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Collaborative Research: CC-NIE Integration: Transforming Computational Science with ADAMANT (Adaptive Data-Aware Multi-Domain Application Network Topologies)

Collaborative Research: CC-NIE Integration: Transforming Computational Science with ADAMANT (Adaptive Data-Aware Multi-Domain Application Network Topologies)
合作研究:CC-NIE 集成:利用 ADAMANT(自适应数据感知多域应用网络拓扑)转变计算科学
批准号:
1246057
负责人:
Ewa Deelman
金额:
$20.41万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-01-01 至 2014-12-31

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中文摘要
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英文摘要
Workflows, especially data-driven workflows and workflow ensembles are becoming a centerpiece of modern computational science. However, scientists lack the tools that integrate the operation of workflow-driven science applications on top of dynamic infrastructures that link campus, institutional and national resources into connected arrangements targeted at solving a specific problem. These tools must (a) orchestrate the infrastructure in response to application demands, (b) manage application lifetime on top of the infrastructure by monitoring various workflow steps and modifying slices in response to application demands, and (c) integrate data movement with the workflows to optimize performance. Project ADAMANT (Adaptive Data-Aware Multi-domain Application Network Topologies) brings together researchers from RENCI/UNC Chapel Hill, Duke University and USC/ISI and two successful software tools to solve these problems: Pegasus workflow management system and ORCA resource control framework, developed for NSF GENI. The integration of Pegasus and ORCA enables powerful application- and data-driven virtual topology embedding into multiple institutional and national substrates (providers of cyber-resources, like computation, storage and networks). ADAMANT leverages ExoGENI - an NSF-funded GENI testbed, as well as national providers of on-demand bandwidth services (NLR, I2, ESnet) and existing OSG computational resources to create elastic, isolated environments to execute complex distributed tasks. This approach improves the performance of these applications and, by explicitly including data movement planning into the application workflow, enables new unique capabilities for distributed data-driven "Big Science" applications.
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Collaborative Research: CyberTraining: Implementation: Medium: CyberInfrastructure Training and Education for Synchrotron X-Ray Science (X-CITE)
  • 批准号:
    2320375
  • 项目类别:
    Standard Grant
  • 资助金额:
    $31.8万
  • 财政年份:
    2023
  • 负责人:
    Ewa Deelman
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Collaborative Research: SHF: Small: Model-driven Design and Optimization of Dataflows for Scientific Applications
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    2331153
  • 项目类别:
    Standard Grant
  • 资助金额:
    $20.0万
  • 财政年份:
    2023
  • 负责人:
    Ewa Deelman
  • 依托单位:
CI CoE: CI Compass: An NSF Cyberinfrastructure (CI) Center of Excellence for Navigating the Major Facilities Data Lifecycle
  • 批准号:
    2127548
  • 项目类别:
    Standard Grant
  • 资助金额:
    $800.0万
  • 财政年份:
    2021
  • 负责人:
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  • 依托单位:
Collaborative Research: Elements: Simulation-driven Evaluation of Cyberinfrastructure Systems
  • 批准号:
    2103508
  • 项目类别:
    Standard Grant
  • 资助金额:
    $31.5万
  • 财政年份:
    2021
  • 负责人:
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国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
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  • 项目类别:
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  • 批准年份:
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  • 负责人:
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  • 依托单位:
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