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SHF: Medium: Collaborative Research: Next-Generation Message Passing for Parallel Programming: Resiliency, Time-to-Solution, Performance-Portability, Scalability, and QoS

SHF: Medium: Collaborative Research: Next-Generation Message Passing for Parallel Programming: Resiliency, Time-to-Solution, Performance-Portability, Scalability, and QoS
SHF:中:协作研究:并行编程的下一代消息传递:弹性、解决时间、性能可移植性、可扩展性和 QoS
批准号:
1822191
负责人:
Anthony Skjellum
金额:
$52.37万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-10-01 至 2022-05-31

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中文摘要
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英文摘要
Parallel programming based on MPI is being used with increased frequency in academia, government (defense and non-defense uses), as well as emerging uses in scalable machine learning and big data analytics. Emerging supercomputer systems will have more faults and MPI needs to be able to workaround such faults to be appropriate to these emerging situations, rather than causing an entire application to fail. Collaborative, transformative message passing research for High Performance Computing (HPC) critical to performance-portable parallel programming in new and forthcoming scalable systems (with a strategy of "best practice-first, standardization-later") is being reduced to practice. A substantial subset of the Message Passing Interface (MPI-3/4) application programmer interface is being made fault tolerant through extensions with weak collective transactions that synchronize between parallel tasks. This research studies the novel model that localizes faults, provides tunable fault-free overhead, allows for multiple kinds of faults, enables hierarchical recovery, and is data-parallel relevant. Fault modeling of underlying networks is being studied. Application developers control the granularity and fault-free overhead in this effort. Performance and scalability results of the middleware prototype are being demonstrated principally through compact applications that relate to real use cases of practical and academic interest. The impact of this work ranges from users of the largest supercomputers in government labs to practical clusters that have long-running, time-critical applications, and to space-based and other parallel processing in "hostile" environments where faults occur more frequently than in past years. The project is producing usable free software that will be widely shared in the community as well as guidance on how better parallel programs can be written in academia, industry, and government. The project also provides guidelines for how to update existing or legacy programs to use the new capabilities that are being reduced to practice.
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会议论文
DOI: 10.1145/3458744.3474046
发表时间: 2021
期刊: ICPP Workshops '21: 50th International Conference on Parallel Processing Workshop
影响因子: --
作者: [Worley, Andrew, Prema Soundararajan, Prema, Schafer, Derek, Bangalore, Purushotham, Grant, Ryan, Dosanjh, Matthew, Skjellum, Anthony, Ghafoor, Sheikh]
通讯作者: Ghafoor, Sheikh
SPX: Collaborative Research: Intelligent Communication Fabrics to Facilitate Extreme Scale Computing
  • 批准号:
    2412182
  • 项目类别:
    Standard Grant
  • 资助金额:
    $45.01万
  • 财政年份:
    2023
  • 负责人:
    Anthony Skjellum
  • 依托单位:
Collaborative Research: EAGER: Real-time Strategies and Synchronized Time Distribution Mechanisms for Enhanced Exascale Performance-Portability and Predictability
  • 批准号:
    2405142
  • 项目类别:
    Standard Grant
  • 资助金额:
    $7.45万
  • 财政年份:
    2023
  • 负责人:
    Anthony Skjellum
  • 依托单位:
Beginnings: Creating and Sustaining a Diverse Community of Expertise in Quantum Information Science (EQUIS) Across the Southeastern United States
  • 批准号:
    2414461
  • 项目类别:
    Cooperative Agreement
  • 资助金额:
    $25.85万
  • 财政年份:
    2023
  • 负责人:
    Anthony Skjellum
  • 依托单位:
Collaborative Research: EAGER: Real-time Strategies and Synchronized Time Distribution Mechanisms for Enhanced Exascale Performance-Portability and Predictability
  • 批准号:
    2151020
  • 项目类别:
    Standard Grant
  • 资助金额:
    $7.45万
  • 财政年份:
    2022
  • 负责人:
    Anthony Skjellum
  • 依托单位:
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