The need for hands-on computer laboratory experience in undergraduate and graduate statistics education has been firmly established in the past decade. As a result a number of attempts have been undertaken to develop novel approaches for problem-driven statistical thinking, data analysis and result interpretation. In this paper we describe an…

An interactive computer approach to performing resource analysis for a multi-resource/multi-project problem. [Spacelab inventory procurement planning

NASA Technical Reports Server (NTRS)

Schlagheck, R. A.

1977-01-01

New planning techniques and supporting computer tools are needed for the optimization of resources and costs for space transportation and payload systems. Heavy emphasis on cost effective utilization of resources has caused NASA program planners to look at the impact of various independent variables that affect procurement buying. A description is presented of a category of resource planning which deals with Spacelab inventory procurement analysis. Spacelab is a joint payload project between NASA and the European Space Agency and will be flown aboard the Space Shuttle starting in 1980. In order to respond rapidly to the various procurement planning exercises, a system was built that could perform resource analysis in a quick and efficient manner. This system is known as the Interactive Resource Utilization Program (IRUP). Attention is given to aspects of problem definition, an IRUP system description, questions of data base entry, the approach used for project scheduling, and problems of resource allocation.

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

Cloud computing in medical imaging.

PubMed

Kagadis, George C; Kloukinas, Christos; Moore, Kevin; Philbin, Jim; Papadimitroulas, Panagiotis; Alexakos, Christos; Nagy, Paul G; Visvikis, Dimitris; Hendee, William R

2013-07-01

Over the past century technology has played a decisive role in defining, driving, and reinventing procedures, devices, and pharmaceuticals in healthcare. Cloud computing has been introduced only recently but is already one of the major topics of discussion in research and clinical settings. The provision of extensive, easily accessible, and reconfigurable resources such as virtual systems, platforms, and applications with low service cost has caught the attention of many researchers and clinicians. Healthcare researchers are moving their efforts to the cloud, because they need adequate resources to process, store, exchange, and use large quantities of medical data. This Vision 20/20 paper addresses major questions related to the applicability of advanced cloud computing in medical imaging. The paper also considers security and ethical issues that accompany cloud computing.

On Using Home Networks and Cloud Computing for a Future Internet of Things

NASA Astrophysics Data System (ADS)

Niedermayer, Heiko; Holz, Ralph; Pahl, Marc-Oliver; Carle, Georg

In this position paper we state four requirements for a Future Internet and sketch our initial concept. The requirements: (1) more comfort, (2) integration of home networks, (3) resources like service clouds in the network, and (4) access anywhere on any machine. Future Internet needs future quality and future comfort. There need to be new possiblities for everyone. Our focus is on higher layers and related to the many overlay proposals. We consider them to run on top of a basic Future Internet core. A new user experience means to include all user devices. Home networks and services should be a fundamental part of the Future Internet. Home networks extend access and allow interaction with the environment. Cloud Computing can provide reliable resources beyond local boundaries. For access anywhere, we also need secure storage for data and profiles in the network, in particular for access with non-personal devices (Internet terminal, ticket machine, ...).

State of the Art of Network Security Perspectives in Cloud Computing

NASA Astrophysics Data System (ADS)

Oh, Tae Hwan; Lim, Shinyoung; Choi, Young B.; Park, Kwang-Roh; Lee, Heejo; Choi, Hyunsang

Cloud computing is now regarded as one of social phenomenon that satisfy customers' needs. It is possible that the customers' needs and the primary principle of economy - gain maximum benefits from minimum investment - reflects realization of cloud computing. We are living in the connected society with flood of information and without connected computers to the Internet, our activities and work of daily living will be impossible. Cloud computing is able to provide customers with custom-tailored features of application software and user's environment based on the customer's needs by adopting on-demand outsourcing of computing resources through the Internet. It also provides cloud computing users with high-end computing power and expensive application software package, and accordingly the users will access their data and the application software where they are located at the remote system. As the cloud computing system is connected to the Internet, network security issues of cloud computing are considered as mandatory prior to real world service. In this paper, survey and issues on the network security in cloud computing are discussed from the perspective of real world service environments.

Pilots 2.0: DIRAC pilots for all the skies

NASA Astrophysics Data System (ADS)

Stagni, F.; Tsaregorodtsev, A.; McNab, A.; Luzzi, C.

2015-12-01

In the last few years, new types of computing infrastructures, such as IAAS (Infrastructure as a Service) and IAAC (Infrastructure as a Client), gained popularity. New resources may come as part of pledged resources, while others are opportunistic. Most of these new infrastructures are based on virtualization techniques. Meanwhile, some concepts, such as distributed queues, lost appeal, while still supporting a vast amount of resources. Virtual Organizations are therefore facing heterogeneity of the available resources and the use of an Interware software like DIRAC to hide the diversity of underlying resources has become essential. The DIRAC WMS is based on the concept of pilot jobs that was introduced back in 2004. A pilot is what creates the possibility to run jobs on a worker node. Within DIRAC, we developed a new generation of pilot jobs, that we dubbed Pilots 2.0. Pilots 2.0 are not tied to a specific infrastructure; rather they are generic, fully configurable and extendible pilots. A Pilot 2.0 can be sent, as a script to be run, or it can be fetched from a remote location. A pilot 2.0 can run on every computing resource, e.g.: on CREAM Computing elements, on DIRAC Computing elements, on Virtual Machines as part of the contextualization script, or IAAC resources, provided that these machines are properly configured, hiding all the details of the Worker Nodes (WNs) infrastructure. Pilots 2.0 can be generated server and client side. Pilots 2.0 are the “pilots to fly in all the skies”, aiming at easy use of computing power, in whatever form it is presented. Another aim is the unification and simplification of the monitoring infrastructure for all kinds of computing resources, by using pilots as a network of distributed sensors coordinated by a central resource monitoring system. Pilots 2.0 have been developed using the command pattern. VOs using DIRAC can tune pilots 2.0 as they need, and extend or replace each and every pilot command in an easy way. In this paper we describe how Pilots 2.0 work with distributed and heterogeneous resources providing the necessary abstraction to deal with different kind of computing resources.

Use of Emerging Grid Computing Technologies for the Analysis of LIGO Data

NASA Astrophysics Data System (ADS)

Koranda, Scott

2004-03-01

The LIGO Scientific Collaboration (LSC) today faces the challenge of enabling analysis of terabytes of LIGO data by hundreds of scientists from institutions all around the world. To meet this challenge the LSC is developing tools, infrastructure, applications, and expertise leveraging Grid Computing technologies available today, and making available to LSC scientists compute resources at sites across the United States and Europe. We use digital credentials for strong and secure authentication and authorization to compute resources and data. Building on top of products from the Globus project for high-speed data transfer and information discovery we have created the Lightweight Data Replicator (LDR) to securely and robustly replicate data to resource sites. We have deployed at our computing sites the Virtual Data Toolkit (VDT) Server and Client packages, developed in collaboration with our partners in the GriPhyN and iVDGL projects, providing uniform access to distributed resources for users and their applications. Taken together these Grid Computing technologies and infrastructure have formed the LSC DataGrid--a coherent and uniform environment across two continents for the analysis of gravitational-wave detector data. Much work, however, remains in order to scale current analyses and recent lessons learned need to be integrated into the next generation of Grid middleware.

SARANA: language, compiler and run-time system support for spatially aware and resource-aware mobile computing.

PubMed

Hari, Pradip; Ko, Kevin; Koukoumidis, Emmanouil; Kremer, Ulrich; Martonosi, Margaret; Ottoni, Desiree; Peh, Li-Shiuan; Zhang, Pei

2008-10-28

Increasingly, spatial awareness plays a central role in many distributed and mobile computing applications. Spatially aware applications rely on information about the geographical position of compute devices and their supported services in order to support novel functionality. While many spatial application drivers already exist in mobile and distributed computing, very little systems research has explored how best to program these applications, to express their spatial and temporal constraints, and to allow efficient implementations on highly dynamic real-world platforms. This paper proposes the SARANA system architecture, which includes language and run-time system support for spatially aware and resource-aware applications. SARANA allows users to express spatial regions of interest, as well as trade-offs between quality of result (QoR), latency and cost. The goal is to produce applications that use resources efficiently and that can be run on diverse resource-constrained platforms ranging from laptops to personal digital assistants and to smart phones. SARANA's run-time system manages QoR and cost trade-offs dynamically by tracking resource availability and locations, brokering usage/pricing agreements and migrating programs to nodes accordingly. A resource cost model permeates the SARANA system layers, permitting users to express their resource needs and QoR expectations in units that make sense to them. Although we are still early in the system development, initial versions have been demonstrated on a nine-node system prototype.

Curriculum and Resources: Computer Provision in a CTC.

ERIC Educational Resources Information Center

Denholm, Lawrence

The program for City Technical Colleges (CTCs) draws on ideas and resources from government, private industry, and education to focus on the educational needs of inner city and urban children. Mathematics, science, and technology are at the center of the CTCs' mission, in a context which includes economic awareness and a commitment to enterprise…

Virtual Learning Environments on the Go: CALL Meets MALL

ERIC Educational Resources Information Center

Arús Hita, Jorge

2016-01-01

This paper presents "Eating out," a Moodle-based digital learning resource for English as a Foreign Language (EFL) teaching that can be run both on computers and mobile devices. It is argued that Mobile Assisted Language Learning (MALL) resources do not necessarily need to be specifically designed for such platforms. Rather, a carefully…

Mobility for GCSS-MC through virtual PCs

DTIC Science & Technology

2017-06-01

their productivity. Mobile device access to GCSS-MC would allow Marines to access a required program for their mission using a form of computing ...network throughput applications with a device running on various operating systems with limited computational ability. The use of VPCs leads to a...reduced need for network throughput and faster overall execution. 14. SUBJECT TERMS GCSS-MC, enterprise resource planning, virtual personal computer

U.S. Geological Survey Groundwater Modeling Software: Making Sense of a Complex Natural Resource

USGS Publications Warehouse

Provost, Alden M.; Reilly, Thomas E.; Harbaugh, Arlen W.; Pollock, David W.

2009-01-01

Computer models of groundwater systems simulate the flow of groundwater, including water levels, and the transport of chemical constituents and thermal energy. Groundwater models afford hydrologists a framework on which to organize their knowledge and understanding of groundwater systems, and they provide insights water-resources managers need to plan effectively for future water demands. Building on decades of experience, the U.S. Geological Survey (USGS) continues to lead in the development and application of computer software that allows groundwater models to address scientific and management questions of increasing complexity.

Collaborative Working Architecture for IoT-Based Applications.

PubMed

Mora, Higinio; Signes-Pont, María Teresa; Gil, David; Johnsson, Magnus

2018-05-23

The new sensing applications need enhanced computing capabilities to handle the requirements of complex and huge data processing. The Internet of Things (IoT) concept brings processing and communication features to devices. In addition, the Cloud Computing paradigm provides resources and infrastructures for performing the computations and outsourcing the work from the IoT devices. This scenario opens new opportunities for designing advanced IoT-based applications, however, there is still much research to be done to properly gear all the systems for working together. This work proposes a collaborative model and an architecture to take advantage of the available computing resources. The resulting architecture involves a novel network design with different levels which combines sensing and processing capabilities based on the Mobile Cloud Computing (MCC) paradigm. An experiment is included to demonstrate that this approach can be used in diverse real applications. The results show the flexibility of the architecture to perform complex computational tasks of advanced applications.

Hospital influenza pandemic stockpiling needs: A computer simulation.

PubMed

Abramovich, Mark N; Hershey, John C; Callies, Byron; Adalja, Amesh A; Tosh, Pritish K; Toner, Eric S

2017-03-01

A severe influenza pandemic could overwhelm hospitals but planning guidance that accounts for the dynamic interrelationships between planning elements is lacking. We developed a methodology to calculate pandemic supply needs based on operational considerations in hospitals and then tested the methodology at Mayo Clinic in Rochester, MN. We upgraded a previously designed computer modeling tool and input carefully researched resource data from the hospital to run 10,000 Monte Carlo simulations using various combinations of variables to determine resource needs across a spectrum of scenarios. Of 10,000 iterations, 1,315 fell within the parameters defined by our simulation design and logical constraints. From these valid iterations, we projected supply requirements by percentile for key supplies, pharmaceuticals, and personal protective equipment requirements needed in a severe pandemic. We projected supplies needs for a range of scenarios that use up to 100% of Mayo Clinic-Rochester's surge capacity of beds and ventilators. The results indicate that there are diminishing patient care benefits for stockpiling on the high side of the range, but that having some stockpile of critical resources, even if it is relatively modest, is most important. We were able to display the probabilities of needing various supply levels across a spectrum of scenarios. The tool could be used to model many other hospital preparedness issues, but validation in other settings is needed. Copyright © 2017 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

Validating the soil vulnerability index for a claypan watershed

USDA-ARS?s Scientific Manuscript database

Assessment studies of conservation efforts have shown that best management practices were not always implemented in the most vulnerable areas where they are most needed. While complex computer simulation models can be used to identify these areas, resources needed for using such models are beyond re...

ATLAS Cloud R&D

NASA Astrophysics Data System (ADS)

Panitkin, Sergey; Barreiro Megino, Fernando; Caballero Bejar, Jose; Benjamin, Doug; Di Girolamo, Alessandro; Gable, Ian; Hendrix, Val; Hover, John; Kucharczyk, Katarzyna; Medrano Llamas, Ramon; Love, Peter; Ohman, Henrik; Paterson, Michael; Sobie, Randall; Taylor, Ryan; Walker, Rodney; Zaytsev, Alexander; Atlas Collaboration

2014-06-01

The computing model of the ATLAS experiment was designed around the concept of grid computing and, since the start of data taking, this model has proven very successful. However, new cloud computing technologies bring attractive features to improve the operations and elasticity of scientific distributed computing. ATLAS sees grid and cloud computing as complementary technologies that will coexist at different levels of resource abstraction, and two years ago created an R&D working group to investigate the different integration scenarios. The ATLAS Cloud Computing R&D has been able to demonstrate the feasibility of offloading work from grid to cloud sites and, as of today, is able to integrate transparently various cloud resources into the PanDA workload management system. The ATLAS Cloud Computing R&D is operating various PanDA queues on private and public resources and has provided several hundred thousand CPU days to the experiment. As a result, the ATLAS Cloud Computing R&D group has gained a significant insight into the cloud computing landscape and has identified points that still need to be addressed in order to fully utilize this technology. This contribution will explain the cloud integration models that are being evaluated and will discuss ATLAS' learning during the collaboration with leading commercial and academic cloud providers.

Evaluating interactive computer-based scenarios designed for learning medical technology.

PubMed

Persson, Johanna; Dalholm, Elisabeth Hornyánszky; Wallergård, Mattias; Johansson, Gerd

2014-11-01

The use of medical equipment is growing in healthcare, resulting in an increased need for resources to educate users in how to manage the various devices. Learning the practical operation of a device is one thing, but learning how to work with the device in the actual clinical context is more challenging. This paper presents a computer-based simulation prototype for learning medical technology in the context of critical care. Properties from simulation and computer games have been adopted to create a visualization-based, interactive and contextually bound tool for learning. A participatory design process, including three researchers and three practitioners from a clinic for infectious diseases, was adopted to adjust the form and content of the prototype to the needs of the clinical practice and to create a situated learning experience. An evaluation with 18 practitioners showed that practitioners were positive to this type of tool for learning and that it served as a good platform for eliciting and sharing knowledge. Our conclusion is that this type of tools can be a complement to traditional learning resources to situate the learning in a context without requiring advanced technology or being resource-demanding. Copyright © 2014 Elsevier Ltd. All rights reserved.

The diverse use of clouds by CMS

DOE PAGES

Andronis, Anastasios; Bauer, Daniela; Chaze, Olivier; ...

2015-12-23

The resources CMS is using are increasingly being offered as clouds. In Run 2 of the LHC the majority of CMS CERN resources, both in Meyrin and at the Wigner Computing Centre, will be presented as cloud resources on which CMS will have to build its own infrastructure. This infrastructure will need to run all of the CMS workflows including: Tier 0, production and user analysis. In addition, the CMS High Level Trigger will provide a compute resource comparable in scale to the total offered by the CMS Tier 1 sites, when it is not running as part of themore » trigger system. During these periods a cloud infrastructure will be overlaid on this resource, making it accessible for general CMS use. Finally, CMS is starting to utilise cloud resources being offered by individual institutes and is gaining experience to facilitate the use of opportunistically available cloud resources. Lastly, we present a snap shot of this infrastructure and its operation at the time of the CHEP2015 conference.« less

An Analysis of Cloud Computing with Amazon Web Services for the Atmospheric Science Data Center

NASA Astrophysics Data System (ADS)

Gleason, J. L.; Little, M. M.

2013-12-01

NASA science and engineering efforts rely heavily on compute and data handling systems. The nature of NASA science data is such that it is not restricted to NASA users, instead it is widely shared across a globally distributed user community including scientists, educators, policy decision makers, and the public. Therefore NASA science computing is a candidate use case for cloud computing where compute resources are outsourced to an external vendor. Amazon Web Services (AWS) is a commercial cloud computing service developed to use excess computing capacity at Amazon, and potentially provides an alternative to costly and potentially underutilized dedicated acquisitions whenever NASA scientists or engineers require additional data processing. AWS desires to provide a simplified avenue for NASA scientists and researchers to share large, complex data sets with external partners and the public. AWS has been extensively used by JPL for a wide range of computing needs and was previously tested on a NASA Agency basis during the Nebula testing program. Its ability to support the Langley Science Directorate needs to be evaluated by integrating it with real world operational needs across NASA and the associated maturity that would come with that. The strengths and weaknesses of this architecture and its ability to support general science and engineering applications has been demonstrated during the previous testing. The Langley Office of the Chief Information Officer in partnership with the Atmospheric Sciences Data Center (ASDC) has established a pilot business interface to utilize AWS cloud computing resources on a organization and project level pay per use model. This poster discusses an effort to evaluate the feasibility of the pilot business interface from a project level perspective by specifically using a processing scenario involving the Clouds and Earth's Radiant Energy System (CERES) project.

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.

Computers-for-edu: An Advanced Business Application Programming (ABAP) Teaching Case

ERIC Educational Resources Information Center

Boyle, Todd A.

2007-01-01

The "Computers-for-edu" case is designed to provide students with hands-on exposure to creating Advanced Business Application Programming (ABAP) reports and dialogue programs, as well as navigating various mySAP Enterprise Resource Planning (ERP) transactions needed by ABAP developers. The case requires students to apply a wide variety…

Virtual pools for interactive analysis and software development through an integrated Cloud environment

NASA Astrophysics Data System (ADS)

Grandi, C.; Italiano, A.; Salomoni, D.; Calabrese Melcarne, A. K.

2011-12-01

WNoDeS, an acronym for Worker Nodes on Demand Service, is software developed at CNAF-Tier1, the National Computing Centre of the Italian Institute for Nuclear Physics (INFN) located in Bologna. WNoDeS provides on demand, integrated access to both Grid and Cloud resources through virtualization technologies. Besides the traditional use of computing resources in batch mode, users need to have interactive and local access to a number of systems. WNoDeS can dynamically select these computers instantiating Virtual Machines, according to the requirements (computing, storage and network resources) of users through either the Open Cloud Computing Interface API, or through a web console. An interactive use is usually limited to activities in user space, i.e. where the machine configuration is not modified. In some other instances the activity concerns development and testing of services and thus implies the modification of the system configuration (and, therefore, root-access to the resource). The former use case is a simple extension of the WNoDeS approach, where the resource is provided in interactive mode. The latter implies saving the virtual image at the end of each user session so that it can be presented to the user at subsequent requests. This work describes how the LHC experiments at INFN-Bologna are testing and making use of these dynamically created ad-hoc machines via WNoDeS to support flexible, interactive analysis and software development at the INFN Tier-1 Computing Centre.

Use of DHCP to provide essential information for care and management of HIV patients.

PubMed Central

Pfeil, C. N.; Ivey, J. L.; Hoffman, J. D.; Kuhn, I. M.

1991-01-01

The Department of Veterans' Affairs (VA) has reported over 10,000 Acquired Immune Deficiency Syndrome (AIDS) cases since the beginning of the epidemic. These cases were distributed throughout 152 of the VA's network of 172 medical centers and outpatient clinics. This network of health care facilities presents a unique opportunity to provide computer based information systems for clinical care and resource monitoring for these patients. The VA further facilitates such a venture through its commitment to the Decentralized Hospital Computer Program (DHCP). This paper describes a new application within DHCP known as the VA's HIV Registry. This project addresses the need to support clinical information as well as the added need to manage the resources necessary to care for HIV patients. PMID:1807575

Databases, data integration, and expert systems: new directions in mineral resource assessment and mineral exploration

USGS Publications Warehouse

McCammon, Richard B.; Ramani, Raja V.; Mozumdar, Bijoy K.; Samaddar, Arun B.

1994-01-01

Overcoming future difficulties in searching for ore deposits deeper in the earth's crust will require closer attention to the collection and analysis of more diverse types of data and to more efficient use of current computer technologies. Computer technologies of greatest interest include methods of storage and retrieval of resource information, methods for integrating geologic, geochemical, and geophysical data, and the introduction of advanced computer technologies such as expert systems, multivariate techniques, and neural networks. Much experience has been gained in the past few years in applying these technologies. More experience is needed if they are to be implemented for everyday use in future assessments and exploration.

Lunar Applications in Reconfigurable Computing

NASA Technical Reports Server (NTRS)

Somervill, Kevin

2008-01-01

NASA s Constellation Program is developing a lunar surface outpost in which reconfigurable computing will play a significant role. Reconfigurable systems provide a number of benefits over conventional software-based implementations including performance and power efficiency, while the use of standardized reconfigurable hardware provides opportunities to reduce logistical overhead. The current vision for the lunar surface architecture includes habitation, mobility, and communications systems, each of which greatly benefit from reconfigurable hardware in applications including video processing, natural feature recognition, data formatting, IP offload processing, and embedded control systems. In deploying reprogrammable hardware, considerations similar to those of software systems must be managed. There needs to be a mechanism for discovery enabling applications to locate and utilize the available resources. Also, application interfaces are needed to provide for both configuring the resources as well as transferring data between the application and the reconfigurable hardware. Each of these topics are explored in the context of deploying reconfigurable resources as an integral aspect of the lunar exploration architecture.

Stream-based Hebbian eigenfilter for real-time neuronal spike discrimination

PubMed Central

2012-01-01

Background Principal component analysis (PCA) has been widely employed for automatic neuronal spike sorting. Calculating principal components (PCs) is computationally expensive, and requires complex numerical operations and large memory resources. Substantial hardware resources are therefore needed for hardware implementations of PCA. General Hebbian algorithm (GHA) has been proposed for calculating PCs of neuronal spikes in our previous work, which eliminates the needs of computationally expensive covariance analysis and eigenvalue decomposition in conventional PCA algorithms. However, large memory resources are still inherently required for storing a large volume of aligned spikes for training PCs. The large size memory will consume large hardware resources and contribute significant power dissipation, which make GHA difficult to be implemented in portable or implantable multi-channel recording micro-systems. Method In this paper, we present a new algorithm for PCA-based spike sorting based on GHA, namely stream-based Hebbian eigenfilter, which eliminates the inherent memory requirements of GHA while keeping the accuracy of spike sorting by utilizing the pseudo-stationarity of neuronal spikes. Because of the reduction of large hardware storage requirements, the proposed algorithm can lead to ultra-low hardware resources and power consumption of hardware implementations, which is critical for the future multi-channel micro-systems. Both clinical and synthetic neural recording data sets were employed for evaluating the accuracy of the stream-based Hebbian eigenfilter. The performance of spike sorting using stream-based eigenfilter and the computational complexity of the eigenfilter were rigorously evaluated and compared with conventional PCA algorithms. Field programmable logic arrays (FPGAs) were employed to implement the proposed algorithm, evaluate the hardware implementations and demonstrate the reduction in both power consumption and hardware memories achieved by the streaming computing Results and discussion Results demonstrate that the stream-based eigenfilter can achieve the same accuracy and is 10 times more computationally efficient when compared with conventional PCA algorithms. Hardware evaluations show that 90.3% logic resources, 95.1% power consumption and 86.8% computing latency can be reduced by the stream-based eigenfilter when compared with PCA hardware. By utilizing the streaming method, 92% memory resources and 67% power consumption can be saved when compared with the direct implementation of GHA. Conclusion Stream-based Hebbian eigenfilter presents a novel approach to enable real-time spike sorting with reduced computational complexity and hardware costs. This new design can be further utilized for multi-channel neuro-physiological experiments or chronic implants. PMID:22490725

Interoperating Cloud-based Virtual Farms

NASA Astrophysics Data System (ADS)

Bagnasco, S.; Colamaria, F.; Colella, D.; Casula, E.; Elia, D.; Franco, A.; Lusso, S.; Luparello, G.; Masera, M.; Miniello, G.; Mura, D.; Piano, S.; Vallero, S.; Venaruzzo, M.; Vino, G.

2015-12-01

The present work aims at optimizing the use of computing resources available at the grid Italian Tier-2 sites of the ALICE experiment at CERN LHC by making them accessible to interactive distributed analysis, thanks to modern solutions based on cloud computing. The scalability and elasticity of the computing resources via dynamic (“on-demand”) provisioning is essentially limited by the size of the computing site, reaching the theoretical optimum only in the asymptotic case of infinite resources. The main challenge of the project is to overcome this limitation by federating different sites through a distributed cloud facility. Storage capacities of the participating sites are seen as a single federated storage area, preventing the need of mirroring data across them: high data access efficiency is guaranteed by location-aware analysis software and storage interfaces, in a transparent way from an end-user perspective. Moreover, the interactive analysis on the federated cloud reduces the execution time with respect to grid batch jobs. The tests of the investigated solutions for both cloud computing and distributed storage on wide area network will be presented.

Distributed storage and cloud computing: a test case

NASA Astrophysics Data System (ADS)

Piano, S.; Delia Ricca, G.

2014-06-01

Since 2003 the computing farm hosted by the INFN Tier3 facility in Trieste supports the activities of many scientific communities. Hundreds of jobs from 45 different VOs, including those of the LHC experiments, are processed simultaneously. Given that normally the requirements of the different computational communities are not synchronized, the probability that at any given time the resources owned by one of the participants are not fully utilized is quite high. A balanced compensation should in principle allocate the free resources to other users, but there are limits to this mechanism. In fact, the Trieste site may not hold the amount of data needed to attract enough analysis jobs, and even in that case there could be a lack of bandwidth for their access. The Trieste ALICE and CMS computing groups, in collaboration with other Italian groups, aim to overcome the limitations of existing solutions using two approaches: sharing the data among all the participants taking full advantage of GARR-X wide area networks (10 GB/s) and integrating the resources dedicated to batch analysis with the ones reserved for dynamic interactive analysis, through modern solutions as cloud computing.

Intellectual Honesty in the Era of Computing.

ERIC Educational Resources Information Center

Connolly, Frank W.

1995-01-01

Discusses the need for intellectual honesty in using technology. Topics include intellectual property laws; ethics; indirect results of copying software and images; the need for institutional policy; and the provision of facilities and resources that encourage respect for policy. A sidebar provides "A Bill of Rights and Responsibilities for…

Wide-Area Network Resources for Teacher Education.

ERIC Educational Resources Information Center

Aust, Ronald

A central feature of the High Performance Computing Act of 1991 is the establishment of a National Research and Education Network (NREN). The level of access that teachers and teacher educators will need to benefit from the NREN and the types of network resources that are most useful for educators are explored, along with design issues that are…

The DoD's High Performance Computing Modernization Program - Ensuing the National Earth Systems Prediction Capability Becomes Operational

NASA Astrophysics Data System (ADS)

Burnett, W.

2016-12-01

The Department of Defense's (DoD) High Performance Computing Modernization Program (HPCMP) provides high performance computing to address the most significant challenges in computational resources, software application support and nationwide research and engineering networks. Today, the HPCMP has a critical role in ensuring the National Earth System Prediction Capability (N-ESPC) achieves initial operational status in 2019. A 2015 study commissioned by the HPCMP found that N-ESPC computational requirements will exceed interconnect bandwidth capacity due to the additional load from data assimilation and passing connecting data between ensemble codes. Memory bandwidth and I/O bandwidth will continue to be significant bottlenecks for the Navy's Hybrid Coordinate Ocean Model (HYCOM) scalability - by far the major driver of computing resource requirements in the N-ESPC. The study also found that few of the N-ESPC model developers have detailed plans to ensure their respective codes scale through 2024. Three HPCMP initiatives are designed to directly address and support these issues: Productivity Enhancement, Technology, Transfer and Training (PETTT), the HPCMP Applications Software Initiative (HASI), and Frontier Projects. PETTT supports code conversion by providing assistance, expertise and training in scalable and high-end computing architectures. HASI addresses the continuing need for modern application software that executes effectively and efficiently on next-generation high-performance computers. Frontier Projects enable research and development that could not be achieved using typical HPCMP resources by providing multi-disciplinary teams access to exceptional amounts of high performance computing resources. Finally, the Navy's DoD Supercomputing Resource Center (DSRC) currently operates a 6 Petabyte system, of which Naval Oceanography receives 15% of operational computational system use, or approximately 1 Petabyte of the processing capability. The DSRC will provide the DoD with future computing assets to initially operate the N-ESPC in 2019. This talk will further describe how DoD's HPCMP will ensure N-ESPC becomes operational, efficiently and effectively, using next-generation high performance computing.

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.

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.

Short-term Temperature Prediction Using Adaptive Computing on Dynamic Scales

NASA Astrophysics Data System (ADS)

Hu, W.; Cervone, G.; Jha, S.; Balasubramanian, V.; Turilli, M.

2017-12-01

When predicting temperature, there are specific places and times when high accuracy predictions are harder. For example, not all the sub-regions in the domain require the same amount of computing resources to generate an accurate prediction. Plateau areas might require less computing resources than mountainous areas because of the steeper gradient of temperature change in the latter. However, it is difficult to estimate beforehand the optimal allocation of computational resources because several parameters play a role in determining the accuracy of the forecasts, in addition to orography. The allocation of resources to perform simulations can become a bottleneck because it requires human intervention to stop jobs or start new ones. The goal of this project is to design and develop a dynamic approach to generate short-term temperature predictions that can automatically determines the required computing resources and the geographic scales of the predictions based on the spatial and temporal uncertainties. The predictions and the prediction quality metrics are computed using a numeric weather prediction model, Analog Ensemble (AnEn), and the parallelization on high performance computing systems is accomplished using Ensemble Toolkit, one component of the RADICAL-Cybertools family of tools. RADICAL-Cybertools decouple the science needs from the computational capabilities by building an intermediate layer to run general ensemble patterns, regardless of the science. In this research, we show how the ensemble toolkit allows generating high resolution temperature forecasts at different spatial and temporal resolution. The AnEn algorithm is run using NAM analysis and forecasts data for the continental United States for a period of 2 years. AnEn results show that temperature forecasts perform well according to different probabilistic and deterministic statistical tests.

NASA Astrophysics Data System (ADS)

Knosp, B.; Neely, S.; Zimdars, P.; Mills, B.; Vance, N.

2007-12-01

The Microwave Limb Sounder (MLS) Science Computing Facility (SCF) stores over 50 terabytes of data, has over 240 computer processing hosts, and 64 users from around the world. These resources are spread over three primary geographical locations - the Jet Propulsion Laboratory (JPL), Raytheon RIS, and New Mexico Institute of Mining and Technology (NMT). A need for a grid network system was identified and defined to solve the problem of users competing for finite, and increasingly scarce, MLS SCF computing resources. Using Sun's Grid Engine software, a grid network was successfully created in a development environment that connected the JPL and Raytheon sites, established master and slave hosts, and demonstrated that transfer queues for jobs can work among multiple clusters in the same grid network. This poster will first describe MLS SCF resources and the lessons that were learned in the design and development phase of this project. It will then go on to discuss the test environment and plans for deployment by highlighting benchmarks and user experiences.

Efficient universal blind quantum computation.

PubMed

Giovannetti, Vittorio; Maccone, Lorenzo; Morimae, Tomoyuki; Rudolph, Terry G

2013-12-06

We give a cheat sensitive protocol for blind universal quantum computation that is efficient in terms of computational and communication resources: it allows one party to perform an arbitrary computation on a second party's quantum computer without revealing either which computation is performed, or its input and output. The first party's computational capabilities can be extremely limited: she must only be able to create and measure single-qubit superposition states. The second party is not required to use measurement-based quantum computation. The protocol requires the (optimal) exchange of O(Jlog2(N)) single-qubit states, where J is the computational depth and N is the number of qubits needed for the computation.

A multipurpose computing center with distributed resources

NASA Astrophysics Data System (ADS)

Chudoba, J.; Adam, M.; Adamová, D.; Kouba, T.; Mikula, A.; Říkal, V.; Švec, J.; Uhlířová, J.; Vokáč, P.; Svatoš, M.

2017-10-01

The Computing Center of the Institute of Physics (CC IoP) of the Czech Academy of Sciences serves a broad spectrum of users with various computing needs. It runs WLCG Tier-2 center for the ALICE and the ATLAS experiments; the same group of services is used by astroparticle physics projects the Pierre Auger Observatory (PAO) and the Cherenkov Telescope Array (CTA). OSG stack is installed for the NOvA experiment. Other groups of users use directly local batch system. Storage capacity is distributed to several locations. DPM servers used by the ATLAS and the PAO are all in the same server room, but several xrootd servers for the ALICE experiment are operated in the Nuclear Physics Institute in Řež, about 10 km away. The storage capacity for the ATLAS and the PAO is extended by resources of the CESNET - the Czech National Grid Initiative representative. Those resources are in Plzen and Jihlava, more than 100 km away from the CC IoP. Both distant sites use a hierarchical storage solution based on disks and tapes. They installed one common dCache instance, which is published in the CC IoP BDII. ATLAS users can use these resources using the standard ATLAS tools in the same way as the local storage without noticing this geographical distribution. Computing clusters LUNA and EXMAG dedicated to users mostly from the Solid State Physics departments offer resources for parallel computing. They are part of the Czech NGI infrastructure MetaCentrum with distributed batch system based on torque with a custom scheduler. Clusters are installed remotely by the MetaCentrum team and a local contact helps only when needed. Users from IoP have exclusive access only to a part of these two clusters and take advantage of higher priorities on the rest (1500 cores in total), which can also be used by any user of the MetaCentrum. IoP researchers can also use distant resources located in several towns of the Czech Republic with a capacity of more than 12000 cores in total.

Production experience with the ATLAS Event Service

NASA Astrophysics Data System (ADS)

Benjamin, D.; Calafiura, P.; Childers, T.; De, K.; Guan, W.; Maeno, T.; Nilsson, P.; Tsulaia, V.; Van Gemmeren, P.; Wenaus, T.; ATLAS Collaboration

2017-10-01

The ATLAS Event Service (AES) has been designed and implemented for efficient running of ATLAS production workflows on a variety of computing platforms, ranging from conventional Grid sites to opportunistic, often short-lived resources, such as spot market commercial clouds, supercomputers and volunteer computing. The Event Service architecture allows real time delivery of fine grained workloads to running payload applications which process dispatched events or event ranges and immediately stream the outputs to highly scalable Object Stores. Thanks to its agile and flexible architecture the AES is currently being used by grid sites for assigning low priority workloads to otherwise idle computing resources; similarly harvesting HPC resources in an efficient back-fill mode; and massively scaling out to the 50-100k concurrent core level on the Amazon spot market to efficiently utilize those transient resources for peak production needs. Platform ports in development include ATLAS@Home (BOINC) and the Google Compute Engine, and a growing number of HPC platforms. After briefly reviewing the concept and the architecture of the Event Service, we will report the status and experience gained in AES commissioning and production operations on supercomputers, and our plans for extending ES application beyond Geant4 simulation to other workflows, such as reconstruction and data analysis.

Cloud Computing - A Unified Approach for Surveillance Issues

NASA Astrophysics Data System (ADS)

Rachana, C. R.; Banu, Reshma, Dr.; Ahammed, G. F. Ali, Dr.; Parameshachari, B. D., Dr.

2017-08-01

Cloud computing describes highly scalable resources provided as an external service via the Internet on a basis of pay-per-use. From the economic point of view, the main attractiveness of cloud computing is that users only use what they need, and only pay for what they actually use. Resources are available for access from the cloud at any time, and from any location through networks. Cloud computing is gradually replacing the traditional Information Technology Infrastructure. Securing data is one of the leading concerns and biggest issue for cloud computing. Privacy of information is always a crucial pointespecially when an individual’s personalinformation or sensitive information is beingstored in the organization. It is indeed true that today; cloud authorization systems are notrobust enough. This paper presents a unified approach for analyzing the various security issues and techniques to overcome the challenges in the cloud environment.

Running Batch Jobs on Peregrine | High-Performance Computing | NREL

Science.gov Websites

Using Resource Feature to Request Different Node Types Peregrine has several types of compute nodes incompatibility and get the job running. More information about requesting different node types in Peregrine is available. Queues In order to meet the needs of different types of jobs, nodes on Peregrine are available

Interpretation of forest characteristics from computer-generated images.

Treesearch

T.M. Barrett; H.R. Zuuring; T. Christopher

2006-01-01

The need for effective communication in the management and planning of forested landscapes has led to a substantial increase in the use of visual information. Using forest plots from California, Oregon, and Washington, and a survey of 183 natural resource professionals in these states, we examined the use of computer-generated images to convey information about forest...

CSNS computing environment Based on OpenStack

NASA Astrophysics Data System (ADS)

Li, Yakang; Qi, Fazhi; Chen, Gang; Wang, Yanming; Hong, Jianshu

2017-10-01

Cloud computing can allow for more flexible configuration of IT resources and optimized hardware utilization, it also can provide computing service according to the real need. We are applying this computing mode to the China Spallation Neutron Source(CSNS) computing environment. So, firstly, CSNS experiment and its computing scenarios and requirements are introduced in this paper. Secondly, the design and practice of cloud computing platform based on OpenStack are mainly demonstrated from the aspects of cloud computing system framework, network, storage and so on. Thirdly, some improvments to openstack we made are discussed further. Finally, current status of CSNS cloud computing environment are summarized in the ending of this paper.

A Simple and Resource-efficient Setup for the Computer-aided Drug Design Laboratory.

PubMed

Moretti, Loris; Sartori, Luca

2016-10-01

Undertaking modelling investigations for Computer-Aided Drug Design (CADD) requires a proper environment. In principle, this could be done on a single computer, but the reality of a drug discovery program requires robustness and high-throughput computing (HTC) to efficiently support the research. Therefore, a more capable alternative is needed but its implementation has no widespread solution. Here, the realization of such a computing facility is discussed, from general layout to technical details all aspects are covered. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Equal Access Initiative HIV/AIDS Information Resources from NLM

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

Templin-Branner W. and N. Dancy

The Equal Access Initiative: HIV/AIDS Information Resources from the National Library of Medicine training is designed specifically for the National Minority AIDS Council 2010 Equal Access Initiative (EAI) Computer Grants Program awardees to provide valuable health information resources from the National Library of Medicine and other reliable sources to increase awareness of the wealth of treatment information and educational materials that are available on the Internet and to improve prevention and treatment education for their clients. These resources will also meet the needs of community-based

Psychiatrists’ Comfort Using Computers and Other Electronic Devices in Clinical Practice

PubMed Central

Fochtmann, Laura J.; Clarke, Diana E.; Barber, Keila; Hong, Seung-Hee; Yager, Joel; Mościcki, Eve K.; Plovnick, Robert M.

2015-01-01

This report highlights findings from the Study of Psychiatrists’ Use of Informational Resources in Clinical Practice, a cross-sectional Web- and paper-based survey that examined psychiatrists’ comfort using computers and other electronic devices in clinical practice. One-thousand psychiatrists were randomly selected from the American Medical Association Physician Masterfile and asked to complete the survey between May and August, 2012. A total of 152 eligible psychiatrists completed the questionnaire (response rate 22.2 %). The majority of psychiatrists reported comfort using computers for educational and personal purposes. However, 26 % of psychiatrists reported not using or not being comfortable using computers for clinical functions. Psychiatrists under age 50 were more likely to report comfort using computers for all purposes than their older counterparts. Clinical tasks for which computers were reportedly used comfortably, specifically by psychiatrists younger than 50, included documenting clinical encounters, prescribing, ordering laboratory tests, accessing read-only patient information (e.g., test results), conducting internet searches for general clinical information, accessing online patient educational materials, and communicating with patients or other clinicians. Psychiatrists generally reported comfort using computers for personal and educational purposes. However, use of computers in clinical care was less common, particularly among psychiatrists 50 and older. Information and educational resources need to be available in a variety of accessible, user-friendly, computer and non-computer-based formats, to support use across all ages. Moreover, ongoing training and technical assistance with use of electronic and mobile device technologies in clinical practice is needed. Research on barriers to clinical use of computers is warranted. PMID:26667248

Psychiatrists' Comfort Using Computers and Other Electronic Devices in Clinical Practice.

PubMed

Duffy, Farifteh F; Fochtmann, Laura J; Clarke, Diana E; Barber, Keila; Hong, Seung-Hee; Yager, Joel; Mościcki, Eve K; Plovnick, Robert M

2016-09-01

This report highlights findings from the Study of Psychiatrists' Use of Informational Resources in Clinical Practice, a cross-sectional Web- and paper-based survey that examined psychiatrists' comfort using computers and other electronic devices in clinical practice. One-thousand psychiatrists were randomly selected from the American Medical Association Physician Masterfile and asked to complete the survey between May and August, 2012. A total of 152 eligible psychiatrists completed the questionnaire (response rate 22.2 %). The majority of psychiatrists reported comfort using computers for educational and personal purposes. However, 26 % of psychiatrists reported not using or not being comfortable using computers for clinical functions. Psychiatrists under age 50 were more likely to report comfort using computers for all purposes than their older counterparts. Clinical tasks for which computers were reportedly used comfortably, specifically by psychiatrists younger than 50, included documenting clinical encounters, prescribing, ordering laboratory tests, accessing read-only patient information (e.g., test results), conducting internet searches for general clinical information, accessing online patient educational materials, and communicating with patients or other clinicians. Psychiatrists generally reported comfort using computers for personal and educational purposes. However, use of computers in clinical care was less common, particularly among psychiatrists 50 and older. Information and educational resources need to be available in a variety of accessible, user-friendly, computer and non-computer-based formats, to support use across all ages. Moreover, ongoing training and technical assistance with use of electronic and mobile device technologies in clinical practice is needed. Research on barriers to clinical use of computers is warranted.

Determining the Number of Participants Needed for the Usability Evaluation of E-Learning Resources: A Monte Carlo Simulation

ERIC Educational Resources Information Center

Davids, Mogamat Razeen; Harvey, Justin; Halperin, Mitchell L.; Chikte, Usuf M. E.

2015-01-01

The usability of computer interfaces has a major influence on learning. Optimising the usability of e-learning resources is therefore essential. However, this may be neglected because of time and monetary constraints. User testing is a common approach to usability evaluation and involves studying typical end-users interacting with the application…

HPC on Competitive Cloud Resources

NASA Astrophysics Data System (ADS)

Bientinesi, Paolo; Iakymchuk, Roman; Napper, Jeff

Computing as a utility has reached the mainstream. Scientists can now easily rent time on large commercial clusters that can be expanded and reduced on-demand in real-time. However, current commercial cloud computing performance falls short of systems specifically designed for scientific applications. Scientific computing needs are quite different from those of the web applications that have been the focus of cloud computing vendors. In this chapter we demonstrate through empirical evaluation the computational efficiency of high-performance numerical applications in a commercial cloud environment when resources are shared under high contention. Using the Linpack benchmark as a case study, we show that cache utilization becomes highly unpredictable and similarly affects computation time. For some problems, not only is it more efficient to underutilize resources, but the solution can be reached sooner in realtime (wall-time). We also show that the smallest, cheapest (64-bit) instance on the studied environment is the best for price to performance ration. In light of the high-contention we witness, we believe that alternative definitions of efficiency for commercial cloud environments should be introduced where strong performance guarantees do not exist. Concepts like average, expected performance and execution time, expected cost to completion, and variance measures--traditionally ignored in the high-performance computing context--now should complement or even substitute the standard definitions of efficiency.

Strategies for teaching pathology to graduate students and allied health professionals.

PubMed

Fenderson, Bruce A

2005-02-01

Pathology is an essential course for many students in the biomedical sciences and allied health professions. These students learn the language of pathology and medicine, develop an appreciation for mechanisms of disease, and understand the close relationship between basic research and clinical medicine. We have developed 3 pathology courses to meet the needs of our undergraduates, graduate students, and allied health professionals. Through experience, we have settled on an approach to teaching pathology that takes into account the diverse educational backgrounds of these students. Educational resources such as assigned reading, online homework, lectures, and review sessions are carefully balanced to adjust course difficulty. Common features of our pathology curricula include a web-based computer laboratory and review sessions on the basis of selected pathology images and open-ended study questions. Lectures, computer-guided homework, and review sessions provide the core educational content for undergraduates. Graduate students, using the same computer program and review material, rely more heavily on assigned reading for core educational content. Our experience adapting a pathology curriculum to the needs of divergent groups of students suggests a general strategy for monitoring course difficulty. We hypothesize that course difficulty is proportional to the information density of specific learning resources (eg, lecture or textbook) multiplied by the weight of those learning resources placed on examinations. This formula allows educators to match the difficulty of a course with the educational needs of students, and provides a useful tool for longitudinal studies of curriculum reform.

Hybrid Cloud Computing Environment for EarthCube and Geoscience Community

NASA Astrophysics Data System (ADS)

Yang, C. P.; Qin, H.

2016-12-01

The NSF EarthCube Integration and Test Environment (ECITE) has built a hybrid cloud computing environment to provides cloud resources from private cloud environments by using cloud system software - OpenStack and Eucalyptus, and also manages public cloud - Amazon Web Service that allow resource synchronizing and bursting between private and public cloud. On ECITE hybrid cloud platform, EarthCube and geoscience community can deploy and manage the applications by using base virtual machine images or customized virtual machines, analyze big datasets by using virtual clusters, and real-time monitor the virtual resource usage on the cloud. Currently, a number of EarthCube projects have deployed or started migrating their projects to this platform, such as CHORDS, BCube, CINERGI, OntoSoft, and some other EarthCube building blocks. To accomplish the deployment or migration, administrator of ECITE hybrid cloud platform prepares the specific needs (e.g. images, port numbers, usable cloud capacity, etc.) of each project in advance base on the communications between ECITE and participant projects, and then the scientists or IT technicians in those projects launch one or multiple virtual machines, access the virtual machine(s) to set up computing environment if need be, and migrate their codes, documents or data without caring about the heterogeneity in structure and operations among different cloud platforms.

Education and information for practicing school nurses: which technology-supported resources meet their needs?

PubMed

Anderson, Lori S; Enge, Karmin J

2012-10-01

School nurses care for children with a variety of health-related conditions and they need information about managing these conditions, which is accessible, current, and useful. The goal of this literature review was to gather and synthesize information on technology-supported resources and to determine which met the educational needs of school nurses. Successful online educational programs were interactive and self-directed. The most common barriers were lack of time to find educational information, lack of knowledge about computers, technology, the Internet and specific programs, and lack of administrative support from school officials to use technology to access information and evidence for practice. Recommendations for successful use of technology to meet practicing school nurse's educational needs are offered.

Science-Driven Computing: NERSC's Plan for 2006-2010

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

Simon, Horst D.; Kramer, William T.C.; Bailey, David H.

NERSC has developed a five-year strategic plan focusing on three components: Science-Driven Systems, Science-Driven Services, and Science-Driven Analytics. (1) Science-Driven Systems: Balanced introduction of the best new technologies for complete computational systems--computing, storage, networking, visualization and analysis--coupled with the activities necessary to engage vendors in addressing the DOE computational science requirements in their future roadmaps. (2) Science-Driven Services: The entire range of support activities, from high-quality operations and user services to direct scientific support, that enable a broad range of scientists to effectively use NERSC systems in their research. NERSC will concentrate on resources needed to realize the promise ofmore » the new highly scalable architectures for scientific discovery in multidisciplinary computational science projects. (3) Science-Driven Analytics: The architectural and systems enhancements and services required to integrate NERSC's powerful computational and storage resources to provide scientists with new tools to effectively manipulate, visualize, and analyze the huge data sets derived from simulations and experiments.« less

Operating systems and network protocols for wireless sensor networks.

PubMed

Dutta, Prabal; Dunkels, Adam

2012-01-13

Sensor network protocols exist to satisfy the communication needs of diverse applications, including data collection, event detection, target tracking and control. Network protocols to enable these services are constrained by the extreme resource scarcity of sensor nodes-including energy, computing, communications and storage-which must be carefully managed and multiplexed by the operating system. These challenges have led to new protocols and operating systems that are efficient in their energy consumption, careful in their computational needs and miserly in their memory footprints, all while discovering neighbours, forming networks, delivering data and correcting failures.

SOCR: Statistics Online Computational Resource

PubMed Central

Dinov, Ivo D.

2011-01-01

The need for hands-on computer laboratory experience in undergraduate and graduate statistics education has been firmly established in the past decade. As a result a number of attempts have been undertaken to develop novel approaches for problem-driven statistical thinking, data analysis and result interpretation. In this paper we describe an integrated educational web-based framework for: interactive distribution modeling, virtual online probability experimentation, statistical data analysis, visualization and integration. Following years of experience in statistical teaching at all college levels using established licensed statistical software packages, like STATA, S-PLUS, R, SPSS, SAS, Systat, etc., we have attempted to engineer a new statistics education environment, the Statistics Online Computational Resource (SOCR). This resource performs many of the standard types of statistical analysis, much like other classical tools. In addition, it is designed in a plug-in object-oriented architecture and is completely platform independent, web-based, interactive, extensible and secure. Over the past 4 years we have tested, fine-tuned and reanalyzed the SOCR framework in many of our undergraduate and graduate probability and statistics courses and have evidence that SOCR resources build student’s intuition and enhance their learning. PMID:21451741

The GeantV project: Preparing the future of simulation

DOE PAGES

Amadio, G.; J. Apostolakis; Bandieramonte, M.; ...

2015-12-23

Detector simulation is consuming at least half of the HEP computing cycles, and even so, experiments have to take hard decisions on what to simulate, as their needs greatly surpass the availability of computing resources. New experiments still in the design phase such as FCC, CLIC and ILC as well as upgraded versions of the existing LHC detectors will push further the simulation requirements. Since the increase in computing resources is not likely to keep pace with our needs, it is therefore necessary to explore innovative ways of speeding up simulation in order to sustain the progress of High Energymore » Physics. The GeantV project aims at developing a high performance detector simulation system integrating fast and full simulation that can be ported on different computing architectures, including CPU accelerators. After more than two years of R&D the project has produced a prototype capable of transporting particles in complex geometries exploiting micro-parallelism, SIMD and multithreading. Portability is obtained via C++ template techniques that allow the development of machine- independent computational kernels. Furthermore, a set of tables derived from Geant4 for cross sections and final states provides a realistic shower development and, having been ported into a Geant4 physics list, can be used as a basis for a direct performance comparison.« less

A cloud-based workflow to quantify transcript-expression levels in public cancer compendia

PubMed Central

Tatlow, PJ; Piccolo, Stephen R.

2016-01-01

Public compendia of sequencing data are now measured in petabytes. Accordingly, it is infeasible for researchers to transfer these data to local computers. Recently, the National Cancer Institute began exploring opportunities to work with molecular data in cloud-computing environments. With this approach, it becomes possible for scientists to take their tools to the data and thereby avoid large data transfers. It also becomes feasible to scale computing resources to the needs of a given analysis. We quantified transcript-expression levels for 12,307 RNA-Sequencing samples from the Cancer Cell Line Encyclopedia and The Cancer Genome Atlas. We used two cloud-based configurations and examined the performance and cost profiles of each configuration. Using preemptible virtual machines, we processed the samples for as little as $0.09 (USD) per sample. As the samples were processed, we collected performance metrics, which helped us track the duration of each processing step and quantified computational resources used at different stages of sample processing. Although the computational demands of reference alignment and expression quantification have decreased considerably, there remains a critical need for researchers to optimize preprocessing steps. We have stored the software, scripts, and processed data in a publicly accessible repository (https://osf.io/gqrz9). PMID:27982081

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 Diffusion of Computer Skills in Communication Curricula: Is There a Gap between the Educational Experience and Employers' Needs?

ERIC Educational Resources Information Center

Chen, Joyce; Bankston, Ronnie

Computers are now perceived as a required resource by business, education, and government, as well as in personal life. The rates of adoption of information technologies among these groups (business, education, government, family/individual) have varied, which may have created knowledge gaps. Based on the data collected from a telephone survey in…

Enabling BOINC in infrastructure as a service cloud system

NASA Astrophysics Data System (ADS)

Montes, Diego; Añel, Juan A.; Pena, Tomás F.; Uhe, Peter; Wallom, David C. H.

2017-02-01

Volunteer or crowd computing is becoming increasingly popular for solving complex research problems from an increasingly diverse range of areas. The majority of these have been built using the Berkeley Open Infrastructure for Network Computing (BOINC) platform, which provides a range of different services to manage all computation aspects of a project. The BOINC system is ideal in those cases where not only does the research community involved need low-cost access to massive computing resources but also where there is a significant public interest in the research being done.We discuss the way in which cloud services can help BOINC-based projects to deliver results in a fast, on demand manner. This is difficult to achieve using volunteers, and at the same time, using scalable cloud resources for short on demand projects can optimize the use of the available resources. We show how this design can be used as an efficient distributed computing platform within the cloud, and outline new approaches that could open up new possibilities in this field, using Climateprediction.net (http://www.climateprediction.net/) as a case study.

ANL statement of site strategy for computing workstations

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

Fenske, K.R.; Boxberger, L.M.; Amiot, L.W.

1991-11-01

This Statement of Site Strategy describes the procedure at Argonne National Laboratory for defining, acquiring, using, and evaluating scientific and office workstations and related equipment and software in accord with DOE Order 1360.1A (5-30-85), and Laboratory policy. It is Laboratory policy to promote the installation and use of computing workstations to improve productivity and communications for both programmatic and support personnel, to ensure that computing workstations acquisitions meet the expressed need in a cost-effective manner, and to ensure that acquisitions of computing workstations are in accord with Laboratory and DOE policies. The overall computing site strategy at ANL is tomore » develop a hierarchy of integrated computing system resources to address the current and future computing needs of the laboratory. The major system components of this hierarchical strategy are: Supercomputers, Parallel computers, Centralized general purpose computers, Distributed multipurpose minicomputers, and Computing workstations and office automation support systems. Computing workstations include personal computers, scientific and engineering workstations, computer terminals, microcomputers, word processing and office automation electronic workstations, and associated software and peripheral devices costing less than $25,000 per item.« less

Quantum computing with incoherent resources and quantum jumps.

PubMed

Santos, M F; Cunha, M Terra; Chaves, R; Carvalho, A R R

2012-04-27

Spontaneous emission and the inelastic scattering of photons are two natural processes usually associated with decoherence and the reduction in the capacity to process quantum information. Here we show that, when suitably detected, these photons are sufficient to build all the fundamental blocks needed to perform quantum computation in the emitting qubits while protecting them from deleterious dissipative effects. We exemplify this by showing how to efficiently prepare graph states for the implementation of measurement-based quantum computation.

The OSG Open Facility: an on-ramp for opportunistic scientific computing

NASA Astrophysics Data System (ADS)

Jayatilaka, B.; Levshina, T.; Sehgal, C.; Gardner, R.; Rynge, M.; Würthwein, F.

2017-10-01

The Open Science Grid (OSG) is a large, robust computing grid that started primarily as a collection of sites associated with large HEP experiments such as ATLAS, CDF, CMS, and DZero, but has evolved in recent years to a much larger user and resource platform. In addition to meeting the US LHC community’s computational needs, the OSG continues to be one of the largest providers of distributed high-throughput computing (DHTC) to researchers from a wide variety of disciplines via the OSG Open Facility. The Open Facility consists of OSG resources that are available opportunistically to users other than resource owners and their collaborators. In the past two years, the Open Facility has doubled its annual throughput to over 200 million wall hours. More than half of these resources are used by over 100 individual researchers from over 60 institutions in fields such as biology, medicine, math, economics, and many others. Over 10% of these individual users utilized in excess of 1 million computational hours each in the past year. The largest source of these cycles is temporary unused capacity at institutions affiliated with US LHC computational sites. An increasing fraction, however, comes from university HPC clusters and large national infrastructure supercomputers offering unused capacity. Such expansions have allowed the OSG to provide ample computational resources to both individual researchers and small groups as well as sizable international science collaborations such as LIGO, AMS, IceCube, and sPHENIX. Opening up access to the Fermilab FabrIc for Frontier Experiments (FIFE) project has also allowed experiments such as mu2e and NOvA to make substantial use of Open Facility resources, the former with over 40 million wall hours in a year. We present how this expansion was accomplished as well as future plans for keeping the OSG Open Facility at the forefront of enabling scientific research by way of DHTC.

The OSG Open Facility: An On-Ramp for Opportunistic Scientific Computing

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

Jayatilaka, B.; Levshina, T.; Sehgal, C.

The Open Science Grid (OSG) is a large, robust computing grid that started primarily as a collection of sites associated with large HEP experiments such as ATLAS, CDF, CMS, and DZero, but has evolved in recent years to a much larger user and resource platform. In addition to meeting the US LHC community’s computational needs, the OSG continues to be one of the largest providers of distributed high-throughput computing (DHTC) to researchers from a wide variety of disciplines via the OSG Open Facility. The Open Facility consists of OSG resources that are available opportunistically to users other than resource ownersmore » and their collaborators. In the past two years, the Open Facility has doubled its annual throughput to over 200 million wall hours. More than half of these resources are used by over 100 individual researchers from over 60 institutions in fields such as biology, medicine, math, economics, and many others. Over 10% of these individual users utilized in excess of 1 million computational hours each in the past year. The largest source of these cycles is temporary unused capacity at institutions affiliated with US LHC computational sites. An increasing fraction, however, comes from university HPC clusters and large national infrastructure supercomputers offering unused capacity. Such expansions have allowed the OSG to provide ample computational resources to both individual researchers and small groups as well as sizable international science collaborations such as LIGO, AMS, IceCube, and sPHENIX. Opening up access to the Fermilab FabrIc for Frontier Experiments (FIFE) project has also allowed experiments such as mu2e and NOvA to make substantial use of Open Facility resources, the former with over 40 million wall hours in a year. We present how this expansion was accomplished as well as future plans for keeping the OSG Open Facility at the forefront of enabling scientific research by way of DHTC.« less

PanDA: Exascale Federation of Resources for the ATLAS Experiment at the LHC

NASA Astrophysics Data System (ADS)

Barreiro Megino, Fernando; Caballero Bejar, Jose; De, Kaushik; Hover, John; Klimentov, Alexei; Maeno, Tadashi; Nilsson, Paul; Oleynik, Danila; Padolski, Siarhei; Panitkin, Sergey; Petrosyan, Artem; Wenaus, Torre

2016-02-01

After a scheduled maintenance and upgrade period, the world's largest and most powerful machine - the Large Hadron Collider(LHC) - is about to enter its second run at unprecedented energies. In order to exploit the scientific potential of the machine, the experiments at the LHC face computational challenges with enormous data volumes that need to be analysed by thousand of physics users and compared to simulated data. Given diverse funding constraints, the computational resources for the LHC have been deployed in a worldwide mesh of data centres, connected to each other through Grid technologies. The PanDA (Production and Distributed Analysis) system was developed in 2005 for the ATLAS experiment on top of this heterogeneous infrastructure to seamlessly integrate the computational resources and give the users the feeling of a unique system. Since its origins, PanDA has evolved together with upcoming computing paradigms in and outside HEP, such as changes in the networking model, Cloud Computing and HPC. It is currently running steadily up to 200 thousand simultaneous cores (limited by the available resources for ATLAS), up to two million aggregated jobs per day and processes over an exabyte of data per year. The success of PanDA in ATLAS is triggering the widespread adoption and testing by other experiments. In this contribution we will give an overview of the PanDA components and focus on the new features and upcoming challenges that are relevant to the next decade of distributed computing workload management using PanDA.

System Resource Allocation Requests | High-Performance Computing | NREL

Science.gov Websites

Account to utilize the online allocation request system. If you need a HPC User Account, please request one online: Visit User Accounts. Click the green "Request Account" Button - this will direct . Follow the online instructions provided in the DocuSign form. Write "Need HPC User Account to use

Mature data transport and command management services for the Space Station

NASA Technical Reports Server (NTRS)

Carper, R. D.

1986-01-01

The duplex space/ground/space data services for the Space Station are described. The need to separate the uplink data service functions from the command functions is discussed. Command management is a process shared by an operation control center and a command management system and consists of four functions: (1) uplink data communications, (2) management of the on-board computer, (3) flight resource allocation and management, and (4) real command management. The new data service capabilities provided by microprocessors, ground and flight nodes, and closed loop and open loop capabilities are studied. The need for and functions of a flight resource allocation management service are examined. The system is designed so only users can access the system; the problems encountered with open loop uplink access are analyzed. The procedures for delivery of operational, verification, computer, and surveillance and monitoring data directly to users are reviewed.

Large-scale educational telecommunications systems for the US: An analysis of educational needs and technological opportunities

NASA Technical Reports Server (NTRS)

Morgan, R. P.; Singh, J. P.; Rothenberg, D.; Robinson, B. E.

1975-01-01

The needs to be served, the subsectors in which the system might be used, the technology employed, and the prospects for future utilization of an educational telecommunications delivery system are described and analyzed. Educational subsectors are analyzed with emphasis on the current status and trends within each subsector. Issues which affect future development, and prospects for future use of media, technology, and large-scale electronic delivery within each subsector are included. Information on technology utilization is presented. Educational telecommunications services are identified and grouped into categories: public television and radio, instructional television, computer aided instruction, computer resource sharing, and information resource sharing. Technology based services, their current utilization, and factors which affect future development are stressed. The role of communications satellites in providing these services is discussed. Efforts to analyze and estimate future utilization of large-scale educational telecommunications are summarized. Factors which affect future utilization are identified. Conclusions are presented.

Stochastic resource allocation in emergency departments with a multi-objective simulation optimization algorithm.

PubMed

Feng, Yen-Yi; Wu, I-Chin; Chen, Tzu-Li

2017-03-01

The number of emergency cases or emergency room visits rapidly increases annually, thus leading to an imbalance in supply and demand and to the long-term overcrowding of hospital emergency departments (EDs). However, current solutions to increase medical resources and improve the handling of patient needs are either impractical or infeasible in the Taiwanese environment. Therefore, EDs must optimize resource allocation given limited medical resources to minimize the average length of stay of patients and medical resource waste costs. This study constructs a multi-objective mathematical model for medical resource allocation in EDs in accordance with emergency flow or procedure. The proposed mathematical model is complex and difficult to solve because its performance value is stochastic; furthermore, the model considers both objectives simultaneously. Thus, this study develops a multi-objective simulation optimization algorithm by integrating a non-dominated sorting genetic algorithm II (NSGA II) with multi-objective computing budget allocation (MOCBA) to address the challenges of multi-objective medical resource allocation. NSGA II is used to investigate plausible solutions for medical resource allocation, and MOCBA identifies effective sets of feasible Pareto (non-dominated) medical resource allocation solutions in addition to effectively allocating simulation or computation budgets. The discrete event simulation model of ED flow is inspired by a Taiwan hospital case and is constructed to estimate the expected performance values of each medical allocation solution as obtained through NSGA II. Finally, computational experiments are performed to verify the effectiveness and performance of the integrated NSGA II and MOCBA method, as well as to derive non-dominated medical resource allocation solutions from the algorithms.

Optimal directed searches for continuous gravitational waves

NASA Astrophysics Data System (ADS)

Ming, Jing; Krishnan, Badri; Papa, Maria Alessandra; Aulbert, Carsten; Fehrmann, Henning

2016-03-01

Wide parameter space searches for long-lived continuous gravitational wave signals are computationally limited. It is therefore critically important that the available computational resources are used rationally. In this paper we consider directed searches, i.e., targets for which the sky position is known accurately but the frequency and spin-down parameters are completely unknown. Given a list of such potential astrophysical targets, we therefore need to prioritize. On which target(s) should we spend scarce computing resources? What parameter space region in frequency and spin-down should we search through? Finally, what is the optimal search setup that we should use? In this paper we present a general framework that allows us to solve all three of these problems. This framework is based on maximizing the probability of making a detection subject to a constraint on the maximum available computational cost. We illustrate the method for a simplified problem.

Efficient Redundancy Techniques in Cloud and Desktop Grid Systems using MAP/G/c-type Queues

NASA Astrophysics Data System (ADS)

Chakravarthy, Srinivas R.; Rumyantsev, Alexander

2018-03-01

Cloud computing is continuing to prove its flexibility and versatility in helping industries and businesses as well as academia as a way of providing needed computing capacity. As an important alternative to cloud computing, desktop grids allow to utilize the idle computer resources of an enterprise/community by means of distributed computing system, providing a more secure and controllable environment with lower operational expenses. Further, both cloud computing and desktop grids are meant to optimize limited resources and at the same time to decrease the expected latency for users. The crucial parameter for optimization both in cloud computing and in desktop grids is the level of redundancy (replication) for service requests/workunits. In this paper we study the optimal replication policies by considering three variations of Fork-Join systems in the context of a multi-server queueing system with a versatile point process for the arrivals. For services we consider phase type distributions as well as shifted exponential and Weibull. We use both analytical and simulation approach in our analysis and report some interesting qualitative results.

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

The Four Scaffolding Modules for Collaborative Problem-Based Learning through the Computer Network on Moodle LMS for the Computer Programming Course

ERIC Educational Resources Information Center

Tiantong, Monchai; Teemuangsai, Sanit

2013-01-01

Scaffolding is a learning approach designed to promote a deeper understanding, it is the support given during the learning process which is tailored to the needs of the student with the intention of helping the student achieve the learning goals, including resources, a compelling task, templates and guides, and guidance on the development of…

What Can Technology Offer to Linguistically Diverse Classrooms? Using Multilingual Content in a Computer-Based Learning Environment for Primary Education

ERIC Educational Resources Information Center

Van Laere, Evelien; Rosiers, Kirsten; Van Avermaet, Piet; Slembrouck, Stef; van Braak, Johan

2017-01-01

Computer-based learning environments (CBLEs) have the potential to integrate the linguistic diversity present in classrooms as a resourceful tool in pupils' learning process. Particularly for pupils who speak a language at home other than the language which is used at school, more understanding is needed on how CBLEs offering multilingual content…

Unconditionally verifiable blind quantum computation

NASA Astrophysics Data System (ADS)

Fitzsimons, Joseph F.; Kashefi, Elham

2017-07-01

Blind quantum computing (BQC) allows a client to have a server carry out a quantum computation for them such that the client's input, output, and computation remain private. A desirable property for any BQC protocol is verification, whereby the client can verify with high probability whether the server has followed the instructions of the protocol or if there has been some deviation resulting in a corrupted output state. A verifiable BQC protocol can be viewed as an interactive proof system leading to consequences for complexity theory. We previously proposed [A. Broadbent, J. Fitzsimons, and E. Kashefi, in Proceedings of the 50th Annual Symposium on Foundations of Computer Science, Atlanta, 2009 (IEEE, Piscataway, 2009), p. 517] a universal and unconditionally secure BQC scheme where the client only needs to be able to prepare single qubits in separable states randomly chosen from a finite set and send them to the server, who has the balance of the required quantum computational resources. In this paper we extend that protocol with additional functionality allowing blind computational basis measurements, which we use to construct another verifiable BQC protocol based on a different class of resource states. We rigorously prove that the probability of failing to detect an incorrect output is exponentially small in a security parameter, while resource overhead remains polynomial in this parameter. This resource state allows entangling gates to be performed between arbitrary pairs of logical qubits with only constant overhead. This is a significant improvement on the original scheme, which required that all computations to be performed must first be put into a nearest-neighbor form, incurring linear overhead in the number of qubits. Such an improvement has important consequences for efficiency and fault-tolerance thresholds.

Semantics-based distributed I/O with the ParaMEDIC framework.

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

Balaji, P.; Feng, W.; Lin, H.

2008-01-01

Many large-scale applications simultaneously rely on multiple resources for efficient execution. For example, such applications may require both large compute and storage resources; however, very few supercomputing centers can provide large quantities of both. Thus, data generated at the compute site oftentimes has to be moved to a remote storage site for either storage or visualization and analysis. Clearly, this is not an efficient model, especially when the two sites are distributed over a wide-area network. Thus, we present a framework called 'ParaMEDIC: Parallel Metadata Environment for Distributed I/O and Computing' which uses application-specific semantic information to convert the generatedmore » data to orders-of-magnitude smaller metadata at the compute site, transfer the metadata to the storage site, and re-process the metadata at the storage site to regenerate the output. Specifically, ParaMEDIC trades a small amount of additional computation (in the form of data post-processing) for a potentially significant reduction in data that needs to be transferred in distributed environments.« less

Do You Need ERP? In the Business World, Enterprise Resource Planning Software Keeps Costs down and Productivity up. Should Districts Follow Suit?

ERIC Educational Resources Information Center

Careless, James

2007-01-01

Enterprise resource planning (ERP) software does what school leaders have always wanted their computer systems to do: It sees all. By integrating every IT application an organization has--from purchasing and inventory control to payroll--ERPs create a single unified system. Not only does this give IT managers a holistic view to what is happening…

Do You Need ERP? In the Business World, Enterprise Resource Planning Software Keeps Costs down and Productivity up. Should Districts Follow Suit?

ERIC Educational Resources Information Center

Careless, James

2007-01-01

Enterprise resource planning software does what school leaders have always wanted their computer systems to do: It sees all. By integrating every IT application an organization has--from purchasing and inventory control to payroll--ERPs create a single unified system. Not only does this give IT managers a holistic view to what is happening in the…

Progress on the Fabric for Frontier Experiments Project at Fermilab

NASA Astrophysics Data System (ADS)

Box, Dennis; Boyd, Joseph; Dykstra, Dave; Garzoglio, Gabriele; Herner, Kenneth; Kirby, Michael; Kreymer, Arthur; Levshina, Tanya; Mhashilkar, Parag; Sharma, Neha

2015-12-01

The FabrIc for Frontier Experiments (FIFE) project is an ambitious, major-impact initiative within the Fermilab Scientific Computing Division designed to lead the computing model for Fermilab experiments. FIFE is a collaborative effort between experimenters and computing professionals to design and develop integrated computing models for experiments of varying needs and infrastructure. The major focus of the FIFE project is the development, deployment, and integration of Open Science Grid solutions for high throughput computing, data management, database access and collaboration within experiment. To accomplish this goal, FIFE has developed workflows that utilize Open Science Grid sites along with dedicated and commercial cloud resources. The FIFE project has made significant progress integrating into experiment computing operations several services including new job submission services, software and reference data distribution through CVMFS repositories, flexible data transfer client, and access to opportunistic resources on the Open Science Grid. The progress with current experiments and plans for expansion with additional projects will be discussed. FIFE has taken a leading role in the definition of the computing model for Fermilab experiments, aided in the design of computing for experiments beyond Fermilab, and will continue to define the future direction of high throughput computing for future physics experiments worldwide.

Universal Blind Quantum Computation

NASA Astrophysics Data System (ADS)

Fitzsimons, Joseph; Kashefi, Elham

2012-02-01

Blind Quantum Computing (BQC) allows a client to have a server carry out a quantum computation for them such that the client's inputs, outputs and computation remain private. Recently we proposed a universal unconditionally secure BQC scheme, based on the conceptual framework of the measurement-based quantum computing model, where the client only needs to be able to prepare single qubits in separable states randomly chosen from a finite set and send them to the server, who has the balance of the required quantum computational resources. Here we present a refinement of the scheme which vastly expands the class of quantum circuits which can be directly implemented as a blind computation, by introducing a new class of resource states which we term dotted-complete graph states and expanding the set of single qubit states the client is required to prepare. These two modifications significantly simplify the overall protocol and remove the previously present restriction that only nearest-neighbor circuits could be implemented as blind computations directly. As an added benefit, the refined protocol admits a substantially more intuitive and simplified verification mechanism, allowing the correctness of a blind computation to be verified with arbitrarily small probability of error.

Elucidating Reaction Mechanisms on Quantum Computers

NASA Astrophysics Data System (ADS)

Wiebe, Nathan; Reiher, Markus; Svore, Krysta; Wecker, Dave; Troyer, Matthias

We show how a quantum computer can be employed to elucidate reaction mechanisms in complex chemical systems, using the open problem of biological nitrogen fixation in nitrogenase as an example. We discuss how quantum computers can augment classical-computer simulations for such problems, to significantly increase their accuracy and enable hitherto intractable simulations. Detailed resource estimates show that, even when taking into account the substantial overhead of quantum error correction, and the need to compile into discrete gate sets, the necessary computations can be performed in reasonable time on small quantum computers. This demonstrates that quantum computers will realistically be able to tackle important problems in chemistry that are both scientifically and economically significant.

The Assistant for Specifying the Quality Software (ASQS) Operational Concept Document. Volume 1

DTIC Science & Technology

1990-09-01

Assistant in which the manager supplies system-specific characteristics and needs and the Assistant fills in the software quality concepts and methods. The...member(s) of the Computer Resources Working Group (CRWG) to aid in performing a software quality engineering study. Figure 3.4-1 outlines the...need to recovery from faults more likely than need _o provide alternative functions or interfaces), and more on Autcncmy - 27 - that Modularity

ASCR/HEP Exascale Requirements Review Report

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

Habib, Salman; Roser, Robert; Gerber, Richard

This draft report summarizes and details the findings, results, and recommendations derived from the ASCR/HEP Exascale Requirements Review meeting held in June, 2015. The main conclusions are as follows. 1) Larger, more capable computing and data facilities are needed to support HEP science goals in all three frontiers: Energy, Intensity, and Cosmic. The expected scale of the demand at the 2025 timescale is at least two orders of magnitude -- and in some cases greater -- than that available currently. 2) The growth rate of data produced by simulations is overwhelming the current ability, of both facilities and researchers, tomore » store and analyze it. Additional resources and new techniques for data analysis are urgently needed. 3) Data rates and volumes from HEP experimental facilities are also straining the ability to store and analyze large and complex data volumes. Appropriately configured leadership-class facilities can play a transformational role in enabling scientific discovery from these datasets. 4) A close integration of HPC simulation and data analysis will aid greatly in interpreting results from HEP experiments. Such an integration will minimize data movement and facilitate interdependent workflows. 5) Long-range planning between HEP and ASCR will be required to meet HEP's research needs. To best use ASCR HPC resources the experimental HEP program needs a) an established long-term plan for access to ASCR computational and data resources, b) an ability to map workflows onto HPC resources, c) the ability for ASCR facilities to accommodate workflows run by collaborations that can have thousands of individual members, d) to transition codes to the next-generation HPC platforms that will be available at ASCR facilities, e) to build up and train a workforce capable of developing and using simulations and analysis to support HEP scientific research on next-generation systems.« less

ASCR/HEP Exascale Requirements Review Report

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

Habib, Salman; et al.

2016-03-30

This draft report summarizes and details the findings, results, and recommendations derived from the ASCR/HEP Exascale Requirements Review meeting held in June, 2015. The main conclusions are as follows. 1) Larger, more capable computing and data facilities are needed to support HEP science goals in all three frontiers: Energy, Intensity, and Cosmic. The expected scale of the demand at the 2025 timescale is at least two orders of magnitude -- and in some cases greater -- than that available currently. 2) The growth rate of data produced by simulations is overwhelming the current ability, of both facilities and researchers, tomore » store and analyze it. Additional resources and new techniques for data analysis are urgently needed. 3) Data rates and volumes from HEP experimental facilities are also straining the ability to store and analyze large and complex data volumes. Appropriately configured leadership-class facilities can play a transformational role in enabling scientific discovery from these datasets. 4) A close integration of HPC simulation and data analysis will aid greatly in interpreting results from HEP experiments. Such an integration will minimize data movement and facilitate interdependent workflows. 5) Long-range planning between HEP and ASCR will be required to meet HEP's research needs. To best use ASCR HPC resources the experimental HEP program needs a) an established long-term plan for access to ASCR computational and data resources, b) an ability to map workflows onto HPC resources, c) the ability for ASCR facilities to accommodate workflows run by collaborations that can have thousands of individual members, d) to transition codes to the next-generation HPC platforms that will be available at ASCR facilities, e) to build up and train a workforce capable of developing and using simulations and analysis to support HEP scientific research on next-generation systems.« less

Opportunistic Computing with Lobster: Lessons Learned from Scaling up to 25k Non-Dedicated Cores

NASA Astrophysics Data System (ADS)

Wolf, Matthias; Woodard, Anna; Li, Wenzhao; Hurtado Anampa, Kenyi; Yannakopoulos, Anna; Tovar, Benjamin; Donnelly, Patrick; Brenner, Paul; Lannon, Kevin; Hildreth, Mike; Thain, Douglas

2017-10-01

We previously described Lobster, a workflow management tool for exploiting volatile opportunistic computing resources for computation in HEP. We will discuss the various challenges that have been encountered while scaling up the simultaneous CPU core utilization and the software improvements required to overcome these challenges. Categories: Workflows can now be divided into categories based on their required system resources. This allows the batch queueing system to optimize assignment of tasks to nodes with the appropriate capabilities. Within each category, limits can be specified for the number of running jobs to regulate the utilization of communication bandwidth. System resource specifications for a task category can now be modified while a project is running, avoiding the need to restart the project if resource requirements differ from the initial estimates. Lobster now implements time limits on each task category to voluntarily terminate tasks. This allows partially completed work to be recovered. Workflow dependency specification: One workflow often requires data from other workflows as input. Rather than waiting for earlier workflows to be completed before beginning later ones, Lobster now allows dependent tasks to begin as soon as sufficient input data has accumulated. Resource monitoring: Lobster utilizes a new capability in Work Queue to monitor the system resources each task requires in order to identify bottlenecks and optimally assign tasks. The capability of the Lobster opportunistic workflow management system for HEP computation has been significantly increased. We have demonstrated efficient utilization of 25 000 non-dedicated cores and achieved a data input rate of 30 Gb/s and an output rate of 500GB/h. This has required new capabilities in task categorization, workflow dependency specification, and resource monitoring.

Computer assisted audit techniques for UNIX (UNIX-CAATS)

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

Polk, W.T.

1991-12-31

Federal and DOE regulations impose specific requirements for internal controls of computer systems. These controls include adequate separation of duties and sufficient controls for access of system and data. The DOE Inspector General`s Office has the responsibility to examine internal controls, as well as efficient use of computer system resources. As a result, DOE supported NIST development of computer assisted audit techniques to examine BSD UNIX computers (UNIX-CAATS). These systems were selected due to the increasing number of UNIX workstations in use within DOE. This paper describes the design and development of these techniques, as well as the results ofmore » testing at NIST and the first audit at a DOE site. UNIX-CAATS consists of tools which examine security of passwords, file systems, and network access. In addition, a tool was developed to examine efficiency of disk utilization. Test results at NIST indicated inadequate password management, as well as weak network resource controls. File system security was considered adequate. Audit results at a DOE site indicated weak password management and inefficient disk utilization. During the audit, we also found improvements to UNIX-CAATS were needed when applied to large systems. NIST plans to enhance the techniques developed for DOE/IG in future work. This future work would leverage currently available tools, along with needed enhancements. These enhancements would enable DOE/IG to audit large systems, such as supercomputers.« less

Computer assisted audit techniques for UNIX (UNIX-CAATS)

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

Polk, W.T.

1991-01-01

Federal and DOE regulations impose specific requirements for internal controls of computer systems. These controls include adequate separation of duties and sufficient controls for access of system and data. The DOE Inspector General's Office has the responsibility to examine internal controls, as well as efficient use of computer system resources. As a result, DOE supported NIST development of computer assisted audit techniques to examine BSD UNIX computers (UNIX-CAATS). These systems were selected due to the increasing number of UNIX workstations in use within DOE. This paper describes the design and development of these techniques, as well as the results ofmore » testing at NIST and the first audit at a DOE site. UNIX-CAATS consists of tools which examine security of passwords, file systems, and network access. In addition, a tool was developed to examine efficiency of disk utilization. Test results at NIST indicated inadequate password management, as well as weak network resource controls. File system security was considered adequate. Audit results at a DOE site indicated weak password management and inefficient disk utilization. During the audit, we also found improvements to UNIX-CAATS were needed when applied to large systems. NIST plans to enhance the techniques developed for DOE/IG in future work. This future work would leverage currently available tools, along with needed enhancements. These enhancements would enable DOE/IG to audit large systems, such as supercomputers.« less

The ACI-REF Program: Empowering Prospective Computational Researchers

NASA Astrophysics Data System (ADS)

Cuma, M.; Cardoen, W.; Collier, G.; Freeman, R. M., Jr.; Kitzmiller, A.; Michael, L.; Nomura, K. I.; Orendt, A.; Tanner, L.

2014-12-01

The ACI-REF program, Advanced Cyberinfrastructure - Research and Education Facilitation, represents a consortium of academic institutions seeking to further advance the capabilities of their respective campus research communities through an extension of the personal connections and educational activities that underlie the unique and often specialized cyberinfrastructure at each institution. This consortium currently includes Clemson University, Harvard University, University of Hawai'i, University of Southern California, University of Utah, and University of Wisconsin. Working together in a coordinated effort, the consortium is dedicated to the adoption of models and strategies which leverage the expertise and experience of its members with a goal of maximizing the impact of each institution's investment in research computing. The ACI-REFs (facilitators) are tasked with making connections and building bridges between the local campus researchers and the many different providers of campus, commercial, and national computing resources. Through these bridges, ACI-REFs assist researchers from all disciplines in understanding their computing and data needs and in mapping these needs to existing capabilities or providing assistance with development of these capabilities. From the Earth sciences perspective, we will give examples of how this assistance improved methods and workflows in geophysics, geography and atmospheric sciences. We anticipate that this effort will expand the number of researchers who become self-sufficient users of advanced computing resources, allowing them to focus on making research discoveries in a more timely and efficient manner.

ANL site response for the DOE FY1994 information resources management long-range plan

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

Boxberger, L.M.

1992-03-01

Argonne National Laboratory`s ANL Site Response for the DOE FY1994 Information Resources Management (IRM) Long-Range Plan (ANL/TM 500) is one of many contributions to the DOE information resources management long-range planning process and, as such, is an integral part of the DOE policy and program planning system. The Laboratory has constructed this response according to instructions in a Call issued in September 1991 by the DOE Office of IRM Policy, Plans and Oversight. As one of a continuing series, this Site Response is an update and extension of the Laboratory`s previous submissions. The response contains both narrative and tabular material.more » It covers an eight-year period consisting of the base year (FY1991), the current year (FY1992), the budget year (FY1993), the plan year (FY1994), and the out years (FY1995-FY1998). This Site Response was compiled by Argonne National Laboratory`s Computing and Telecommunications Division (CTD), which has the responsibility to provide leadership in optimizing computing and information services and disseminating computer-related technologies throughout the Laboratory. The Site Response consists of 5 parts: (1) a site overview, describes the ANL mission, overall organization structure, the strategic approach to meet information resource needs, the planning process, major issues and points of contact. (2) a software plan for DOE contractors, Part 2B, ``Software Plan FMS plan for DOE organizations, (3) computing resources telecommunications, (4) telecommunications, (5) printing and publishing.« less

ANL site response for the DOE FY1994 information resources management long-range plan

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

Boxberger, L.M.

1992-03-01

Argonne National Laboratory's ANL Site Response for the DOE FY1994 Information Resources Management (IRM) Long-Range Plan (ANL/TM 500) is one of many contributions to the DOE information resources management long-range planning process and, as such, is an integral part of the DOE policy and program planning system. The Laboratory has constructed this response according to instructions in a Call issued in September 1991 by the DOE Office of IRM Policy, Plans and Oversight. As one of a continuing series, this Site Response is an update and extension of the Laboratory's previous submissions. The response contains both narrative and tabular material.more » It covers an eight-year period consisting of the base year (FY1991), the current year (FY1992), the budget year (FY1993), the plan year (FY1994), and the out years (FY1995-FY1998). This Site Response was compiled by Argonne National Laboratory's Computing and Telecommunications Division (CTD), which has the responsibility to provide leadership in optimizing computing and information services and disseminating computer-related technologies throughout the Laboratory. The Site Response consists of 5 parts: (1) a site overview, describes the ANL mission, overall organization structure, the strategic approach to meet information resource needs, the planning process, major issues and points of contact. (2) a software plan for DOE contractors, Part 2B, Software Plan FMS plan for DOE organizations, (3) computing resources telecommunications, (4) telecommunications, (5) printing and publishing.« less

Responding to Information Needs in the 1980s.

ERIC Educational Resources Information Center

McGraw, Harold W., Jr.

1979-01-01

Argues that technological developments in cable television, computers, and telecommunications could decentralize power and put the resources of the new technology more broadly at the command of individuals and small groups, but that this potential requires action to be realized. (Author)

Federal Barriers to Innovation

ERIC Educational Resources Information Center

Miller, Raegen; Lake, Robin

2012-01-01

With educational outcomes inadequate, resources tight, and students' academic needs growing more complex, America's education system is certainly ready for technological innovation. And technology itself is ripe to be exploited. Devices harnessing cheap computing power have become smart and connected. Voice recognition, artificial intelligence,…

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

Not Available

The Computing and Communications (C) Division is responsible for the Laboratory's Integrated Computing Network (ICN) as well as Laboratory-wide communications. Our computing network, used by 8,000 people distributed throughout the nation, constitutes one of the most powerful scientific computing facilities in the world. In addition to the stable production environment of the ICN, we have taken a leadership role in high-performance computing and have established the Advanced Computing Laboratory (ACL), the site of research on experimental, massively parallel computers; high-speed communication networks; distributed computing; and a broad variety of advanced applications. The computational resources available in the ACL are ofmore » the type needed to solve problems critical to national needs, the so-called Grand Challenge'' problems. The purpose of this publication is to inform our clients of our strategic and operating plans in these important areas. We review major accomplishments since late 1990 and describe our strategic planning goals and specific projects that will guide our operations over the next few years. Our mission statement, planning considerations, and management policies and practices are also included.« less

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

Not Available

The Computing and Communications (C) Division is responsible for the Laboratory`s Integrated Computing Network (ICN) as well as Laboratory-wide communications. Our computing network, used by 8,000 people distributed throughout the nation, constitutes one of the most powerful scientific computing facilities in the world. In addition to the stable production environment of the ICN, we have taken a leadership role in high-performance computing and have established the Advanced Computing Laboratory (ACL), the site of research on experimental, massively parallel computers; high-speed communication networks; distributed computing; and a broad variety of advanced applications. The computational resources available in the ACL are ofmore » the type needed to solve problems critical to national needs, the so-called ``Grand Challenge`` problems. The purpose of this publication is to inform our clients of our strategic and operating plans in these important areas. We review major accomplishments since late 1990 and describe our strategic planning goals and specific projects that will guide our operations over the next few years. Our mission statement, planning considerations, and management policies and practices are also included.« less

RSTensorFlow: GPU Enabled TensorFlow for Deep Learning on Commodity Android Devices

PubMed Central

Alzantot, Moustafa; Wang, Yingnan; Ren, Zhengshuang; Srivastava, Mani B.

2018-01-01

Mobile devices have become an essential part of our daily lives. By virtue of both their increasing computing power and the recent progress made in AI, mobile devices evolved to act as intelligent assistants in many tasks rather than a mere way of making phone calls. However, popular and commonly used tools and frameworks for machine intelligence are still lacking the ability to make proper use of the available heterogeneous computing resources on mobile devices. In this paper, we study the benefits of utilizing the heterogeneous (CPU and GPU) computing resources available on commodity android devices while running deep learning models. We leveraged the heterogeneous computing framework RenderScript to accelerate the execution of deep learning models on commodity Android devices. Our system is implemented as an extension to the popular open-source framework TensorFlow. By integrating our acceleration framework tightly into TensorFlow, machine learning engineers can now easily make benefit of the heterogeneous computing resources on mobile devices without the need of any extra tools. We evaluate our system on different android phones models to study the trade-offs of running different neural network operations on the GPU. We also compare the performance of running different models architectures such as convolutional and recurrent neural networks on CPU only vs using heterogeneous computing resources. Our result shows that although GPUs on the phones are capable of offering substantial performance gain in matrix multiplication on mobile devices. Therefore, models that involve multiplication of large matrices can run much faster (approx. 3 times faster in our experiments) due to GPU support. PMID:29629431

RSTensorFlow: GPU Enabled TensorFlow for Deep Learning on Commodity Android Devices.

PubMed

Alzantot, Moustafa; Wang, Yingnan; Ren, Zhengshuang; Srivastava, Mani B

2017-06-01

Mobile devices have become an essential part of our daily lives. By virtue of both their increasing computing power and the recent progress made in AI, mobile devices evolved to act as intelligent assistants in many tasks rather than a mere way of making phone calls. However, popular and commonly used tools and frameworks for machine intelligence are still lacking the ability to make proper use of the available heterogeneous computing resources on mobile devices. In this paper, we study the benefits of utilizing the heterogeneous (CPU and GPU) computing resources available on commodity android devices while running deep learning models. We leveraged the heterogeneous computing framework RenderScript to accelerate the execution of deep learning models on commodity Android devices. Our system is implemented as an extension to the popular open-source framework TensorFlow. By integrating our acceleration framework tightly into TensorFlow, machine learning engineers can now easily make benefit of the heterogeneous computing resources on mobile devices without the need of any extra tools. We evaluate our system on different android phones models to study the trade-offs of running different neural network operations on the GPU. We also compare the performance of running different models architectures such as convolutional and recurrent neural networks on CPU only vs using heterogeneous computing resources. Our result shows that although GPUs on the phones are capable of offering substantial performance gain in matrix multiplication on mobile devices. Therefore, models that involve multiplication of large matrices can run much faster (approx. 3 times faster in our experiments) due to GPU support.

Verifiable fault tolerance in measurement-based quantum computation

NASA Astrophysics Data System (ADS)

Fujii, Keisuke; Hayashi, Masahito

2017-09-01

Quantum systems, in general, cannot be simulated efficiently by a classical computer, and hence are useful for solving certain mathematical problems and simulating quantum many-body systems. This also implies, unfortunately, that verification of the output of the quantum systems is not so trivial, since predicting the output is exponentially hard. As another problem, the quantum system is very delicate for noise and thus needs an error correction. Here, we propose a framework for verification of the output of fault-tolerant quantum computation in a measurement-based model. In contrast to existing analyses on fault tolerance, we do not assume any noise model on the resource state, but an arbitrary resource state is tested by using only single-qubit measurements to verify whether or not the output of measurement-based quantum computation on it is correct. Verifiability is equipped by a constant time repetition of the original measurement-based quantum computation in appropriate measurement bases. Since full characterization of quantum noise is exponentially hard for large-scale quantum computing systems, our framework provides an efficient way to practically verify the experimental quantum error correction.

Analog synthetic biology.

PubMed

Sarpeshkar, R

2014-03-28

We analyse the pros and cons of analog versus digital computation in living cells. Our analysis is based on fundamental laws of noise in gene and protein expression, which set limits on the energy, time, space, molecular count and part-count resources needed to compute at a given level of precision. We conclude that analog computation is significantly more efficient in its use of resources than deterministic digital computation even at relatively high levels of precision in the cell. Based on this analysis, we conclude that synthetic biology must use analog, collective analog, probabilistic and hybrid analog-digital computational approaches; otherwise, even relatively simple synthetic computations in cells such as addition will exceed energy and molecular-count budgets. We present schematics for efficiently representing analog DNA-protein computation in cells. Analog electronic flow in subthreshold transistors and analog molecular flux in chemical reactions obey Boltzmann exponential laws of thermodynamics and are described by astoundingly similar logarithmic electrochemical potentials. Therefore, cytomorphic circuits can help to map circuit designs between electronic and biochemical domains. We review recent work that uses positive-feedback linearization circuits to architect wide-dynamic-range logarithmic analog computation in Escherichia coli using three transcription factors, nearly two orders of magnitude more efficient in parts than prior digital implementations.

Analog synthetic biology

PubMed Central

Sarpeshkar, R.

2014-01-01

We analyse the pros and cons of analog versus digital computation in living cells. Our analysis is based on fundamental laws of noise in gene and protein expression, which set limits on the energy, time, space, molecular count and part-count resources needed to compute at a given level of precision. We conclude that analog computation is significantly more efficient in its use of resources than deterministic digital computation even at relatively high levels of precision in the cell. Based on this analysis, we conclude that synthetic biology must use analog, collective analog, probabilistic and hybrid analog–digital computational approaches; otherwise, even relatively simple synthetic computations in cells such as addition will exceed energy and molecular-count budgets. We present schematics for efficiently representing analog DNA–protein computation in cells. Analog electronic flow in subthreshold transistors and analog molecular flux in chemical reactions obey Boltzmann exponential laws of thermodynamics and are described by astoundingly similar logarithmic electrochemical potentials. Therefore, cytomorphic circuits can help to map circuit designs between electronic and biochemical domains. We review recent work that uses positive-feedback linearization circuits to architect wide-dynamic-range logarithmic analog computation in Escherichia coli using three transcription factors, nearly two orders of magnitude more efficient in parts than prior digital implementations. PMID:24567476

The OSG open facility: A sharing ecosystem

DOE PAGES

Jayatilaka, B.; Levshina, T.; Rynge, M.; ...

2015-12-23

The Open Science Grid (OSG) ties together individual experiments’ computing power, connecting their resources to create a large, robust computing grid, this computing infrastructure started primarily as a collection of sites associated with large HEP experiments such as ATLAS, CDF, CMS, and DZero. In the years since, the OSG has broadened its focus to also address the needs of other US researchers and increased delivery of Distributed High Through-put Computing (DHTC) to users from a wide variety of disciplines via the OSG Open Facility. Presently, the Open Facility delivers about 100 million computing wall hours per year to researchers whomore » are not already associated with the owners of the computing sites, this is primarily accomplished by harvesting and organizing the temporarily unused capacity (i.e. opportunistic cycles) from the sites in the OSG. Using these methods, OSG resource providers and scientists share computing hours with researchers in many other fields to enable their science, striving to make sure that these computing power used with maximal efficiency. Furthermore, we believe that expanded access to DHTC is an essential tool for scientific innovation and work continues in expanding this service.« less

Towards Cloud-based Asynchronous Elasticity for Iterative HPC Applications

NASA Astrophysics Data System (ADS)

da Rosa Righi, Rodrigo; Facco Rodrigues, Vinicius; André da Costa, Cristiano; Kreutz, Diego; Heiss, Hans-Ulrich

2015-10-01

Elasticity is one of the key features of cloud computing. It allows applications to dynamically scale computing and storage resources, avoiding over- and under-provisioning. In high performance computing (HPC), initiatives are normally modeled to handle bag-of-tasks or key-value applications through a load balancer and a loosely-coupled set of virtual machine (VM) instances. In the joint-field of Message Passing Interface (MPI) and tightly-coupled HPC applications, we observe the need of rewriting source codes, previous knowledge of the application and/or stop-reconfigure-and-go approaches to address cloud elasticity. Besides, there are problems related to how profit this new feature in the HPC scope, since in MPI 2.0 applications the programmers need to handle communicators by themselves, and a sudden consolidation of a VM, together with a process, can compromise the entire execution. To address these issues, we propose a PaaS-based elasticity model, named AutoElastic. It acts as a middleware that allows iterative HPC applications to take advantage of dynamic resource provisioning of cloud infrastructures without any major modification. AutoElastic provides a new concept denoted here as asynchronous elasticity, i.e., it provides a framework to allow applications to either increase or decrease their computing resources without blocking the current execution. The feasibility of AutoElastic is demonstrated through a prototype that runs a CPU-bound numerical integration application on top of the OpenNebula middleware. The results showed the saving of about 3 min at each scaling out operations, emphasizing the contribution of the new concept on contexts where seconds are precious.

American Productivity Center Computer Conference on Training and Productivity for the White House Conference on Productivity (Washington, D.C., September 22-23, 1983). Final Report.

ERIC Educational Resources Information Center

1983

Delegates to this training computer conference agreed that the scope of economic change is both accelerating and profound and, therefore, will require a wide variety of approaches to human resource development. Training is only a small part of this development. To meet future needs, the conferees discussed and made recommendations in four areas:…

Extended outlook: description, utilization, and daily applications of cloud technology in radiology.

PubMed

Gerard, Perry; Kapadia, Neil; Chang, Patricia T; Acharya, Jay; Seiler, Michael; Lefkovitz, Zvi

2013-12-01

The purpose of this article is to discuss the concept of cloud technology, its role in medical applications and radiology, the role of the radiologist in using and accessing these vast resources of information, and privacy concerns and HIPAA compliance strategies. Cloud computing is the delivery of shared resources, software, and information to computers and other devices as a metered service. This technology has a promising role in the sharing of patient medical information and appears to be particularly suited for application in radiology, given the field's inherent need for storage and access to large amounts of data. The radiology cloud has significant strengths, such as providing centralized storage and access, reducing unnecessary repeat radiologic studies, and potentially allowing radiologic second opinions more easily. There are significant cost advantages to cloud computing because of a decreased need for infrastructure and equipment by the institution. Private clouds may be used to ensure secure storage of data and compliance with HIPAA. In choosing a cloud service, there are important aspects, such as disaster recovery plans, uptime, and security audits, that must be considered. Given that the field of radiology has become almost exclusively digital in recent years, the future of secure storage and easy access to imaging studies lies within cloud computing technology.

Galileo Teacher Training Program - GTTP Days

NASA Astrophysics Data System (ADS)

Heenatigala, T.; Doran, R.

2012-09-01

Despite the vast availability of teaching resources on the internet, finding a quality and user-friendly materials is a challenge. Many teachers are not trained with proper computing skills to search for the right materials. With years of expertise training teachers globally, Galileo Teacher Training Program (GTTP) [1] recognize the need of having a go-to place for teachers to access resources. To fill this need GTTP developed - GTTP Days - a program creating resource guides for planetary, lunar and solar fields. Avoiding the imbalance in science resources between the developed and undeveloped world, GTTP Days is available both online and offline as a printable version. Each resource guide covers areas such as scientific knowledge, exploration, observation, photography, art & culture and web tools. The lesson plans of each guide include hands-on activities, web tools, software tools, and activities for people with disabilities [2]. Each activity indicate the concepts used, the skills required and age level which guides the teachers and educators to select the correct content suitable for local curriculum.

The expanded role of computers in Space Station Freedom real-time operations

NASA Technical Reports Server (NTRS)

Crawford, R. Paul; Cannon, Kathleen V.

1990-01-01

The challenges that NASA and its international partners face in their real-time operation of the Space Station Freedom necessitate an increased role on the part of computers. In building the operational concepts concerning the role of the computer, the Space Station program is using lessons learned experience from past programs, knowledge of the needs of future space programs, and technical advances in the computer industry. The computer is expected to contribute most significantly in real-time operations by forming a versatile operating architecture, a responsive operations tool set, and an environment that promotes effective and efficient utilization of Space Station Freedom resources.

A smarter way to search, share and utilize open-spatial online data for energy R&D - Custom machine learning and GIS tools in U.S. DOE's virtual data library & laboratory, EDX

NASA Astrophysics Data System (ADS)

Rose, K.; Bauer, J.; Baker, D.; Barkhurst, A.; Bean, A.; DiGiulio, J.; Jones, K.; Jones, T.; Justman, D.; Miller, R., III; Romeo, L.; Sabbatino, M.; Tong, A.

2017-12-01

As spatial datasets are increasingly accessible through open, online systems, the opportunity to use these resources to address a range of Earth system questions grows. Simultaneously, there is a need for better infrastructure and tools to find and utilize these resources. We will present examples of advanced online computing capabilities, hosted in the U.S. DOE's Energy Data eXchange (EDX), that address these needs for earth-energy research and development. In one study the computing team developed a custom, machine learning, big data computing tool designed to parse the web and return priority datasets to appropriate servers to develop an open-source global oil and gas infrastructure database. The results of this spatial smart search approach were validated against expert-driven, manual search results which required a team of seven spatial scientists three months to produce. The custom machine learning tool parsed online, open systems, including zip files, ftp sites and other web-hosted resources, in a matter of days. The resulting resources were integrated into a geodatabase now hosted for open access via EDX. Beyond identifying and accessing authoritative, open spatial data resources, there is also a need for more efficient tools to ingest, perform, and visualize multi-variate, spatial data analyses. Within the EDX framework, there is a growing suite of processing, analytical and visualization capabilities that allow multi-user teams to work more efficiently in private, virtual workspaces. An example of these capabilities are a set of 5 custom spatio-temporal models and data tools that form NETL's Offshore Risk Modeling suite that can be used to quantify oil spill risks and impacts. Coupling the data and advanced functions from EDX with these advanced spatio-temporal models has culminated with an integrated web-based decision-support tool. This platform has capabilities to identify and combine data across scales and disciplines, evaluate potential environmental, social, and economic impacts, highlight knowledge or technology gaps, and reduce uncertainty for a range of `what if' scenarios relevant to oil spill prevention efforts. These examples illustrate EDX's growing capabilities for advanced spatial data search and analysis to support geo-data science needs.

Facilitating NASA Earth Science Data Processing Using Nebula Cloud Computing

NASA Technical Reports Server (NTRS)

Pham, Long; Chen, Aijun; Kempler, Steven; Lynnes, Christopher; Theobald, Michael; Asghar, Esfandiari; Campino, Jane; Vollmer, Bruce

2011-01-01

Cloud Computing has been implemented in several commercial arenas. The NASA Nebula Cloud Computing platform is an Infrastructure as a Service (IaaS) built in 2008 at NASA Ames Research Center and 2010 at GSFC. Nebula is an open source Cloud platform intended to: a) Make NASA realize significant cost savings through efficient resource utilization, reduced energy consumption, and reduced labor costs. b) Provide an easier way for NASA scientists and researchers to efficiently explore and share large and complex data sets. c) Allow customers to provision, manage, and decommission computing capabilities on an as-needed bases

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.

Dynamic Collaboration Infrastructure for Hydrologic Science

NASA Astrophysics Data System (ADS)

Tarboton, D. G.; Idaszak, R.; Castillo, C.; Yi, H.; Jiang, F.; Jones, N.; Goodall, J. L.

2016-12-01

Data and modeling infrastructure is becoming increasingly accessible to water scientists. HydroShare is a collaborative environment that currently offers water scientists the ability to access modeling and data infrastructure in support of data intensive modeling and analysis. It supports the sharing of and collaboration around "resources" which are social objects defined to include both data and models in a structured standardized format. Users collaborate around these objects via comments, ratings, and groups. HydroShare also supports web services and cloud based computation for the execution of hydrologic models and analysis and visualization of hydrologic data. However, the quantity and variety of data and modeling infrastructure available that can be accessed from environments like HydroShare is increasing. Storage infrastructure can range from one's local PC to campus or organizational storage to storage in the cloud. Modeling or computing infrastructure can range from one's desktop to departmental clusters to national HPC resources to grid and cloud computing resources. How does one orchestrate this vast number of data and computing infrastructure without needing to correspondingly learn each new system? A common limitation across these systems is the lack of efficient integration between data transport mechanisms and the corresponding high-level services to support large distributed data and compute operations. A scientist running a hydrology model from their desktop may require processing a large collection of files across the aforementioned storage and compute resources and various national databases. To address these community challenges a proof-of-concept prototype was created integrating HydroShare with RADII (Resource Aware Data-centric collaboration Infrastructure) to provide software infrastructure to enable the comprehensive and rapid dynamic deployment of what we refer to as "collaborative infrastructure." In this presentation we discuss the results of this proof-of-concept prototype which enabled HydroShare users to readily instantiate virtual infrastructure marshaling arbitrary combinations, varieties, and quantities of distributed data and computing infrastructure in addressing big problems in hydrology.

Batching System for Superior Service

NASA Technical Reports Server (NTRS)

2001-01-01

Veridian's Portable Batch System (PBS) was the recipient of the 1997 NASA Space Act Award for outstanding software. A batch system is a set of processes for managing queues and jobs. Without a batch system, it is difficult to manage the workload of a computer system. By bundling the enterprise's computing resources, the PBS technology offers users a single coherent interface, resulting in efficient management of the batch services. Users choose which information to package into "containers" for system-wide use. PBS also provides detailed system usage data, a procedure not easily executed without this software. PBS operates on networked, multi-platform UNIX environments. Veridian's new version, PBS Pro,TM has additional features and enhancements, including support for additional operating systems. Veridian distributes the original version of PBS as Open Source software via the PBS website. Customers can register and download the software at no cost. PBS Pro is also available via the web and offers additional features such as increased stability, reliability, and fault tolerance.A company using PBS can expect a significant increase in the effective management of its computing resources. Tangible benefits include increased utilization of costly resources and enhanced understanding of computational requirements and user needs.

NeuroManager: a workflow analysis based simulation management engine for computational neuroscience

PubMed Central

Stockton, David B.; Santamaria, Fidel

2015-01-01

We developed NeuroManager, an object-oriented simulation management software engine for computational neuroscience. NeuroManager automates the workflow of simulation job submissions when using heterogeneous computational resources, simulators, and simulation tasks. The object-oriented approach (1) provides flexibility to adapt to a variety of neuroscience simulators, (2) simplifies the use of heterogeneous computational resources, from desktops to super computer clusters, and (3) improves tracking of simulator/simulation evolution. We implemented NeuroManager in MATLAB, a widely used engineering and scientific language, for its signal and image processing tools, prevalence in electrophysiology analysis, and increasing use in college Biology education. To design and develop NeuroManager we analyzed the workflow of simulation submission for a variety of simulators, operating systems, and computational resources, including the handling of input parameters, data, models, results, and analyses. This resulted in 22 stages of simulation submission workflow. The software incorporates progress notification, automatic organization, labeling, and time-stamping of data and results, and integrated access to MATLAB's analysis and visualization tools. NeuroManager provides users with the tools to automate daily tasks, and assists principal investigators in tracking and recreating the evolution of research projects performed by multiple people. Overall, NeuroManager provides the infrastructure needed to improve workflow, manage multiple simultaneous simulations, and maintain provenance of the potentially large amounts of data produced during the course of a research project. PMID:26528175

NeuroManager: a workflow analysis based simulation management engine for computational neuroscience.

PubMed

Stockton, David B; Santamaria, Fidel

2015-01-01

We developed NeuroManager, an object-oriented simulation management software engine for computational neuroscience. NeuroManager automates the workflow of simulation job submissions when using heterogeneous computational resources, simulators, and simulation tasks. The object-oriented approach (1) provides flexibility to adapt to a variety of neuroscience simulators, (2) simplifies the use of heterogeneous computational resources, from desktops to super computer clusters, and (3) improves tracking of simulator/simulation evolution. We implemented NeuroManager in MATLAB, a widely used engineering and scientific language, for its signal and image processing tools, prevalence in electrophysiology analysis, and increasing use in college Biology education. To design and develop NeuroManager we analyzed the workflow of simulation submission for a variety of simulators, operating systems, and computational resources, including the handling of input parameters, data, models, results, and analyses. This resulted in 22 stages of simulation submission workflow. The software incorporates progress notification, automatic organization, labeling, and time-stamping of data and results, and integrated access to MATLAB's analysis and visualization tools. NeuroManager provides users with the tools to automate daily tasks, and assists principal investigators in tracking and recreating the evolution of research projects performed by multiple people. Overall, NeuroManager provides the infrastructure needed to improve workflow, manage multiple simultaneous simulations, and maintain provenance of the potentially large amounts of data produced during the course of a research project.

Markov decision processes in natural resources management: observability and uncertainty

USGS Publications Warehouse

Williams, Byron K.

2015-01-01

The breadth and complexity of stochastic decision processes in natural resources presents a challenge to analysts who need to understand and use these approaches. The objective of this paper is to describe a class of decision processes that are germane to natural resources conservation and management, namely Markov decision processes, and to discuss applications and computing algorithms under different conditions of observability and uncertainty. A number of important similarities are developed in the framing and evaluation of different decision processes, which can be useful in their applications in natural resources management. The challenges attendant to partial observability are highlighted, and possible approaches for dealing with it are discussed.

KITTEN Lightweight Kernel 0.1 Beta

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

Pedretti, Kevin; Levenhagen, Michael; Kelly, Suzanne

2007-12-12

The Kitten Lightweight Kernel is a simplified OS (operating system) kernel that is intended to manage a compute node's hardware resources. It provides a set of mechanisms to user-level applications for utilizing hardware resources (e.g., allocating memory, creating processes, accessing the network). Kitten is much simpler than general-purpose OS kernels, such as Linux or Windows, but includes all of the esssential functionality needed to support HPC (high-performance computing) MPI, PGAS and OpenMP applications. Kitten provides unique capabilities such as physically contiguous application memory, transparent large page support, and noise-free tick-less operation, which enable HPC applications to obtain greater efficiency andmore » scalability than with general purpose OS kernels.« less

Real-time robot deliberation by compilation and monitoring of anytime algorithms

NASA Technical Reports Server (NTRS)

Zilberstein, Shlomo

1994-01-01

Anytime algorithms are algorithms whose quality of results improves gradually as computation time increases. Certainty, accuracy, and specificity are metrics useful in anytime algorighm construction. It is widely accepted that a successful robotic system must trade off between decision quality and the computational resources used to produce it. Anytime algorithms were designed to offer such a trade off. A model of compilation and monitoring mechanisms needed to build robots that can efficiently control their deliberation time is presented. This approach simplifies the design and implementation of complex intelligent robots, mechanizes the composition and monitoring processes, and provides independent real time robotic systems that automatically adjust resource allocation to yield optimum performance.

[Earth Science Technology Office's Computational Technologies Project

NASA Technical Reports Server (NTRS)

Fischer, James (Technical Monitor); Merkey, Phillip

2005-01-01

This grant supported the effort to characterize the problem domain of the Earth Science Technology Office's Computational Technologies Project, to engage the Beowulf Cluster Computing Community as well as the High Performance Computing Research Community so that we can predict the applicability of said technologies to the scientific community represented by the CT project and formulate long term strategies to provide the computational resources necessary to attain the anticipated scientific objectives of the CT project. Specifically, the goal of the evaluation effort is to use the information gathered over the course of the Round-3 investigations to quantify the trends in scientific expectations, the algorithmic requirements and capabilities of high-performance computers to satisfy this anticipated need.

Utility Computing: Reality and Beyond

NASA Astrophysics Data System (ADS)

Ivanov, Ivan I.

Utility Computing is not a new concept. It involves organizing and providing a wide range of computing-related services as public utilities. Much like water, gas, electricity and telecommunications, the concept of computing as public utility was announced in 1955. Utility Computing remained a concept for near 50 years. Now some models and forms of Utility Computing are emerging such as storage and server virtualization, grid computing, and automated provisioning. Recent trends in Utility Computing as a complex technology involve business procedures that could profoundly transform the nature of companies' IT services, organizational IT strategies and technology infrastructure, and business models. In the ultimate Utility Computing models, organizations will be able to acquire as much IT services as they need, whenever and wherever they need them. Based on networked businesses and new secure online applications, Utility Computing would facilitate "agility-integration" of IT resources and services within and between virtual companies. With the application of Utility Computing there could be concealment of the complexity of IT, reduction of operational expenses, and converting of IT costs to variable `on-demand' services. How far should technology, business and society go to adopt Utility Computing forms, modes and models?

Advanced Simulation & Computing FY15 Implementation Plan Volume 2, Rev. 0.5

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

McCoy, Michel; Archer, Bill; Matzen, M. Keith

2014-09-16

The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the surety and reliability of the U.S. nuclear stockpile. The SSP uses nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of experimental facilities and programs, and the computational enhancements to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities andmore » computational resources that support annual stockpile assessment and certification, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balance of resource, including technical staff, hardware, simulation software, and computer science solutions. As the program approaches the end of its second decade, ASC is intently focused on increasing predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), quantify critical margins and uncertainties, and resolve increasingly difficult analyses needed for the SSP. Where possible, the program also enables the use of high-performance simulation and computing tools to address broader national security needs, such as foreign nuclear weapon assessments and counternuclear terrorism.« less

Changing physiological status predicts severe injury and need for specialized trauma center resources.

PubMed

Talbert, Steven

2009-01-01

This study evaluated the association between changing physiological status (delta data) with severe injury (SI) or need for trauma center resources (TCR). Prehospital and emergency department arrival weighted RTS (RTSw) were computed for patients with complete records entered into the registry from 2002 to 2004 (n = 23,753). Physiological change was classified as unchanged, deteriorated, or improved (PreRTSw vs EDRTSw). Performance of delta data was evaluated using standard epidemiological approaches and multiple logistic regression. Deterioration status predicted SI (operating room [OR] = 1.38) and TCR (OR = 2.09). Improved status predicted TCR (OR = 1.27). Delta data independently predicted both SI and TCR.

DREAMS and IMAGE: A Model and Computer Implementation for Concurrent, Life-Cycle Design of Complex Systems

NASA Technical Reports Server (NTRS)

Hale, Mark A.; Craig, James I.; Mistree, Farrokh; Schrage, Daniel P.

1995-01-01

Computing architectures are being assembled that extend concurrent engineering practices by providing more efficient execution and collaboration on distributed, heterogeneous computing networks. Built on the successes of initial architectures, requirements for a next-generation design computing infrastructure can be developed. These requirements concentrate on those needed by a designer in decision-making processes from product conception to recycling and can be categorized in two areas: design process and design information management. A designer both designs and executes design processes throughout design time to achieve better product and process capabilities while expanding fewer resources. In order to accomplish this, information, or more appropriately design knowledge, needs to be adequately managed during product and process decomposition as well as recomposition. A foundation has been laid that captures these requirements in a design architecture called DREAMS (Developing Robust Engineering Analysis Models and Specifications). In addition, a computing infrastructure, called IMAGE (Intelligent Multidisciplinary Aircraft Generation Environment), is being developed that satisfies design requirements defined in DREAMS and incorporates enabling computational technologies.

Human and Robotic Space Mission Use Cases for High-Performance Spaceflight Computing

NASA Technical Reports Server (NTRS)

Some, Raphael; Doyle, Richard; Bergman, Larry; Whitaker, William; Powell, Wesley; Johnson, Michael; Goforth, Montgomery; Lowry, Michael

2013-01-01

Spaceflight computing is a key resource in NASA space missions and a core determining factor of spacecraft capability, with ripple effects throughout the spacecraft, end-to-end system, and mission. Onboard computing can be aptly viewed as a "technology multiplier" in that advances provide direct dramatic improvements in flight functions and capabilities across the NASA mission classes, and enable new flight capabilities and mission scenarios, increasing science and exploration return. Space-qualified computing technology, however, has not advanced significantly in well over ten years and the current state of the practice fails to meet the near- to mid-term needs of NASA missions. Recognizing this gap, the NASA Game Changing Development Program (GCDP), under the auspices of the NASA Space Technology Mission Directorate, commissioned a study on space-based computing needs, looking out 15-20 years. The study resulted in a recommendation to pursue high-performance spaceflight computing (HPSC) for next-generation missions, and a decision to partner with the Air Force Research Lab (AFRL) in this development.

Cyberinfrastructure for End-to-End Environmental Explorations

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

Fast and Scalable Computation of the Forward and Inverse Discrete Periodic Radon Transform.

PubMed

Carranza, Cesar; Llamocca, Daniel; Pattichis, Marios

2016-01-01

The discrete periodic radon transform (DPRT) has extensively been used in applications that involve image reconstructions from projections. Beyond classic applications, the DPRT can also be used to compute fast convolutions that avoids the use of floating-point arithmetic associated with the use of the fast Fourier transform. Unfortunately, the use of the DPRT has been limited by the need to compute a large number of additions and the need for a large number of memory accesses. This paper introduces a fast and scalable approach for computing the forward and inverse DPRT that is based on the use of: a parallel array of fixed-point adder trees; circular shift registers to remove the need for accessing external memory components when selecting the input data for the adder trees; an image block-based approach to DPRT computation that can fit the proposed architecture to available resources; and fast transpositions that are computed in one or a few clock cycles that do not depend on the size of the input image. As a result, for an N × N image (N prime), the proposed approach can compute up to N(2) additions per clock cycle. Compared with the previous approaches, the scalable approach provides the fastest known implementations for different amounts of computational resources. For example, for a 251×251 image, for approximately 25% fewer flip-flops than required for a systolic implementation, we have that the scalable DPRT is computed 36 times faster. For the fastest case, we introduce optimized just 2N + ⌈log(2) N⌉ + 1 and 2N + 3 ⌈log(2) N⌉ + B + 2 cycles, architectures that can compute the DPRT and its inverse in respectively, where B is the number of bits used to represent each input pixel. On the other hand, the scalable DPRT approach requires more 1-b additions than for the systolic implementation and provides a tradeoff between speed and additional 1-b additions. All of the proposed DPRT architectures were implemented in VHSIC Hardware Description Language (VHDL) and validated using an Field-Programmable Gate Array (FPGA) implementation.

Autonomic Management of Application Workflows on Hybrid Computing Infrastructure

DOE PAGES

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

2011-01-01

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

Cloud-based opportunities in scientific computing: insights from processing Suomi National Polar-Orbiting Partnership (S-NPP) Direct Broadcast data

NASA Astrophysics Data System (ADS)

Evans, J. D.; Hao, W.; Chettri, S.

2013-12-01

The cloud is proving to be a uniquely promising platform for scientific computing. Our experience with processing satellite data using Amazon Web Services highlights several opportunities for enhanced performance, flexibility, and cost effectiveness in the cloud relative to traditional computing -- for example: - Direct readout from a polar-orbiting satellite such as the Suomi National Polar-Orbiting Partnership (S-NPP) requires bursts of processing a few times a day, separated by quiet periods when the satellite is out of receiving range. In the cloud, by starting and stopping virtual machines in minutes, we can marshal significant computing resources quickly when needed, but not pay for them when not needed. To take advantage of this capability, we are automating a data-driven approach to the management of cloud computing resources, in which new data availability triggers the creation of new virtual machines (of variable size and processing power) which last only until the processing workflow is complete. - 'Spot instances' are virtual machines that run as long as one's asking price is higher than the provider's variable spot price. Spot instances can greatly reduce the cost of computing -- for software systems that are engineered to withstand unpredictable interruptions in service (as occurs when a spot price exceeds the asking price). We are implementing an approach to workflow management that allows data processing workflows to resume with minimal delays after temporary spot price spikes. This will allow systems to take full advantage of variably-priced 'utility computing.' - Thanks to virtual machine images, we can easily launch multiple, identical machines differentiated only by 'user data' containing individualized instructions (e.g., to fetch particular datasets or to perform certain workflows or algorithms) This is particularly useful when (as is the case with S-NPP data) we need to launch many very similar machines to process an unpredictable number of data files concurrently. Our experience shows the viability and flexibility of this approach to workflow management for scientific data processing. - Finally, cloud computing is a promising platform for distributed volunteer ('interstitial') computing, via mechanisms such as the Berkeley Open Infrastructure for Network Computing (BOINC) popularized with the SETI@Home project and others such as ClimatePrediction.net and NASA's Climate@Home. Interstitial computing faces significant challenges as commodity computing shifts from (always on) desktop computers towards smartphones and tablets (untethered and running on scarce battery power); but cloud computing offers significant slack capacity. This capacity includes virtual machines with unused RAM or underused CPUs; virtual storage volumes allocated (& paid for) but not full; and virtual machines that are paid up for the current hour but whose work is complete. We are devising ways to facilitate the reuse of these resources (i.e., cloud-based interstitial computing) for satellite data processing and related analyses. We will present our findings and research directions on these and related topics.

Review of the Water Resources Information System of Argentina

USGS Publications Warehouse

Hutchison, N.E.

1987-01-01

A representative of the U.S. Geological Survey traveled to Buenos Aires, Argentina, in November 1986, to discuss water information systems and data bank implementation in the Argentine Government Center for Water Resources Information. Software has been written by Center personnel for a minicomputer to be used to manage inventory (index) data and water quality data. Additional hardware and software have been ordered to upgrade the existing computer. Four microcomputers, statistical and data base management software, and network hardware and software for linking the computers have also been ordered. The Center plans to develop a nationwide distributed data base for Argentina that will include the major regional offices as nodes. Needs for continued development of the water resources information system for Argentina were reviewed. Identified needs include: (1) conducting a requirements analysis to define the content of the data base and insure that all user requirements are met, (2) preparing a plan for the development, implementation, and operation of the data base, and (3) developing a conceptual design to inform all development personnel and users of the basic functionality planned for the system. A quality assurance and configuration management program to provide oversight to the development process was also discussed. (USGS)

Overview of the LINCS architecture

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

Fletcher, J.G.; Watson, R.W.

1982-01-13

Computing at the Lawrence Livermore National Laboratory (LLNL) has evolved over the past 15 years with a computer network based resource sharing environment. The increasing use of low cost and high performance micro, mini and midi computers and commercially available local networking systems will accelerate this trend. Further, even the large scale computer systems, on which much of the LLNL scientific computing depends, are evolving into multiprocessor systems. It is our belief that the most cost effective use of this environment will depend on the development of application systems structured into cooperating concurrent program modules (processes) distributed appropriately over differentmore » nodes of the environment. A node is defined as one or more processors with a local (shared) high speed memory. Given the latter view, the environment can be characterized as consisting of: multiple nodes communicating over noisy channels with arbitrary delays and throughput, heterogenous base resources and information encodings, no single administration controlling all resources, distributed system state, and no uniform time base. The system design problem is - how to turn the heterogeneous base hardware/firmware/software resources of this environment into a coherent set of resources that facilitate development of cost effective, reliable, and human engineered applications. We believe the answer lies in developing a layered, communication oriented distributed system architecture; layered and modular to support ease of understanding, reconfiguration, extensibility, and hiding of implementation or nonessential local details; communication oriented because that is a central feature of the environment. The Livermore Interactive Network Communication System (LINCS) is a hierarchical architecture designed to meet the above needs. While having characteristics in common with other architectures, it differs in several respects.« less

An efficient two-stage approach for image-based FSI analysis of atherosclerotic arteries

PubMed Central

Rayz, Vitaliy L.; Mofrad, Mohammad R. K.; Saloner, David

2010-01-01

Patient-specific biomechanical modeling of atherosclerotic arteries has the potential to aid clinicians in characterizing lesions and determining optimal treatment plans. To attain high levels of accuracy, recent models use medical imaging data to determine plaque component boundaries in three dimensions, and fluid–structure interaction is used to capture mechanical loading of the diseased vessel. As the plaque components and vessel wall are often highly complex in shape, constructing a suitable structured computational mesh is very challenging and can require a great deal of time. Models based on unstructured computational meshes require relatively less time to construct and are capable of accurately representing plaque components in three dimensions. These models unfortunately require additional computational resources and computing time for accurate and meaningful results. A two-stage modeling strategy based on unstructured computational meshes is proposed to achieve a reasonable balance between meshing difficulty and computational resource and time demand. In this method, a coarsegrained simulation of the full arterial domain is used to guide and constrain a fine-scale simulation of a smaller region of interest within the full domain. Results for a patient-specific carotid bifurcation model demonstrate that the two-stage approach can afford a large savings in both time for mesh generation and time and resources needed for computation. The effects of solid and fluid domain truncation were explored, and were shown to minimally affect accuracy of the stress fields predicted with the two-stage approach. PMID:19756798

Triple-server blind quantum computation using entanglement swapping

NASA Astrophysics Data System (ADS)

Li, Qin; Chan, Wai Hong; Wu, Chunhui; Wen, Zhonghua

2014-04-01

Blind quantum computation allows a client who does not have enough quantum resources or technologies to achieve quantum computation on a remote quantum server such that the client's input, output, and algorithm remain unknown to the server. Up to now, single- and double-server blind quantum computation have been considered. In this work, we propose a triple-server blind computation protocol where the client can delegate quantum computation to three quantum servers by the use of entanglement swapping. Furthermore, the three quantum servers can communicate with each other and the client is almost classical since one does not require any quantum computational power, quantum memory, and the ability to prepare any quantum states and only needs to be capable of getting access to quantum channels.

Rich client data exploration and research prototyping for NOAA

NASA Astrophysics Data System (ADS)

Grossberg, Michael; Gladkova, Irina; Guch, Ingrid; Alabi, Paul; Shahriar, Fazlul; Bonev, George; Aizenman, Hannah

2009-08-01

Data from satellites and model simulations is increasing exponentially as observations and model computing power improve rapidly. Not only is technology producing more data, but it often comes from sources all over the world. Researchers and scientists who must collaborate are also located globally. This work presents a software design and technologies which will make it possible for groups of researchers to explore large data sets visually together without the need to download these data sets locally. The design will also make it possible to exploit high performance computing remotely and transparently to analyze and explore large data sets. Computer power, high quality sensing, and data storage capacity have improved at a rate that outstrips our ability to develop software applications that exploit these resources. It is impractical for NOAA scientists to download all of the satellite and model data that may be relevant to a given problem and the computing environments available to a given researcher range from supercomputers to only a web browser. The size and volume of satellite and model data are increasing exponentially. There are at least 50 multisensor satellite platforms collecting Earth science data. On the ground and in the sea there are sensor networks, as well as networks of ground based radar stations, producing a rich real-time stream of data. This new wealth of data would have limited use were it not for the arrival of large-scale high-performance computation provided by parallel computers, clusters, grids, and clouds. With these computational resources and vast archives available, it is now possible to analyze subtle relationships which are global, multi-modal and cut across many data sources. Researchers, educators, and even the general public, need tools to access, discover, and use vast data center archives and high performance computing through a simple yet flexible interface.

Computational Difficulties in the Identification and Optimization of Control Systems.

DTIC Science & Technology

1980-01-01

necessary and Identify by block number) - -. 3. iABSTRACT (Continue on revers, side It necessary and Identify by block number) As more realistic models ...Island 02912 ABSTRACT As more realistic models for resource management are developed, the need for efficient computational techniques for parameter...optimization (optimal control) in "state" models which This research was supported in part by ttfe National Science Foundation under grant NSF-MCS 79-05774

Prototyping an institutional IAIMS/UMLS information environment for an academic medical center.

PubMed

Miller, P L; Paton, J A; Clyman, J I; Powsner, S M

1992-07-01

The paper describes a prototype information environment designed to link network-based information resources in an integrated fashion and thus enhance the information capabilities of an academic medical center. The prototype was implemented on a single Macintosh computer to permit exploration of the overall "information architecture" and to demonstrate the various desired capabilities prior to full-scale network-based implementation. At the heart of the prototype are two components: a diverse set of information resources available over an institutional computer network and an information sources map designed to assist users in finding and accessing information resources relevant to their needs. The paper describes these and other components of the prototype and presents a scenario illustrating its use. The prototype illustrates the link between the goals of two National Library of Medicine initiatives, the Integrated Academic Information Management System (IAIMS) and the Unified Medical Language System (UMLS).

Autonomy for Constellation

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Szczur, Martha R. (Technical Monitor)

2000-01-01

The newer types of space systems, which are planned for the future, are placing challenging demands for newer autonomy concepts and techniques. Motivating these challenges are resource constraints. Even though onboard computing power will surely increase in the coming years, the resource constraints associated with space-based processes will continue to be a major factor that needs to be considered when dealing with, for example, agent-based spacecraft autonomy. To realize "economical intelligence", i.e., constrained computational intelligence that can reside within a process under severe resource constraints (time, power, space, etc.), is a major goal for such space systems as the Nanosat constellations. To begin to address the new challenges, we are developing approaches to constellation autonomy with constraints in mind. Within the Agent Concepts Testbed (ACT) at the Goddard Space Flight Center we are currently developing a Nanosat-related prototype for the first of the two-step program.

[Pediatric surgery 2.0].

PubMed

Mesa-Gutiérrez, J C; Bardají, C; Brun, N; Núñez, B; Sánchez, B; Sanvicente, B; Obiols, P; Rigol, S

2012-04-01

New tools from the web are a complete breakthrough in management of information. The aim of this paper is to present different resources in a friendly way, with apps and examples in the different phases of the knowledge management for the paediatric surgeon: search, filter, reception, classification, sharing, collaborative work and publication. We are assisting to a real revolution on how to manage knowledge and information. The main charateristics are: immediateness, social component, growing interaction, and easiness. Every physician has clinical questions and the Internet gives us more and more resources to make searchs easier. Along with them we need electronic resources to filter information of quality and to make easier transfer of knowledge to clinical practice. Cloud computing is on continuous development and makes possible sharing information with differents users and computers. The main feature of the apps from the Intenet is the social component, that makes possible interaction, sharing and collaborative work.

Progress on the FabrIc for Frontier Experiments project at Fermilab

DOE PAGES

Box, Dennis; Boyd, Joseph; Dykstra, Dave; ...

2015-12-23

The FabrIc for Frontier Experiments (FIFE) project is an ambitious, major-impact initiative within the Fermilab Scientific Computing Division designed to lead the computing model for Fermilab experiments. FIFE is a collaborative effort between experimenters and computing professionals to design and develop integrated computing models for experiments of varying needs and infrastructure. The major focus of the FIFE project is the development, deployment, and integration of Open Science Grid solutions for high throughput computing, data management, database access and collaboration within experiment. To accomplish this goal, FIFE has developed workflows that utilize Open Science Grid sites along with dedicated and commercialmore » cloud resources. The FIFE project has made significant progress integrating into experiment computing operations several services including new job submission services, software and reference data distribution through CVMFS repositories, flexible data transfer client, and access to opportunistic resources on the Open Science Grid. Hence, the progress with current experiments and plans for expansion with additional projects will be discussed. FIFE has taken a leading role in the definition of the computing model for Fermilab experiments, aided in the design of computing for experiments beyond Fermilab, and will continue to define the future direction of high throughput computing for future physics experiments worldwide« less

The FIFE Project at Fermilab

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

Box, D.; Boyd, J.; Di Benedetto, V.

2016-01-01

The FabrIc for Frontier Experiments (FIFE) project is an initiative within the Fermilab Scientific Computing Division designed to steer the computing model for non-LHC Fermilab experiments across multiple physics areas. FIFE is a collaborative effort between experimenters and computing professionals to design and develop integrated computing models for experiments of varying size, needs, and infrastructure. The major focus of the FIFE project is the development, deployment, and integration of solutions for high throughput computing, data management, database access and collaboration management within an experiment. To accomplish this goal, FIFE has developed workflows that utilize Open Science Grid compute sites alongmore » with dedicated and commercial cloud resources. The FIFE project has made significant progress integrating into experiment computing operations several services including a common job submission service, software and reference data distribution through CVMFS repositories, flexible and robust data transfer clients, and access to opportunistic resources on the Open Science Grid. The progress with current experiments and plans for expansion with additional projects will be discussed. FIFE has taken the leading role in defining the computing model for Fermilab experiments, aided in the design of experiments beyond those hosted at Fermilab, and will continue to define the future direction of high throughput computing for future physics experiments worldwide.« less

Efficient operating system level virtualization techniques for cloud resources

NASA Astrophysics Data System (ADS)

Ansu, R.; Samiksha; Anju, S.; Singh, K. John

2017-11-01

Cloud computing is an advancing technology which provides the servcies of Infrastructure, Platform and Software. Virtualization and Computer utility are the keys of Cloud computing. The numbers of cloud users are increasing day by day. So it is the need of the hour to make resources available on demand to satisfy user requirements. The technique in which resources namely storage, processing power, memory and network or I/O are abstracted is known as Virtualization. For executing the operating systems various virtualization techniques are available. They are: Full System Virtualization and Para Virtualization. In Full Virtualization, the whole architecture of hardware is duplicated virtually. No modifications are required in Guest OS as the OS deals with the VM hypervisor directly. In Para Virtualization, modifications of OS is required to run in parallel with other OS. For the Guest OS to access the hardware, the host OS must provide a Virtual Machine Interface. OS virtualization has many advantages such as migrating applications transparently, consolidation of server, online maintenance of OS and providing security. This paper briefs both the virtualization techniques and discusses the issues in OS level virtualization.

Application-oriented offloading in heterogeneous networks for mobile cloud computing

NASA Astrophysics Data System (ADS)

Tseng, Fan-Hsun; Cho, Hsin-Hung; Chang, Kai-Di; Li, Jheng-Cong; Shih, Timothy K.

2018-04-01

Nowadays Internet applications have become more complicated that mobile device needs more computing resources for shorter execution time but it is restricted to limited battery capacity. Mobile cloud computing (MCC) is emerged to tackle the finite resource problem of mobile device. MCC offloads the tasks and jobs of mobile devices to cloud and fog environments by using offloading scheme. It is vital to MCC that which task should be offloaded and how to offload efficiently. In the paper, we formulate the offloading problem between mobile device and cloud data center and propose two algorithms based on application-oriented for minimum execution time, i.e. the Minimum Offloading Time for Mobile device (MOTM) algorithm and the Minimum Execution Time for Cloud data center (METC) algorithm. The MOTM algorithm minimizes offloading time by selecting appropriate offloading links based on application categories. The METC algorithm minimizes execution time in cloud data center by selecting virtual and physical machines with corresponding resource requirements of applications. Simulation results show that the proposed mechanism not only minimizes total execution time for mobile devices but also decreases their energy consumption.

JANUS: A Compilation System for Balancing Parallelism and Performance in OpenVX

NASA Astrophysics Data System (ADS)

Omidian, Hossein; Lemieux, Guy G. F.

2018-04-01

Embedded systems typically do not have enough on-chip memory for entire an image buffer. Programming systems like OpenCV operate on entire image frames at each step, making them use excessive memory bandwidth and power. In contrast, the paradigm used by OpenVX is much more efficient; it uses image tiling, and the compilation system is allowed to analyze and optimize the operation sequence, specified as a compute graph, before doing any pixel processing. In this work, we are building a compilation system for OpenVX that can analyze and optimize the compute graph to take advantage of parallel resources in many-core systems or FPGAs. Using a database of prewritten OpenVX kernels, it automatically adjusts the image tile size as well as using kernel duplication and coalescing to meet a defined area (resource) target, or to meet a specified throughput target. This allows a single compute graph to target implementations with a wide range of performance needs or capabilities, e.g. from handheld to datacenter, that use minimal resources and power to reach the performance target.

Virtualization and cloud computing in dentistry.

PubMed

Chow, Frank; Muftu, Ali; Shorter, Richard

2014-01-01

The use of virtualization and cloud computing has changed the way we use computers. Virtualization is a method of placing software called a hypervisor on the hardware of a computer or a host operating system. It allows a guest operating system to run on top of the physical computer with a virtual machine (i.e., virtual computer). Virtualization allows multiple virtual computers to run on top of one physical computer and to share its hardware resources, such as printers, scanners, and modems. This increases the efficient use of the computer by decreasing costs (e.g., hardware, electricity administration, and management) since only one physical computer is needed and running. This virtualization platform is the basis for cloud computing. It has expanded into areas of server and storage virtualization. One of the commonly used dental storage systems is cloud storage. Patient information is encrypted as required by the Health Insurance Portability and Accountability Act (HIPAA) and stored on off-site private cloud services for a monthly service fee. As computer costs continue to increase, so too will the need for more storage and processing power. Virtual and cloud computing will be a method for dentists to minimize costs and maximize computer efficiency in the near future. This article will provide some useful information on current uses of cloud computing.

Computed discharges at five sites in lower Laguna Madre near Port Isabel, Texas, June 1997

USGS Publications Warehouse

East, Jeffrey W.; Solis, R.S.; Ockerman, D.J.

1998-01-01

The Texas Water Development Board (TWDB), Texas Parks and Wildlife Department (TPWD), and Texas Natural Resource Conservation Commission (TNRCC) are charged by the Texas Legislature with determining freshwater inflows required to maintain the ecological health of streams, bays, and estuaries in Texas. To determine required inflows, the three agencies collect data and conduct studies on the needs for freshwater inflows to estuaries. The TWDB uses estuarine hydrodynamic and conservativetransport computer models to predict the effects of altering freshwater inflows on estuarine circulation and salinity. To calibrate these models, a variety of water-quality and discharge data are needed.

Shipping Science Worldwide with Open Source Containers

NASA Astrophysics Data System (ADS)

Molineaux, J. P.; McLaughlin, B. D.; Pilone, D.; Plofchan, P. G.; Murphy, K. J.

2014-12-01

Scientific applications often present difficult web-hosting needs. Their compute- and data-intensive nature, as well as an increasing need for high-availability and distribution, combine to create a challenging set of hosting requirements. In the past year, advancements in container-based virtualization and related tooling have offered new lightweight and flexible ways to accommodate diverse applications with all the isolation and portability benefits of traditional virtualization. This session will introduce and demonstrate an open-source, single-interface, Platform-as-a-Serivce (PaaS) that empowers application developers to seamlessly leverage geographically distributed, public and private compute resources to achieve highly-available, performant hosting for scientific applications.

The CompTox Chemistry Dashboard - A Community Data Resource for Environmental Chemistry

EPA Science Inventory

Despite an abundance of online databases providing access to chemical data, there is increasing demand for high-quality, structure-curated, open data to meet the various needs of the environmental sciences and computational toxicology communities. The U.S. Environmental Protectio...

40 CFR 1.33 - Office of Administration and Resources Management.

Code of Federal Regulations, 2011 CFR

2011-07-01

... provides national program policy and technical guidance for: The acquisition of all information technology... acquired by grantees and contractors using Agency funds; the operation of all Agency computers and... Management Interns, OHRM establishes policies; assesses and projects Agency executive needs and workforce...

40 CFR 1.33 - Office of Administration and Resources Management.

Code of Federal Regulations, 2012 CFR

2012-07-01

... provides national program policy and technical guidance for: The acquisition of all information technology... acquired by grantees and contractors using Agency funds; the operation of all Agency computers and... Management Interns, OHRM establishes policies; assesses and projects Agency executive needs and workforce...

40 CFR 1.33 - Office of Administration and Resources Management.

Code of Federal Regulations, 2014 CFR

2014-07-01

... provides national program policy and technical guidance for: The acquisition of all information technology... acquired by grantees and contractors using Agency funds; the operation of all Agency computers and... Management Interns, OHRM establishes policies; assesses and projects Agency executive needs and workforce...

40 CFR 1.33 - Office of Administration and Resources Management.

Code of Federal Regulations, 2013 CFR

2013-07-01

... provides national program policy and technical guidance for: The acquisition of all information technology... acquired by grantees and contractors using Agency funds; the operation of all Agency computers and... Management Interns, OHRM establishes policies; assesses and projects Agency executive needs and workforce...

JINR cloud infrastructure evolution

NASA Astrophysics Data System (ADS)

Baranov, A. V.; Balashov, N. A.; Kutovskiy, N. A.; Semenov, R. N.

2016-09-01

To fulfil JINR commitments in different national and international projects related to the use of modern information technologies such as cloud and grid computing as well as to provide a modern tool for JINR users for their scientific research a cloud infrastructure was deployed at Laboratory of Information Technologies of Joint Institute for Nuclear Research. OpenNebula software was chosen as a cloud platform. Initially it was set up in simple configuration with single front-end host and a few cloud nodes. Some custom development was done to tune JINR cloud installation to fit local needs: web form in the cloud web-interface for resources request, a menu item with cloud utilization statistics, user authentication via Kerberos, custom driver for OpenVZ containers. Because of high demand in that cloud service and its resources over-utilization it was re-designed to cover increasing users' needs in capacity, availability and reliability. Recently a new cloud instance has been deployed in high-availability configuration with distributed network file system and additional computing power.

Computing at h1 - Experience and Future

NASA Astrophysics Data System (ADS)

Eckerlin, G.; Gerhards, R.; Kleinwort, C.; KrÜNer-Marquis, U.; Egli, S.; Niebergall, F.

The H1 experiment has now been successfully operating at the electron proton collider HERA at DESY for three years. During this time the computing environment has gradually shifted from a mainframe oriented environment to the distributed server/client Unix world. This transition is now almost complete. Computing needs are largely determined by the present amount of 1.5 TB of reconstructed data per year (1994), corresponding to 1.2 × 107 accepted events. All data are centrally available at DESY. In addition to data analysis, which is done in all collaborating institutes, most of the centrally organized Monte Carlo production is performed outside of DESY. New software tools to cope with offline computing needs include CENTIPEDE, a tool for the use of distributed batch and interactive resources for Monte Carlo production, and H1 UNIX, a software package for automatic updates of H1 software on all UNIX platforms.

Benchmarking information needs and use in the Tennessee public health community*

PubMed Central

Lee, Patricia; Giuse, Nunzia B.; Sathe, Nila A.

2003-01-01

Objective: The objective is to provide insight to understanding public health officials' needs and promote access to data repositories and communication tools. Methods: Survey questions were identified by a focus group with members drawn from the fields of librarianship, public health, and informatics. The resulting comprehensive information needs survey, organized in five distinct broad categories, was distributed to 775 Tennessee public health workers from ninety-five counties in 1999 as part of the National Library of Medicine–funded Partners in Information Access contract. Results: The assessment pooled responses from 571 public health workers (73% return rate) representing seventy-two of ninety-five counties (53.4% urban and 46.6% rural) about their information-seeking behaviors, frequency of resources used, computer skills, and level of Internet access. Sixty-four percent of urban and 43% of rural respondents had email access at work and more than 50% of both urban and rural respondents had email at home (N = 289). Approximately 70% of urban and 78% of rural public health officials never or seldom used or needed the Centers for Disease Control (CDC) Website. Frequency data pooled from eleven job categories representing a subgroup of 232 health care professionals showed 72% never or seldom used or needed MEDLINE. Electronic resources used daily or weekly were email, Internet search engines, internal databases and mailing lists, and the Tennessee Department of Health Website. Conclusions: While, due to the small sample size, data cannot be generalized to the larger population, a clear trend of significant barriers to computer and Internet access can be identified across the public health community. This contributes to an overall limited use of existing electronic resources that inhibits evidence-based practice. PMID:12883562

BigData and computing challenges in high energy and nuclear physics

NASA Astrophysics Data System (ADS)

Klimentov, A.; Grigorieva, M.; Kiryanov, A.; Zarochentsev, A.

2017-06-01

In this contribution we discuss the various aspects of the computing resource needs experiments in High Energy and Nuclear Physics, in particular at the Large Hadron Collider. This will evolve in the future when moving from LHC to HL-LHC in ten years from now, when the already exascale levels of data we are processing could increase by a further order of magnitude. The distributed computing environment has been a great success and the inclusion of new super-computing facilities, cloud computing and volunteering computing for the future is a big challenge, which we are successfully mastering with a considerable contribution from many super-computing centres around the world, academic and commercial cloud providers. We also discuss R&D computing projects started recently in National Research Center ``Kurchatov Institute''

Automating usability of ATLAS Distributed Computing resources

NASA Astrophysics Data System (ADS)

Tupputi, S. A.; Di Girolamo, A.; Kouba, T.; Schovancová, J.; Atlas Collaboration

2014-06-01

The automation of ATLAS Distributed Computing (ADC) operations is essential to reduce manpower costs and allow performance-enhancing actions, which improve the reliability of the system. In this perspective a crucial case is the automatic handling of outages of ATLAS computing sites storage resources, which are continuously exploited at the edge of their capabilities. It is challenging to adopt unambiguous decision criteria for storage resources of non-homogeneous types, sizes and roles. The recently developed Storage Area Automatic Blacklisting (SAAB) tool has provided a suitable solution, by employing an inference algorithm which processes history of storage monitoring tests outcome. SAAB accomplishes both the tasks of providing global monitoring as well as automatic operations on single sites. The implementation of the SAAB tool has been the first step in a comprehensive review of the storage areas monitoring and central management at all levels. Such review has involved the reordering and optimization of SAM tests deployment and the inclusion of SAAB results in the ATLAS Site Status Board with both dedicated metrics and views. The resulting structure allows monitoring the storage resources status with fine time-granularity and automatic actions to be taken in foreseen cases, like automatic outage handling and notifications to sites. Hence, the human actions are restricted to reporting and following up problems, where and when needed. In this work we show SAAB working principles and features. We present also the decrease of human interactions achieved within the ATLAS Computing Operation team. The automation results in a prompt reaction to failures, which leads to the optimization of resource exploitation.

Development of a SaaS application probe to the physical properties of the Earth's interior: An attempt at moving HPC to the cloud

NASA Astrophysics Data System (ADS)

Huang, Qian

2014-09-01

Scientific computing often requires the availability of a massive number of computers for performing large-scale simulations, and computing in mineral physics is no exception. In order to investigate physical properties of minerals at extreme conditions in computational mineral physics, parallel computing technology is used to speed up the performance by utilizing multiple computer resources to process a computational task simultaneously thereby greatly reducing computation time. Traditionally, parallel computing has been addressed by using High Performance Computing (HPC) solutions and installed facilities such as clusters and super computers. Today, it has been seen that there is a tremendous growth in cloud computing. Infrastructure as a Service (IaaS), the on-demand and pay-as-you-go model, creates a flexible and cost-effective mean to access computing resources. In this paper, a feasibility report of HPC on a cloud infrastructure is presented. It is found that current cloud services in IaaS layer still need to improve performance to be useful to research projects. On the other hand, Software as a Service (SaaS), another type of cloud computing, is introduced into an HPC system for computing in mineral physics, and an application of which is developed. In this paper, an overall description of this SaaS application is presented. This contribution can promote cloud application development in computational mineral physics, and cross-disciplinary studies.

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.

Program on application of communications satellites to educational development

NASA Technical Reports Server (NTRS)

Morgan, R. P.; Singh, J. P.

1971-01-01

Interdisciplinary research in needs analysis, communications technology studies, and systems synthesis is reported. Existing and planned educational telecommunications services are studied and library utilization of telecommunications is described. Preliminary estimates are presented of ranges of utilization of educational telecommunications services for 1975 and 1985; instructional and public television, computer-aided instruction, computing resources, and information resource sharing for various educational levels and purposes. Communications technology studies include transmission schemes for still-picture television, use of Gunn effect devices, and TV receiver front ends for direct satellite reception at 12 GHz. Two major studies in the systems synthesis project concern (1) organizational and administrative aspects of a large-scale instructional satellite system to be used with schools and (2) an analysis of future development of instructional television, with emphasis on the use of video tape recorders and cable television. A communications satellite system synthesis program developed for NASA is now operational on the university IBM 360-50 computer.

Cluster state generation in one-dimensional Kitaev honeycomb model via shortcut to adiabaticity

NASA Astrophysics Data System (ADS)

Kyaw, Thi Ha; Kwek, Leong-Chuan

2018-04-01

We propose a mean to obtain computationally useful resource states also known as cluster states, for measurement-based quantum computation, via transitionless quantum driving algorithm. The idea is to cool the system to its unique ground state and tune some control parameters to arrive at computationally useful resource state, which is in one of the degenerate ground states. Even though there is set of conserved quantities already present in the model Hamiltonian, which prevents the instantaneous state to go to any other eigenstate subspaces, one cannot quench the control parameters to get the desired state. In that case, the state will not evolve. With involvement of the shortcut Hamiltonian, we obtain cluster states in fast-forward manner. We elaborate our proposal in the one-dimensional Kitaev honeycomb model, and show that the auxiliary Hamiltonian needed for the counterdiabatic driving is of M-body interaction.

Building a Data Science capability for USGS water research and communication

NASA Astrophysics Data System (ADS)

Appling, A.; Read, E. K.

2015-12-01

Interpreting and communicating water issues in an era of exponentially increasing information requires a blend of domain expertise, computational proficiency, and communication skills. The USGS Office of Water Information has established a Data Science team to meet these needs, providing challenging careers for diverse domain scientists and innovators in the fields of information technology and data visualization. Here, we detail the experience of building a Data Science capability as a bridging element between traditional water resources analyses and modern computing tools and data management techniques. This approach includes four major components: 1) building reusable research tools, 2) documenting data-intensive research approaches in peer reviewed journals, 3) communicating complex water resources issues with interactive web visualizations, and 4) offering training programs for our peers in scientific computing. These components collectively improve the efficiency, transparency, and reproducibility of USGS data analyses and scientific workflows.

A regional land use survey based on remote sensing and other data: A report on a LANDSAT and computer mapping project, volume 2

NASA Technical Reports Server (NTRS)

Nez, G. (Principal Investigator); Mutter, D.

1977-01-01

The author has identified the following significant results. The project mapped land use/cover classifications from LANDSAT computer compatible tape data and combined those results with other multisource data via computer mapping/compositing techniques to analyze various land use planning/natural resource management problems. Data were analyzed on 1:24,000 scale maps at 1.1 acre resolution. LANDSAT analysis software and linkages with other computer mapping software were developed. Significant results were also achieved in training, communication, and identification of needs for developing the LANDSAT/computer mapping technologies into operational tools for use by decision makers.

[Earth and Space Sciences Project Services for NASA HPCC

NASA Technical Reports Server (NTRS)

Merkey, Phillip

2002-01-01

This grant supported the effort to characterize the problem domain of the Earth Science Technology Office's Computational Technologies Project, to engage the Beowulf Cluster Computing Community as well as the High Performance Computing Research Community so that we can predict the applicability of said technologies to the scientific community represented by the CT project and formulate long term strategies to provide the computational resources necessary to attain the anticipated scientific objectives of the CT project. Specifically, the goal of the evaluation effort is to use the information gathered over the course of the Round-3 investigations to quantify the trends in scientific expectations, the algorithmic requirements and capabilities of high-performance computers to satisfy this anticipated need.

Exploring the use of I/O nodes for computation in a MIMD multiprocessor

NASA Technical Reports Server (NTRS)

Kotz, David; Cai, Ting

1995-01-01

As parallel systems move into the production scientific-computing world, the emphasis will be on cost-effective solutions that provide high throughput for a mix of applications. Cost effective solutions demand that a system make effective use of all of its resources. Many MIMD multiprocessors today, however, distinguish between 'compute' and 'I/O' nodes, the latter having attached disks and being dedicated to running the file-system server. This static division of responsibilities simplifies system management but does not necessarily lead to the best performance in workloads that need a different balance of computation and I/O. Of course, computational processes sharing a node with a file-system service may receive less CPU time, network bandwidth, and memory bandwidth than they would on a computation-only node. In this paper we begin to examine this issue experimentally. We found that high performance I/O does not necessarily require substantial CPU time, leaving plenty of time for application computation. There were some complex file-system requests, however, which left little CPU time available to the application. (The impact on network and memory bandwidth still needs to be determined.) For applications (or users) that cannot tolerate an occasional interruption, we recommend that they continue to use only compute nodes. For tolerant applications needing more cycles than those provided by the compute nodes, we recommend that they take full advantage of both compute and I/O nodes for computation, and that operating systems should make this possible.

The prediction of satellite ephemeris errors as they result from surveillance system measurement errors

NASA Astrophysics Data System (ADS)

Simmons, B. E.

1981-08-01

This report derives equations predicting satellite ephemeris error as a function of measurement errors of space-surveillance sensors. These equations lend themselves to rapid computation with modest computer resources. They are applicable over prediction times such that measurement errors, rather than uncertainties of atmospheric drag and of Earth shape, dominate in producing ephemeris error. This report describes the specialization of these equations underlying the ANSER computer program, SEEM (Satellite Ephemeris Error Model). The intent is that this report be of utility to users of SEEM for interpretive purposes, and to computer programmers who may need a mathematical point of departure for limited generalization of SEEM.

Fermilab computing at the Intensity Frontier

DOE PAGES

Group, Craig; Fuess, S.; Gutsche, O.; ...

2015-12-23

The Intensity Frontier refers to a diverse set of particle physics experiments using high- intensity beams. In this paper I will focus the discussion on the computing requirements and solutions of a set of neutrino and muon experiments in progress or planned to take place at the Fermi National Accelerator Laboratory located near Chicago, Illinois. In addition, the experiments face unique challenges, but also have overlapping computational needs. In principle, by exploiting the commonality and utilizing centralized computing tools and resources, requirements can be satisfied efficiently and scientists of individual experiments can focus more on the science and less onmore » the development of tools and infrastructure.« less

Assessment of computational prediction of tail buffeting

NASA Technical Reports Server (NTRS)

Edwards, John W.

1990-01-01

Assessments of the viability of computational methods and the computer resource requirements for the prediction of tail buffeting are made. Issues involved in the use of Euler and Navier-Stokes equations in modeling vortex-dominated and buffet flows are discussed and the requirement for sufficient grid density to allow accurate, converged calculations is stressed. Areas in need of basic fluid dynamics research are highlighted: vorticity convection, vortex breakdown, dynamic turbulence modeling for free shear layers, unsteady flow separation for moderately swept, rounded leading-edge wings, vortex flows about wings at high subsonic speeds. An estimate of the computer run time for a buffeting response calculation for a full span F-15 aircraft indicates that an improvement in computer and/or algorithm efficiency of three orders of magnitude is needed to enable routine use of such methods. Attention is also drawn to significant uncertainties in the estimates, in particular with regard to nonlinearities contained within the modeling and the question of the repeatability or randomness of buffeting response.

The iPad and EFL Digital Literacy

NASA Astrophysics Data System (ADS)

Meurant, Robert C.

In future, the uses of English by non-native speakers will predominantly be online, using English language digital resources, and in computer-mediated communication with other non-native speakers of English. Thus for Korea to be competitive in the global economy, its EFL should develop L2 Digital Literacy in English. With its fast Internet connections, Korea is the most wired nation on Earth; but ICT facilities in educational institutions need reorganization. Opportunities for computer-mediated second language learning need to be increased, providing multimedia-capable, mobile web solutions that put the Internet into the hands of all students and teachers. Wi-Fi networked campuses allow any campus space to act as a wireless classroom. Every classroom should have a teacher's computer console. All students should be provided with adequate computing facilities, that are available anywhere, anytime. Ubiquitous computing has now become feasible by providing every student on enrollment with a tablet: a Wi-Fi+3G enabled Apple iPad.

CMS Distributed Computing Integration in the LHC sustained operations era

NASA Astrophysics Data System (ADS)

Grandi, C.; Bockelman, B.; Bonacorsi, D.; Fisk, I.; González Caballero, I.; Farina, F.; Hernández, J. M.; Padhi, S.; Sarkar, S.; Sciabà, A.; Sfiligoi, I.; Spiga, F.; Úbeda García, M.; Van Der Ster, D. C.; Zvada, M.

2011-12-01

After many years of preparation the CMS computing system has reached a situation where stability in operations limits the possibility to introduce innovative features. Nevertheless it is the same need of stability and smooth operations that requires the introduction of features that were considered not strategic in the previous phases. Examples are: adequate authorization to control and prioritize the access to storage and computing resources; improved monitoring to investigate problems and identify bottlenecks on the infrastructure; increased automation to reduce the manpower needed for operations; effective process to deploy in production new releases of the software tools. We present the work of the CMS Distributed Computing Integration Activity that is responsible for providing a liaison between the CMS distributed computing infrastructure and the software providers, both internal and external to CMS. In particular we describe the introduction of new middleware features during the last 18 months as well as the requirements to Grid and Cloud software developers for the future.

A hazy outlook for cloud computing.

PubMed

Perna, Gabriel

2012-01-01

Because of competing priorities as well as cost, security, and implementation concerns, cloud-based storage development has gotten off to a slow start in healthcare. CIOs, CTOs, and other healthcare IT leaders are adopting a variety of strategies in this area, based on their organizations' needs, resources, and priorities.

Individualized Healthcare Plans for the School Nurse

ERIC Educational Resources Information Center

American School Health Association (NJ3), 2005

2005-01-01

This resource sets the standard for school nurses concerning the formulation of individualized healthcare plans designed to fit the unique health needs of students. Eighteen chapters focus on special issues and school nursing concepts. Computer software, which accompanies the manual, assists in the development and creation of individualized…

Development of improved ambient computation methods in support of the National Parks Air Tour Management Act

DOT National Transportation Integrated Search

2008-09-01

Approximately 85 National Park units with commercial air tours will need Air Tour : Management Plans (ATMPs). The objective of an ATMP is to prevent or mitigate : significant adverse impacts to National Park resources. Noise impacts must be : charact...

Manufacturing Processes: New Methods for the "Materials Age." Resources in Technology.

ERIC Educational Resources Information Center

Technology Teacher, 1990

1990-01-01

To make the best use of new materials developed for everything from computers to artificial hearts to more fuel-efficient cars, improved materials syntheses and manufacturing processes are needed. This instructional module includes teacher materials, a student quiz, and possible student outcomes. (JOW)

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.

Squid - a simple bioinformatics grid.

PubMed

Carvalho, Paulo C; Glória, Rafael V; de Miranda, Antonio B; Degrave, Wim M

2005-08-03

BLAST is a widely used genetic research tool for analysis of similarity between nucleotide and protein sequences. This paper presents a software application entitled "Squid" that makes use of grid technology. The current version, as an example, is configured for BLAST applications, but adaptation for other computing intensive repetitive tasks can be easily accomplished in the open source version. This enables the allocation of remote resources to perform distributed computing, making large BLAST queries viable without the need of high-end computers. Most distributed computing / grid solutions have complex installation procedures requiring a computer specialist, or have limitations regarding operating systems. Squid is a multi-platform, open-source program designed to "keep things simple" while offering high-end computing power for large scale applications. Squid also has an efficient fault tolerance and crash recovery system against data loss, being able to re-route jobs upon node failure and recover even if the master machine fails. Our results show that a Squid application, working with N nodes and proper network resources, can process BLAST queries almost N times faster than if working with only one computer. Squid offers high-end computing, even for the non-specialist, and is freely available at the project web site. Its open-source and binary Windows distributions contain detailed instructions and a "plug-n-play" instalation containing a pre-configured example.

Controlling user access to electronic resources without password

DOEpatents

Smith, Fred Hewitt

2015-06-16

Described herein are devices and techniques for remotely controlling user access to a restricted computer resource. The process includes pre-determining an association of the restricted computer resource and computer-resource-proximal environmental information. Indicia of user-proximal environmental information are received from a user requesting access to the restricted computer resource. Received indicia of user-proximal environmental information are compared to associated computer-resource-proximal environmental information. User access to the restricted computer resource is selectively granted responsive to a favorable comparison in which the user-proximal environmental information is sufficiently similar to the computer-resource proximal environmental information. In at least some embodiments, the process further includes comparing user-supplied biometric measure and comparing it with a predetermined association of at least one biometric measure of an authorized user. Access to the restricted computer resource is granted in response to a favorable comparison.

Laboratory Computing Resource Center

Science.gov Websites

Systems Computing and Data Resources Purchasing Resources Future Plans For Users Getting Started Using LCRC Software Best Practices and Policies Getting Help Support Laboratory Computing Resource Center Laboratory Computing Resource Center Latest Announcements See All April 27, 2018, Announcements, John Low

United States Air Force Computer-Aided Acquisition and Logistics Support (CALS) Evolution of Computer Integrated Manufacturing (CIM) Technologies

DTIC Science & Technology

1988-11-01

Manufacturing System 22 4. Similar Parts Based Shape or Manufactuting Process 24 5. Projected Annual Unit Robot Sales and Installed Base Through 1992 30 6. U.S...effort needed to perform personnel, product design, marketing , and advertising, and finance tasks of the firm. Level III controls the resource...planning and accounting functions of the firm. Systems at this level support purchasing, accounts payable, accounts receivable, master scheduling and sales

The Cloud2SM Project

NASA Astrophysics Data System (ADS)

Crinière, Antoine; Dumoulin, Jean; Mevel, Laurent; Andrade-Barosso, Guillermo; Simonin, Matthieu

2015-04-01

From the past decades the monitoring of civil engineering structure became a major field of research and development process in the domains of modelling and integrated instrumentation. This increasing of interest can be attributed in part to the need of controlling the aging of such structures and on the other hand to the need to optimize maintenance costs. From this standpoint the project Cloud2SM (Cloud architecture design for Structural Monitoring with in-line Sensors and Models tasking), has been launched to develop a robust information system able to assess the long term monitoring of civil engineering structures as well as interfacing various sensors and data. The specificity of such architecture is to be based on the notion of data processing through physical or statistical models. Thus the data processing, whether material or mathematical, can be seen here as a resource of the main architecture. The project can be divided in various items: -The sensors and their measurement process: Those items provide data to the main architecture and can embed storage or computational resources. Dependent of onboard capacity and the amount of data generated it can be distinguished heavy and light sensors. - The storage resources: Based on the cloud concept this resource can store at least two types of data, raw data and processed ones. - The computational resources: This item includes embedded "pseudo real time" resources as the dedicated computer cluster or computational resources. - The models: Used for the conversion of raw data to meaningful data. Those types of resources inform the system of their needs they can be seen as independents blocks of the system. - The user interface: This item can be divided in various HMI to assess maintaining operation on the sensors or pop-up some information to the user. - The demonstrators: The structures themselves. This project follows previous research works initiated in the European project ISTIMES [1]. It includes the infrared thermal monitoring of civil engineering structures [2-3] and/or the vibration monitoring of such structures [4-5]. The chosen architecture is based on the OGC standard in order to ensure the interoperability between the various measurement systems. This concept is extended to the notion of physical models. The last but not the least main objective of this project is to explore the feasibility and the reliability to deploy mathematical models and process a large amount of data using the GPGPU capacity of a dedicated computational cluster, while studying OGC standardization to those technical concepts. References [1] M. Proto et al., « Transport Infrastructure surveillance and Monitoring by Electromagnetic Sensing: the ISTIMES project », Journal Sensors, Sensors 2010, 10(12), 10620-10639; doi:10.3390/s101210620, December 2010. [2] J. Dumoulin, A. Crinière, R. Averty ," Detection and thermal characterization of the inner structure of the "Musmeci" bridge deck by infrared thermography monitoring ",Journal of Geophysics and Engineering, Volume 10, Number 2, 17 pages ,November 2013, IOP Science, doi:10.1088/1742-2132/10/6/064003. [3] J Dumoulin and V Boucher; "Infrared thermography system for transport infrastructures survey with inline local atmospheric parameter measurements and offline model for radiation attenuation evaluations," J. Appl. Remote Sens., 8(1), 084978 (2014). doi:10.1117/1.JRS.8.084978. [4] V. Le Cam, M. Doehler, M. Le Pen, L. Mevel. "Embedded modal analysis algorithms on the smart wireless sensor platform PEGASE", In Proc. 9th International Workshop on Structural Health Monitoring, Stanford, CA, USA, 2013. [5] M. Zghal, L. Mevel, P. Del Moral, "Modal parameter estimation using interacting Kalman filter", Mechanical Systems and Signal Processing, 2014.

An efficient dynamic load balancing algorithm

NASA Astrophysics Data System (ADS)

Lagaros, Nikos D.

2014-01-01

In engineering problems, randomness and uncertainties are inherent. Robust design procedures, formulated in the framework of multi-objective optimization, have been proposed in order to take into account sources of randomness and uncertainty. These design procedures require orders of magnitude more computational effort than conventional analysis or optimum design processes since a very large number of finite element analyses is required to be dealt. It is therefore an imperative need to exploit the capabilities of computing resources in order to deal with this kind of problems. In particular, parallel computing can be implemented at the level of metaheuristic optimization, by exploiting the physical parallelization feature of the nondominated sorting evolution strategies method, as well as at the level of repeated structural analyses required for assessing the behavioural constraints and for calculating the objective functions. In this study an efficient dynamic load balancing algorithm for optimum exploitation of available computing resources is proposed and, without loss of generality, is applied for computing the desired Pareto front. In such problems the computation of the complete Pareto front with feasible designs only, constitutes a very challenging task. The proposed algorithm achieves linear speedup factors and almost 100% speedup factor values with reference to the sequential procedure.

JMS: An Open Source Workflow Management System and Web-Based Cluster Front-End for High Performance Computing.

PubMed

Brown, David K; Penkler, David L; Musyoka, Thommas M; Bishop, Özlem Tastan

2015-01-01

Complex computational pipelines are becoming a staple of modern scientific research. Often these pipelines are resource intensive and require days of computing time. In such cases, it makes sense to run them over high performance computing (HPC) clusters where they can take advantage of the aggregated resources of many powerful computers. In addition to this, researchers often want to integrate their workflows into their own web servers. In these cases, software is needed to manage the submission of jobs from the web interface to the cluster and then return the results once the job has finished executing. We have developed the Job Management System (JMS), a workflow management system and web interface for high performance computing (HPC). JMS provides users with a user-friendly web interface for creating complex workflows with multiple stages. It integrates this workflow functionality with the resource manager, a tool that is used to control and manage batch jobs on HPC clusters. As such, JMS combines workflow management functionality with cluster administration functionality. In addition, JMS provides developer tools including a code editor and the ability to version tools and scripts. JMS can be used by researchers from any field to build and run complex computational pipelines and provides functionality to include these pipelines in external interfaces. JMS is currently being used to house a number of bioinformatics pipelines at the Research Unit in Bioinformatics (RUBi) at Rhodes University. JMS is an open-source project and is freely available at https://github.com/RUBi-ZA/JMS.

JMS: An Open Source Workflow Management System and Web-Based Cluster Front-End for High Performance Computing

PubMed Central

Brown, David K.; Penkler, David L.; Musyoka, Thommas M.; Bishop, Özlem Tastan

2015-01-01

Complex computational pipelines are becoming a staple of modern scientific research. Often these pipelines are resource intensive and require days of computing time. In such cases, it makes sense to run them over high performance computing (HPC) clusters where they can take advantage of the aggregated resources of many powerful computers. In addition to this, researchers often want to integrate their workflows into their own web servers. In these cases, software is needed to manage the submission of jobs from the web interface to the cluster and then return the results once the job has finished executing. We have developed the Job Management System (JMS), a workflow management system and web interface for high performance computing (HPC). JMS provides users with a user-friendly web interface for creating complex workflows with multiple stages. It integrates this workflow functionality with the resource manager, a tool that is used to control and manage batch jobs on HPC clusters. As such, JMS combines workflow management functionality with cluster administration functionality. In addition, JMS provides developer tools including a code editor and the ability to version tools and scripts. JMS can be used by researchers from any field to build and run complex computational pipelines and provides functionality to include these pipelines in external interfaces. JMS is currently being used to house a number of bioinformatics pipelines at the Research Unit in Bioinformatics (RUBi) at Rhodes University. JMS is an open-source project and is freely available at https://github.com/RUBi-ZA/JMS. PMID:26280450

Extending the farm on external sites: the INFN Tier-1 experience

NASA Astrophysics Data System (ADS)

Boccali, T.; Cavalli, A.; Chiarelli, L.; Chierici, A.; Cesini, D.; Ciaschini, V.; Dal Pra, S.; dell'Agnello, L.; De Girolamo, D.; Falabella, A.; Fattibene, E.; Maron, G.; Prosperini, A.; Sapunenko, V.; Virgilio, S.; Zani, S.

2017-10-01

The Tier-1 at CNAF is the main INFN computing facility offering computing and storage resources to more than 30 different scientific collaborations including the 4 experiments at the LHC. It is also foreseen a huge increase in computing needs in the following years mainly driven by the experiments at the LHC (especially starting with the run 3 from 2021) but also by other upcoming experiments such as CTA[1] While we are considering the upgrade of the infrastructure of our data center, we are also evaluating the possibility of using CPU resources available in other data centres or even leased from commercial cloud providers. Hence, at INFN Tier-1, besides participating to the EU project HNSciCloud, we have also pledged a small amount of computing resources (˜ 2000 cores) located at the Bari ReCaS[2] for the WLCG experiments for 2016 and we are testing the use of resources provided by a commercial cloud provider. While the Bari ReCaS data center is directly connected to the GARR network[3] with the obvious advantage of a low latency and high bandwidth connection, in the case of the commercial provider we rely only on the General Purpose Network. In this paper we describe the set-up phase and the first results of these installations started in the last quarter of 2015, focusing on the issues that we have had to cope with and discussing the measured results in terms of efficiency.

Drug information resources used by nurse practitioners and collaborating physicians at the point of care in Nova Scotia, Canada: a survey and review of the literature

PubMed Central

Murphy, Andrea L; Fleming, Mark; Martin-Misener, Ruth; Sketris, Ingrid S; MacCara, Mary; Gass, David

2006-01-01

Background Keeping current with drug therapy information is challenging for health care practitioners. Technologies are often implemented to facilitate access to current and credible drug information sources. In the Canadian province of Nova Scotia, legislation was passed in 2002 to allow nurse practitioners (NPs) to practice collaboratively with physician partners. The purpose of this study was to determine the current utilization patterns of information technologies by these groups of practitioners. Methods Nurse practitioners and their collaborating physician partners in Nova Scotia were sent a survey in February 2005 to determine the frequency of use, usefulness, accessibility, credibility, and current/timeliness of personal digital assistant (PDA), computer, and print drug information resources. Two surveys were developed (one for PDA users and one for computer users) and revised based on a literature search, stakeholder consultation, and pilot-testing results. A second distribution to nonresponders occurred two weeks following the first. Data were entered and analysed with SPSS. Results Twenty-seven (14 NPs and 13 physicians) of 36 (75%) recipients responded. 22% (6) returned personal digital assistant (PDA) surveys. Respondents reported print, health professionals, and online/electronic resources as the most to least preferred means to access drug information, respectively. 37% and 35% of respondents reported using "both print and electronic but print more than electronic" and "print only", respectively, to search monograph-related drug information queries whereas 4% reported using "PDA only". Analysis of respondent ratings for all resources in the categories print, health professionals and other, and online/electronic resources, indicated that the Compendium of Pharmaceuticals and Specialties and pharmacists ranked highly for frequency of use, usefulness, accessibility, credibility, and current/timeliness by both groups of practitioners. Respondents' preferences and resource ratings were consistent with self-reported methods for conducting drug information queries. Few differences existed between NP and physician rankings of resources. Conclusion The use of computers and PDAs remains limited, which is also consistent with preferred and frequent use of print resources. Education for these practitioners regarding available electronic drug information resources may facilitate future computer and PDA use. Further research is needed to determine methods to increase computer and PDA use and whether these technologies affect prescribing and patient outcomes. PMID:16822323

Research on elastic resource management for multi-queue under cloud computing environment

NASA Astrophysics Data System (ADS)

CHENG, Zhenjing; LI, Haibo; HUANG, Qiulan; Cheng, Yaodong; CHEN, Gang

2017-10-01

As a new approach to manage computing resource, virtualization technology is more and more widely applied in the high-energy physics field. A virtual computing cluster based on Openstack was built at IHEP, using HTCondor as the job queue management system. In a traditional static cluster, a fixed number of virtual machines are pre-allocated to the job queue of different experiments. However this method cannot be well adapted to the volatility of computing resource requirements. To solve this problem, an elastic computing resource management system under cloud computing environment has been designed. This system performs unified management of virtual computing nodes on the basis of job queue in HTCondor based on dual resource thresholds as well as the quota service. A two-stage pool is designed to improve the efficiency of resource pool expansion. This paper will present several use cases of the elastic resource management system in IHEPCloud. The practical run shows virtual computing resource dynamically expanded or shrunk while computing requirements change. Additionally, the CPU utilization ratio of computing resource was significantly increased when compared with traditional resource management. The system also has good performance when there are multiple condor schedulers and multiple job queues.

From Answer Garden to Answer Jungle.

ERIC Educational Resources Information Center

Dron, Jon; Mitchell, Richard; Siviter, Phil

1998-01-01

The use of Usenet newsgroups in a computing and information systems classroom at the University of Brighton showed how Internet-based learning systems can encourage rapid evolution so that resources adapt to learners' needs. Although not always used as intended, and including off-topic distractions, newsgroups did accommodate learning styles and…

A computerized system for portrayal of landscape alterations

Treesearch

A. E. Stevenson; J. A. Conley; J. B. Carey

1979-01-01

The growing public awareness of and participation in the visual resource decision process has stimulated interest to find improved means of accurately and realistically displaying proposed alterations. The traditional artist renderings often lack the accuracy and objectivity needed for critical decisions. One approach, using computer graphics, led to the MOSAIC system...

A Rich Metadata Filesystem for Scientific Data

ERIC Educational Resources Information Center

Bui, Hoang

2012-01-01

As scientific research becomes more data intensive, there is an increasing need for scalable, reliable, and high performance storage systems. Such data repositories must provide both data archival services and rich metadata, and cleanly integrate with large scale computing resources. ROARS is a hybrid approach to distributed storage that provides…

Exploring Evolutionary Patterns in Genetic Sequence: A Computer Exercise

ERIC Educational Resources Information Center

Shumate, Alice M.; Windsor, Aaron J.

2010-01-01

The increase in publications presenting molecular evolutionary analyses and the availability of comparative sequence data through resources such as NCBI's GenBank underscore the necessity of providing undergraduates with hands-on sequence analysis skills in an evolutionary context. This need is particularly acute given that students have been…

Assessing Teaching Skills with a Mobile Simulation

ERIC Educational Resources Information Center

Gibson, David

2013-01-01

Because mobile technologies are overtaking personal computers as the primary tools of Internet access, and cloud-based resources are fundamentally transforming the world's knowledge, new forms of teaching and assessment are required to foster 21st century literacies, including those needed by K-12 teachers. A key feature of mobile technology…

The ICCB Computer Based Facilities Inventory & Utilization Management Information Subsystem.

ERIC Educational Resources Information Center

Lach, Ivan J.

The Illinois Community College Board (ICCB) Facilities Inventory and Utilization subsystem, a part of the ICCB management information system, was designed to provide decision makers with needed information to better manage the facility resources of Illinois community colleges. This subsystem, dependent upon facilities inventory data and course…

Computing at DESY — current setup, trends and strategic directions

NASA Astrophysics Data System (ADS)

Ernst, Michael

1998-05-01

Since the HERA experiments H1 and ZEUS started data taking in '92, the computing environment at DESY has changed dramatically. Running a mainframe centred computing for more than 20 years, DESY switched to a heterogeneous, fully distributed computing environment within only about two years in almost every corner where computing has its applications. The computing strategy was highly influenced by the needs of the user community. The collaborations are usually limited by current technology and their ever increasing demands is the driving force for central computing to always move close to the technology edge. While DESY's central computing has a multidecade experience in running Central Data Recording/Central Data Processing for HEP experiments, the most challenging task today is to provide for clear and homogeneous concepts in the desktop area. Given that lowest level commodity hardware draws more and more attention, combined with the financial constraints we are facing already today, we quickly need concepts for integrated support of a versatile device which has the potential to move into basically any computing area in HEP. Though commercial solutions, especially addressing the PC management/support issues, are expected to come to market in the next 2-3 years, we need to provide for suitable solutions now. Buying PC's at DESY currently at a rate of about 30/month will otherwise absorb any available manpower in central computing and still will leave hundreds of unhappy people alone. Though certainly not the only region, the desktop issue is one of the most important one where we need HEP-wide collaboration to a large extent, and right now. Taking into account that there is traditionally no room for R&D at DESY, collaboration, meaning sharing experience and development resources within the HEP community, is a predominant factor for us.

Issues in undergraduate education in computational science and high performance computing

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

Marchioro, T.L. II; Martin, D.

1994-12-31

The ever increasing need for mathematical and computational literacy within their society and among members of the work force has generated enormous pressure to revise and improve the teaching of related subjects throughout the curriculum, particularly at the undergraduate level. The Calculus Reform movement is perhaps the best known example of an organized initiative in this regard. The UCES (Undergraduate Computational Engineering and Science) project, an effort funded by the Department of Energy and administered through the Ames Laboratory, is sponsoring an informal and open discussion of the salient issues confronting efforts to improve and expand the teaching of computationalmore » science as a problem oriented, interdisciplinary approach to scientific investigation. Although the format is open, the authors hope to consider pertinent questions such as: (1) How can faculty and research scientists obtain the recognition necessary to further excellence in teaching the mathematical and computational sciences? (2) What sort of educational resources--both hardware and software--are needed to teach computational science at the undergraduate level? Are traditional procedural languages sufficient? Are PCs enough? Are massively parallel platforms needed? (3) How can electronic educational materials be distributed in an efficient way? Can they be made interactive in nature? How should such materials be tied to the World Wide Web and the growing ``Information Superhighway``?« less

A tool for modeling concurrent real-time computation

NASA Technical Reports Server (NTRS)

Sharma, D. D.; Huang, Shie-Rei; Bhatt, Rahul; Sridharan, N. S.

1990-01-01

Real-time computation is a significant area of research in general, and in AI in particular. The complexity of practical real-time problems demands use of knowledge-based problem solving techniques while satisfying real-time performance constraints. Since the demands of a complex real-time problem cannot be predicted (owing to the dynamic nature of the environment) powerful dynamic resource control techniques are needed to monitor and control the performance. A real-time computation model for a real-time tool, an implementation of the QP-Net simulator on a Symbolics machine, and an implementation on a Butterfly multiprocessor machine are briefly described.

GapMap: Enabling Comprehensive Autism Resource Epidemiology

PubMed Central

Albert, Nikhila; Schwartz, Jessey; Du, Michael

2017-01-01

Background For individuals with autism spectrum disorder (ASD), finding resources can be a lengthy and difficult process. The difficulty in obtaining global, fine-grained autism epidemiological data hinders researchers from quickly and efficiently studying large-scale correlations among ASD, environmental factors, and geographical and cultural factors. Objective The objective of this study was to define resource load and resource availability for families affected by autism and subsequently create a platform to enable a more accurate representation of prevalence rates and resource epidemiology. Methods We created a mobile application, GapMap, to collect locational, diagnostic, and resource use information from individuals with autism to compute accurate prevalence rates and better understand autism resource epidemiology. GapMap is hosted on AWS S3, running on a React and Redux front-end framework. The backend framework is comprised of an AWS API Gateway and Lambda Function setup, with secure and scalable end points for retrieving prevalence and resource data, and for submitting participant data. Measures of autism resource scarcity, including resource load, resource availability, and resource gaps were defined and preliminarily computed using simulated or scraped data. Results The average distance from an individual in the United States to the nearest diagnostic center is approximately 182 km (50 miles), with a standard deviation of 235 km (146 miles). The average distance from an individual with ASD to the nearest diagnostic center, however, is only 32 km (20 miles), suggesting that individuals who live closer to diagnostic services are more likely to be diagnosed. Conclusions This study confirmed that individuals closer to diagnostic services are more likely to be diagnosed and proposes GapMap, a means to measure and enable the alleviation of increasingly overburdened diagnostic centers and resource-poor areas where parents are unable to diagnose their children as quickly and easily as needed. GapMap will collect information that will provide more accurate data for computing resource loads and availability, uncovering the impact of resource epidemiology on age and likelihood of diagnosis, and gathering localized autism prevalence rates. PMID:28473303

GapMap: Enabling Comprehensive Autism Resource Epidemiology.

PubMed

Albert, Nikhila; Daniels, Jena; Schwartz, Jessey; Du, Michael; Wall, Dennis P

2017-05-04

For individuals with autism spectrum disorder (ASD), finding resources can be a lengthy and difficult process. The difficulty in obtaining global, fine-grained autism epidemiological data hinders researchers from quickly and efficiently studying large-scale correlations among ASD, environmental factors, and geographical and cultural factors. The objective of this study was to define resource load and resource availability for families affected by autism and subsequently create a platform to enable a more accurate representation of prevalence rates and resource epidemiology. We created a mobile application, GapMap, to collect locational, diagnostic, and resource use information from individuals with autism to compute accurate prevalence rates and better understand autism resource epidemiology. GapMap is hosted on AWS S3, running on a React and Redux front-end framework. The backend framework is comprised of an AWS API Gateway and Lambda Function setup, with secure and scalable end points for retrieving prevalence and resource data, and for submitting participant data. Measures of autism resource scarcity, including resource load, resource availability, and resource gaps were defined and preliminarily computed using simulated or scraped data. The average distance from an individual in the United States to the nearest diagnostic center is approximately 182 km (50 miles), with a standard deviation of 235 km (146 miles). The average distance from an individual with ASD to the nearest diagnostic center, however, is only 32 km (20 miles), suggesting that individuals who live closer to diagnostic services are more likely to be diagnosed. This study confirmed that individuals closer to diagnostic services are more likely to be diagnosed and proposes GapMap, a means to measure and enable the alleviation of increasingly overburdened diagnostic centers and resource-poor areas where parents are unable to diagnose their children as quickly and easily as needed. GapMap will collect information that will provide more accurate data for computing resource loads and availability, uncovering the impact of resource epidemiology on age and likelihood of diagnosis, and gathering localized autism prevalence rates. ©Nikhila Albert, Jena Daniels, Jessey Schwartz, Michael Du, Dennis P Wall. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 04.05.2017.

Survey on Security Issues in Cloud Computing and Associated Mitigation Techniques

NASA Astrophysics Data System (ADS)

Bhadauria, Rohit; Sanyal, Sugata

2012-06-01

Cloud Computing holds the potential to eliminate the requirements for setting up of high-cost computing infrastructure for IT-based solutions and services that the industry uses. It promises to provide a flexible IT architecture, accessible through internet for lightweight portable devices. This would allow multi-fold increase in the capacity or capabilities of the existing and new software. In a cloud computing environment, the entire data reside over a set of networked resources, enabling the data to be accessed through virtual machines. Since these data-centers may lie in any corner of the world beyond the reach and control of users, there are multifarious security and privacy challenges that need to be understood and taken care of. Also, one can never deny the possibility of a server breakdown that has been witnessed, rather quite often in the recent times. There are various issues that need to be dealt with respect to security and privacy in a cloud computing scenario. This extensive survey paper aims to elaborate and analyze the numerous unresolved issues threatening the cloud computing adoption and diffusion affecting the various stake-holders linked to it.

Cloud Computing for radiologists.

PubMed

Kharat, Amit T; Safvi, Amjad; Thind, Ss; Singh, Amarjit

2012-07-01

Cloud computing is a concept wherein a computer grid is created using the Internet with the sole purpose of utilizing shared resources such as computer software, hardware, on a pay-per-use model. Using Cloud computing, radiology users can efficiently manage multimodality imaging units by using the latest software and hardware without paying huge upfront costs. Cloud computing systems usually work on public, private, hybrid, or community models. Using the various components of a Cloud, such as applications, client, infrastructure, storage, services, and processing power, Cloud computing can help imaging units rapidly scale and descale operations and avoid huge spending on maintenance of costly applications and storage. Cloud computing allows flexibility in imaging. It sets free radiology from the confines of a hospital and creates a virtual mobile office. The downsides to Cloud computing involve security and privacy issues which need to be addressed to ensure the success of Cloud computing in the future.

Cloud Computing for radiologists

PubMed Central

Kharat, Amit T; Safvi, Amjad; Thind, SS; Singh, Amarjit

2012-01-01

Cloud computing is a concept wherein a computer grid is created using the Internet with the sole purpose of utilizing shared resources such as computer software, hardware, on a pay-per-use model. Using Cloud computing, radiology users can efficiently manage multimodality imaging units by using the latest software and hardware without paying huge upfront costs. Cloud computing systems usually work on public, private, hybrid, or community models. Using the various components of a Cloud, such as applications, client, infrastructure, storage, services, and processing power, Cloud computing can help imaging units rapidly scale and descale operations and avoid huge spending on maintenance of costly applications and storage. Cloud computing allows flexibility in imaging. It sets free radiology from the confines of a hospital and creates a virtual mobile office. The downsides to Cloud computing involve security and privacy issues which need to be addressed to ensure the success of Cloud computing in the future. PMID:23599560

BioQueue: a novel pipeline framework to accelerate bioinformatics analysis.

PubMed

Yao, Li; Wang, Heming; Song, Yuanyuan; Sui, Guangchao

2017-10-15

With the rapid development of Next-Generation Sequencing, a large amount of data is now available for bioinformatics research. Meanwhile, the presence of many pipeline frameworks makes it possible to analyse these data. However, these tools concentrate mainly on their syntax and design paradigms, and dispatch jobs based on users' experience about the resources needed by the execution of a certain step in a protocol. As a result, it is difficult for these tools to maximize the potential of computing resources, and avoid errors caused by overload, such as memory overflow. Here, we have developed BioQueue, a web-based framework that contains a checkpoint before each step to automatically estimate the system resources (CPU, memory and disk) needed by the step and then dispatch jobs accordingly. BioQueue possesses a shell command-like syntax instead of implementing a new script language, which means most biologists without computer programming background can access the efficient queue system with ease. BioQueue is freely available at https://github.com/liyao001/BioQueue. The extensive documentation can be found at http://bioqueue.readthedocs.io. li_yao@outlook.com or gcsui@nefu.edu.cn. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Tools for Analyzing Computing Resource Management Strategies and Algorithms for SDR Clouds

NASA Astrophysics Data System (ADS)

Marojevic, Vuk; Gomez-Miguelez, Ismael; Gelonch, Antoni

2012-09-01

Software defined radio (SDR) clouds centralize the computing resources of base stations. The computing resource pool is shared between radio operators and dynamically loads and unloads digital signal processing chains for providing wireless communications services on demand. Each new user session request particularly requires the allocation of computing resources for executing the corresponding SDR transceivers. The huge amount of computing resources of SDR cloud data centers and the numerous session requests at certain hours of a day require an efficient computing resource management. We propose a hierarchical approach, where the data center is divided in clusters that are managed in a distributed way. This paper presents a set of computing resource management tools for analyzing computing resource management strategies and algorithms for SDR clouds. We use the tools for evaluating a different strategies and algorithms. The results show that more sophisticated algorithms can achieve higher resource occupations and that a tradeoff exists between cluster size and algorithm complexity.

Are Cloud Environments Ready for Scientific Applications?

NASA Astrophysics Data System (ADS)

Mehrotra, P.; Shackleford, K.

2011-12-01

Cloud computing environments are becoming widely available both in the commercial and government sectors. They provide flexibility to rapidly provision resources in order to meet dynamic and changing computational needs without the customers incurring capital expenses and/or requiring technical expertise. Clouds also provide reliable access to resources even though the end-user may not have in-house expertise for acquiring or operating such resources. Consolidation and pooling in a cloud environment allow organizations to achieve economies of scale in provisioning or procuring computing resources and services. Because of these and other benefits, many businesses and organizations are migrating their business applications (e.g., websites, social media, and business processes) to cloud environments-evidenced by the commercial success of offerings such as the Amazon EC2. In this paper, we focus on the feasibility of utilizing cloud environments for scientific workloads and workflows particularly of interest to NASA scientists and engineers. There is a wide spectrum of such technical computations. These applications range from small workstation-level computations to mid-range computing requiring small clusters to high-performance simulations requiring supercomputing systems with high bandwidth/low latency interconnects. Data-centric applications manage and manipulate large data sets such as satellite observational data and/or data previously produced by high-fidelity modeling and simulation computations. Most of the applications are run in batch mode with static resource requirements. However, there do exist situations that have dynamic demands, particularly ones with public-facing interfaces providing information to the general public, collaborators and partners, as well as to internal NASA users. In the last few months we have been studying the suitability of cloud environments for NASA's technical and scientific workloads. We have ported several applications to multiple cloud environments including NASA's Nebula environment, Amazon's EC2, Magellan at NERSC, and SGI's Cyclone system. We critically examined the performance of the applications on these systems. We also collected information on the usability of these cloud environments. In this talk we will present the results of our study focusing on the efficacy of using clouds for NASA's scientific applications.

Satellites for U.S. education - Needs, opportunities and systems.

NASA Technical Reports Server (NTRS)

Morgan, R. P.; Singh, J. P.; Anderson, B. D.; Greenberg, E.

1972-01-01

This paper presents results of a continuing interdisciplinary study of the potential applications of Fixed- and Broadcast-Satellites for educational information transfer in the United States for the period 1975-1985. The status of U.S. education is examined and needs, trends and issues are discussed. The existing educational telecommunications infrastructure is examined and opportunities for satellite services are defined. Potential uses include networking of educational institutions and service centers for delivery of public and instructional television, computer-aided instruction, computing and information resources to regions and groups not now adequately served. Systems alternatives and some of the organizational and economic issues inherent in the deployment of an educational satellite system are discussed.-

Introduction to the LaRC central scientific computing complex

NASA Technical Reports Server (NTRS)

Shoosmith, John N.

1993-01-01

The computers and associated equipment that make up the Central Scientific Computing Complex of the Langley Research Center are briefly described. The electronic networks that provide access to the various components of the complex and a number of areas that can be used by Langley and contractors staff for special applications (scientific visualization, image processing, software engineering, and grid generation) are also described. Flight simulation facilities that use the central computers are described. Management of the complex, procedures for its use, and available services and resources are discussed. This document is intended for new users of the complex, for current users who wish to keep appraised of changes, and for visitors who need to understand the role of central scientific computers at Langley.

Radiotherapy Monte Carlo simulation using cloud computing technology.

PubMed

Poole, C M; Cornelius, I; Trapp, J V; Langton, C M

2012-12-01

Cloud computing allows for vast computational resources to be leveraged quickly and easily in bursts as and when required. Here we describe a technique that allows for Monte Carlo radiotherapy dose calculations to be performed using GEANT4 and executed in the cloud, with relative simulation cost and completion time evaluated as a function of machine count. As expected, simulation completion time decreases as 1/n for n parallel machines, and relative simulation cost is found to be optimal where n is a factor of the total simulation time in hours. Using the technique, we demonstrate the potential usefulness of cloud computing as a solution for rapid Monte Carlo simulation for radiotherapy dose calculation without the need for dedicated local computer hardware as a proof of principal.

A prototype expert/information system for examining environmental risks of KSC activities

NASA Technical Reports Server (NTRS)

Engel, Bernard A.

1993-01-01

Protection of the environment and natural resources at the Kennedy Space Center (KSC) is of great concern. An expert/information system to replace the paper-based KSC Environmental Checklist was developed. The computer-based system requests information only as a required and supplies assistance as needed. The most comprehensive portion of the system provides information about endangered species habitat at KSC. This module uses geographic information system (GIS) data and tools, expert rules, color graphics, computer-based video, and hypertext to provide information.

Optimization of coupled systems: A critical overview of approaches

NASA Technical Reports Server (NTRS)

Balling, R. J.; Sobieszczanski-Sobieski, J.

1994-01-01

A unified overview is given of problem formulation approaches for the optimization of multidisciplinary coupled systems. The overview includes six fundamental approaches upon which a large number of variations may be made. Consistent approach names and a compact approach notation are given. The approaches are formulated to apply to general nonhierarchic systems. The approaches are compared both from a computational viewpoint and a managerial viewpoint. Opportunities for parallelism of both computation and manpower resources are discussed. Recommendations regarding the need for future research are advanced.

The Future is Hera: Analyzing Astronomical Data Over the Internet

NASA Astrophysics Data System (ADS)

Valencic, Lynne A.; Snowden, S.; Chai, P.; Shafer, R.

2009-01-01

Hera is the new data processing facility provided by the HEASARC at the NASA Goddard Space Flight Center for analyzing astronomical data. Hera provides all the preinstalled software packages, local disk space, and computing resources needed to do general processing of FITS format data files residing on the user's local computer, and to do advanced research using the publicly available data from High Energy Astrophysics missions. Qualified students, educators, and researchers may freely use the Hera services over the internet for research and educational purposes.

In-situ resource utilization for the human exploration of Mars : a Bayesian approach to valuation of precursor missions

NASA Technical Reports Server (NTRS)

Smith, Jeffrey H.

2006-01-01

The need for sufficient quantities of oxygen, water, and fuel resources to support a crew on the surface of Mars presents a critical logistical issue of whether to transport such resources from Earth or manufacture them on Mars. An approach based on the classical Wildcat Drilling Problem of Bayesian decision theory was applied to the problem of finding water in order to compute the expected value of precursor mission sample information. An implicit (required) probability of finding water on Mars was derived from the value of sample information using the expected mass savings of alternative precursor missions.

Pharmacist Computer Skills and Needs Assessment Survey

PubMed Central

Jewesson, Peter J

2004-01-01

Background To use technology effectively for the advancement of patient care, pharmacists must possess a variety of computer skills. We recently introduced a novel applied informatics program in this Canadian hospital clinical service unit to enhance the informatics skills of our members. Objective This study was conducted to gain a better understanding of the baseline computer skills and needs of our hospital pharmacists immediately prior to the implementation of an applied informatics program. Methods In May 2001, an 84-question written survey was distributed by mail to 106 practicing hospital pharmacists in our multi-site, 1500-bed, acute-adult-tertiary care Canadian teaching hospital in Vancouver, British Columbia. Results Fifty-eight surveys (55% of total) were returned within the two-week study period. The survey responses reflected the opinions of licensed BSc and PharmD hospital pharmacists with a broad range of pharmacy practice experience. Most respondents had home access to personal computers, and regularly used computers in the work environment for drug distribution, information management, and communication purposes. Few respondents reported experience with handheld computers. Software use experience varied according to application. Although patient-care information software and e-mail were commonly used, experience with spreadsheet, statistical, and presentation software was negligible. The respondents were familiar with Internet search engines, and these were reported to be the most common method of seeking clinical information online. Although many respondents rated themselves as being generally computer literate and not particularly anxious about using computers, the majority believed they required more training to reach their desired level of computer literacy. Lack of familiarity with computer-related terms was prevalent. Self-reported basic computer skill was typically at a moderate level, and varied depending on the task. Specifically, respondents rated their ability to manipulate files, use software help features, and install software as low, but rated their ability to access and navigate the Internet as high. Respondents were generally aware of what online resources were available to them and Clinical Pharmacology was the most commonly employed reference. In terms of anticipated needs, most pharmacists believed they needed to upgrade their computer skills. Medical database and Internet searching skills were identified as those in greatest need of improvement. Conclusions Most pharmacists believed they needed to upgrade their computer skills. Medical database and Internet searching skills were identified as those in greatest need of improvement for the purposes of improving practice effectiveness. PMID:15111277

A Review Study on Cloud Computing Issues

NASA Astrophysics Data System (ADS)

Kanaan Kadhim, Qusay; Yusof, Robiah; Sadeq Mahdi, Hamid; Al-shami, Sayed Samer Ali; Rahayu Selamat, Siti

2018-05-01

Cloud computing is the most promising current implementation of utility computing in the business world, because it provides some key features over classic utility computing, such as elasticity to allow clients dynamically scale-up and scale-down the resources in execution time. Nevertheless, cloud computing is still in its premature stage and experiences lack of standardization. The security issues are the main challenges to cloud computing adoption. Thus, critical industries such as government organizations (ministries) are reluctant to trust cloud computing due to the fear of losing their sensitive data, as it resides on the cloud with no knowledge of data location and lack of transparency of Cloud Service Providers (CSPs) mechanisms used to secure their data and applications which have created a barrier against adopting this agile computing paradigm. This study aims to review and classify the issues that surround the implementation of cloud computing which a hot area that needs to be addressed by future research.

ASME V\\&V challenge problem: Surrogate-based V&V

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

Beghini, Lauren L.; Hough, Patricia D.

2015-12-18

The process of verification and validation can be resource intensive. From the computational model perspective, the resource demand typically arises from long simulation run times on multiple cores coupled with the need to characterize and propagate uncertainties. In addition, predictive computations performed for safety and reliability analyses have similar resource requirements. For this reason, there is a tradeoff between the time required to complete the requisite studies and the fidelity or accuracy of the results that can be obtained. At a high level, our approach is cast within a validation hierarchy that provides a framework in which we perform sensitivitymore » analysis, model calibration, model validation, and prediction. The evidence gathered as part of these activities is mapped into the Predictive Capability Maturity Model to assess credibility of the model used for the reliability predictions. With regard to specific technical aspects of our analysis, we employ surrogate-based methods, primarily based on polynomial chaos expansions and Gaussian processes, for model calibration, sensitivity analysis, and uncertainty quantification in order to reduce the number of simulations that must be done. The goal is to tip the tradeoff balance to improving accuracy without increasing the computational demands.« less

Mouse Genome Informatics (MGI) Resource: Genetic, Genomic, and Biological Knowledgebase for the Laboratory Mouse.

PubMed

Eppig, Janan T

2017-07-01

The Mouse Genome Informatics (MGI) Resource supports basic, translational, and computational research by providing high-quality, integrated data on the genetics, genomics, and biology of the laboratory mouse. MGI serves a strategic role for the scientific community in facilitating biomedical, experimental, and computational studies investigating the genetics and processes of diseases and enabling the development and testing of new disease models and therapeutic interventions. This review describes the nexus of the body of growing genetic and biological data and the advances in computer technology in the late 1980s, including the World Wide Web, that together launched the beginnings of MGI. MGI develops and maintains a gold-standard resource that reflects the current state of knowledge, provides semantic and contextual data integration that fosters hypothesis testing, continually develops new and improved tools for searching and analysis, and partners with the scientific community to assure research data needs are met. Here we describe one slice of MGI relating to the development of community-wide large-scale mutagenesis and phenotyping projects and introduce ways to access and use these MGI data. References and links to additional MGI aspects are provided. © The Author 2017. Published by Oxford University Press.

Mouse Genome Informatics (MGI) Resource: Genetic, Genomic, and Biological Knowledgebase for the Laboratory Mouse

PubMed Central

Eppig, Janan T.

2017-01-01

Abstract The Mouse Genome Informatics (MGI) Resource supports basic, translational, and computational research by providing high-quality, integrated data on the genetics, genomics, and biology of the laboratory mouse. MGI serves a strategic role for the scientific community in facilitating biomedical, experimental, and computational studies investigating the genetics and processes of diseases and enabling the development and testing of new disease models and therapeutic interventions. This review describes the nexus of the body of growing genetic and biological data and the advances in computer technology in the late 1980s, including the World Wide Web, that together launched the beginnings of MGI. MGI develops and maintains a gold-standard resource that reflects the current state of knowledge, provides semantic and contextual data integration that fosters hypothesis testing, continually develops new and improved tools for searching and analysis, and partners with the scientific community to assure research data needs are met. Here we describe one slice of MGI relating to the development of community-wide large-scale mutagenesis and phenotyping projects and introduce ways to access and use these MGI data. References and links to additional MGI aspects are provided. PMID:28838066

Stochastic population dynamics under resource constraints

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

Gavane, Ajinkya S., E-mail: ajinkyagavane@gmail.com; Nigam, Rahul, E-mail: rahul.nigam@hyderabad.bits-pilani.ac.in

This paper investigates the population growth of a certain species in which every generation reproduces thrice over a period of predefined time, under certain constraints of resources needed for survival of population. We study the survival period of a species by randomizing the reproduction probabilities within a window at same predefined ages and the resources are being produced by the working force of the population at a variable rate. This randomness in the reproduction rate makes the population growth stochastic in nature and one cannot predict the exact form of evolution. Hence we study the growth by running simulations formore » such a population and taking an ensemble averaged over 500 to 5000 such simulations as per the need. While the population reproduces in a stochastic manner, we have implemented a constraint on the amount of resources available for the population. This is important to make the simulations more realistic. The rate of resource production then is tuned to find the rate which suits the survival of the species. We also compute the mean life time of the species corresponding to different resource production rate. Study for these outcomes in the parameter space defined by the reproduction probabilities and rate of resource production is carried out.« less

A resource management architecture based on complex network theory in cloud computing federation

NASA Astrophysics Data System (ADS)

Zhang, Zehua; Zhang, Xuejie

2011-10-01

Cloud Computing Federation is a main trend of Cloud Computing. Resource Management has significant effect on the design, realization, and efficiency of Cloud Computing Federation. Cloud Computing Federation has the typical characteristic of the Complex System, therefore, we propose a resource management architecture based on complex network theory for Cloud Computing Federation (abbreviated as RMABC) in this paper, with the detailed design of the resource discovery and resource announcement mechanisms. Compare with the existing resource management mechanisms in distributed computing systems, a Task Manager in RMABC can use the historical information and current state data get from other Task Managers for the evolution of the complex network which is composed of Task Managers, thus has the advantages in resource discovery speed, fault tolerance and adaptive ability. The result of the model experiment confirmed the advantage of RMABC in resource discovery performance.

Multi-model approach to petroleum resource appraisal using analytic methodologies for probabilistic systems

USGS Publications Warehouse

Crovelli, R.A.

1988-01-01

The geologic appraisal model that is selected for a petroleum resource assessment depends upon purpose of the assessment, basic geologic assumptions of the area, type of available data, time available before deadlines, available human and financial resources, available computer facilities, and, most importantly, the available quantitative methodology with corresponding computer software and any new quantitative methodology that would have to be developed. Therefore, different resource assessment projects usually require different geologic models. Also, more than one geologic model might be needed in a single project for assessing different regions of the study or for cross-checking resource estimates of the area. Some geologic analyses used in the past for petroleum resource appraisal involved play analysis. The corresponding quantitative methodologies of these analyses usually consisted of Monte Carlo simulation techniques. A probabilistic system of petroleum resource appraisal for play analysis has been designed to meet the following requirements: (1) includes a variety of geologic models, (2) uses an analytic methodology instead of Monte Carlo simulation, (3) possesses the capacity to aggregate estimates from many areas that have been assessed by different geologic models, and (4) runs quickly on a microcomputer. Geologic models consist of four basic types: reservoir engineering, volumetric yield, field size, and direct assessment. Several case histories and present studies by the U.S. Geological Survey are discussed. ?? 1988 International Association for Mathematical Geology.

Reconsidering the Resources Needed for Multiple Casualty Events: Lessons Learned From the Crash of Asiana Airlines Flight 214.

PubMed

Campion, Eric M; Juillard, Catherine; Knudson, M Margaret; Dicker, Rochelle; Cohen, Mitchell J; Mackersie, Robert; Campbell, Andre R; Callcut, Rachael A

2016-06-01

To date, a substantial portion of multiple casualty incident literature has focused exclusively on prehospital and emergency department resources needed for optimal disaster response. Thus, inpatient resources required to care for individuals injured in multiple casualty events are not well described. To highlight the resources beyond initial emergency department triage needed for multiple casualty events, using one of the largest commercial aviation disasters in modern US history as a case study. Prospective case series of injured individuals treated at an urban level I trauma center following the crash of Asiana Airlines flight 214 on July 6, 2013. This analysis was conducted between June 1, 2014, and December 1, 2015. Commercial jetliner crash. Medical records, imaging data, nursing overtime, blood bank records, and trauma registry data were analyzed. Disaster logs, patient injuries, and blood product data were prospectively collected during the incident. Among 307 people aboard the flight, 192 were injured; 63 of the injured patients were initially evaluated at San Francisco General Hospital and Trauma Center (the highest number at any of the receiving medical facilities; age range, 4-74 years [23 were aged <17 years and 3 were aged >60 years]; median injury severity score of 19 admitted patients, 9 [range, 9-45]), including the highest number of critically injured patients (10 of 12). Despite the high impact of the crash, only 3 persons (<1%) died, including 1 in-hospital death. Among the 63 patients, 32 (50.8%) underwent a computed tomographic imaging study, with imaging of the abdomen and pelvis being the most common. Sixteen of the 32 patients undergoing computed tomography (50.0%) had a positive finding on at least 1 scan. Nineteen patients had major injuries and required admission, with 5 taken directly from the emergency department to the operating room. The most frequent injury was spinal fracture (13 patients). In the first 48 hours, 15 operations were performed and 117 total units of blood products were transfused. A total of 370 nursing overtime hours were required to treat the injured patients on the day of the event. Proper disaster preparedness requires attention to hospital-level needs beyond initial emergency department triage. The Asiana Airlines flight 214 crash highlights the need to plan for high use of advanced imaging, blood products, operating room availability, nursing resources, and management of inpatient hospital beds.

Computational chemistry

NASA Technical Reports Server (NTRS)

Arnold, J. O.

1987-01-01

With the advent of supercomputers, modern computational chemistry algorithms and codes, a powerful tool was created to help fill NASA's continuing need for information on the properties of matter in hostile or unusual environments. Computational resources provided under the National Aerodynamics Simulator (NAS) program were a cornerstone for recent advancements in this field. Properties of gases, materials, and their interactions can be determined from solutions of the governing equations. In the case of gases, for example, radiative transition probabilites per particle, bond-dissociation energies, and rates of simple chemical reactions can be determined computationally as reliably as from experiment. The data are proving to be quite valuable in providing inputs to real-gas flow simulation codes used to compute aerothermodynamic loads on NASA's aeroassist orbital transfer vehicles and a host of problems related to the National Aerospace Plane Program. Although more approximate, similar solutions can be obtained for ensembles of atoms simulating small particles of materials with and without the presence of gases. Computational chemistry has application in studying catalysis, properties of polymers, all of interest to various NASA missions, including those previously mentioned. In addition to discussing these applications of computational chemistry within NASA, the governing equations and the need for supercomputers for their solution is outlined.

Computing Platforms for Big Biological Data Analytics: Perspectives and Challenges.

PubMed

Yin, Zekun; Lan, Haidong; Tan, Guangming; Lu, Mian; Vasilakos, Athanasios V; Liu, Weiguo

2017-01-01

The last decade has witnessed an explosion in the amount of available biological sequence data, due to the rapid progress of high-throughput sequencing projects. However, the biological data amount is becoming so great that traditional data analysis platforms and methods can no longer meet the need to rapidly perform data analysis tasks in life sciences. As a result, both biologists and computer scientists are facing the challenge of gaining a profound insight into the deepest biological functions from big biological data. This in turn requires massive computational resources. Therefore, high performance computing (HPC) platforms are highly needed as well as efficient and scalable algorithms that can take advantage of these platforms. In this paper, we survey the state-of-the-art HPC platforms for big biological data analytics. We first list the characteristics of big biological data and popular computing platforms. Then we provide a taxonomy of different biological data analysis applications and a survey of the way they have been mapped onto various computing platforms. After that, we present a case study to compare the efficiency of different computing platforms for handling the classical biological sequence alignment problem. At last we discuss the open issues in big biological data analytics.

The Cloud Area Padovana: from pilot to production

NASA Astrophysics Data System (ADS)

Andreetto, P.; Costa, F.; Crescente, A.; Dorigo, A.; Fantinel, S.; Fanzago, F.; Sgaravatto, M.; Traldi, S.; Verlato, M.; Zangrando, L.

2017-10-01

The Cloud Area Padovana has been running for almost two years. This is an OpenStack-based scientific cloud, spread across two different sites: the INFN Padova Unit and the INFN Legnaro National Labs. The hardware resources have been scaled horizontally and vertically, by upgrading some hypervisors and by adding new ones: currently it provides about 1100 cores. Some in-house developments were also integrated in the OpenStack dashboard, such as a tool for user and project registrations with direct support for the INFN-AAI Identity Provider as a new option for the user authentication. In collaboration with the EU-funded Indigo DataCloud project, the integration with Docker-based containers has been experimented with and will be available in production soon. This computing facility now satisfies the computational and storage demands of more than 70 users affiliated with about 20 research projects. We present here the architecture of this Cloud infrastructure, the tools and procedures used to operate it. We also focus on the lessons learnt in these two years, describing the problems that were found and the corrective actions that had to be applied. We also discuss about the chosen strategy for upgrades, which combines the need to promptly integrate the OpenStack new developments, the demand to reduce the downtimes of the infrastructure, and the need to limit the effort requested for such updates. We also discuss how this Cloud infrastructure is being used. In particular we focus on two big physics experiments which are intensively exploiting this computing facility: CMS and SPES. CMS deployed on the cloud a complex computational infrastructure, composed of several user interfaces for job submission in the Grid environment/local batch queues or for interactive processes; this is fully integrated with the local Tier-2 facility. To avoid a static allocation of the resources, an elastic cluster, based on cernVM, has been configured: it allows to automatically create and delete virtual machines according to the user needs. SPES, using a client-server system called TraceWin, exploits INFN’s virtual resources performing a very large number of simulations on about a thousand nodes elastically managed.

Computer network access to scientific information systems for minority universities

NASA Astrophysics Data System (ADS)

Thomas, Valerie L.; Wakim, Nagi T.

1993-08-01

The evolution of computer networking technology has lead to the establishment of a massive networking infrastructure which interconnects various types of computing resources at many government, academic, and corporate institutions. A large segment of this infrastructure has been developed to facilitate information exchange and resource sharing within the scientific community. The National Aeronautics and Space Administration (NASA) supports both the development and the application of computer networks which provide its community with access to many valuable multi-disciplinary scientific information systems and on-line databases. Recognizing the need to extend the benefits of this advanced networking technology to the under-represented community, the National Space Science Data Center (NSSDC) in the Space Data and Computing Division at the Goddard Space Flight Center has developed the Minority University-Space Interdisciplinary Network (MU-SPIN) Program: a major networking and education initiative for Historically Black Colleges and Universities (HBCUs) and Minority Universities (MUs). In this paper, we will briefly explain the various components of the MU-SPIN Program while highlighting how, by providing access to scientific information systems and on-line data, it promotes a higher level of collaboration among faculty and students and NASA scientists.

Comparison of OPC job prioritization schemes to generate data for mask manufacturing

NASA Astrophysics Data System (ADS)

Lewis, Travis; Veeraraghavan, Vijay; Jantzen, Kenneth; Kim, Stephen; Park, Minyoung; Russell, Gordon; Simmons, Mark

2015-03-01

Delivering mask ready OPC corrected data to the mask shop on-time is critical for a foundry to meet the cycle time commitment for a new product. With current OPC compute resource sharing technology, different job scheduling algorithms are possible, such as, priority based resource allocation and fair share resource allocation. In order to maximize computer cluster efficiency, minimize the cost of the data processing and deliver data on schedule, the trade-offs of each scheduling algorithm need to be understood. Using actual production jobs, each of the scheduling algorithms will be tested in a production tape-out environment. Each scheduling algorithm will be judged on its ability to deliver data on schedule and the trade-offs associated with each method will be analyzed. It is now possible to introduce advance scheduling algorithms to the OPC data processing environment to meet the goals of on-time delivery of mask ready OPC data while maximizing efficiency and reducing cost.

A model to forecast data centre infrastructure costs.

NASA Astrophysics Data System (ADS)

Vernet, R.

2015-12-01

The computing needs in the HEP community are increasing steadily, but the current funding situation in many countries is tight. As a consequence experiments, data centres, and funding agencies have to rationalize resource usage and expenditures. CC-IN2P3 (Lyon, France) provides computing resources to many experiments including LHC, and is a major partner for astroparticle projects like LSST, CTA or Euclid. The financial cost to accommodate all these experiments is substantial and has to be planned well in advance for funding and strategic reasons. In that perspective, leveraging infrastructure expenses, electric power cost and hardware performance observed in our site over the last years, we have built a model that integrates these data and provides estimates of the investments that would be required to cater to the experiments for the mid-term future. We present how our model is built and the expenditure forecast it produces, taking into account the experiment roadmaps. We also examine the resource growth predicted by our model over the next years assuming a flat-budget scenario.

Modeling of the Global Water Cycle - Analytical Models

Treesearch

Yongqiang Liu; Roni Avissar

2005-01-01

Both numerical and analytical models of coupled atmosphere and its underlying ground components (land, ocean, ice) are useful tools for modeling the global and regional water cycle. Unlike complex three-dimensional climate models, which need very large computing resources and involve a large number of complicated interactions often difficult to interpret, analytical...

Working for America. Career Schools: A Tremendous Resource for Employers.

ERIC Educational Resources Information Center

Career Education, 1992

1992-01-01

Discusses industries that are vital to the nation's economy and the numbers of skilled workers they will need to keep moving ahead. Industries profiled are aviation, automotive, allied health, trucking, paralegal, electronics, and computer-aided drafting. Also looks at proprietary schools that are educating the work force of the future. (JOW)

An Assessment of Remote Laboratory Experiments in Radio Communication

ERIC Educational Resources Information Center

Gampe, Andreas; Melkonyan, Arsen; Pontual, Murillo; Akopian, David

2014-01-01

Today's electrical and computer engineering graduates need marketable skills to work with electronic devices. Hands-on experiments prepare students to deal with real-world problems and help them to comprehend theoretical concepts and relate these to practical tasks. However, shortage of equipment, high costs, and a lack of human resources for…

Computer-Supported Collaborative Learning: Best Practices and Principles for Instructors

ERIC Educational Resources Information Center

Orvis, Kara L., Ed.; Lassiter, Andrea L. R., Ed.

2008-01-01

Decades of research have shown that student collaboration in groups doesn't just happen; rather it needs to be a deliberate process facilitated by the instructor. Promoting collaboration in virtual learning environments presents a variety of challenges. This book answers the demand for a thorough resource on techniques to facilitate effective …

An Expert System for Designing Fire Prescriptions

Treesearch

Elizabeth Reinhardt

1987-01-01

Managers use prescribed fire to accomplish a variety of resource objectives. The knowledge needed to design successful prescriptions is both quantitative and qualitative. Some of it is available through publications and computer programs, but much of the knowledge of expert practitioners has never been collected or published. An expert system being developed at the,...

The New Venture Growth: Functional Differentiation and the Need for Human Resource Development Interventions.

ERIC Educational Resources Information Center

Ardichvili, Alexander; Harmon, Brian; Cardozo, Richard N.; Reynolds, Paul D.; Williams, Mary L.

1998-01-01

New businesses (n=539) were surveyed in 1986-87 and 1992-93. People responsible for start-up retained responsibility for marketing and related functions. Production, service delivery, purchasing, shipping, and computer functions were most often delegated, usually to internal employees. Organization size did not influence functional…

Interdisciplinary research on the application of ERTS-1 data to the regional land use planning process

NASA Technical Reports Server (NTRS)

Clapp, J. L. (Principal Investigator); Kiefer, R. W.; Mccarthy, M. M.; Niemann, B. J., Jr.

1972-01-01

The author has identified the following significant results. Although the degree to which ERTS-1 imagery can satisfy regional land use planning data needs is not yet known, it appears to offer means by which the data acquisition process can be immeasurably improved. The initial experiences of an interdisciplinary group attempting to formulate ways of analyzing the effectiveness of ERTS-1 imagery as a base for environmental monitoring and the resolution of regional land allocation problems are documented. Application of imagery to the regional planning process consists of utilizing representative geographical regions within the state of Wisconsin. Because of the need to describe and depict regional resource complexity in an interrelatable state, certain resources within the geographical regions have been inventoried and stored in a two-dimensional computer-based map form. Computer oriented processes were developed to provide for the economical storage, analysis, and spatial display of natural and cultural data for regional land use planning purposes. The authors are optimistic that the imagery will provide revelant data for land use decision making at regional levels.

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

Friese, Ryan; Khemka, Bhavesh; Maciejewski, Anthony A

Rising costs of energy consumption and an ongoing effort for increases in computing performance are leading to a significant need for energy-efficient computing. Before systems such as supercomputers, servers, and datacenters can begin operating in an energy-efficient manner, the energy consumption and performance characteristics of the system must be analyzed. In this paper, we provide an analysis framework that will allow a system administrator to investigate the tradeoffs between system energy consumption and utility earned by a system (as a measure of system performance). We model these trade-offs as a bi-objective resource allocation problem. We use a popular multi-objective geneticmore » algorithm to construct Pareto fronts to illustrate how different resource allocations can cause a system to consume significantly different amounts of energy and earn different amounts of utility. We demonstrate our analysis framework using real data collected from online benchmarks, and further provide a method to create larger data sets that exhibit similar heterogeneity characteristics to real data sets. This analysis framework can provide system administrators with insight to make intelligent scheduling decisions based on the energy and utility needs of their systems.« less

A resource-sharing model based on a repeated game in fog computing.

PubMed

Sun, Yan; Zhang, Nan

2017-03-01

With the rapid development of cloud computing techniques, the number of users is undergoing exponential growth. It is difficult for traditional data centers to perform many tasks in real time because of the limited bandwidth of resources. The concept of fog computing is proposed to support traditional cloud computing and to provide cloud services. In fog computing, the resource pool is composed of sporadic distributed resources that are more flexible and movable than a traditional data center. In this paper, we propose a fog computing structure and present a crowd-funding algorithm to integrate spare resources in the network. Furthermore, to encourage more resource owners to share their resources with the resource pool and to supervise the resource supporters as they actively perform their tasks, we propose an incentive mechanism in our algorithm. Simulation results show that our proposed incentive mechanism can effectively reduce the SLA violation rate and accelerate the completion of tasks.

Use of handheld computers in clinical practice: a systematic review.

PubMed

Mickan, Sharon; Atherton, Helen; Roberts, Nia Wyn; Heneghan, Carl; Tilson, Julie K

2014-07-06

Many healthcare professionals use smartphones and tablets to inform patient care. Contemporary research suggests that handheld computers may support aspects of clinical diagnosis and management. This systematic review was designed to synthesise high quality evidence to answer the question; Does healthcare professionals' use of handheld computers improve their access to information and support clinical decision making at the point of care? A detailed search was conducted using Cochrane, MEDLINE, EMBASE, PsycINFO, Science and Social Science Citation Indices since 2001. Interventions promoting healthcare professionals seeking information or making clinical decisions using handheld computers were included. Classroom learning and the use of laptop computers were excluded. Two authors independently selected studies, assessed quality using the Cochrane Risk of Bias tool and extracted data. High levels of data heterogeneity negated statistical synthesis. Instead, evidence for effectiveness was summarised narratively, according to each study's aim for assessing the impact of handheld computer use. We included seven randomised trials investigating medical or nursing staffs' use of Personal Digital Assistants. Effectiveness was demonstrated across three distinct functions that emerged from the data: accessing information for clinical knowledge, adherence to guidelines and diagnostic decision making. When healthcare professionals used handheld computers to access clinical information, their knowledge improved significantly more than peers who used paper resources. When clinical guideline recommendations were presented on handheld computers, clinicians made significantly safer prescribing decisions and adhered more closely to recommendations than peers using paper resources. Finally, healthcare professionals made significantly more appropriate diagnostic decisions using clinical decision making tools on handheld computers compared to colleagues who did not have access to these tools. For these clinical decisions, the numbers need to test/screen were all less than 11. Healthcare professionals' use of handheld computers may improve their information seeking, adherence to guidelines and clinical decision making. Handheld computers can provide real time access to and analysis of clinical information. The integration of clinical decision support systems within handheld computers offers clinicians the highest level of synthesised evidence at the point of care. Future research is needed to replicate these early results and to identify beneficial clinical outcomes.

Use of handheld computers in clinical practice: a systematic review

PubMed Central

2014-01-01

Background Many healthcare professionals use smartphones and tablets to inform patient care. Contemporary research suggests that handheld computers may support aspects of clinical diagnosis and management. This systematic review was designed to synthesise high quality evidence to answer the question; Does healthcare professionals’ use of handheld computers improve their access to information and support clinical decision making at the point of care? Methods A detailed search was conducted using Cochrane, MEDLINE, EMBASE, PsycINFO, Science and Social Science Citation Indices since 2001. Interventions promoting healthcare professionals seeking information or making clinical decisions using handheld computers were included. Classroom learning and the use of laptop computers were excluded. Two authors independently selected studies, assessed quality using the Cochrane Risk of Bias tool and extracted data. High levels of data heterogeneity negated statistical synthesis. Instead, evidence for effectiveness was summarised narratively, according to each study’s aim for assessing the impact of handheld computer use. Results We included seven randomised trials investigating medical or nursing staffs’ use of Personal Digital Assistants. Effectiveness was demonstrated across three distinct functions that emerged from the data: accessing information for clinical knowledge, adherence to guidelines and diagnostic decision making. When healthcare professionals used handheld computers to access clinical information, their knowledge improved significantly more than peers who used paper resources. When clinical guideline recommendations were presented on handheld computers, clinicians made significantly safer prescribing decisions and adhered more closely to recommendations than peers using paper resources. Finally, healthcare professionals made significantly more appropriate diagnostic decisions using clinical decision making tools on handheld computers compared to colleagues who did not have access to these tools. For these clinical decisions, the numbers need to test/screen were all less than 11. Conclusion Healthcare professionals’ use of handheld computers may improve their information seeking, adherence to guidelines and clinical decision making. Handheld computers can provide real time access to and analysis of clinical information. The integration of clinical decision support systems within handheld computers offers clinicians the highest level of synthesised evidence at the point of care. Future research is needed to replicate these early results and to identify beneficial clinical outcomes. PMID:24998515

Smart Data Infrastructure: The Sixth Generation of Mediation for Data Science

NASA Astrophysics Data System (ADS)

Fox, P. A.

2014-12-01

In the emergent "fourth paradigm" (data-driven) science, the scientific method is enhanced by the integration of significant data sources into the practice of scientific research. To address Big Science, there are challenges in understanding the role of data in enabling researchers to attack not just disciplinary issues, but also the system-level, large-scale, and transdisciplinary global scientific challenges facing society.Recognizing that the volume of data is only one of many dimensions to be considered, there is a clear need for improved data infrastructures to mediate data and information exchange, which we contend will need to be powered by semantic technologies. One clear need is to provide computational approaches for researchers to discover appropriate data resources, rapidly integrate data collections from heterogeneously resources or multiple data sets, and inter-compare results to allow generation and validation of hypotheses. Another trend is toward automated tools that allow researchers to better find and reuse data that they currently don't know they need, let alone know how to find. Again semantic technologies will be required. Finally, to turn data analytics from "art to science", technical solutions are needed for cross-dataset validation, reproducibility studies on data-driven results, and the concomitant citation of data products allowing recognition for those who curate and share important data resources.

A review of Computer Science resources for learning and teaching with K-12 computing curricula: an Australian case study

NASA Astrophysics Data System (ADS)

Falkner, Katrina; Vivian, Rebecca

2015-10-01

To support teachers to implement Computer Science curricula into classrooms from the very first year of school, teachers, schools and organisations seek quality curriculum resources to support implementation and teacher professional development. Until now, many Computer Science resources and outreach initiatives have targeted K-12 school-age children, with the intention to engage children and increase interest, rather than to formally teach concepts and skills. What is the educational quality of existing Computer Science resources and to what extent are they suitable for classroom learning and teaching? In this paper, an assessment framework is presented to evaluate the quality of online Computer Science resources. Further, a semi-systematic review of available online Computer Science resources was conducted to evaluate resources available for classroom learning and teaching and to identify gaps in resource availability, using the Australian curriculum as a case study analysis. The findings reveal a predominance of quality resources, however, a number of critical gaps were identified. This paper provides recommendations and guidance for the development of new and supplementary resources and future research.

iTools: a framework for classification, categorization and integration of computational biology resources.

PubMed

Dinov, Ivo D; Rubin, Daniel; Lorensen, William; Dugan, Jonathan; Ma, Jeff; Murphy, Shawn; Kirschner, Beth; Bug, William; Sherman, Michael; Floratos, Aris; Kennedy, David; Jagadish, H V; Schmidt, Jeanette; Athey, Brian; Califano, Andrea; Musen, Mark; Altman, Russ; Kikinis, Ron; Kohane, Isaac; Delp, Scott; Parker, D Stott; Toga, Arthur W

2008-05-28

The advancement of the computational biology field hinges on progress in three fundamental directions--the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources--data, software tools and web-services. The iTools design, implementation and resource meta-data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long-term resource management. We demonstrate several applications of iTools as a framework for integrated bioinformatics. iTools and the complete details about its specifications, usage and interfaces are available at the iTools web page http://iTools.ccb.ucla.edu.

Centralized Authorization Using a Direct Service, Part II

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

Wachsmann, A

Authorization is the process of deciding if entity X is allowed to have access to resource Y. Determining the identity of X is the job of the authentication process. One task of authorization in computer networks is to define and determine which user has access to which computers in the network. On Linux, the tendency exists to create a local account for each single user who should be allowed to logon to a computer. This is typically the case because a user not only needs login privileges to a computer but also additional resources like a home directory to actuallymore » do some work. Creating a local account on every computer takes care of all this. The problem with this approach is that these local accounts can be inconsistent with each other. The same user name could have a different user ID and/or group ID on different computers. Even more problematic is when two different accounts share the same user ID and group ID on different computers: User joe on computer1 could have user ID 1234 and group ID 56 and user jane on computer2 could have the same user ID 1234 and group ID 56. This is a big security risk in case shared resources like NFS are used. These two different accounts are the same for an NFS server so that these users can wipe out each other's files. The solution to this inconsistency problem is to have only one central, authoritative data source for this kind of information and a means of providing all your computers with access to this central source. This is what a ''Directory Service'' is. The two directory services most widely used for centralizing authorization data are the Network Information Service (NIS, formerly known as Yellow Pages or YP) and Lightweight Directory Access Protocol (LDAP).« less

JobCenter: an open source, cross-platform, and distributed job queue management system optimized for scalability and versatility.

PubMed

Jaschob, Daniel; Riffle, Michael

2012-07-30

Laboratories engaged in computational biology or bioinformatics frequently need to run lengthy, multistep, and user-driven computational jobs. Each job can tie up a computer for a few minutes to several days, and many laboratories lack the expertise or resources to build and maintain a dedicated computer cluster. JobCenter is a client-server application and framework for job management and distributed job execution. The client and server components are both written in Java and are cross-platform and relatively easy to install. All communication with the server is client-driven, which allows worker nodes to run anywhere (even behind external firewalls or "in the cloud") and provides inherent load balancing. Adding a worker node to the worker pool is as simple as dropping the JobCenter client files onto any computer and performing basic configuration, which provides tremendous ease-of-use, flexibility, and limitless horizontal scalability. Each worker installation may be independently configured, including the types of jobs it is able to run. Executed jobs may be written in any language and may include multistep workflows. JobCenter is a versatile and scalable distributed job management system that allows laboratories to very efficiently distribute all computational work among available resources. JobCenter is freely available at http://code.google.com/p/jobcenter/.

Integration of Russian Tier-1 Grid Center with High Performance Computers at NRC-KI for LHC experiments and beyond HENP

NASA Astrophysics Data System (ADS)

Belyaev, A.; Berezhnaya, A.; Betev, L.; Buncic, P.; De, K.; Drizhuk, D.; Klimentov, A.; Lazin, Y.; Lyalin, I.; Mashinistov, R.; Novikov, A.; Oleynik, D.; Polyakov, A.; Poyda, A.; Ryabinkin, E.; Teslyuk, A.; Tkachenko, I.; Yasnopolskiy, L.

2015-12-01

The LHC experiments are preparing for the precision measurements and further discoveries that will be made possible by higher LHC energies from April 2015 (LHC Run2). The need for simulation, data processing and analysis would overwhelm the expected capacity of grid infrastructure computing facilities deployed by the Worldwide LHC Computing Grid (WLCG). To meet this challenge the integration of the opportunistic resources into LHC computing model is highly important. The Tier-1 facility at Kurchatov Institute (NRC-KI) in Moscow is a part of WLCG and it will process, simulate and store up to 10% of total data obtained from ALICE, ATLAS and LHCb experiments. In addition Kurchatov Institute has supercomputers with peak performance 0.12 PFLOPS. The delegation of even a fraction of supercomputing resources to the LHC Computing will notably increase total capacity. In 2014 the development a portal combining a Tier-1 and a supercomputer in Kurchatov Institute was started to provide common interfaces and storage. The portal will be used not only for HENP experiments, but also by other data- and compute-intensive sciences like biology with genome sequencing analysis; astrophysics with cosmic rays analysis, antimatter and dark matter search, etc.

Seismic waveform modeling over cloud

NASA Astrophysics Data System (ADS)

Luo, Cong; Friederich, Wolfgang

2016-04-01

With the fast growing computational technologies, numerical simulation of seismic wave propagation achieved huge successes. Obtaining the synthetic waveforms through numerical simulation receives an increasing amount of attention from seismologists. However, computational seismology is a data-intensive research field, and the numerical packages usually come with a steep learning curve. Users are expected to master considerable amount of computer knowledge and data processing skills. Training users to use the numerical packages, correctly access and utilize the computational resources is a troubled task. In addition to that, accessing to HPC is also a common difficulty for many users. To solve these problems, a cloud based solution dedicated on shallow seismic waveform modeling has been developed with the state-of-the-art web technologies. It is a web platform integrating both software and hardware with multilayer architecture: a well designed SQL database serves as the data layer, HPC and dedicated pipeline for it is the business layer. Through this platform, users will no longer need to compile and manipulate various packages on the local machine within local network to perform a simulation. By providing users professional access to the computational code through its interfaces and delivering our computational resources to the users over cloud, users can customize the simulation at expert-level, submit and run the job through it.

Parallel high-performance grid computing: capabilities and opportunities of a novel demanding service and business class allowing highest resource efficiency.

PubMed

Kepper, Nick; Ettig, Ramona; Dickmann, Frank; Stehr, Rene; Grosveld, Frank G; Wedemann, Gero; Knoch, Tobias A

2010-01-01

Especially in the life-science and the health-care sectors the huge IT requirements are imminent due to the large and complex systems to be analysed and simulated. Grid infrastructures play here a rapidly increasing role for research, diagnostics, and treatment, since they provide the necessary large-scale resources efficiently. Whereas grids were first used for huge number crunching of trivially parallelizable problems, increasingly parallel high-performance computing is required. Here, we show for the prime example of molecular dynamic simulations how the presence of large grid clusters including very fast network interconnects within grid infrastructures allows now parallel high-performance grid computing efficiently and thus combines the benefits of dedicated super-computing centres and grid infrastructures. The demands for this service class are the highest since the user group has very heterogeneous requirements: i) two to many thousands of CPUs, ii) different memory architectures, iii) huge storage capabilities, and iv) fast communication via network interconnects, are all needed in different combinations and must be considered in a highly dedicated manner to reach highest performance efficiency. Beyond, advanced and dedicated i) interaction with users, ii) the management of jobs, iii) accounting, and iv) billing, not only combines classic with parallel high-performance grid usage, but more importantly is also able to increase the efficiency of IT resource providers. Consequently, the mere "yes-we-can" becomes a huge opportunity like e.g. the life-science and health-care sectors as well as grid infrastructures by reaching higher level of resource efficiency.

INFN-Pisa scientific computation environment (GRID, HPC and Interactive Analysis)

NASA Astrophysics Data System (ADS)

Arezzini, S.; Carboni, A.; Caruso, G.; Ciampa, A.; Coscetti, S.; Mazzoni, E.; Piras, S.

2014-06-01

The INFN-Pisa Tier2 infrastructure is described, optimized not only for GRID CPU and Storage access, but also for a more interactive use of the resources in order to provide good solutions for the final data analysis step. The Data Center, equipped with about 6700 production cores, permits the use of modern analysis techniques realized via advanced statistical tools (like RooFit and RooStat) implemented in multicore systems. In particular a POSIX file storage access integrated with standard SRM access is provided. Therefore the unified storage infrastructure is described, based on GPFS and Xrootd, used both for SRM data repository and interactive POSIX access. Such a common infrastructure allows a transparent access to the Tier2 data to the users for their interactive analysis. The organization of a specialized many cores CPU facility devoted to interactive analysis is also described along with the login mechanism integrated with the INFN-AAI (National INFN Infrastructure) to extend the site access and use to a geographical distributed community. Such infrastructure is used also for a national computing facility in use to the INFN theoretical community, it enables a synergic use of computing and storage resources. Our Center initially developed for the HEP community is now growing and includes also HPC resources fully integrated. In recent years has been installed and managed a cluster facility (1000 cores, parallel use via InfiniBand connection) and we are now updating this facility that will provide resources for all the intermediate level HPC computing needs of the INFN theoretical national community.

A Formal Valuation Framework for Emotions and Their Control.

PubMed

Huys, Quentin J M; Renz, Daniel

2017-09-15

Computational psychiatry aims to apply mathematical and computational techniques to help improve psychiatric care. To achieve this, the phenomena under scrutiny should be within the scope of formal methods. As emotions play an important role across many psychiatric disorders, such computational methods must encompass emotions. Here, we consider formal valuation accounts of emotions. We focus on the fact that the flexibility of emotional responses and the nature of appraisals suggest the need for a model-based valuation framework for emotions. However, resource limitations make plain model-based valuation impossible and require metareasoning strategies to apportion cognitive resources adaptively. We argue that emotions may implement such metareasoning approximations by restricting the range of behaviors and states considered. We consider the processes that guide the deployment of the approximations, discerning between innate, model-free, heuristic, and model-based controllers. A formal valuation and metareasoning framework may thus provide a principled approach to examining emotions. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

ICT in the Education of Students with SEN: Perceptions of Stakeholders

NASA Astrophysics Data System (ADS)

Ribeiro, Jaime; Moreira, António; Almeida, Ana Margarida

Portugal is experiencing a technological reform in education. Technological refurbishing of schools and training of students and teachers is a reality on the rise, enhanced by the implementation of the Education Technological Plan, which also aims at computer skills certification, by 2010, of 90% of teachers. In a School that must be adjusted to all pupils, Special Educational Needs cannot be neglected and the nature and constitution of its computer resources should obviate the support of these students. ICT training is essential to benefit all students from its use. In the case of SEN, this need for training is of paramount importance to establish itself as a facilitator for these students. ICT Coordinators are the visible face of ICT implementation in schools; their functions include the management of the schools computer facilities and to zeal for the ICT training of fellow teachers.

Information Power Grid (IPG) Tutorial 2003

NASA Technical Reports Server (NTRS)

Meyers, George

2003-01-01

For NASA and the general community today Grid middleware: a) provides tools to access/use data sources (databases, instruments, ...); b) provides tools to access computing (unique and generic); c) Is an enabler of large scale collaboration. Dynamically responding to needs is a key selling point of a grid. Independent resources can be joined as appropriate to solve a problem. Provide tools to enable the building of a frameworks for application. Provide value added service to the NASA user base for utilizing resources on the grid in new and more efficient ways. Provides tools for development of Frameworks.

Design of a Microcomputer Application for a Mobile Mammography Unit

PubMed Central

Knott, Mark

1990-01-01

This paper illustrates the development of a departmental microcomputer based system. The approach taken is to distill requirements from the users, and to determine those tasks that belong on the computer and those that should be done manually. It also takes into account the realities of system design and implementation in a hospital environment where both personnel and financial resources are scarce. Operating under these conditions provides for a system that gives users the critical items they need to perform their jobs, while making use of existing resources.

Selecting and implementing the PBS scheduler on an SGI Onyx 2/Orgin 2000.

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

Bittner, S.

1999-06-28

In the Mathematics and Computer Science Division at Argonne, the demand for resources on the Onyx 2 exceeds the resources available for consumption. To distribute these scarce resources effectively, we need a scheduling and resource management package with multiple capabilities. In particular, it must accept standard interactive user logins, allow batch jobs, backfill the system based on available resources, and permit system activities such as accounting to proceed without interruption. The package must include a mechanism to treat the graphic pipes as a schedulable resource. Also required is the ability to create advance reservations, offer dedicated system modes for largemore » resource runs and benchmarking, and track the resources consumed for each job run. Furthermore, our users want to be able to obtain repeatable timing results on job runs. And, of course, package costs must be carefully considered. We explored several options, including NQE and various third-party products, before settling on the PBS scheduler.« less

Computational mechanics needs study

NASA Technical Reports Server (NTRS)

Griffin, O. Hayden, Jr.

1993-01-01

In order to assess the needs in computational mechanics over the next decade, we formulated a questionnaire and contacted computational mechanics researchers and users in industry, government, and academia. As expected, we found a wide variety of computational mechanics usage and research. This report outlines the activity discussed with those contacts, as well as that in our own organizations. It should be noted that most of the contacts were made before the recent decline of the defense industry. Therefore, areas which are strongly defense-oriented may decrease in relative importance. In order to facilitate updating of this study, names of a few key researchers in each area are included as starting points for future literature surveys. These lists of names are not intended to represent those persons doing the best research in that area, nor are they intended to be comprehensive. They are, as previously stated, offered as starting points for future literature searches. Overall, there is currently a broad activity in computational mechanics in this country, with the breadth and depth increasing as more sophisticated software and faster computers become more available. The needs and desires of the workers in this field are as diverse as their background and organizational products. There seems to be some degree of software development in any organization (although the level of activity is highly variable from one organization to another) which has any research component in its mission. It seems, however, that there is considerable use of commercial software in almost all organizations. In most industrial research organizations, it appears that very little actual software development is contracted out, but that most is done in-house, using a mixture of funding sources. Government agencies vary widely in the ratio of in-house to out-house ratio. There is a considerable amount of experimental verification in most, but not all, organizations. Generally, the amount of experimental verification is more than we expected. Of all the survey contacts, one or two believe that the resources they are allocated are sufficient, but most do not. Some believe they have only half the resources they need. Some see their resource deficits as short-term, while others see it as a trend which will continue or perhaps worsen. The pessimism is stronger in the defense and aerospace industry. When considering only the nonlinear development efforts, there appears to be an even mix of geometric and material nonlinearity. There is not much particular emphasis in linear analysis unless it is in extension of current analysis capabilities to larger problems. The primary exception is concern about modeling of composites, where proven methodologies have trailed element and computer hardware development. Most of the people we spoke to use finite element techniques, but there is some finite difference and boundary element work ongoing. There is also some interest in multiple methods. Coupling of finite elements and boundary elements appears to be of high interest, since the two analysis types are complementary.

Multicore job scheduling in the Worldwide LHC Computing Grid

NASA Astrophysics Data System (ADS)

Forti, A.; Pérez-Calero Yzquierdo, A.; Hartmann, T.; Alef, M.; Lahiff, A.; Templon, J.; Dal Pra, S.; Gila, M.; Skipsey, S.; Acosta-Silva, C.; Filipcic, A.; Walker, R.; Walker, C. J.; Traynor, D.; Gadrat, S.

2015-12-01

After the successful first run of the LHC, data taking is scheduled to restart in Summer 2015 with experimental conditions leading to increased data volumes and event complexity. In order to process the data generated in such scenario and exploit the multicore architectures of current CPUs, the LHC experiments have developed parallelized software for data reconstruction and simulation. However, a good fraction of their computing effort is still expected to be executed as single-core tasks. Therefore, jobs with diverse resources requirements will be distributed across the Worldwide LHC Computing Grid (WLCG), making workload scheduling a complex problem in itself. In response to this challenge, the WLCG Multicore Deployment Task Force has been created in order to coordinate the joint effort from experiments and WLCG sites. The main objective is to ensure the convergence of approaches from the different LHC Virtual Organizations (VOs) to make the best use of the shared resources in order to satisfy their new computing needs, minimizing any inefficiency originated from the scheduling mechanisms, and without imposing unnecessary complexities in the way sites manage their resources. This paper describes the activities and progress of the Task Force related to the aforementioned topics, including experiences from key sites on how to best use different batch system technologies, the evolution of workload submission tools by the experiments and the knowledge gained from scale tests of the different proposed job submission strategies.

Status and Roadmap of CernVM

NASA Astrophysics Data System (ADS)

Berzano, D.; Blomer, J.; Buncic, P.; Charalampidis, I.; Ganis, G.; Meusel, R.

2015-12-01

Cloud resources nowadays contribute an essential share of resources for computing in high-energy physics. Such resources can be either provided by private or public IaaS clouds (e.g. OpenStack, Amazon EC2, Google Compute Engine) or by volunteers computers (e.g. LHC@Home 2.0). In any case, experiments need to prepare a virtual machine image that provides the execution environment for the physics application at hand. The CernVM virtual machine since version 3 is a minimal and versatile virtual machine image capable of booting different operating systems. The virtual machine image is less than 20 megabyte in size. The actual operating system is delivered on demand by the CernVM File System. CernVM 3 has matured from a prototype to a production environment. It is used, for instance, to run LHC applications in the cloud, to tune event generators using a network of volunteer computers, and as a container for the historic Scientific Linux 5 and Scientific Linux 4 based software environments in the course of long-term data preservation efforts of the ALICE, CMS, and ALEPH experiments. We present experience and lessons learned from the use of CernVM at scale. We also provide an outlook on the upcoming developments. These developments include adding support for Scientific Linux 7, the use of container virtualization, such as provided by Docker, and the streamlining of virtual machine contextualization towards the cloud-init industry standard.

Water Intelligence and the Cyber-Infrastructure Revolution

NASA Astrophysics Data System (ADS)

Cline, D. W.

2015-12-01

As an intrinsic factor in national security, the global economy, food and energy production, and human and ecological health, fresh water resources are increasingly being considered by an ever-widening array of stakeholders. The U.S. intelligence community has identified water as a key factor in the Nation's security risk profile. Water industries are growing rapidly, and seek to revolutionize the role of water in the global economy, making water an economic value rather than a limitation on operations. Recent increased focus on the complex interrelationships and interdependencies between water, food, and energy signal a renewed effort to move towards integrated water resource management. Throughout all of this, hydrologic extremes continue to wreak havoc on communities and regions around the world, in some cases threatening long-term economic stability. This increased attention on water coincides with the "second IT revolution" of cyber-infrastructure (CI). The CI concept is a convergence of technology, data, applications and human resources, all coalescing into a tightly integrated global grid of computing, information, networking and sensor resources, and ultimately serving as an engine of change for collaboration, education and scientific discovery and innovation. In the water arena, we have unprecedented opportunities to apply the CI concept to help address complex water challenges and shape the future world of water resources - on both science and socio-economic application fronts. Providing actionable local "water intelligence" nationally or globally is now becoming feasible through high-performance computing, data technologies, and advanced hydrologic modeling. Further development on all of these fronts appears likely and will help advance this much-needed capability. Lagging behind are water observation systems, especially in situ networks, which need significant innovation to keep pace with and help fuel rapid advancements in water intelligence.

Roads towards fault-tolerant universal quantum computation

NASA Astrophysics Data System (ADS)

Campbell, Earl T.; Terhal, Barbara M.; Vuillot, Christophe

2017-09-01

A practical quantum computer must not merely store information, but also process it. To prevent errors introduced by noise from multiplying and spreading, a fault-tolerant computational architecture is required. Current experiments are taking the first steps toward noise-resilient logical qubits. But to convert these quantum devices from memories to processors, it is necessary to specify how a universal set of gates is performed on them. The leading proposals for doing so, such as magic-state distillation and colour-code techniques, have high resource demands. Alternative schemes, such as those that use high-dimensional quantum codes in a modular architecture, have potential benefits, but need to be explored further.

Roads towards fault-tolerant universal quantum computation.

PubMed

Campbell, Earl T; Terhal, Barbara M; Vuillot, Christophe

2017-09-13

A practical quantum computer must not merely store information, but also process it. To prevent errors introduced by noise from multiplying and spreading, a fault-tolerant computational architecture is required. Current experiments are taking the first steps toward noise-resilient logical qubits. But to convert these quantum devices from memories to processors, it is necessary to specify how a universal set of gates is performed on them. The leading proposals for doing so, such as magic-state distillation and colour-code techniques, have high resource demands. Alternative schemes, such as those that use high-dimensional quantum codes in a modular architecture, have potential benefits, but need to be explored further.

Access and visualization using clusters and other parallel computers

NASA Technical Reports Server (NTRS)

Katz, Daniel S.; Bergou, Attila; Berriman, Bruce; Block, Gary; Collier, Jim; Curkendall, Dave; Good, John; Husman, Laura; Jacob, Joe; Laity, Anastasia;

Paranoia.Ada: A diagnostic program to evaluate Ada floating-point arithmetic

NASA Technical Reports Server (NTRS)

Hjermstad, Chris

1986-01-01

Many essential software functions in the mission critical computer resource application domain depend on floating point arithmetic. Numerically intensive functions associated with the Space Station project, such as emphemeris generation or the implementation of Kalman filters, are likely to employ the floating point facilities of Ada. Paranoia.Ada appears to be a valuabe program to insure that Ada environments and their underlying hardware exhibit the precision and correctness required to satisfy mission computational requirements. As a diagnostic tool, Paranoia.Ada reveals many essential characteristics of an Ada floating point implementation. Equipped with such knowledge, programmers need not tremble before the complex task of floating point computation.

Sharing Service Resource Information for Application Integration in a Virtual Enterprise - Modeling the Communication Protocol for Exchanging Service Resource Information

NASA Astrophysics Data System (ADS)

Yamada, Hiroshi; Kawaguchi, Akira

Grid computing and web service technologies enable us to use networked resources in a coordinated manner. An integrated service is made of individual services running on coordinated resources. In order to achieve such coordinated services autonomously, the initiator of a coordinated service needs to know detailed service resource information. This information ranges from static attributes like the IP address of the application server to highly dynamic ones like the CPU load. The most famous wide-area service discovery mechanism based on names is DNS. Its hierarchical tree organization and caching methods take advantage of the static information managed. However, in order to integrate business applications in a virtual enterprise, we need a discovery mechanism to search for the optimal resources based on the given a set of criteria (search keys). In this paper, we propose a communication protocol for exchanging service resource information among wide-area systems. We introduce the concept of the service domain that consists of service providers managed under the same management policy. This concept of the service domain is similar to that for autonomous systems (ASs). In each service domain, the service information provider manages the service resource information of service providers that exist in this service domain. The service resource information provider exchanges this information with other service resource information providers that belong to the different service domains. We also verified the protocol's behavior and effectiveness using a simulation model developed for proposed protocol.

A European Federated Cloud: Innovative distributed computing solutions by EGI

NASA Astrophysics Data System (ADS)

Sipos, Gergely; Turilli, Matteo; Newhouse, Steven; Kacsuk, Peter

2013-04-01

The European Grid Infrastructure (EGI) is the result of pioneering work that has, over the last decade, built a collaborative production infrastructure of uniform services through the federation of national resource providers that supports multi-disciplinary science across Europe and around the world. This presentation will provide an overview of the recently established 'federated cloud computing services' that the National Grid Initiatives (NGIs), operators of EGI, offer to scientific communities. The presentation will explain the technical capabilities of the 'EGI Federated Cloud' and the processes whereby earth and space science researchers can engage with it. EGI's resource centres have been providing services for collaborative, compute- and data-intensive applications for over a decade. Besides the well-established 'grid services', several NGIs already offer privately run cloud services to their national researchers. Many of these researchers recently expressed the need to share these cloud capabilities within their international research collaborations - a model similar to the way the grid emerged through the federation of institutional batch computing and file storage servers. To facilitate the setup of a pan-European cloud service from the NGIs' resources, the EGI-InSPIRE project established a Federated Cloud Task Force in September 2011. The Task Force has a mandate to identify and test technologies for a multinational federated cloud that could be provisioned within EGI by the NGIs. A guiding principle for the EGI Federated Cloud is to remain technology neutral and flexible for both resource providers and users: • Resource providers are allowed to use any cloud hypervisor and management technology to join virtualised resources into the EGI Federated Cloud as long as the site is subscribed to the user-facing interfaces selected by the EGI community. • Users can integrate high level services - such as brokers, portals and customised Virtual Research Environments - with the EGI Federated Cloud as long as these services access cloud resources through the user-facing interfaces selected by the EGI community. The Task Force will be closed in May 2013. It already • Identified key enabling technologies by which a multinational, federated 'Infrastructure as a Service' (IaaS) type cloud can be built from the NGIs' resources; • Deployed a test bed to evaluate the integration of virtualised resources within EGI and to engage with early adopter use cases from different scientific domains; • Integrated cloud resources into the EGI production infrastructure through cloud specific bindings of the EGI information system, monitoring system, authentication system, etc.; • Collected and catalogued requirements concerning the federated cloud services from the feedback of early adopter use cases; • Provided feedback and requirements to relevant technology providers on their implementations and worked with these providers to address those requirements; • Identified issues that need to be addressed by other areas of EGI (such as portal solutions, resource allocation policies, marketing and user support) to reach a production system. The Task Force will publish a blueprint in April 2013. The blueprint will drive the establishment of a production level EGI Federated Cloud service after May 2013.

Provider-Independent Use of the Cloud

NASA Astrophysics Data System (ADS)

Harmer, Terence; Wright, Peter; Cunningham, Christina; Perrott, Ron

Utility computing offers researchers and businesses the potential of significant cost-savings, making it possible for them to match the cost of their computing and storage to their demand for such resources. A utility compute provider enables the purchase of compute infrastructures on-demand; when a user requires computing resources a provider will provision a resource for them and charge them only for their period of use of that resource. There has been a significant growth in the number of cloud computing resource providers and each has a different resource usage model, application process and application programming interface (API)-developing generic multi-resource provider applications is thus difficult and time consuming. We have developed an abstraction layer that provides a single resource usage model, user authentication model and API for compute providers that enables cloud-provider neutral applications to be developed. In this paper we outline the issues in using external resource providers, give examples of using a number of the most popular cloud providers and provide examples of developing provider neutral applications. In addition, we discuss the development of the API to create a generic provisioning model based on a common architecture for cloud computing providers.

Noise Threshold and Resource Cost of Fault-Tolerant Quantum Computing with Majorana Fermions in Hybrid Systems.

PubMed

Li, Ying

2016-09-16

Fault-tolerant quantum computing in systems composed of both Majorana fermions and topologically unprotected quantum systems, e.g., superconducting circuits or quantum dots, is studied in this Letter. Errors caused by topologically unprotected quantum systems need to be corrected with error-correction schemes, for instance, the surface code. We find that the error-correction performance of such a hybrid topological quantum computer is not superior to a normal quantum computer unless the topological charge of Majorana fermions is insusceptible to noise. If errors changing the topological charge are rare, the fault-tolerance threshold is much higher than the threshold of a normal quantum computer and a surface-code logical qubit could be encoded in only tens of topological qubits instead of about 1,000 normal qubits.

Uncover the Cloud for Geospatial Sciences and Applications to Adopt Cloud Computing

NASA Astrophysics Data System (ADS)

Yang, C.; Huang, Q.; Xia, J.; Liu, K.; Li, J.; Xu, C.; Sun, M.; Bambacus, M.; Xu, Y.; Fay, D.

2012-12-01

Cloud computing is emerging as the future infrastructure for providing computing resources to support and enable scientific research, engineering development, and application construction, as well as work force education. On the other hand, there is a lot of doubt about the readiness of cloud computing to support a variety of scientific research, development and educations. This research is a project funded by NASA SMD to investigate through holistic studies how ready is the cloud computing to support geosciences. Four applications with different computing characteristics including data, computing, concurrent, and spatiotemporal intensities are taken to test the readiness of cloud computing to support geosciences. Three popular and representative cloud platforms including Amazon EC2, Microsoft Azure, and NASA Nebula as well as a traditional cluster are utilized in the study. Results illustrates that cloud is ready to some degree but more research needs to be done to fully implemented the cloud benefit as advertised by many vendors and defined by NIST. Specifically, 1) most cloud platform could help stand up new computing instances, a new computer, in a few minutes as envisioned, therefore, is ready to support most computing needs in an on demand fashion; 2) the load balance and elasticity, a defining characteristic, is ready in some cloud platforms, such as Amazon EC2, to support bigger jobs, e.g., needs response in minutes, while some are not ready to support the elasticity and load balance well. All cloud platform needs further research and development to support real time application at subminute level; 3) the user interface and functionality of cloud platforms vary a lot and some of them are very professional and well supported/documented, such as Amazon EC2, some of them needs significant improvement for the general public to adopt cloud computing without professional training or knowledge about computing infrastructure; 4) the security is a big concern in cloud computing platform, with the sharing spirit of cloud computing, it is very hard to ensure higher level security, except a private cloud is built for a specific organization without public access, public cloud platform does not support FISMA medium level yet and may never be able to support FISMA high level; 5) HPC jobs needs of cloud computing is not well supported and only Amazon EC2 supports this well. The research is being taken by NASA and other agencies to consider cloud computing adoption. We hope the publication of the research would also benefit the public to adopt cloud computing.

Symmetrically private information retrieval based on blind quantum computing

NASA Astrophysics Data System (ADS)

Sun, Zhiwei; Yu, Jianping; Wang, Ping; Xu, Lingling

2015-05-01

Universal blind quantum computation (UBQC) is a new secure quantum computing protocol which allows a user Alice who does not have any sophisticated quantum technology to delegate her computing to a server Bob without leaking any privacy. Using the features of UBQC, we propose a protocol to achieve symmetrically private information retrieval, which allows a quantum limited Alice to query an item from Bob with a fully fledged quantum computer; meanwhile, the privacy of both parties is preserved. The security of our protocol is based on the assumption that malicious Alice has no quantum computer, which avoids the impossibility proof of Lo. For the honest Alice, she is almost classical and only requires minimal quantum resources to carry out the proposed protocol. Therefore, she does not need any expensive laboratory which can maintain the coherence of complicated quantum experimental setups.

Planning and management of cloud computing networks

NASA Astrophysics Data System (ADS)

Larumbe, Federico

The evolution of the Internet has a great impact on a big part of the population. People use it to communicate, query information, receive news, work, and as entertainment. Its extraordinary usefulness as a communication media made the number of applications and technological resources explode. However, that network expansion comes at the cost of an important power consumption. If the power consumption of telecommunication networks and data centers is considered as the power consumption of a country, it would rank at the 5 th place in the world. Furthermore, the number of servers in the world is expected to grow by a factor of 10 between 2013 and 2020. This context motivates us to study techniques and methods to allocate cloud computing resources in an optimal way with respect to cost, quality of service (QoS), power consumption, and environmental impact. The results we obtained from our test cases show that besides minimizing capital expenditures (CAPEX) and operational expenditures (OPEX), the response time can be reduced up to 6 times, power consumption by 30%, and CO2 emissions by a factor of 60. Cloud computing provides dynamic access to IT resources as a service. In this paradigm, programs are executed in servers connected to the Internet that users access from their computers and mobile devices. The first advantage of this architecture is to reduce the time of application deployment and interoperability, because a new user only needs a web browser and does not need to install software on local computers with specific operating systems. Second, applications and information are available from everywhere and with any device with an Internet access. Also, servers and IT resources can be dynamically allocated depending on the number of users and workload, a feature called elasticity. This thesis studies the resource management of cloud computing networks and is divided in three main stages. We start by analyzing the planning of cloud computing networks to get a comprehensive vision. The first question to be solved is what are the optimal data center locations. We found that the location of each data center has a big impact on cost, QoS, power consumption, and greenhouse gas emissions. An optimization problem with a multi-criteria objective function is proposed to decide jointly the optimal location of data centers and software components, link capacities, and information routing. Once the network planning has been analyzed, the problem of dynamic resource provisioning in real time is addressed. In this context, virtualization is a key technique in cloud computing because each server can be shared by multiple Virtual Machines (VMs) and the total power consumption can be reduced. In the same line of location problems, we propose a Green Cloud Broker that optimizes VM placement across multiple data centers. In fact, when multiple data centers are considered, response time can be reduced by placing VMs close to users, cost can be minimized, power consumption can be optimized by using energy efficient data centers, and CO2 emissions can be decreased by choosing data centers provided with renewable energy sources. The third stage of the analysis is the short-term management of a cloud data center. In particular, a method is proposed to assign VMs to servers by considering communication traffic among VMs. Cloud data centers receive new applications over time and these applications need on-demand resource provisioning. Each application is composed of multiple types of VMs that interact among themselves. A program called scheduler must place each new VM in a server and that impacts the QoS and power consumption. Our method places VMs that communicate among themselves in servers that are close to each other in the network topology, thus reducing communication delay and increasing the throughput available among VMs. Furthermore, the power consumption of each type of server is considered and the most efficient ones are chosen to place the VMs. The number of VMs of each application can be dynamically changed to match the workload and servers not needed in a particular period can be suspended to save energy. The methodology developed is based on Mixed Integer Programming (MIP) models to formalize the problems and use state of the art optimization solvers. Then, heuristics are developed to solve cases with more than 1,000 potential data center locations for the planning problem, 1,000 nodes for the cloud broker, and 128,000 servers for the VM placement problem. Solutions with very short optimality gaps, between 0% and 1.95%, are obtained, and execution time in the order of minutes for the planning problem and less than a second for real time cases. We consider that this thesis on resource provisioning of cloud computing networks includes important contributions on this research area, and innovative commercial applications based on the proposed methods have promising future.

iTools: A Framework for Classification, Categorization and Integration of Computational Biology Resources

PubMed Central

Dinov, Ivo D.; Rubin, Daniel; Lorensen, William; Dugan, Jonathan; Ma, Jeff; Murphy, Shawn; Kirschner, Beth; Bug, William; Sherman, Michael; Floratos, Aris; Kennedy, David; Jagadish, H. V.; Schmidt, Jeanette; Athey, Brian; Califano, Andrea; Musen, Mark; Altman, Russ; Kikinis, Ron; Kohane, Isaac; Delp, Scott; Parker, D. Stott; Toga, Arthur W.

2008-01-01

The advancement of the computational biology field hinges on progress in three fundamental directions – the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources–data, software tools and web-services. The iTools design, implementation and resource meta - data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long-term resource management. We demonstrate several applications of iTools as a framework for integrated bioinformatics. iTools and the complete details about its specifications, usage and interfaces are available at the iTools web page http://iTools.ccb.ucla.edu. PMID:18509477

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.

Humanity's unsustainable environmental footprint.

PubMed

Hoekstra, Arjen Y; Wiedmann, Thomas O

2014-06-06

Within the context of Earth's limited natural resources and assimilation capacity, the current environmental footprint of humankind is not sustainable. Assessing land, water, energy, material, and other footprints along supply chains is paramount in understanding the sustainability, efficiency, and equity of resource use from the perspective of producers, consumers, and government. We review current footprints and relate those to maximum sustainable levels, highlighting the need for future work on combining footprints, assessing trade-offs between them, improving computational techniques, estimating maximum sustainable footprint levels, and benchmarking efficiency of resource use. Ultimately, major transformative changes in the global economy are necessary to reduce humanity's environmental footprint to sustainable levels. Copyright © 2014, American Association for the Advancement of Science.

Proposal for a Security Management in Cloud Computing for Health Care

PubMed Central

Dzombeta, Srdan; Brandis, Knud

2014-01-01

Cloud computing is actually one of the most popular themes of information systems research. Considering the nature of the processed information especially health care organizations need to assess and treat specific risks according to cloud computing in their information security management system. Therefore, in this paper we propose a framework that includes the most important security processes regarding cloud computing in the health care sector. Starting with a framework of general information security management processes derived from standards of the ISO 27000 family the most important information security processes for health care organizations using cloud computing will be identified considering the main risks regarding cloud computing and the type of information processed. The identified processes will help a health care organization using cloud computing to focus on the most important ISMS processes and establish and operate them at an appropriate level of maturity considering limited resources. PMID:24701137

Proposal for a security management in cloud computing for health care.

PubMed

Haufe, Knut; Dzombeta, Srdan; Brandis, Knud

2014-01-01

Cloud computing is actually one of the most popular themes of information systems research. Considering the nature of the processed information especially health care organizations need to assess and treat specific risks according to cloud computing in their information security management system. Therefore, in this paper we propose a framework that includes the most important security processes regarding cloud computing in the health care sector. Starting with a framework of general information security management processes derived from standards of the ISO 27000 family the most important information security processes for health care organizations using cloud computing will be identified considering the main risks regarding cloud computing and the type of information processed. The identified processes will help a health care organization using cloud computing to focus on the most important ISMS processes and establish and operate them at an appropriate level of maturity considering limited resources.

The application of cloud computing to scientific workflows: a study of cost and performance.

PubMed

Berriman, G Bruce; Deelman, Ewa; Juve, Gideon; Rynge, Mats; Vöckler, Jens-S

2013-01-28

The current model of transferring data from data centres to desktops for analysis will soon be rendered impractical by the accelerating growth in the volume of science datasets. Processing will instead often take place on high-performance servers co-located with data. Evaluations of how new technologies such as cloud computing would support such a new distributed computing model are urgently needed. Cloud computing is a new way of purchasing computing and storage resources on demand through virtualization technologies. We report here the results of investigations of the applicability of commercial cloud computing to scientific computing, with an emphasis on astronomy, including investigations of what types of applications can be run cheaply and efficiently on the cloud, and an example of an application well suited to the cloud: processing a large dataset to create a new science product.

``Carbon Credits'' for Resource-Bounded Computations Using Amortised Analysis

NASA Astrophysics Data System (ADS)

Jost, Steffen; Loidl, Hans-Wolfgang; Hammond, Kevin; Scaife, Norman; Hofmann, Martin

Bounding resource usage is important for a number of areas, notably real-time embedded systems and safety-critical systems. In this paper, we present a fully automatic static type-based analysis for inferring upper bounds on resource usage for programs involving general algebraic datatypes and full recursion. Our method can easily be used to bound any countable resource, without needing to revisit proofs. We apply the analysis to the important metrics of worst-case execution time, stack- and heap-space usage. Our results from several realistic embedded control applications demonstrate good matches between our inferred bounds and measured worst-case costs for heap and stack usage. For time usage we infer good bounds for one application. Where we obtain less tight bounds, this is due to the use of software floating-point libraries.

Advanced Optical Burst Switched Network Concepts

NASA Astrophysics Data System (ADS)

Nejabati, Reza; Aracil, Javier; Castoldi, Piero; de Leenheer, Marc; Simeonidou, Dimitra; Valcarenghi, Luca; Zervas, Georgios; Wu, Jian

In recent years, as the bandwidth and the speed of networks have increased significantly, a new generation of network-based applications using the concept of distributed computing and collaborative services is emerging (e.g., Grid computing applications). The use of the available fiber and DWDM infrastructure for these applications is a logical choice offering huge amounts of cheap bandwidth and ensuring global reach of computing resources [230]. Currently, there is a great deal of interest in deploying optical circuit (wavelength) switched network infrastructure for distributed computing applications that require long-lived wavelength paths and address the specific needs of a small number of well-known users. Typical users are particle physicists who, due to their international collaborations and experiments, generate enormous amounts of data (Petabytes per year). These users require a network infrastructures that can support processing and analysis of large datasets through globally distributed computing resources [230]. However, providing wavelength granularity bandwidth services is not an efficient and scalable solution for applications and services that address a wider base of user communities with different traffic profiles and connectivity requirements. Examples of such applications may be: scientific collaboration in smaller scale (e.g., bioinformatics, environmental research), distributed virtual laboratories (e.g., remote instrumentation), e-health, national security and defense, personalized learning environments and digital libraries, evolving broadband user services (i.e., high resolution home video editing, real-time rendering, high definition interactive TV). As a specific example, in e-health services and in particular mammography applications due to the size and quantity of images produced by remote mammography, stringent network requirements are necessary. Initial calculations have shown that for 100 patients to be screened remotely, the network would have to securely transport 1.2 GB of data every 30 s [230]. According to the above explanation it is clear that these types of applications need a new network infrastructure and transport technology that makes large amounts of bandwidth at subwavelength granularity, storage, computation, and visualization resources potentially available to a wide user base for specified time durations. As these types of collaborative and network-based applications evolve addressing a wide range and large number of users, it is infeasible to build dedicated networks for each application type or category. Consequently, there should be an adaptive network infrastructure able to support all application types, each with their own access, network, and resource usage patterns. This infrastructure should offer flexible and intelligent network elements and control mechanism able to deploy new applications quickly and efficiently.

A Boundary Delineation System for the Bureau of Ocean Energy Management

NASA Astrophysics Data System (ADS)

Vandegraft, Douglas L.

2018-05-01

Federal government mapping of the offshore areas of the United States in support of the development of oil and gas resources began in 1954. The first mapping system utilized a network of rectangular blocks defined by State Plane coordinates which was later revised to utilize the Universal Transverse Mercator grid. Creation of offshore boundaries directed by the Submerged Lands Act and Outer Continental Shelf Lands Act were mathematically determined using early computer programs that performed the required computations, but required many steps. The Bureau of Ocean Energy Management has revised these antiquated methods using GIS technology which provide the required accuracy and produce the mapping products needed for leasing of energy resources, including renewable energy projects, on the outer continental shelf. (Note: this is an updated version of a paper of the same title written and published in 2015).

Putting Order Into the Cloud: Object-oriented UML-based Rule Enforcement for Document and Application Organization

DTIC Science & Technology

2010-09-01

Cloud computing describes a new distributed computing paradigm for IT data and services that involves over-the-Internet provision of dynamically scalable and often virtualized resources. While cost reduction and flexibility in storage, services, and maintenance are important considerations when deciding on whether or how to migrate data and applications to the cloud, large organizations like the Department of Defense need to consider the organization and structure of data on the cloud and the operations on such data in order to reap the full benefit of cloud

The Future is Hera! Analyzing Astronomical Over the Internet

NASA Technical Reports Server (NTRS)

Valencic, L. A.; Chai, P.; Pence, W.; Shafer, R.; Snowden, S.

2008-01-01

Hera is the data processing facility provided by the High Energy Astrophysics Science Archive Research Center (HEASARC) at the NASA Goddard Space Flight Center for analyzing astronomical data. Hera provides all the pre-installed software packages, local disk space, and computing resources need to do general processing of FITS format data files residing on the users local computer, and to do research using the publicly available data from the High ENergy Astrophysics Division. Qualified students, educators and researchers may freely use the Hera services over the internet of research and educational purposes.

Evolving Storage and Cyber Infrastructure at the NASA Center for Climate Simulation

NASA Technical Reports Server (NTRS)

Salmon, Ellen; Duffy, Daniel; Spear, Carrie; Sinno, Scott; Vaughan, Garrison; Bowen, Michael

2018-01-01

This talk will describe recent developments at the NASA Center for Climate Simulation, which is funded by NASAs Science Mission Directorate, and supports the specialized data storage and computational needs of weather, ocean, and climate researchers, as well as astrophysicists, heliophysicists, and planetary scientists. To meet requirements for higher-resolution, higher-fidelity simulations, the NCCS augments its High Performance Computing (HPC) and storage retrieval environment. As the petabytes of model and observational data grow, the NCCS is broadening data services offerings and deploying and expanding virtualization resources for high performance analytics.

Energy Awareness and Scheduling in Mobile Devices and High End Computing

ERIC Educational Resources Information Center

Pawaskar, Sachin S.

2013-01-01

In the context of the big picture as energy demands rise due to growing economies and growing populations, there will be greater emphasis on sustainable supply, conservation, and efficient usage of this vital resource. Even at a smaller level, the need for minimizing energy consumption continues to be compelling in embedded, mobile, and server…

Utilizing Technology to Examine the Impacts of Academic Program Plans on Faculty Staffing Levels. AIR 1984 Annual Forum Paper.

ERIC Educational Resources Information Center

Spiro, Louis M.; Campbell, Jill F.

The development and use of a campus-based computerized faculty staffing model is described. In addition to considering market demands for current and proposed programs, decisionmakers need to consider how program development, modification, and elimination affect the total college faculty resource base. The application of computer technology,…

Librarians on the Loose: Breaking out of the Library to Create a Culture of Literacy

ERIC Educational Resources Information Center

Lawrence, Ellen

2014-01-01

With the influx of technology, school library programs started to adapt traditional services by embracing new innovative resources. However, even with online research databases and cloud computing, most school libraries still occupy a fixed physical space in the school, a destination for students and teachers when they need help with reading or…

An Investigation of the Determinants of Employees' Decisions to Use Organizational Computing Resources for Non-Work Purposes

ERIC Educational Resources Information Center

Campbell, Stephen Matthew

2010-01-01

Internet access in the workplace has become ubiquitous in many organizations. Often, employees need this access to perform their duties. However, many studies report a large percentage of employees use their work Internet access for non-work-related activities. These activities can result in reduced efficiency, increased vulnerability to cyber…

A two-phase method for timber supply analysis

Treesearch

Stephen Smith

1978-01-01

There is an increasing need to clarify the long-term wood supply implications of current harvesting rates. To assess the wood supply and to set timber production objectives, different linear programming techniques are applied to the short and long term. The transportation method is applied to the short term and the B. C. Forest Service computer-assisted resource...

Cloud Computing Implementation Organizational Success in the Department of Defense

DTIC Science & Technology

2014-03-27

advisor, I am grateful for your time and patience. My thesis committee, I have learned from our discussions that gave me the direction I needed to...instructors in the Information Resource Management program. I have learned much from my attendance at AFIT. MSgt Corey Perkins viii...29 6. TAM (Adapted from Venkatesh and Davis, 2000

Analyzing the requirements for a robust security criteria and management of multi-level security in the clouds

NASA Astrophysics Data System (ADS)

Farroha, Bassam S.; Farroha, Deborah L.

2011-06-01

The new corporate approach to efficient processing and storage is migrating from in-house service-center services to the newly coined approach of Cloud Computing. This approach advocates thin clients and providing services by the service provider over time-shared resources. The concept is not new, however the implementation approach presents a strategic shift in the way organizations provision and manage their IT resources. The requirements on some of the data sets targeted to be run on the cloud vary depending on the data type, originator, user, and confidentiality level. Additionally, the systems that fuse such data would have to deal with the classifying the product and clearing the computing resources prior to allowing new application to be executed. This indicates that we could end up with a multi-level security system that needs to follow specific rules and can send the output to a protected network and systems in order not to have data spill or contaminated resources. The paper discusses these requirements and potential impact on the cloud architecture. Additionally, the paper discusses the unexpected advantages of the cloud framework providing a sophisticated environment for information sharing and data mining.

Userscripts for the life sciences.

PubMed

Willighagen, Egon L; O'Boyle, Noel M; Gopalakrishnan, Harini; Jiao, Dazhi; Guha, Rajarshi; Steinbeck, Christoph; Wild, David J

2007-12-21

The web has seen an explosion of chemistry and biology related resources in the last 15 years: thousands of scientific journals, databases, wikis, blogs and resources are available with a wide variety of types of information. There is a huge need to aggregate and organise this information. However, the sheer number of resources makes it unrealistic to link them all in a centralised manner. Instead, search engines to find information in those resources flourish, and formal languages like Resource Description Framework and Web Ontology Language are increasingly used to allow linking of resources. A recent development is the use of userscripts to change the appearance of web pages, by on-the-fly modification of the web content. This opens possibilities to aggregate information and computational results from different web resources into the web page of one of those resources. Several userscripts are presented that enrich biology and chemistry related web resources by incorporating or linking to other computational or data sources on the web. The scripts make use of Greasemonkey-like plugins for web browsers and are written in JavaScript. Information from third-party resources are extracted using open Application Programming Interfaces, while common Universal Resource Locator schemes are used to make deep links to related information in that external resource. The userscripts presented here use a variety of techniques and resources, and show the potential of such scripts. This paper discusses a number of userscripts that aggregate information from two or more web resources. Examples are shown that enrich web pages with information from other resources, and show how information from web pages can be used to link to, search, and process information in other resources. Due to the nature of userscripts, scientists are able to select those scripts they find useful on a daily basis, as the scripts run directly in their own web browser rather than on the web server. This flexibility allows the scientists to tune the features of web resources to optimise their productivity.

Userscripts for the Life Sciences

PubMed Central

Willighagen, Egon L; O'Boyle, Noel M; Gopalakrishnan, Harini; Jiao, Dazhi; Guha, Rajarshi; Steinbeck, Christoph; Wild, David J

2007-01-01

Background The web has seen an explosion of chemistry and biology related resources in the last 15 years: thousands of scientific journals, databases, wikis, blogs and resources are available with a wide variety of types of information. There is a huge need to aggregate and organise this information. However, the sheer number of resources makes it unrealistic to link them all in a centralised manner. Instead, search engines to find information in those resources flourish, and formal languages like Resource Description Framework and Web Ontology Language are increasingly used to allow linking of resources. A recent development is the use of userscripts to change the appearance of web pages, by on-the-fly modification of the web content. This opens possibilities to aggregate information and computational results from different web resources into the web page of one of those resources. Results Several userscripts are presented that enrich biology and chemistry related web resources by incorporating or linking to other computational or data sources on the web. The scripts make use of Greasemonkey-like plugins for web browsers and are written in JavaScript. Information from third-party resources are extracted using open Application Programming Interfaces, while common Universal Resource Locator schemes are used to make deep links to related information in that external resource. The userscripts presented here use a variety of techniques and resources, and show the potential of such scripts. Conclusion This paper discusses a number of userscripts that aggregate information from two or more web resources. Examples are shown that enrich web pages with information from other resources, and show how information from web pages can be used to link to, search, and process information in other resources. Due to the nature of userscripts, scientists are able to select those scripts they find useful on a daily basis, as the scripts run directly in their own web browser rather than on the web server. This flexibility allows the scientists to tune the features of web resources to optimise their productivity. PMID:18154664

Quantum computation for solving linear systems

NASA Astrophysics Data System (ADS)

Cao, Yudong

Quantum computation is a subject born out of the combination between physics and computer science. It studies how the laws of quantum mechanics can be exploited to perform computations much more efficiently than current computers (termed classical computers as oppose to quantum computers). The thesis starts by introducing ideas from quantum physics and theoretical computer science and based on these ideas, introducing the basic concepts in quantum computing. These introductory discussions are intended for non-specialists to obtain the essential knowledge needed for understanding the new results presented in the subsequent chapters. After introducing the basics of quantum computing, we focus on the recently proposed quantum algorithm for linear systems. The new results include i) special instances of quantum circuits that can be implemented using current experimental resources; ii) detailed quantum algorithms that are suitable for a broader class of linear systems. We show that for some particular problems the quantum algorithm is able to achieve exponential speedup over their classical counterparts.

A data management system to enable urgent natural disaster computing

NASA Astrophysics Data System (ADS)

Leong, Siew Hoon; Kranzlmüller, Dieter; Frank, Anton

2014-05-01

Civil protection, in particular natural disaster management, is very important to most nations and civilians in the world. When disasters like flash floods, earthquakes and tsunamis are expected or have taken place, it is of utmost importance to make timely decisions for managing the affected areas and reduce casualties. Computer simulations can generate information and provide predictions to facilitate this decision making process. Getting the data to the required resources is a critical requirement to enable the timely computation of the predictions. An urgent data management system to support natural disaster computing is thus necessary to effectively carry out data activities within a stipulated deadline. Since the trigger of a natural disaster is usually unpredictable, it is not always possible to prepare required resources well in advance. As such, an urgent data management system for natural disaster computing has to be able to work with any type of resources. Additional requirements include the need to manage deadlines and huge volume of data, fault tolerance, reliable, flexibility to changes, ease of usage, etc. The proposed data management platform includes a service manager to provide a uniform and extensible interface for the supported data protocols, a configuration manager to check and retrieve configurations of available resources, a scheduler manager to ensure that the deadlines can be met, a fault tolerance manager to increase the reliability of the platform and a data manager to initiate and perform the data activities. These managers will enable the selection of the most appropriate resource, transfer protocol, etc. such that the hard deadline of an urgent computation can be met for a particular urgent activity, e.g. data staging or computation. We associated 2 types of deadlines [2] with an urgent computing system. Soft-hard deadline: Missing a soft-firm deadline will render the computation less useful resulting in a cost that can have severe consequences Hard deadline: Missing a hard deadline renders the computation useless and results in full catastrophic consequences. A prototype of this system has a REST-based service manager. The REST-based implementation provides a uniform interface that is easy to use. New and upcoming file transfer protocols can easily be extended and accessed via the service manager. The service manager interacts with the other four managers to coordinate the data activities so that the fundamental natural disaster urgent computing requirement, i.e. deadline, can be fulfilled in a reliable manner. A data activity can include data storing, data archiving and data storing. Reliability is ensured by the choice of a network of managers organisation model[1] the configuration manager and the fault tolerance manager. With this proposed design, an easy to use, resource-independent data management system that can support and fulfill the computation of a natural disaster prediction within stipulated deadlines can thus be realised. References [1] H. G. Hegering, S. Abeck, and B. Neumair, Integrated management of networked systems - concepts, architectures, and their operational application, Morgan Kaufmann Publishers, 340 Pine Stret, Sixth Floor, San Francisco, CA 94104-3205, USA, 1999. [2] H. Kopetz, Real-time systems design principles for distributed embedded applications, second edition, Springer, LLC, 233 Spring Street, New York, NY 10013, USA, 2011. [3] S. H. Leong, A. Frank, and D. Kranzlmu¨ ller, Leveraging e-infrastructures for urgent computing, Procedia Computer Science 18 (2013), no. 0, 2177 - 2186, 2013 International Conference on Computational Science. [4] N. Trebon, Enabling urgent computing within the existing distributed computing infrastructure, Ph.D. thesis, University of Chicago, August 2011, http://people.cs.uchicago.edu/~ntrebon/docs/dissertation.pdf.

Statistics Online Computational Resource for Education

ERIC Educational Resources Information Center

Dinov, Ivo D.; Christou, Nicolas

2009-01-01

The Statistics Online Computational Resource (http://www.SOCR.ucla.edu) provides one of the largest collections of free Internet-based resources for probability and statistics education. SOCR develops, validates and disseminates two core types of materials--instructional resources and computational libraries. (Contains 2 figures.)

Adaptive Management of Computing and Network Resources for Spacecraft Systems

NASA Technical Reports Server (NTRS)

Pfarr, Barbara; Welch, Lonnie R.; Detter, Ryan; Tjaden, Brett; Huh, Eui-Nam; Szczur, Martha R. (Technical Monitor)

2000-01-01

It is likely that NASA's future spacecraft systems will consist of distributed processes which will handle dynamically varying workloads in response to perceived scientific events, the spacecraft environment, spacecraft anomalies and user commands. Since all situations and possible uses of sensors cannot be anticipated during pre-deployment phases, an approach for dynamically adapting the allocation of distributed computational and communication resources is needed. To address this, we are evolving the DeSiDeRaTa adaptive resource management approach to enable reconfigurable ground and space information systems. The DeSiDeRaTa approach embodies a set of middleware mechanisms for adapting resource allocations, and a framework for reasoning about the real-time performance of distributed application systems. The framework and middleware will be extended to accommodate (1) the dynamic aspects of intra-constellation network topologies, and (2) the complete real-time path from the instrument to the user. We are developing a ground-based testbed that will enable NASA to perform early evaluation of adaptive resource management techniques without the expense of first deploying them in space. The benefits of the proposed effort are numerous, including the ability to use sensors in new ways not anticipated at design time; the production of information technology that ties the sensor web together; the accommodation of greater numbers of missions with fewer resources; and the opportunity to leverage the DeSiDeRaTa project's expertise, infrastructure and models for adaptive resource management for distributed real-time systems.

An Architecture for Cross-Cloud System Management

NASA Astrophysics Data System (ADS)

Dodda, Ravi Teja; Smith, Chris; van Moorsel, Aad

The emergence of the cloud computing paradigm promises flexibility and adaptability through on-demand provisioning of compute resources. As the utilization of cloud resources extends beyond a single provider, for business as well as technical reasons, the issue of effectively managing such resources comes to the fore. Different providers expose different interfaces to their compute resources utilizing varied architectures and implementation technologies. This heterogeneity poses a significant system management problem, and can limit the extent to which the benefits of cross-cloud resource utilization can be realized. We address this problem through the definition of an architecture to facilitate the management of compute resources from different cloud providers in an homogenous manner. This preserves the flexibility and adaptability promised by the cloud computing paradigm, whilst enabling the benefits of cross-cloud resource utilization to be realized. The practical efficacy of the architecture is demonstrated through an implementation utilizing compute resources managed through different interfaces on the Amazon Elastic Compute Cloud (EC2) service. Additionally, we provide empirical results highlighting the performance differential of these different interfaces, and discuss the impact of this performance differential on efficiency and profitability.

Quantum Computing: Selected Internet Resources for Librarians, Researchers, and the Casually Curious

ERIC Educational Resources Information Center

Cirasella, Jill

2009-01-01

This article presents an annotated selection of the most important and informative Internet resources for learning about quantum computing, finding quantum computing literature, and tracking quantum computing news. All of the quantum computing resources described in this article are freely available, English-language web sites that fall into one…

Costs of cloud computing for a biometry department. A case study.

PubMed

Knaus, J; Hieke, S; Binder, H; Schwarzer, G

2013-01-01

"Cloud" computing providers, such as the Amazon Web Services (AWS), offer stable and scalable computational resources based on hardware virtualization, with short, usually hourly, billing periods. The idea of pay-as-you-use seems appealing for biometry research units which have only limited access to university or corporate data center resources or grids. This case study compares the costs of an existing heterogeneous on-site hardware pool in a Medical Biometry and Statistics department to a comparable AWS offer. The "total cost of ownership", including all direct costs, is determined for the on-site hardware, and hourly prices are derived, based on actual system utilization during the year 2011. Indirect costs, which are difficult to quantify are not included in this comparison, but nevertheless some rough guidance from our experience is given. To indicate the scale of costs for a methodological research project, a simulation study of a permutation-based statistical approach is performed using AWS and on-site hardware. In the presented case, with a system utilization of 25-30 percent and 3-5-year amortization, on-site hardware can result in smaller costs, compared to hourly rental in the cloud dependent on the instance chosen. Renting cloud instances with sufficient main memory is a deciding factor in this comparison. Costs for on-site hardware may vary, depending on the specific infrastructure at a research unit, but have only moderate impact on the overall comparison and subsequent decision for obtaining affordable scientific computing resources. Overall utilization has a much stronger impact as it determines the actual computing hours needed per year. Taking this into ac count, cloud computing might still be a viable option for projects with limited maturity, or as a supplement for short peaks in demand.

Threaded cognition: an integrated theory of concurrent multitasking.

PubMed

Salvucci, Dario D; Taatgen, Niels A

2008-01-01

The authors propose the idea of threaded cognition, an integrated theory of concurrent multitasking--that is, performing 2 or more tasks at once. Threaded cognition posits that streams of thought can be represented as threads of processing coordinated by a serial procedural resource and executed across other available resources (e.g., perceptual and motor resources). The theory specifies a parsimonious mechanism that allows for concurrent execution, resource acquisition, and resolution of resource conflicts, without the need for specialized executive processes. By instantiating this mechanism as a computational model, threaded cognition provides explicit predictions of how multitasking behavior can result in interference, or lack thereof, for a given set of tasks. The authors illustrate the theory in model simulations of several representative domains ranging from simple laboratory tasks such as dual-choice tasks to complex real-world domains such as driving and driver distraction. (c) 2008 APA, all rights reserved

Lessons learned from implementing a national infrastructure in Sweden for storage and analysis of next-generation sequencing data

PubMed Central

2013-01-01

Analyzing and storing data and results from next-generation sequencing (NGS) experiments is a challenging task, hampered by ever-increasing data volumes and frequent updates of analysis methods and tools. Storage and computation have grown beyond the capacity of personal computers and there is a need for suitable e-infrastructures for processing. Here we describe UPPNEX, an implementation of such an infrastructure, tailored to the needs of data storage and analysis of NGS data in Sweden serving various labs and multiple instruments from the major sequencing technology platforms. UPPNEX comprises resources for high-performance computing, large-scale and high-availability storage, an extensive bioinformatics software suite, up-to-date reference genomes and annotations, a support function with system and application experts as well as a web portal and support ticket system. UPPNEX applications are numerous and diverse, and include whole genome-, de novo- and exome sequencing, targeted resequencing, SNP discovery, RNASeq, and methylation analysis. There are over 300 projects that utilize UPPNEX and include large undertakings such as the sequencing of the flycatcher and Norwegian spruce. We describe the strategic decisions made when investing in hardware, setting up maintenance and support, allocating resources, and illustrate major challenges such as managing data growth. We conclude with summarizing our experiences and observations with UPPNEX to date, providing insights into the successful and less successful decisions made. PMID:23800020

Build It: Will They Come?

NASA Astrophysics Data System (ADS)

Corrie, Brian; Zimmerman, Todd

Scientific research is fundamentally collaborative in nature, and many of today's complex scientific problems require domain expertise in a wide range of disciplines. In order to create research groups that can effectively explore such problems, research collaborations are often formed that involve colleagues at many institutions, sometimes spanning a country and often spanning the world. An increasingly common manifestation of such a collaboration is the collaboratory (Bos et al., 2007), a “…center without walls in which the nation's researchers can perform research without regard to geographical location — interacting with colleagues, accessing instrumentation, sharing data and computational resources, and accessing information from digital libraries.” In order to bring groups together on such a scale, a wide range of components need to be available to researchers, including distributed computer systems, remote instrumentation, data storage, collaboration tools, and the financial and human resources to operate and run such a system (National Research Council, 1993). Media Spaces, as both a technology and a social facilitator, have the potential to meet many of these needs. In this chapter, we focus on the use of scientific media spaces (SMS) as a tool for supporting collaboration in scientific research. In particular, we discuss the design, deployment, and use of a set of SMS environments deployed by WestGrid and one of its collaborating organizations, the Centre for Interdisciplinary Research in the Mathematical and Computational Sciences (IRMACS) over a 5-year period.

Relating Solar Resource Variability to Cloud Type

NASA Astrophysics Data System (ADS)

Hinkelman, L. M.; Sengupta, M.

2012-12-01

Power production from renewable energy (RE) resources is rapidly increasing. Generation of renewable energy is quite variable since the solar and wind resources that form the inputs are, themselves, inherently variable. There is thus a need to understand the impact of renewable generation on the transmission grid. Such studies require estimates of high temporal and spatial resolution power output under various scenarios, which can be created from corresponding solar resource data. Satellite-based solar resource estimates are the best source of long-term solar irradiance data for the typically large areas covered by transmission studies. As satellite-based resource datasets are generally available at lower temporal and spatial resolution than required, there is, in turn, a need to downscale these resource data. Downscaling in both space and time requires information about solar irradiance variability, which is primarily a function of cloud types and properties. In this study, we analyze the relationship between solar resource variability and satellite-based cloud properties. One-minute resolution surface irradiance data were obtained from a number of stations operated by the National Oceanic and Atmospheric Administration (NOAA) under the Surface Radiation (SURFRAD) and Integrated Surface Irradiance Study (ISIS) networks as well as from NREL's Solar Radiation Research Laboratory (SRRL) in Golden, Colorado. Individual sites were selected so that a range of meteorological conditions would be represented. Cloud information at a nominal 4 km resolution and half hour intervals was derived from NOAA's Geostationary Operation Environmental Satellite (GOES) series of satellites. Cloud class information from the GOES data set was then used to select and composite irradiance data from the measurement sites. The irradiance variability for each cloud classification was characterized using general statistics of the fluxes themselves and their variability in time, as represented by ramps computed for time scales from 10 s to 0.5 hr. The statistical relationships derived using this method will be presented, comparing and contrasting the statistics computed for the different cloud types. The implications for downscaling irradiances from satellites or forecast models will also be discussed.

Resources and Approaches for Teaching Quantitative and Computational Skills in the Geosciences and Allied Fields

NASA Astrophysics Data System (ADS)

Orr, C. H.; Mcfadden, R. R.; Manduca, C. A.; Kempler, L. A.

2016-12-01

Teaching with data, simulations, and models in the geosciences can increase many facets of student success in the classroom, and in the workforce. Teaching undergraduates about programming and improving students' quantitative and computational skills expands their perception of Geoscience beyond field-based studies. Processing data and developing quantitative models are critically important for Geoscience students. Students need to be able to perform calculations, analyze data, create numerical models and visualizations, and more deeply understand complex systems—all essential aspects of modern science. These skills require students to have comfort and skill with languages and tools such as MATLAB. To achieve comfort and skill, computational and quantitative thinking must build over a 4-year degree program across courses and disciplines. However, in courses focused on Geoscience content it can be challenging to get students comfortable with using computational methods to answers Geoscience questions. To help bridge this gap, we have partnered with MathWorks to develop two workshops focused on collecting and developing strategies and resources to help faculty teach students to incorporate data, simulations, and models into the curriculum at the course and program levels. We brought together faculty members from the sciences, including Geoscience and allied fields, who teach computation and quantitative thinking skills using MATLAB to build a resource collection for teaching. These materials, and the outcomes of the workshops are freely available on our website. The workshop outcomes include a collection of teaching activities, essays, and course descriptions that can help faculty incorporate computational skills at the course or program level. The teaching activities include in-class assignments, problem sets, labs, projects, and toolboxes. These activities range from programming assignments to creating and using models. The outcomes also include workshop syntheses that highlights best practices, a set of webpages to support teaching with software such as MATLAB, and an interest group actively discussing aspects these issues in Geoscience and allied fields. Learn more and view the resources at http://serc.carleton.edu/matlab_computation2016/index.html

Barriers and benefits associated with nurses information seeking related to patient education needs on clinical nursing units.

PubMed

Jones, Josette; Schilling, Katherine; Pesut, Daniel

2011-01-01

The purpose of this study was to answer the following two questions: What are clinical nurses' rationales for their approaches to finding patient educational materials on the web? What are perceived barriers and benefits associated with the use of web-based information resources for patient education in the context of nursing clinical practice?Over 179 individual data units were analyzed to understand clinical nurses' rationales for their approaches to find patient educational materials on the web. Rationales were defined as those underlying catalysts or activators leading to an information need. Analyses found that the primary reasons why clinical nurses conducted web-based information searches included direct patient requests ( 9 requests), colleague requests (6 requests), building patient materials collections (4), patients' family requests (3), routine teaching (1), personal development (1), or staff development (1). From these data, four broad themes emerged: professional reasons, personal reasons, technology reasons, and organization reasons for selecting information resources. Content analysis identified 306 individual data units representing either 'benefits' (178 units) or 'barriers' (128) to the nurses' use of web resources for on-unit patient care. Inter-rater reliability was assessed and found to be excellent (r = 0.943 to 0.961). The primary themes that emerged as barriers to the used of web-based resources included: 1) time requirements to perform a search, 2) nurses' experience and knowledge about the resources or required technology, 3) specific characteristics of individuals electronic information resources, and 4) organizational procedures and policies. Three primary themes that represented the benefits of using web-based resources were also identified: 1) past experiences and knowledge of a specific resource or the required technologies, 2) availability and accessibility on the unit, and 3) specific characteristics of individual information tool. In many cases, nurses commented on specific characteristics or features of favorite information resources. Favorite sites included a variety or reputable health care organizations that displayed context in text, audio, and/or video. In addition such sites were described as easy-to read and provided content related to patient-focused information or specific content such as toll free telephone contact numbers.Information searching is the interaction between and among information users and computer-based information systems. Information seeking is becoming an important part of the knowledge work of nurses. Information seeking and searching intersects with the field of human computer interaction (HCI), which focuses on all aspects of human, and computer interactions. Users of an information system are understood as "actors" in situations, with a set of skills and shared practices based on work experiences with others. Designing better tools and developing information searching strategies that support, extend, and transform practices, begins by asking: Who are the users? What are the tasks? What is the interplay between the technology and the organization of the task? This study contributes fundamental data and information about the rationales nurses use in information seeking tasks. In addition it provides empirical evidences regarding barriers and benefits of information seeking in the context of patient education needs in inpatient clinical settings.

From Three-Photon Greenberger-Horne-Zeilinger States to Ballistic Universal Quantum Computation.

PubMed

Gimeno-Segovia, Mercedes; Shadbolt, Pete; Browne, Dan E; Rudolph, Terry

2015-07-10

Single photons, manipulated using integrated linear optics, constitute a promising platform for universal quantum computation. A series of increasingly efficient proposals have shown linear-optical quantum computing to be formally scalable. However, existing schemes typically require extensive adaptive switching, which is experimentally challenging and noisy, thousands of photon sources per renormalized qubit, and/or large quantum memories for repeat-until-success strategies. Our work overcomes all these problems. We present a scheme to construct a cluster state universal for quantum computation, which uses no adaptive switching, no large memories, and which is at least an order of magnitude more resource efficient than previous passive schemes. Unlike previous proposals, it is constructed entirely from loss-detecting gates and offers a robustness to photon loss. Even without the use of an active loss-tolerant encoding, our scheme naturally tolerates a total loss rate ∼1.6% in the photons detected in the gates. This scheme uses only 3 Greenberger-Horne-Zeilinger states as a resource, together with a passive linear-optical network. We fully describe and model the iterative process of cluster generation, including photon loss and gate failure. This demonstrates that building a linear-optical quantum computer needs to be less challenging than previously thought.

Computer-facilitated rapid HIV testing in emergency care settings: provider and patient usability and acceptability.

PubMed

Spielberg, Freya; Kurth, Ann E; Severynen, Anneleen; Hsieh, Yu-Hsiang; Moring-Parris, Daniel; Mackenzie, Sara; Rothman, Richard

2011-06-01

Providers in emergency care settings (ECSs) often face barriers to expanded HIV testing. We undertook formative research to understand the potential utility of a computer tool, "CARE," to facilitate rapid HIV testing in ECSs. Computer tool usability and acceptability were assessed among 35 adult patients, and provider focus groups were held, in two ECSs in Washington State and Maryland. The computer tool was usable by patients of varying computer literacy. Patients appreciated the tool's privacy and lack of judgment and their ability to reflect on HIV risks and create risk reduction plans. Staff voiced concerns regarding ECS-based HIV testing generally, including resources for follow-up of newly diagnosed people. Computer-delivered HIV testing support was acceptable and usable among low-literacy populations in two ECSs. Such tools may help circumvent some practical barriers associated with routine HIV testing in busy settings though linkages to care will still be needed.

Methods for Prediction of High-Speed Reacting Flows in Aerospace Propulsion

NASA Technical Reports Server (NTRS)

Drummond, J. Philip

2014-01-01

Research to develop high-speed airbreathing aerospace propulsion systems was underway in the late 1950s. A major part of the effort involved the supersonic combustion ramjet, or scramjet, engine. Work had also begun to develop computational techniques for solving the equations governing the flow through a scramjet engine. However, scramjet technology and the computational methods to assist in its evolution would remain apart for another decade. The principal barrier was that the computational methods needed for engine evolution lacked the computer technology required for solving the discrete equations resulting from the numerical methods. Even today, computer resources remain a major pacing item in overcoming this barrier. Significant advances have been made over the past 35 years, however, in modeling the supersonic chemically reacting flow in a scramjet combustor. To see how scramjet development and the required computational tools finally merged, we briefly trace the evolution of the technology in both areas.

Computational materials science and engineering education: A survey of trends and needs

NASA Astrophysics Data System (ADS)

Thornton, K.; Nola, Samanthule; Edwin Garcia, R.; Asta, Mark; Olson, G. B.

2009-10-01

Results from a recent reassessment of the state of computational materials science and engineering (CMSE) education are reported. Surveys were distributed to the chairs and heads of materials programs, faculty members engaged in computational research, and employers of materials scientists and engineers, mainly in the United States. The data was compiled to assess current course offerings related to CMSE, the general climate for introducing computational methods in MSE curricula, and the requirements from the employers’ viewpoint. Furthermore, the available educational resources and their utilization by the community are examined. The surveys show a general support for integrating computational content into MSE education. However, they also reflect remaining issues with implementation, as well as a gap between the tools being taught in courses and those that are used by employers. Overall, the results suggest the necessity for a comprehensively developed vision and plans to further the integration of computational methods into MSE curricula.

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.

Computer simulation as a teaching aid in pharmacy management--Part 1: Principles of accounting.

PubMed

Morrison, D J

1987-06-01

The need for pharmacists to develop management expertise through participation in formal courses is now widely acknowledged. Many schools of pharmacy lay the foundations for future management training by providing introductory courses as an integral or elective part of the undergraduate syllabus. The benefit of such courses may, however, be limited by the lack of opportunity for the student to apply the concepts and procedures in a practical working environment. Computer simulations provide a means to overcome this problem, particularly in the field of resource management. In this, the first of two articles, the use of a computer model to demonstrate basic accounting principles is described.

Reinforcement learning techniques for controlling resources in power networks

NASA Astrophysics Data System (ADS)

Kowli, Anupama Sunil

As power grids transition towards increased reliance on renewable generation, energy storage and demand response resources, an effective control architecture is required to harness the full functionalities of these resources. There is a critical need for control techniques that recognize the unique characteristics of the different resources and exploit the flexibility afforded by them to provide ancillary services to the grid. The work presented in this dissertation addresses these needs. Specifically, new algorithms are proposed, which allow control synthesis in settings wherein the precise distribution of the uncertainty and its temporal statistics are not known. These algorithms are based on recent developments in Markov decision theory, approximate dynamic programming and reinforcement learning. They impose minimal assumptions on the system model and allow the control to be "learned" based on the actual dynamics of the system. Furthermore, they can accommodate complex constraints such as capacity and ramping limits on generation resources, state-of-charge constraints on storage resources, comfort-related limitations on demand response resources and power flow limits on transmission lines. Numerical studies demonstrating applications of these algorithms to practical control problems in power systems are discussed. Results demonstrate how the proposed control algorithms can be used to improve the performance and reduce the computational complexity of the economic dispatch mechanism in a power network. We argue that the proposed algorithms are eminently suitable to develop operational decision-making tools for large power grids with many resources and many sources of uncertainty.

Analysis of the availability of the resources necessary for urgent and emergency healthcare in São Paulo between 2009-2013.

PubMed

Coimbra, Silvana Hebe; Camanho, Eliete Dominguez Lopez; Heringer, Lindolfo Carlos; Botelho, Ricardo Vieira; Vasconcellos, Cidia

2017-06-01

The Regulatory Complex is the structure that operationalizes actions for making resources available to meet the needs of urgent and emergency care in the municipality of São Paulo. In the case of urgent care, needs are immediate and associated with high morbidity and mortality. To identify the most frequently requested resources, the resolution capacity and the mortality rate associated with the unavailability of a certain resource. Our study was based on data from medical bulletins issued by the Urgent and Emergency Regulation Center (CRUE) in the city of São Paulo from 2009 to 2013. 91,823 requests were made over the five years of the study (2009 to 2013). Neurosurgery requests were the most frequent in all years (4,828, 5,159, 4,251, 5,008 and 4,394, respectively), followed by computed tomography (CT) scans, adult intensive care unit (ICU) beds, cardiac catheterization, and pediatric ICU beds. On average, requests for neurosurgery, adult ICU, pediatric ICU, CT scans, catheterization and vascular surgery were answered in 70%, 27%, 39%, 97%, 87% and 77% of cases. The total number of deaths relating to requests for neurosurgery, CT scans, adult ICU, pediatric ICU, catheterization and vascular surgeon assessment were 182, 9, 1,536, 1,536, 135, 49 and 24 cases, respectively. There is a lack of resources to meet urgent and emergency needs in the city of São Paulo.

Fluid/Structure Interaction Studies of Aircraft Using High Fidelity Equations on Parallel Computers

NASA Technical Reports Server (NTRS)

Guruswamy, Guru; VanDalsem, William (Technical Monitor)

1994-01-01

Abstract Aeroelasticity which involves strong coupling of fluids, structures and controls is an important element in designing an aircraft. Computational aeroelasticity using low fidelity methods such as the linear aerodynamic flow equations coupled with the modal structural equations are well advanced. Though these low fidelity approaches are computationally less intensive, they are not adequate for the analysis of modern aircraft such as High Speed Civil Transport (HSCT) and Advanced Subsonic Transport (AST) which can experience complex flow/structure interactions. HSCT can experience vortex induced aeroelastic oscillations whereas AST can experience transonic buffet associated structural oscillations. Both aircraft may experience a dip in the flutter speed at the transonic regime. For accurate aeroelastic computations at these complex fluid/structure interaction situations, high fidelity equations such as the Navier-Stokes for fluids and the finite-elements for structures are needed. Computations using these high fidelity equations require large computational resources both in memory and speed. Current conventional super computers have reached their limitations both in memory and speed. As a result, parallel computers have evolved to overcome the limitations of conventional computers. This paper will address the transition that is taking place in computational aeroelasticity from conventional computers to parallel computers. The paper will address special techniques needed to take advantage of the architecture of new parallel computers. Results will be illustrated from computations made on iPSC/860 and IBM SP2 computer by using ENSAERO code that directly couples the Euler/Navier-Stokes flow equations with high resolution finite-element structural equations.

JobCenter: an open source, cross-platform, and distributed job queue management system optimized for scalability and versatility

PubMed Central

2012-01-01

Background Laboratories engaged in computational biology or bioinformatics frequently need to run lengthy, multistep, and user-driven computational jobs. Each job can tie up a computer for a few minutes to several days, and many laboratories lack the expertise or resources to build and maintain a dedicated computer cluster. Results JobCenter is a client–server application and framework for job management and distributed job execution. The client and server components are both written in Java and are cross-platform and relatively easy to install. All communication with the server is client-driven, which allows worker nodes to run anywhere (even behind external firewalls or “in the cloud”) and provides inherent load balancing. Adding a worker node to the worker pool is as simple as dropping the JobCenter client files onto any computer and performing basic configuration, which provides tremendous ease-of-use, flexibility, and limitless horizontal scalability. Each worker installation may be independently configured, including the types of jobs it is able to run. Executed jobs may be written in any language and may include multistep workflows. Conclusions JobCenter is a versatile and scalable distributed job management system that allows laboratories to very efficiently distribute all computational work among available resources. JobCenter is freely available at http://code.google.com/p/jobcenter/. PMID:22846423

The Requirements and Design of the Rapid Prototyping Capabilities System

NASA Astrophysics Data System (ADS)

Haupt, T. A.; Moorhead, R.; O'Hara, C.; Anantharaj, V.

2006-12-01

The Rapid Prototyping Capabilities (RPC) system will provide the capability to rapidly evaluate innovative methods of linking science observations. To this end, the RPC will provide the capability to integrate the software components and tools needed to evaluate the use of a wide variety of current and future NASA sensors, numerical models, and research results, model outputs, and knowledge, collectively referred to as "resources". It is assumed that the resources are geographically distributed, and thus RPC will provide the support for the location transparency of the resources. The RPC system requires providing support for: (1) discovery, semantic understanding, secure access and transport mechanisms for data products available from the known data provides; (2) data assimilation and geo- processing tools for all data transformations needed to match given data products to the model input requirements; (3) model management including catalogs of models and model metadata, and mechanisms for creation environments for model execution; and (4) tools for model output analysis and model benchmarking. The challenge involves developing a cyberinfrastructure for a coordinated aggregate of software, hardware and other technologies, necessary to facilitate RPC experiments, as well as human expertise to provide an integrated, "end-to-end" platform to support the RPC objectives. Such aggregation is to be achieved through a horizontal integration of loosely coupled services. The cyberinfrastructure comprises several software layers. At the bottom, the Grid fabric encompasses network protocols, optical networks, computational resources, storage devices, and sensors. At the top, applications use workload managers to coordinate their access to physical resources. Applications are not tightly bounded to a single physical resource. Instead, they bind dynamically to resources (i.e., they are provisioned) via a common grid infrastructure layer. For the RPC system, the cyberinfrastructure must support organizing computations (or "data transformations" in general) into complex workflows with resource discovery, automatic resource allocation, monitoring, preserving provenance as well as to aggregate heterogeneous, distributed data into knowledge databases. Such service orchestration is the responsibility of the "collective services" layer. For RPC, this layer will be based on Java Business Integration (JBI, [JSR-208]) specification which is a standards-based integration platform that combines messaging, web services, data transformation, and intelligent routing to reliably connect and coordinate the interaction of significant numbers of diverse applications (plug-in components) across organizational boundaries. JBI concept is a new approach to integration that can provide the underpinnings for loosely coupled, highly distributed integration network that can scale beyond the limits of currently used hub-and-spoke brokers. This presentation discusses the requirements, design and early prototype of the NASA-sponsored RPC system under development at Mississippi State University, demonstrating the integration of data provisioning mechanisms, data transformation tools and computational models into a single interoperable system enabling rapid execution of RPC experiments.

A Flexible Computational Framework Using R and Map-Reduce for Permutation Tests of Massive Genetic Analysis of Complex Traits.

PubMed

Mahjani, Behrang; Toor, Salman; Nettelblad, Carl; Holmgren, Sverker

2017-01-01

In quantitative trait locus (QTL) mapping significance of putative QTL is often determined using permutation testing. The computational needs to calculate the significance level are immense, 10 4 up to 10 8 or even more permutations can be needed. We have previously introduced the PruneDIRECT algorithm for multiple QTL scan with epistatic interactions. This algorithm has specific strengths for permutation testing. Here, we present a flexible, parallel computing framework for identifying multiple interacting QTL using the PruneDIRECT algorithm which uses the map-reduce model as implemented in Hadoop. The framework is implemented in R, a widely used software tool among geneticists. This enables users to rearrange algorithmic steps to adapt genetic models, search algorithms, and parallelization steps to their needs in a flexible way. Our work underlines the maturity of accessing distributed parallel computing for computationally demanding bioinformatics applications through building workflows within existing scientific environments. We investigate the PruneDIRECT algorithm, comparing its performance to exhaustive search and DIRECT algorithm using our framework on a public cloud resource. We find that PruneDIRECT is vastly superior for permutation testing, and perform 2 ×10 5 permutations for a 2D QTL problem in 15 hours, using 100 cloud processes. We show that our framework scales out almost linearly for a 3D QTL search.

Conference summary: computers in respiratory care.

PubMed

Nelson, Steven B

2004-05-01

Computers and data management in respiratory care reflect the larger practices of hospital information systems: the diversity of conference topics provides evidence. Respiratory care computing has shown a steady, slow progression from writing programs that calculate shunt equations to departmental management systems. Wider acceptance and utilization have been stifled by costs, both initial and on-going. Several authors pointed out the savings that were realized from information systems exceeded the costs of implementation and maintenance. The most significant finding from one of the presentations was that no other structure or skilled personnel could provide respiratory care more efficiently or cost-effectively than respiratory therapists. Online information resources have increased, in forms ranging from peer-reviewed journals to corporate-sponsored advertising posing as authoritative treatment regimens. Practitioners and patients need to know how to use these resources as well as how to judge the value of information they present. Departments are using computers for training on a schedule that is more convenient for the staff, providing information in a timely manner and potentially in more useful formats. Portable devices, such as personal digital assistants (PDAs) have improved the ability not only to share data to dispersed locations, but also to collect data at the point of care, thus greatly improving data capture. Ventilators are changing from simple automated bellows to complex systems collecting numerous respiratory parameters and offering feedback to improve ventilation. Clinical databases routinely collect information from a wide variety of resources and can be used for analysis to improve patient outcomes. What could possibly go wrong?

Exploiting Parallel R in the Cloud with SPRINT

PubMed Central

Piotrowski, M.; McGilvary, G.A.; Sloan, T. M.; Mewissen, M.; Lloyd, A.D.; Forster, T.; Mitchell, L.; Ghazal, P.; Hill, J.

2012-01-01

Background Advances in DNA Microarray devices and next-generation massively parallel DNA sequencing platforms have led to an exponential growth in data availability but the arising opportunities require adequate computing resources. High Performance Computing (HPC) in the Cloud offers an affordable way of meeting this need. Objectives Bioconductor, a popular tool for high-throughput genomic data analysis, is distributed as add-on modules for the R statistical programming language but R has no native capabilities for exploiting multi-processor architectures. SPRINT is an R package that enables easy access to HPC for genomics researchers. This paper investigates: setting up and running SPRINT-enabled genomic analyses on Amazon’s Elastic Compute Cloud (EC2), the advantages of submitting applications to EC2 from different parts of the world and, if resource underutilization can improve application performance. Methods The SPRINT parallel implementations of correlation, permutation testing, partitioning around medoids and the multi-purpose papply have been benchmarked on data sets of various size on Amazon EC2. Jobs have been submitted from both the UK and Thailand to investigate monetary differences. Results It is possible to obtain good, scalable performance but the level of improvement is dependent upon the nature of algorithm. Resource underutilization can further improve the time to result. End-user’s location impacts on costs due to factors such as local taxation. Conclusions: Although not designed to satisfy HPC requirements, Amazon EC2 and cloud computing in general provides an interesting alternative and provides new possibilities for smaller organisations with limited funds. PMID:23223611

Exploiting parallel R in the cloud with SPRINT.

PubMed

Piotrowski, M; McGilvary, G A; Sloan, T M; Mewissen, M; Lloyd, A D; Forster, T; Mitchell, L; Ghazal, P; Hill, J

2013-01-01

Advances in DNA Microarray devices and next-generation massively parallel DNA sequencing platforms have led to an exponential growth in data availability but the arising opportunities require adequate computing resources. High Performance Computing (HPC) in the Cloud offers an affordable way of meeting this need. Bioconductor, a popular tool for high-throughput genomic data analysis, is distributed as add-on modules for the R statistical programming language but R has no native capabilities for exploiting multi-processor architectures. SPRINT is an R package that enables easy access to HPC for genomics researchers. This paper investigates: setting up and running SPRINT-enabled genomic analyses on Amazon's Elastic Compute Cloud (EC2), the advantages of submitting applications to EC2 from different parts of the world and, if resource underutilization can improve application performance. The SPRINT parallel implementations of correlation, permutation testing, partitioning around medoids and the multi-purpose papply have been benchmarked on data sets of various size on Amazon EC2. Jobs have been submitted from both the UK and Thailand to investigate monetary differences. It is possible to obtain good, scalable performance but the level of improvement is dependent upon the nature of the algorithm. Resource underutilization can further improve the time to result. End-user's location impacts on costs due to factors such as local taxation. Although not designed to satisfy HPC requirements, Amazon EC2 and cloud computing in general provides an interesting alternative and provides new possibilities for smaller organisations with limited funds.

TERSSE: Definition of the Total Earth Resources System for the Shuttle Era. Volume 8: User's Mission and System Requirements Data (appendix A of Volume 3)

NASA Technical Reports Server (NTRS)

1974-01-01

A computer printout is presented of the mission requirement for the TERSSE missions and their associated user tasks. The data included in the data base represents a broad-based attempt to define the amount, extent, and type of information needed for an earth resources management program in the era of the space shuttle. An effort was made to consider all aspects of remote sensing and resource management; because of its broad scope, it is not intended that the data be used without verification for in-depth studies of particular missions and/or users. The data base represents the quantitative structure necessary to define the TERSSE architecture and requirements, and to an overall integrated view of the earth resources technology requirements of the 1980's.

The Integration of CloudStack and OCCI/OpenNebula with DIRAC

NASA Astrophysics Data System (ADS)

Méndez Muñoz, Víctor; Fernández Albor, Víctor; Graciani Diaz, Ricardo; Casajús Ramo, Adriàn; Fernández Pena, Tomás; Merino Arévalo, Gonzalo; José Saborido Silva, Juan

2012-12-01

The increasing availability of Cloud resources is arising as a realistic alternative to the Grid as a paradigm for enabling scientific communities to access large distributed computing resources. The DIRAC framework for distributed computing is an easy way to efficiently access to resources from both systems. This paper explains the integration of DIRAC with two open-source Cloud Managers: OpenNebula (taking advantage of the OCCI standard) and CloudStack. These are computing tools to manage the complexity and heterogeneity of distributed data center infrastructures, allowing to create virtual clusters on demand, including public, private and hybrid clouds. This approach has required to develop an extension to the previous DIRAC Virtual Machine engine, which was developed for Amazon EC2, allowing the connection with these new cloud managers. In the OpenNebula case, the development has been based on the CernVM Virtual Software Appliance with appropriate contextualization, while in the case of CloudStack, the infrastructure has been kept more general, which permits other Virtual Machine sources and operating systems being used. In both cases, CernVM File System has been used to facilitate software distribution to the computing nodes. With the resulting infrastructure, the cloud resources are transparent to the users through a friendly interface, like the DIRAC Web Portal. The main purpose of this integration is to get a system that can manage cloud and grid resources at the same time. This particular feature pushes DIRAC to a new conceptual denomination as interware, integrating different middleware. Users from different communities do not need to care about the installation of the standard software that is available at the nodes, nor the operating system of the host machine which is transparent to the user. This paper presents an analysis of the overhead of the virtual layer, doing some tests to compare the proposed approach with the existing Grid solution. License Notice: Published under licence in Journal of Physics: Conference Series by IOP Publishing Ltd.

Comparison of Classifier Architectures for Online Neural Spike Sorting.

PubMed

Saeed, Maryam; Khan, Amir Ali; Kamboh, Awais Mehmood

2017-04-01

High-density, intracranial recordings from micro-electrode arrays need to undergo Spike Sorting in order to associate the recorded neuronal spikes to particular neurons. This involves spike detection, feature extraction, and classification. To reduce the data transmission and power requirements, on-chip real-time processing is becoming very popular. However, high computational resources are required for classifiers in on-chip spike-sorters, making scalability a great challenge. In this review paper, we analyze several popular classifiers to propose five new hardware architectures using the off-chip training with on-chip classification approach. These include support vector classification, fuzzy C-means classification, self-organizing maps classification, moving-centroid K-means classification, and Cosine distance classification. The performance of these architectures is analyzed in terms of accuracy and resource requirement. We establish that the neural networks based Self-Organizing Maps classifier offers the most viable solution. A spike sorter based on the Self-Organizing Maps classifier, requires only 7.83% of computational resources of the best-reported spike sorter, hierarchical adaptive means, while offering a 3% better accuracy at 7 dB SNR.

Cloud-based computation for accelerating vegetation mapping and change detection at regional to national scales

Treesearch

Matthew J. Gregory; Zhiqiang Yang; David M. Bell; Warren B. Cohen; Sean Healey; Janet L. Ohmann; Heather M. Roberts

2015-01-01

Mapping vegetation and landscape change at fine spatial scales is needed to inform natural resource and conservation planning, but such maps are expensive and time-consuming to produce. For Landsat-based methodologies, mapping efforts are hampered by the daunting task of manipulating multivariate data for millions to billions of pixels. The advent of cloud-based...

Are Patterns Important? An Investigation of the Relationships between Proficiencies in Patterns, Computation, Executive Functioning, and Algebraic Word Problems

ERIC Educational Resources Information Center

Lee, Kerry; Ng, Swee Fong; Bull, Rebecca; Pe, Madeline Lee; Ho, Ringo Ho Moon

2011-01-01

Although mathematical pattern tasks are often found in elementary school curricula and are deemed a building block for algebra, a recent report (National Mathematics Advisory Panel, 2008) suggests the resources devoted to its teaching and assessment need to be rebalanced. We examined whether children's developing proficiency in solving algebraic…

The Need for Integration of Technology in K-12 School Settings in Kenya, Africa

ERIC Educational Resources Information Center

Momanyi, Lilian; Norby, RenaFaye; Strand, Sharon

2006-01-01

Many computer users around the world have access to the latest advances in technology and use of the World Wide Web (WWW or Web). However, for a variety of political, economic, and social reasons, some peoples of the world do not have access to these resources. The educational systems of developing countries have not completely missed the…

MetaStorm: A Public Resource for Customizable Metagenomics Annotation

PubMed Central

Arango-Argoty, Gustavo; Singh, Gargi; Heath, Lenwood S.; Pruden, Amy; Xiao, Weidong; Zhang, Liqing

2016-01-01

Metagenomics is a trending research area, calling for the need to analyze large quantities of data generated from next generation DNA sequencing technologies. The need to store, retrieve, analyze, share, and visualize such data challenges current online computational systems. Interpretation and annotation of specific information is especially a challenge for metagenomic data sets derived from environmental samples, because current annotation systems only offer broad classification of microbial diversity and function. Moreover, existing resources are not configured to readily address common questions relevant to environmental systems. Here we developed a new online user-friendly metagenomic analysis server called MetaStorm (http://bench.cs.vt.edu/MetaStorm/), which facilitates customization of computational analysis for metagenomic data sets. Users can upload their own reference databases to tailor the metagenomics annotation to focus on various taxonomic and functional gene markers of interest. MetaStorm offers two major analysis pipelines: an assembly-based annotation pipeline and the standard read annotation pipeline used by existing web servers. These pipelines can be selected individually or together. Overall, MetaStorm provides enhanced interactive visualization to allow researchers to explore and manipulate taxonomy and functional annotation at various levels of resolution. PMID:27632579

MetaStorm: A Public Resource for Customizable Metagenomics Annotation.

PubMed

Arango-Argoty, Gustavo; Singh, Gargi; Heath, Lenwood S; Pruden, Amy; Xiao, Weidong; Zhang, Liqing

2016-01-01

Metagenomics is a trending research area, calling for the need to analyze large quantities of data generated from next generation DNA sequencing technologies. The need to store, retrieve, analyze, share, and visualize such data challenges current online computational systems. Interpretation and annotation of specific information is especially a challenge for metagenomic data sets derived from environmental samples, because current annotation systems only offer broad classification of microbial diversity and function. Moreover, existing resources are not configured to readily address common questions relevant to environmental systems. Here we developed a new online user-friendly metagenomic analysis server called MetaStorm (http://bench.cs.vt.edu/MetaStorm/), which facilitates customization of computational analysis for metagenomic data sets. Users can upload their own reference databases to tailor the metagenomics annotation to focus on various taxonomic and functional gene markers of interest. MetaStorm offers two major analysis pipelines: an assembly-based annotation pipeline and the standard read annotation pipeline used by existing web servers. These pipelines can be selected individually or together. Overall, MetaStorm provides enhanced interactive visualization to allow researchers to explore and manipulate taxonomy and functional annotation at various levels of resolution.

Flexible services for the support of research.

PubMed

Turilli, Matteo; Wallom, David; Williams, Chris; Gough, Steve; Curran, Neal; Tarrant, Richard; Bretherton, Dan; Powell, Andy; Johnson, Matt; Harmer, Terry; Wright, Peter; Gordon, John

2013-01-28

Cloud computing has been increasingly adopted by users and providers to promote a flexible, scalable and tailored access to computing resources. Nonetheless, the consolidation of this paradigm has uncovered some of its limitations. Initially devised by corporations with direct control over large amounts of computational resources, cloud computing is now being endorsed by organizations with limited resources or with a more articulated, less direct control over these resources. The challenge for these organizations is to leverage the benefits of cloud computing while dealing with limited and often widely distributed computing resources. This study focuses on the adoption of cloud computing by higher education institutions and addresses two main issues: flexible and on-demand access to a large amount of storage resources, and scalability across a heterogeneous set of cloud infrastructures. The proposed solutions leverage a federated approach to cloud resources in which users access multiple and largely independent cloud infrastructures through a highly customizable broker layer. This approach allows for a uniform authentication and authorization infrastructure, a fine-grained policy specification and the aggregation of accounting and monitoring. Within a loosely coupled federation of cloud infrastructures, users can access vast amount of data without copying them across cloud infrastructures and can scale their resource provisions when the local cloud resources become insufficient.

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

Radtke, M.A.

This paper will chronicle the activity at Wisconsin Public Service Corporation (WPSC) that resulted in the complete migration of a traditional, late 1970`s vintage, Energy Management System (EMS). The new environment includes networked microcomputers, minicomputers, and the corporate mainframe, and provides on-line access to employees outside the energy control center and some WPSC customers. In the late 1980`s, WPSC was forecasting an EMS computer upgrade or replacement to address both capacity and technology needs. Reasoning that access to diverse computing resources would best position the company to accommodate the uncertain needs of the energy industry in the 90`s, WPSC chosemore » to investigate an in-place migration to a network of computers, able to support heterogeneous hardware and operating systems. The system was developed in a modular fashion, with individual modules being deployed as soon as they were completed. The functional and technical specification was continuously enhanced as operating experience was gained from each operational module. With the migration off the original EMS computers complete, the networked system called DEMAXX (Distributed Energy Management Architecture with eXtensive eXpandability) has exceeded expectations in the areas of: cost, performance, flexibility, and reliability.« less

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

Radtke, M.A.

This paper will chronicle the activity at Wisconsin Public Service Corporation (WPSC) that resulted in the complete migration of a traditional, late 1970`s vintage, Energy management System (EMS). The new environment includes networked microcomputers, minicomputers, and the corporate mainframe, and provides on-line access to employees outside the energy control center and some WPSC customers. In the late 1980`s, WPSC was forecasting an EMS computer upgrade or replacement to address both capacity and technology needs. Reasoning that access to diverse computing resources would best position the company to accommodate the uncertain needs of the energy industry in the 90`s, WPSC chosemore » to investigate an in-place migration to a network of computers, able to support heterogeneous hardware and operating systems. The system was developed in a modular fashion, with individual modules being deployed as soon as they were completed. The functional and technical specification was continuously enhanced as operating experience was gained from each operational module. With the migration of the original EMS computers complete, the networked system called DEMAXX (Distributed Energy Management Architecture with eXtensive eXpandability) has exceeded expectations in the areas of: cost, performance, flexibility, and reliability.« less

Application of remote sensing to land and water resource planning: The Pocomoke River Basin, Maryland

NASA Technical Reports Server (NTRS)

Wildesen, S. E.; Phillips, E. P.

1981-01-01

Because of the size of the Pocomoke River Basin, the inaccessibility of certain areas, and study time constraints, several remote sensing techniques were used to collect base information on the river corridor, (a 23.2 km channel) and on a 1.2 km wooded floodplain. This information provided an adequate understanding of the environment and its resources, thus enabling effective management options to be designed. The remote sensing techniques used for assessment included manual analysis of high altitude color-infrared photography, computer-assisted analysis of LANDSAT-2 imagery, and the application of airborne oceanographic Lidar for topographic mapping. Results show that each techniques was valuable in providing the needed base data necessary for resource planning.

Description of a user-oriented geographic information system - The resource analysis program

NASA Technical Reports Server (NTRS)

Tilmann, S. E.; Mokma, D. L.

1980-01-01

This paper describes the Resource Analysis Program, an applied geographic information system. Several applications are presented which utilized soil, and other natural resource data, to develop integrated maps and data analyses. These applications demonstrate the methods of analysis and the philosophy of approach used in the mapping system. The applications are evaluated in reference to four major needs of a functional mapping system: data capture, data libraries, data analysis, and mapping and data display. These four criteria are then used to describe an effort to develop the next generation of applied mapping systems. This approach uses inexpensive microcomputers for field applications and should prove to be a viable entry point for users heretofore unable or unwilling to venture into applied computer mapping.

The tractable cognition thesis.

PubMed

Van Rooij, Iris

2008-09-01

The recognition that human minds/brains are finite systems with limited resources for computation has led some researchers to advance the Tractable Cognition thesis: Human cognitive capacities are constrained by computational tractability. This thesis, if true, serves cognitive psychology by constraining the space of computational-level theories of cognition. To utilize this constraint, a precise and workable definition of "computational tractability" is needed. Following computer science tradition, many cognitive scientists and psychologists define computational tractability as polynomial-time computability, leading to the P-Cognition thesis. This article explains how and why the P-Cognition thesis may be overly restrictive, risking the exclusion of veridical computational-level theories from scientific investigation. An argument is made to replace the P-Cognition thesis by the FPT-Cognition thesis as an alternative formalization of the Tractable Cognition thesis (here, FPT stands for fixed-parameter tractable). Possible objections to the Tractable Cognition thesis, and its proposed formalization, are discussed, and existing misconceptions are clarified. 2008 Cognitive Science Society, Inc.

Distributed information system (water fact sheet)

USGS Publications Warehouse

Harbaugh, A.W.

1986-01-01

During 1982-85, the Water Resources Division (WRD) of the U.S. Geological Survey (USGS) installed over 70 large minicomputers in offices across the country to support its mission in the science of hydrology. These computers are connected by a communications network that allows information to be shared among computers in each office. The computers and network together are known as the Distributed Information System (DIS). The computers are accessed through the use of more than 1500 terminals and minicomputers. The WRD has three fundamentally different needs for computing: data management; hydrologic analysis; and administration. Data management accounts for 50% of the computational workload of WRD because hydrologic data are collected in all 50 states, Puerto Rico, and the Pacific trust territories. Hydrologic analysis consists of 40% of the computational workload of WRD. Cost accounting, payroll, personnel records, and planning for WRD programs occupies an estimated 10% of the computer workload. The DIS communications network is shown on a map. (Lantz-PTT)

Distributed project scheduling at NASA: Requirements for manual protocols and computer-based support

NASA Technical Reports Server (NTRS)

Richards, Stephen F.

1992-01-01

The increasing complexity of space operations and the inclusion of interorganizational and international groups in the planning and control of space missions lead to requirements for greater communication, coordination, and cooperation among mission schedulers. These schedulers must jointly allocate scarce shared resources among the various operational and mission oriented activities while adhering to all constraints. This scheduling environment is complicated by such factors as the presence of varying perspectives and conflicting objectives among the schedulers, the need for different schedulers to work in parallel, and limited communication among schedulers. Smooth interaction among schedulers requires the use of protocols that govern such issues as resource sharing, authority to update the schedule, and communication of updates. This paper addresses the development and characteristics of such protocols and their use in a distributed scheduling environment that incorporates computer-aided scheduling tools. An example problem is drawn from the domain of Space Shuttle mission planning.

The INDIGO-Datacloud Authentication and Authorization Infrastructure

NASA Astrophysics Data System (ADS)

Ceccanti, A.; Hardt, M.; Wegh, B.; Millar, AP; Caberletti, M.; Vianello, E.; Licehammer, S.

2017-10-01

Contemporary distributed computing infrastructures (DCIs) are not easily and securely accessible by scientists. These computing environments are typically hard to integrate due to interoperability problems resulting from the use of different authentication mechanisms, identity negotiation protocols and access control policies. Such limitations have a big impact on the user experience making it hard for user communities to port and run their scientific applications on resources aggregated from multiple providers. The INDIGO-DataCloud project wants to provide the services and tools needed to enable a secure composition of resources from multiple providers in support of scientific applications. In order to do so, a common AAI architecture has to be defined that supports multiple authentication mechanisms, support delegated authorization across services and can be easily integrated in off-the-shelf software. In this contribution we introduce the INDIGO Authentication and Authorization Infrastructure, describing its main components and their status and how authentication, delegation and authorization flows are implemented across services.

Variable Generation Power Forecasting as a Big Data Problem

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

Haupt, Sue Ellen; Kosovic, Branko

To blend growing amounts of power from renewable resources into utility operations requires accurate forecasts. For both day ahead planning and real-time operations, the power from the wind and solar resources must be predicted based on real-time observations and a series of models that span the temporal and spatial scales of the problem, using the physical and dynamical knowledge as well as computational intelligence. Accurate prediction is a Big Data problem that requires disparate data, multiple models that are each applicable for a specific time frame, and application of computational intelligence techniques to successfully blend all of the model andmore » observational information in real-time and deliver it to the decision makers at utilities and grid operators. This paper describes an example system that has been used for utility applications and how it has been configured to meet utility needs while addressing the Big Data issues.« less

Development of Fuel Shuffling Module for PHISICS

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

Allan Mabe; Andrea Alfonsi; Cristian Rabiti

2013-06-01

PHISICS (Parallel and Highly Innovative Simulation for the INL Code System) [4] code toolkit has been in development at the Idaho National Laboratory. This package is intended to provide a modern analysis tool for reactor physics investigation. It is designed with the mindset to maximize accuracy for a given availability of computational resources and to give state of the art tools to the modern nuclear engineer. This is obtained by implementing several different algorithms and meshing approaches among which the user will be able to choose, in order to optimize his computational resources and accuracy needs. The software is completelymore » modular in order to simplify the independent development of modules by different teams and future maintenance. The package is coupled with the thermo-hydraulic code RELAP5-3D [3]. In the following the structure of the different PHISICS modules is briefly recalled, focusing on the new shuffling module (SHUFFLE), object of this paper.« less

The use of LANDSAT-1 imagery in mapping and managing soil and range resources in the Sand Hills region of Nebraska

NASA Technical Reports Server (NTRS)

Seevers, P. M. (Principal Investigator); Drew, J. V.

1976-01-01

The author has identified the following significant results. Evaluation of ERTS-1 imagery for the Sand Hills region of Nebraska has shown that the data can be used to effectively measure several parameters of inventory needs. (1) Vegetative biomass can be estimated with a high degree of confidence using computer compatable tape data. (2) Soils can be mapped to the subgroup level with high altitude aircraft color infrared photography and to the association level with multitemporal ERTS-1 imagery. (3) Water quality in Sand Hills lakes can be estimated utilizing computer compatable tape data. (4) Center pivot irrigation can be inventoried from satellite data and can be monitored regarding site selection and relative success of establishment from high altitude aircraft color infrared photography. (5) ERTS-1 data is of exceptional value in wide-area inventory of natural resource data in the Sand Hills region of Nebraska.

Variable Generation Power Forecasting as a Big Data Problem

DOE PAGES

Haupt, Sue Ellen; Kosovic, Branko

2016-10-10

To blend growing amounts of power from renewable resources into utility operations requires accurate forecasts. For both day ahead planning and real-time operations, the power from the wind and solar resources must be predicted based on real-time observations and a series of models that span the temporal and spatial scales of the problem, using the physical and dynamical knowledge as well as computational intelligence. Accurate prediction is a Big Data problem that requires disparate data, multiple models that are each applicable for a specific time frame, and application of computational intelligence techniques to successfully blend all of the model andmore » observational information in real-time and deliver it to the decision makers at utilities and grid operators. This paper describes an example system that has been used for utility applications and how it has been configured to meet utility needs while addressing the Big Data issues.« less

Networks in ATLAS

NASA Astrophysics Data System (ADS)

McKee, Shawn; ATLAS Collaboration

2017-10-01

Networks have played a critical role in high-energy physics (HEP), enabling us to access and effectively utilize globally distributed resources to meet the needs of our physicists. Because of their importance in enabling our grid computing infrastructure many physicists have taken leading roles in research and education (R&E) networking, participating in, and even convening, network related meetings and research programs with the broader networking community worldwide. This has led to HEP benefiting from excellent global networking capabilities for little to no direct cost. However, as other science domains ramp-up their need for similar networking it becomes less clear that this situation will continue unchanged. What this means for ATLAS in particular needs to be understood. ATLAS has evolved its computing model since the LHC started based upon its experience with using globally distributed resources. The most significant theme of those changes has been increased reliance upon, and use of, its networks. We will report on a number of networking initiatives in ATLAS including participation in the global perfSONAR network monitoring and measuring efforts of WLCG and OSG, the collaboration with the LHCOPN/LHCONE effort, the integration of network awareness into PanDA, the use of the evolving ATLAS analytics framework to better understand our networks and the changes in our DDM system to allow remote access to data. We will also discuss new efforts underway that are exploring the inclusion and use of software defined networks (SDN) and how ATLAS might benefit from: • Orchestration and optimization of distributed data access and data movement. • Better control of workflows, end to end. • Enabling prioritization of time-critical vs normal tasks • Improvements in the efficiency of resource usage

Networking Cyberinfrastructure Resources to Support Global, Cross-disciplinary Science

NASA Astrophysics Data System (ADS)

Lehnert, K.; Ramamurthy, M. K.

2016-12-01

Geosciences are globally connected by nature and the grand challenge problems like climate change, ocean circulations, seasonal predictions, impact of volcanic eruptions, etc. all transcend both disciplinary and geographic boundaries, requiring cross-disciplinary and international partnerships. Cross-disciplinary and international collaborations are also needed to unleash the power of cyber- (or e-) infrastructure (CI) by networking globally distributed, multi-disciplinary data, software, and computing resources to accelerate new scientific insights and discoveries. While the promises of a global and cross-disciplinary CI are exhilarating and real, a range of technical, organizational, and social challenges needs to be overcome in order to achieve alignment and linking of operational data systems, software tools, and computing facilities. New modes of collaboration require agreement on and governance of technical standards and best practices, and funding for necessary modifications. This presentation will contribute the perspective of domain-specific data facilities to the discussion of cross-disciplinary and international collaboration in CI development and deployment, in particular those of IEDA (Interdisciplinary Earth Data Alliance) serving the solid Earth sciences and Unidata serving atmospheric sciences. Both facilities are closely involved with the US NSF EarthCube program that aims to network and augment existing Geoscience CI capabilities "to make disciplinary boundaries permeable, nurture and facilitate knowledge sharing, …, and enhance collaborative pursuit of cross-disciplinary research" (EarthCube Strategic Vision), while also collaborating internationally to network domain-specific and cross-disciplinary CI resources. These collaborations are driven by the substantial benefits to the science community, but create challenges, when operational and funding constraints need to be balanced with adjustments to new joint data curation practices and interoperability standards.

Synthetic analog computation in living cells.

PubMed

Daniel, Ramiz; Rubens, Jacob R; Sarpeshkar, Rahul; Lu, Timothy K

2013-05-30

A central goal of synthetic biology is to achieve multi-signal integration and processing in living cells for diagnostic, therapeutic and biotechnology applications. Digital logic has been used to build small-scale circuits, but other frameworks may be needed for efficient computation in the resource-limited environments of cells. Here we demonstrate that synthetic analog gene circuits can be engineered to execute sophisticated computational functions in living cells using just three transcription factors. Such synthetic analog gene circuits exploit feedback to implement logarithmically linear sensing, addition, ratiometric and power-law computations. The circuits exhibit Weber's law behaviour as in natural biological systems, operate over a wide dynamic range of up to four orders of magnitude and can be designed to have tunable transfer functions. Our circuits can be composed to implement higher-order functions that are well described by both intricate biochemical models and simple mathematical functions. By exploiting analog building-block functions that are already naturally present in cells, this approach efficiently implements arithmetic operations and complex functions in the logarithmic domain. Such circuits may lead to new applications for synthetic biology and biotechnology that require complex computations with limited parts, need wide-dynamic-range biosensing or would benefit from the fine control of gene expression.

An Interface for Biomedical Big Data Processing on the Tianhe-2 Supercomputer.

PubMed

Yang, Xi; Wu, Chengkun; Lu, Kai; Fang, Lin; Zhang, Yong; Li, Shengkang; Guo, Guixin; Du, YunFei

2017-12-01

Big data, cloud computing, and high-performance computing (HPC) are at the verge of convergence. Cloud computing is already playing an active part in big data processing with the help of big data frameworks like Hadoop and Spark. The recent upsurge of high-performance computing in China provides extra possibilities and capacity to address the challenges associated with big data. In this paper, we propose Orion-a big data interface on the Tianhe-2 supercomputer-to enable big data applications to run on Tianhe-2 via a single command or a shell script. Orion supports multiple users, and each user can launch multiple tasks. It minimizes the effort needed to initiate big data applications on the Tianhe-2 supercomputer via automated configuration. Orion follows the "allocate-when-needed" paradigm, and it avoids the idle occupation of computational resources. We tested the utility and performance of Orion using a big genomic dataset and achieved a satisfactory performance on Tianhe-2 with very few modifications to existing applications that were implemented in Hadoop/Spark. In summary, Orion provides a practical and economical interface for big data processing on Tianhe-2.

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.

Resource Aware Intelligent Network Services (RAINS) Final Technical Report

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

Lehman, Tom; Yang, Xi

The Resource Aware Intelligent Network Services (RAINS) project conducted research and developed technologies in the area of cyber infrastructure resource modeling and computation. The goal of this work was to provide a foundation to enable intelligent, software defined services which spanned the network AND the resources which connect to the network. A Multi-Resource Service Plane (MRSP) was defined, which allows resource owners/managers to locate and place themselves from a topology and service availability perspective within the dynamic networked cyberinfrastructure ecosystem. The MRSP enables the presentation of integrated topology views and computation results which can include resources across the spectrum ofmore » compute, storage, and networks. The RAINS project developed MSRP includes the following key components: i) Multi-Resource Service (MRS) Ontology/Multi-Resource Markup Language (MRML), ii) Resource Computation Engine (RCE), iii) Modular Driver Framework (to allow integration of a variety of external resources). The MRS/MRML is a general and extensible modeling framework that allows for resource owners to model, or describe, a wide variety of resource types. All resources are described using three categories of elements: Resources, Services, and Relationships between the elements. This modeling framework defines a common method for the transformation of cyber infrastructure resources into data in the form of MRML models. In order to realize this infrastructure datification, the RAINS project developed a model based computation system, i.e. “RAINS Computation Engine (RCE)”. The RCE has the ability to ingest, process, integrate, and compute based on automatically generated MRML models. The RCE interacts with the resources thru system drivers which are specific to the type of external network or resource controller. The RAINS project developed a modular and pluggable driver system which facilities a variety of resource controllers to automatically generate, maintain, and distribute MRML based resource descriptions. Once all of the resource topologies are absorbed by the RCE, a connected graph of the full distributed system topology is constructed, which forms the basis for computation and workflow processing. The RCE includes a Modular Computation Element (MCE) framework which allows for tailoring of the computation process to the specific set of resources under control, and the services desired. The input and output of an MCE are both model data based on MRS/MRML ontology and schema. Some of the RAINS project accomplishments include: Development of general and extensible multi-resource modeling framework; Design of a Resource Computation Engine (RCE) system which includes the following key capabilities; Absorb a variety of multi-resource model types and build integrated models; Novel architecture which uses model based communications across the full stack for all Flexible provision of abstract or intent based user facing interfaces; Workflow processing based on model descriptions; Release of the RCE as an open source software; Deployment of RCE in the University of Maryland/Mid-Atlantic Crossroad ScienceDMZ in prototype mode with a plan under way to transition to production; Deployment at the Argonne National Laboratory DTN Facility in prototype mode; Selection of RCE by the DOE SENSE (SDN for End-to-end Networked Science at the Exascale) project as the basis for their orchestration service.« less

Guidance on the Stand Down, Mothball, and Reactivation of Ground Test Facilities

NASA Technical Reports Server (NTRS)

Volkman, Gregrey T.; Dunn, Steven C.

2013-01-01

The development of aerospace and aeronautics products typically requires three distinct types of testing resources across research, development, test, and evaluation: experimental ground testing, computational "testing" and development, and flight testing. Over the last twenty plus years, computational methods have replaced some physical experiments and this trend is continuing. The result is decreased utilization of ground test capabilities and, along with market forces, industry consolidation, and other factors, has resulted in the stand down and oftentimes closure of many ground test facilities. Ground test capabilities are (and very likely will continue to be for many years) required to verify computational results and to provide information for regimes where computational methods remain immature. Ground test capabilities are very costly to build and to maintain, so once constructed and operational it may be desirable to retain access to those capabilities even if not currently needed. One means of doing this while reducing ongoing sustainment costs is to stand down the facility into a "mothball" status - keeping it alive to bring it back when needed. Both NASA and the US Department of Defense have policies to accomplish the mothball of a facility, but with little detail. This paper offers a generic process to follow that can be tailored based on the needs of the owner and the applicable facility.

Analysis of self-reported versus biomarker based smoking prevalence: methodology to compute corrected smoking prevalence rates.

PubMed

Jain, Ram B

2017-07-01

Prevalence of smoking is needed to estimate the need for future public health resources. To compute and compare smoking prevalence rates by using self-reported smoking statuses, two serum cotinine (SCOT) based biomarker methods, and one urinary 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) based biomarker method. These estimates were then used to develop correction factors to be applicable to self-reported prevalences to arrive at corrected smoking prevalence rates. Data from National Health and Nutrition Examination Survey (NHANES) for 2007-2012 for those aged ≥20 years (N = 16826) were used. Self-reported prevalence rate for the total population computed as the weighted number of self-reported smokers divided by weighted number of all participants was 21.6% and 24% when computed by weighted number of self-reported smokers divided by the weighted number of self-reported smokers and nonsmokers. The corrected prevalence rate was found to be 25.8%. A 1% underestimate in smoking prevalence is equivalent to not being able to identify 2.2 million smokers in US in a given year. This underestimation, if not corrected, could lead to serious gap in the public health services available and needed to provide adequate preventive and corrective treatment to smokers.

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.

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

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

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

2008-03-01

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

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

PubMed Central

Pinthong, Watthanai; Muangruen, Panya

2016-01-01

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

Economic resilience through "One-Water" management

USGS Publications Warehouse

Hanson, Randall T.; Schmid, Wolfgang

2013-01-01

Disruption of water availability leads to food scarcity and loss of economic opportunity. Development of effective water-resource policies and management strategies could provide resiliance to local economies in the face of water disruptions such as drought, flood, and climate change. To accomplish this, a detailed understanding of human water use and natural water resource availability is needed. A hydrologic model is a computer software system that simulates the movement and use of water in a geographic area. It takes into account all components of the water cycle--“One Water”--and helps estimate water budgets for groundwater, surface water, and landscape features. The U.S. Geological Survey MODFLOW One-Water Integrated Hydrologic Model (MODFLOWOWHM) software and scientific methods can provide water managers and political leaders with hydrologic information they need to help ensure water security and economic resilience.

Wind Energy Facilities

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

Laurie, Carol

2017-02-01

This book takes readers inside the places where daily discoveries shape the next generation of wind power systems. Energy Department laboratory facilities span the United States and offer wind research capabilities to meet industry needs. The facilities described in this book make it possible for industry players to increase reliability, improve efficiency, and reduce the cost of wind energy -- one discovery at a time. Whether you require blade testing or resource characterization, grid integration or high-performance computing, Department of Energy laboratory facilities offer a variety of capabilities to meet your wind research needs.

Wind Energy Facilities

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

Office of Energy Efficiency and Renewable Energy

This book takes readers inside the places where daily discoveries shape the next generation of wind power systems. Energy Department laboratory facilities span the United States and offer wind research capabilities to meet industry needs. The facilities described in this book make it possible for industry players to increase reliability, improve efficiency, and reduce the cost of wind energy -- one discovery at a time. Whether you require blade testing or resource characterization, grid integration or high-performance computing, Department of Energy laboratory facilities offer a variety of capabilities to meet your wind research needs.

Key Technology Research on Open Architecture for The Sharing of Heterogeneous Geographic Analysis Models

NASA Astrophysics Data System (ADS)

Yue, S. S.; Wen, Y. N.; Lv, G. N.; Hu, D.

2013-10-01

In recent years, the increasing development of cloud computing technologies laid critical foundation for efficiently solving complicated geographic issues. However, it is still difficult to realize the cooperative operation of massive heterogeneous geographical models. Traditional cloud architecture is apt to provide centralized solution to end users, while all the required resources are often offered by large enterprises or special agencies. Thus, it's a closed framework from the perspective of resource utilization. Solving comprehensive geographic issues requires integrating multifarious heterogeneous geographical models and data. In this case, an open computing platform is in need, with which the model owners can package and deploy their models into cloud conveniently, while model users can search, access and utilize those models with cloud facility. Based on this concept, the open cloud service strategies for the sharing of heterogeneous geographic analysis models is studied in this article. The key technology: unified cloud interface strategy, sharing platform based on cloud service, and computing platform based on cloud service are discussed in detail, and related experiments are conducted for further verification.

Dawn Usage, Scheduling, and Governance Model

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

Louis, S

2009-11-02

This document describes Dawn use, scheduling, and governance concerns. Users started running full-machine science runs in early April 2009 during the initial open shakedown period. Scheduling Dawn while in the Open Computing Facility (OCF) was controlled and coordinated via phone calls, emails, and a small number of controlled banks. With Dawn moving to the Secure Computing Facility (SCF) in fall of 2009, a more detailed scheduling and governance model is required. The three major objectives are: (1) Ensure Dawn resources are allocated on a program priority-driven basis; (2) Utilize Dawn resources on the job mixes for which they were intended;more » and (3) Minimize idle cycles through use of partitions, banks and proper job mix. The SCF workload for Dawn will be inherently different than Purple or BG/L, and therefore needs a different approach. Dawn's primary function is to permit adequate access for tri-lab code development in preparation for Sequoia, and in particular for weapons multi-physics codes in support of UQ. A second purpose is to provide time allocations for large-scale science runs and for UQ suite calculations to advance SSP program priorities. This proposed governance model will be the basis for initial time allocation of Dawn computing resources for the science and UQ workloads that merit priority on this class of resource, either because they cannot be reasonably attempted on any other resources due to size of problem, or because of the unavailability of sizable allocations on other ASC capability or capacity platforms. This proposed model intends to make the most effective use of Dawn as possible, but without being overly constrained by more formal proposal processes such as those now used for Purple CCCs.« less

Elastic Extension of a CMS Computing Centre Resources on External Clouds

NASA Astrophysics Data System (ADS)

Codispoti, G.; Di Maria, R.; Aiftimiei, C.; Bonacorsi, D.; Calligola, P.; Ciaschini, V.; Costantini, A.; Dal Pra, S.; DeGirolamo, D.; Grandi, C.; Michelotto, D.; Panella, M.; Peco, G.; Sapunenko, V.; Sgaravatto, M.; Taneja, S.; Zizzi, G.

2016-10-01

After the successful LHC data taking in Run-I and in view of the future runs, the LHC experiments are facing new challenges in the design and operation of the computing facilities. The computing infrastructure for Run-II is dimensioned to cope at most with the average amount of data recorded. The usage peaks, as already observed in Run-I, may however originate large backlogs, thus delaying the completion of the data reconstruction and ultimately the data availability for physics analysis. In order to cope with the production peaks, CMS - along the lines followed by other LHC experiments - is exploring the opportunity to access Cloud resources provided by external partners or commercial providers. Specific use cases have already been explored and successfully exploited during Long Shutdown 1 (LS1) and the first part of Run 2. In this work we present the proof of concept of the elastic extension of a CMS site, specifically the Bologna Tier-3, on an external OpenStack infrastructure. We focus on the “Cloud Bursting” of a CMS Grid site using a newly designed LSF configuration that allows the dynamic registration of new worker nodes to LSF. In this approach, the dynamically added worker nodes instantiated on the OpenStack infrastructure are transparently accessed by the LHC Grid tools and at the same time they serve as an extension of the farm for the local usage. The amount of resources allocated thus can be elastically modeled to cope up with the needs of CMS experiment and local users. Moreover, a direct access/integration of OpenStack resources to the CMS workload management system is explored. In this paper we present this approach, we report on the performances of the on-demand allocated resources, and we discuss the lessons learned and the next steps.

Experience and Attitudes towards Information Technology among First-Year Medical Students in Denmark: Longitudinal Questionnaire Survey

PubMed Central

2004-01-01

Background As more and more information technology (IT) resources become available both for support of campus- based medical education and for Web-based learning, it becomes increasingly interesting to map the information technology resources available to medical students and the attitudes students have towards their use. Objective To determine how extensively and effectively information handling skills are being taught in the medical curriculum, the study investigated Internet and computer availability and usage, and attitudes towards information technology among first-year medical students in Aarhus, Denmark, during a five-year period. Methods In the period from 1998 to 2002, students beginning the first semester of medical school were given courses on effective use of IT in their studies. As a part of the tutorials, the students were asked to complete a web-based questionnaire which included questions related to IT readiness and attitudes towards using IT in studies. Results A total of 1159 students (78%) responded. Overall, 71.7% of the respondents indicating they had access to a computer at home, a number that did not change significantly during the study period. Over time, the power of students' computers and the use of e-mail and Internet did increase significantly. By fall 2002, approximately 90% of students used e-mail regularly, 80% used the Internet regularly, and 60% had access to the Internet from home. Significantly more males than females had access to a computer at home, and males had a more positive attitude towards the use of computers in their medical studies. A fairly constant number of students (3-7%) stated that they would prefer not to have to use computers in their studies. Conclusions Taken together with our experience from classroom teaching, these results indicate optional teaching of basic information technology still needs to be integrated into medical studies, and that this need does not seem likely to disappear in the near future. PMID:15111276

A Framework for Understanding Physics Students' Computational Modeling Practices

NASA Astrophysics Data System (ADS)

Lunk, Brandon Robert

With the growing push to include computational modeling in the physics classroom, we are faced with the need to better understand students' computational modeling practices. While existing research on programming comprehension explores how novices and experts generate programming algorithms, little of this discusses how domain content knowledge, and physics knowledge in particular, can influence students' programming practices. In an effort to better understand this issue, I have developed a framework for modeling these practices based on a resource stance towards student knowledge. A resource framework models knowledge as the activation of vast networks of elements called "resources." Much like neurons in the brain, resources that become active can trigger cascading events of activation throughout the broader network. This model emphasizes the connectivity between knowledge elements and provides a description of students' knowledge base. Together with resources resources, the concepts of "epistemic games" and "frames" provide a means for addressing the interaction between content knowledge and practices. Although this framework has generally been limited to describing conceptual and mathematical understanding, it also provides a means for addressing students' programming practices. In this dissertation, I will demonstrate this facet of a resource framework as well as fill in an important missing piece: a set of epistemic games that can describe students' computational modeling strategies. The development of this theoretical framework emerged from the analysis of video data of students generating computational models during the laboratory component of a Matter & Interactions: Modern Mechanics course. Student participants across two semesters were recorded as they worked in groups to fix pre-written computational models that were initially missing key lines of code. Analysis of this video data showed that the students' programming practices were highly influenced by their existing physics content knowledge, particularly their knowledge of analytic procedures. While this existing knowledge was often applied in inappropriate circumstances, the students were still able to display a considerable amount of understanding of the physics content and of analytic solution procedures. These observations could not be adequately accommodated by the existing literature of programming comprehension. In extending the resource framework to the task of computational modeling, I model students' practices in terms of three important elements. First, a knowledge base includes re- sources for understanding physics, math, and programming structures. Second, a mechanism for monitoring and control describes students' expectations as being directed towards numerical, analytic, qualitative or rote solution approaches and which can be influenced by the problem representation. Third, a set of solution approaches---many of which were identified in this study---describe what aspects of the knowledge base students use and how they use that knowledge to enact their expectations. This framework allows us as researchers to track student discussions and pinpoint the source of difficulties. This work opens up many avenues of potential research. First, this framework gives researchers a vocabulary for extending Resource Theory to other domains of instruction, such as modeling how physics students use graphs. Second, this framework can be used as the basis for modeling expert physicists' programming practices. Important instructional implications also follow from this research. Namely, as we broaden the use of computational modeling in the physics classroom, our instructional practices should focus on helping students understand the step-by-step nature of programming in contrast to the already salient analytic procedures.

Contextuality as a Resource for Models of Quantum Computation with Qubits

NASA Astrophysics Data System (ADS)

Bermejo-Vega, Juan; Delfosse, Nicolas; Browne, Dan E.; Okay, Cihan; Raussendorf, Robert

2017-09-01

A central question in quantum computation is to identify the resources that are responsible for quantum speed-up. Quantum contextuality has been recently shown to be a resource for quantum computation with magic states for odd-prime dimensional qudits and two-dimensional systems with real wave functions. The phenomenon of state-independent contextuality poses a priori an obstruction to characterizing the case of regular qubits, the fundamental building block of quantum computation. Here, we establish contextuality of magic states as a necessary resource for a large class of quantum computation schemes on qubits. We illustrate our result with a concrete scheme related to measurement-based quantum computation.

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

PubMed Central

Joyce, Blake L.; Haug-Baltzell, Asher K.; Hulvey, Jonathan P.; McCarthy, Fiona; Devisetty, Upendra Kumar; Lyons, Eric

2017-01-01

This workflow allows novice researchers to leverage advanced computational resources such as cloud computing to carry out pairwise comparative transcriptomics. It also serves as a primer for biologists to develop data scientist computational skills, e.g. executing bash commands, visualization and management of large data sets. All command line code and further explanations of each command or step can be found on the wiki (https://wiki.cyverse.org/wiki/x/dgGtAQ). The Discovery Environment and Atmosphere platforms are connected together through the CyVerse Data Store. As such, once the initial raw sequencing data has been uploaded there is no more need to transfer large data files over an Internet connection, minimizing the amount of time needed to conduct analyses. This protocol is designed to analyze only two experimental treatments or conditions. Differential gene expression analysis is conducted through pairwise comparisons, and will not be suitable to test multiple factors. This workflow is also designed to be manual rather than automated. Each step must be executed and investigated by the user, yielding a better understanding of data and analytical outputs, and therefore better results for the user. Once complete, this protocol will yield de novo assembled transcriptome(s) for underserved (non-model) organisms without the need to map to previously assembled reference genomes (which are usually not available in underserved organism). These de novo transcriptomes are further used in pairwise differential gene expression analysis to investigate genes differing between two experimental conditions. Differentially expressed genes are then functionally annotated to understand the genetic response organisms have to experimental conditions. In total, the data derived from this protocol is used to test hypotheses about biological responses of underserved organisms. PMID:28518075

Password Cracking Using Sony Playstations

NASA Astrophysics Data System (ADS)

Kleinhans, Hugo; Butts, Jonathan; Shenoi, Sujeet

Law enforcement agencies frequently encounter encrypted digital evidence for which the cryptographic keys are unknown or unavailable. Password cracking - whether it employs brute force or sophisticated cryptanalytic techniques - requires massive computational resources. This paper evaluates the benefits of using the Sony PlayStation 3 (PS3) to crack passwords. The PS3 offers massive computational power at relatively low cost. Moreover, multiple PS3 systems can be introduced easily to expand parallel processing when additional power is needed. This paper also describes a distributed framework designed to enable law enforcement agents to crack encrypted archives and applications in an efficient and cost-effective manner.

The Importance of Simulation Workflow and Data Management in the Accelerated Climate Modeling for Energy Project

NASA Astrophysics Data System (ADS)

Bader, D. C.

2015-12-01

The Accelerated Climate Modeling for Energy (ACME) Project is concluding its first year. Supported by the Office of Science in the U.S. Department of Energy (DOE), its vision is to be "an ongoing, state-of-the-science Earth system modeling, modeling simulation and prediction project that optimizes the use of DOE laboratory resources to meet the science needs of the nation and the mission needs of DOE." Included in the "laboratory resources," is a large investment in computational, network and information technologies that will be utilized to both build better and more accurate climate models and broadly disseminate the data they generate. Current model diagnostic analysis and data dissemination technologies will not scale to the size of the simulations and the complexity of the models envisioned by ACME and other top tier international modeling centers. In this talk, the ACME Workflow component plans to meet these future needs will be described and early implementation examples will be highlighted.

Flexible Job-Shop Scheduling with Dual-Resource Constraints to Minimize Tardiness Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Paksi, A. B. N.; Ma'ruf, A.

2016-02-01

In general, both machines and human resources are needed for processing a job on production floor. However, most classical scheduling problems have ignored the possible constraint caused by availability of workers and have considered only machines as a limited resource. In addition, along with production technology development, routing flexibility appears as a consequence of high product variety and medium demand for each product. Routing flexibility is caused by capability of machines that offers more than one machining process. This paper presents a method to address scheduling problem constrained by both machines and workers, considering routing flexibility. Scheduling in a Dual-Resource Constrained shop is categorized as NP-hard problem that needs long computational time. Meta-heuristic approach, based on Genetic Algorithm, is used due to its practical implementation in industry. Developed Genetic Algorithm uses indirect chromosome representative and procedure to transform chromosome into Gantt chart. Genetic operators, namely selection, elitism, crossover, and mutation are developed to search the best fitness value until steady state condition is achieved. A case study in a manufacturing SME is used to minimize tardiness as objective function. The algorithm has shown 25.6% reduction of tardiness, equal to 43.5 hours.

Computing arrival times of firefighting resources for initial attack

Treesearch

Romain M. Mees

1978-01-01

Dispatching of firefighting resources requires instantaneous or precalculated decisions. A FORTRAN computer program has been developed that can provide a list of resources in order of computed arrival time for initial attack on a fire. The program requires an accurate description of the existing road system and a list of all resources available on a planning unit....

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

A Review of Computer Science Resources for Learning and Teaching with K-12 Computing Curricula: An Australian Case Study

ERIC Educational Resources Information Center

Falkner, Katrina; Vivian, Rebecca

2015-01-01

To support teachers to implement Computer Science curricula into classrooms from the very first year of school, teachers, schools and organisations seek quality curriculum resources to support implementation and teacher professional development. Until now, many Computer Science resources and outreach initiatives have targeted K-12 school-age…

Parallel workflow manager for non-parallel bioinformatic applications to solve large-scale biological problems on a supercomputer.

PubMed

Suplatov, Dmitry; Popova, Nina; Zhumatiy, Sergey; Voevodin, Vladimir; Švedas, Vytas

2016-04-01

Rapid expansion of online resources providing access to genomic, structural, and functional information associated with biological macromolecules opens an opportunity to gain a deeper understanding of the mechanisms of biological processes due to systematic analysis of large datasets. This, however, requires novel strategies to optimally utilize computer processing power. Some methods in bioinformatics and molecular modeling require extensive computational resources. Other algorithms have fast implementations which take at most several hours to analyze a common input on a modern desktop station, however, due to multiple invocations for a large number of subtasks the full task requires a significant computing power. Therefore, an efficient computational solution to large-scale biological problems requires both a wise parallel implementation of resource-hungry methods as well as a smart workflow to manage multiple invocations of relatively fast algorithms. In this work, a new computer software mpiWrapper has been developed to accommodate non-parallel implementations of scientific algorithms within the parallel supercomputing environment. The Message Passing Interface has been implemented to exchange information between nodes. Two specialized threads - one for task management and communication, and another for subtask execution - are invoked on each processing unit to avoid deadlock while using blocking calls to MPI. The mpiWrapper can be used to launch all conventional Linux applications without the need to modify their original source codes and supports resubmission of subtasks on node failure. We show that this approach can be used to process huge amounts of biological data efficiently by running non-parallel programs in parallel mode on a supercomputer. The C++ source code and documentation are available from http://biokinet.belozersky.msu.ru/mpiWrapper .

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

Bland, Arthur S Buddy; Hack, James J; Baker, Ann E

Oak Ridge National Laboratory's (ORNL's) Cray XT5 supercomputer, Jaguar, kicked off the era of petascale scientific computing in 2008 with applications that sustained more than a thousand trillion floating point calculations per second - or 1 petaflop. Jaguar continues to grow even more powerful as it helps researchers broaden the boundaries of knowledge in virtually every domain of computational science, including weather and climate, nuclear energy, geosciences, combustion, bioenergy, fusion, and materials science. Their insights promise to broaden our knowledge in areas that are vitally important to the Department of Energy (DOE) and the nation as a whole, particularly energymore » assurance and climate change. The science of the 21st century, however, will demand further revolutions in computing, supercomputers capable of a million trillion calculations a second - 1 exaflop - and beyond. These systems will allow investigators to continue attacking global challenges through modeling and simulation and to unravel longstanding scientific questions. Creating such systems will also require new approaches to daunting challenges. High-performance systems of the future will need to be codesigned for scientific and engineering applications with best-in-class communications networks and data-management infrastructures and teams of skilled researchers able to take full advantage of these new resources. The Oak Ridge Leadership Computing Facility (OLCF) provides the nation's most powerful open resource for capability computing, with a sustainable path that will maintain and extend national leadership for DOE's Office of Science (SC). The OLCF has engaged a world-class team to support petascale science and to take a dramatic step forward, fielding new capabilities for high-end science. This report highlights the successful delivery and operation of a petascale system and shows how the OLCF fosters application development teams, developing cutting-edge tools and resources for next-generation systems.« less

Software for Allocating Resources in the Deep Space Network

NASA Technical Reports Server (NTRS)

Wang, Yeou-Fang; Borden, Chester; Zendejas, Silvino; Baldwin, John

2003-01-01

TIGRAS 2.0 is a computer program designed to satisfy a need for improved means for analyzing the tracking demands of interplanetary space-flight missions upon the set of ground antenna resources of the Deep Space Network (DSN) and for allocating those resources. Written in Microsoft Visual C++, TIGRAS 2.0 provides a single rich graphical analysis environment for use by diverse DSN personnel, by connecting to various data sources (relational databases or files) based on the stages of the analyses being performed. Notable among the algorithms implemented by TIGRAS 2.0 are a DSN antenna-load-forecasting algorithm and a conflict-aware DSN schedule-generating algorithm. Computers running TIGRAS 2.0 can also be connected using SOAP/XML to a Web services server that provides analysis services via the World Wide Web. TIGRAS 2.0 supports multiple windows and multiple panes in each window for users to view and use information, all in the same environment, to eliminate repeated switching among various application programs and Web pages. TIGRAS 2.0 enables the use of multiple windows for various requirements, trajectory-based time intervals during which spacecraft are viewable, ground resources, forecasts, and schedules. Each window includes a time navigation pane, a selection pane, a graphical display pane, a list pane, and a statistics pane.

Resource Balancing Control Allocation

NASA Technical Reports Server (NTRS)

Frost, Susan A.; Bodson, Marc

2010-01-01

Next generation aircraft with a large number of actuators will require advanced control allocation methods to compute the actuator commands needed to follow desired trajectories while respecting system constraints. Previously, algorithms were proposed to minimize the l1 or l2 norms of the tracking error and of the control effort. The paper discusses the alternative choice of using the l1 norm for minimization of the tracking error and a normalized l(infinity) norm, or sup norm, for minimization of the control effort. The algorithm computes the norm of the actuator deflections scaled by the actuator limits. Minimization of the control effort then translates into the minimization of the maximum actuator deflection as a percentage of its range of motion. The paper shows how the problem can be solved effectively by converting it into a linear program and solving it using a simplex algorithm. Properties of the algorithm are investigated through examples. In particular, the min-max criterion results in a type of resource balancing, where the resources are the control surfaces and the algorithm balances these resources to achieve the desired command. A study of the sensitivity of the algorithms to the data is presented, which shows that the normalized l(infinity) algorithm has the lowest sensitivity, although high sensitivities are observed whenever the limits of performance are reached.

Cartographic production for the Florida Shelf Habitat (FLaSH) map study: generation of surface grids, contours, and KMZ files

USGS Publications Warehouse

Robbins, Lisa L.; Hansen, Mark; Raabe, Ellen; Knorr, Paul O.; Browne, Joseph

2007-01-01

The Florida shelf represents a finite source of economic resources, including commercial and recreational fisheries, tourism, recreation, sand and gravel resources, phosphate, and freshwater reserves. Yet the basic information needed to locate resources, or to interpret and utilize existing data, comes from many sources, dates, and formats. A multi-agency effort is underway to coordinate and prioritize the compilation of suitable datasets for an integrated information system of Florida’s coastal and ocean resources. This report and the associated data files represent part of the effort to make data accessible and useable with computer-mapping systems, web-based technologies, and user-friendly visualization tools. Among the datasets compiled and developed are seafloor imagery, marine sediment data, and existing bathymetric data. A U.S. Geological Survey-sponsored workshop in January 2007 resulted in the establishment of mapping priorities for the state. Bathymetry was identified as a common priority among agencies and researchers. State-of-the-art computer-mapping techniques and data-processing tools were used to develop shelf-wide raster and vector data layers. Florida Shelf Habitat (FLaSH) Mapping Project (http://coastal.er.usgs.gov/flash) endeavors to locate available data, identify data gaps, synthesize existing information, and expand our understanding of geologic processes in our dynamic coastal and marine systems.

Modeling Biodegradation and Reactive Transport: Analytical and Numerical Models

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

Sun, Y; Glascoe, L

The computational modeling of the biodegradation of contaminated groundwater systems accounting for biochemical reactions coupled to contaminant transport is a valuable tool for both the field engineer/planner with limited computational resources and the expert computational researcher less constrained by time and computer power. There exists several analytical and numerical computer models that have been and are being developed to cover the practical needs put forth by users to fulfill this spectrum of computational demands. Generally, analytical models provide rapid and convenient screening tools running on very limited computational power, while numerical models can provide more detailed information with consequent requirementsmore » of greater computational time and effort. While these analytical and numerical computer models can provide accurate and adequate information to produce defensible remediation strategies, decisions based on inadequate modeling output or on over-analysis can have costly and risky consequences. In this chapter we consider both analytical and numerical modeling approaches to biodegradation and reactive transport. Both approaches are discussed and analyzed in terms of achieving bioremediation goals, recognizing that there is always a tradeoff between computational cost and the resolution of simulated systems.« less

Operating Dedicated Data Centers - Is It Cost-Effective?

NASA Astrophysics Data System (ADS)

Ernst, M.; Hogue, R.; Hollowell, C.; Strecker-Kellog, W.; Wong, A.; Zaytsev, A.

2014-06-01

The advent of cloud computing centres such as Amazon's EC2 and Google's Computing Engine has elicited comparisons with dedicated computing clusters. Discussions on appropriate usage of cloud resources (both academic and commercial) and costs have ensued. This presentation discusses a detailed analysis of the costs of operating and maintaining the RACF (RHIC and ATLAS Computing Facility) compute cluster at Brookhaven National Lab and compares them with the cost of cloud computing resources under various usage scenarios. An extrapolation of likely future cost effectiveness of dedicated computing resources is also presented.

Computing the Envelope for Stepwise-Constant Resource Allocations

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Clancy, Daniel (Technical Monitor)

2002-01-01

Computing tight resource-level bounds is a fundamental problem in the construction of flexible plans with resource utilization. In this paper we describe an efficient algorithm that builds a resource envelope, the tightest possible such bound. The algorithm is based on transforming the temporal network of resource consuming and producing events into a flow network with nodes equal to the events and edges equal to the necessary predecessor links between events. A staged maximum flow problem on the network is then used to compute the time of occurrence and the height of each step of the resource envelope profile. Each stage has the same computational complexity of solving a maximum flow problem on the entire flow network. This makes this method computationally feasible and promising for use in the inner loop of flexible-time scheduling algorithms.

A national-scale authentication infrastructure.

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

Butler, R.; Engert, D.; Foster, I.

2000-12-01

Today, individuals and institutions in science and industry are increasingly forming virtual organizations to pool resources and tackle a common goal. Participants in virtual organizations commonly need to share resources such as data archives, computer cycles, and networks - resources usually available only with restrictions based on the requested resource's nature and the user's identity. Thus, any sharing mechanism must have the ability to authenticate the user's identity and determine if the user is authorized to request the resource. Virtual organizations tend to be fluid, however, so authentication mechanisms must be flexible and lightweight, allowing administrators to quickly establish andmore » change resource-sharing arrangements. However, because virtual organizations complement rather than replace existing institutions, sharing mechanisms cannot change local policies and must allow individual institutions to maintain control over their own resources. Our group has created and deployed an authentication and authorization infrastructure that meets these requirements: the Grid Security Infrastructure. GSI offers secure single sign-ons and preserves site control over access policies and local security. It provides its own versions of common applications, such as FTP and remote login, and a programming interface for creating secure applications.« less

VirTUal remoTe labORatories managEment System (TUTORES): Using Cloud Computing to Acquire University Practical Skills

ERIC Educational Resources Information Center

Caminero, Agustín C.; Ros, Salvador; Hernández, Roberto; Robles-Gómez, Antonio; Tobarra, Llanos; Tolbaños Granjo, Pedro J.

2016-01-01

The use of practical laboratories is a key in engineering education in order to provide our students with the resources needed to acquire practical skills. This is specially true in the case of distance education, where no physical interactions between lecturers and students take place, so virtual or remote laboratories must be used. UNED has…

Please Move Inactive Files Off the /projects File System | High-Performance

Science.gov Websites

Computing | NREL Please Move Inactive Files Off the /projects File System Please Move Inactive Files Off the /projects File System January 11, 2018 The /projects file system is a shared resource . This year this has created a space crunch - the file system is now about 90% full and we need your help

Evaluation of Management Systems Performance at Navy Regional Data Automation Centers.

DTIC Science & Technology

1984-03-01

REPORT NUMBER 7 . AUTHN~s) S. CONTRACT OR GRANT NUM@ER(@) Gloria Jean Cummings Scott 9. PERFORMING OROANIZATION NAME AND ADDRESS 10. PROGR3AM1 ELEMENT...120 BIBLIOGRAPHY . .. .. .. .. ... . . . . .. ... 124 I INITIAl DISTRIBUTION LIST ............... 125 7 p I,, 7 7 t I...invest- ment in information resources-- people , machines, and technologies. Unit costs of hardware continue to decline [Ref. 1]. Because computer needs

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.

Mathematics and online learning experiences: a gateway site for engineering students

NASA Astrophysics Data System (ADS)

Masouros, Spyridon D.; Alpay, Esat

2010-03-01

This paper focuses on the preliminary design of a multifaceted computer-based mathematics resource for undergraduate and pre-entry engineering students. Online maths resources, while attractive in their flexibility of delivery, have seen variable interest from students and teachers alike. Through student surveys and wide consultations, guidelines have been developed for effectively collating and integrating learning, support, application and diagnostic tools to produce an Engineer's Mathematics Gateway. Specific recommendations include: the development of a shared database of engineering discipline-specific problems and examples; the identification of, and resource development for, troublesome mathematics topics which encompass ideas of threshold concepts and mastery components; the use of motivational and promotional material to raise student interest in learning mathematics in an engineering context; the use of general and lecture-specific concept maps and matrices to identify the needs and relevance of mathematics to engineering topics; and further exploration of the facilitation of peer-based learning through online resources.

Determining Optimal Nursing Resources in Relation to Functions During the Oulu University Hospital Nurse Staffing Management Project.

PubMed

Liljamo, Pia; Lavander, Päivi; Kejonen, Pirjo

2016-01-01

The Oulu University Hospital's staffing management project sought information on the number of nursing staff in relation to treatment days and visits, using existing indicators to describe the activities involved. The retrospective data obtained was compared to human resources and the personnel structure. On this basis an optimal number of staff was determined for the units, taking account of a range of explanatory indicator data. The project made use of the computational model for nurse staffing and the World Health Organisation's (WHO) Workload Indicators of Staffing Need (WISN) method. The project provided extensive information on human resources issues within the units. Its results indicated the differences between wards with respect to the number and structure of resources. In addition, the nurse administrators lacked skills in gathering and using data from administrative datasets. This information will provide support for the further development of nursing operations and nursing management decision-making.