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: University of Tennessee Chattanooga
• 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
• 起止时间: 2017-10-01 至 2022-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1822191&HistoricalAwards=false
• 关键词: SHF; Medium; Collaborative; Research; Next; SHF; Medium; Collaborative; Research; Next

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.

基于MPI的并行编程在学术界，政府（防御和非防御用途）以及可扩展机器学习和大数据分析中的新兴用途中使用。 新兴的超级计算机系统将具有更多的故障，MPI需要能够解决此类故障，以适合这些新兴情况，而不是导致整个应用程序失败。 在新的和即将推出的可扩展系统中对高性能和可行的并行编程至关重要的高性能计算（HPC）的协作，变革性消息传递研究（HPC）正在减少到“最佳实践优先，标准化者”的策略。消息传递接口（MPI-3/4）应用程序程序员接口的大量子集通过具有弱集体交易的扩展来使空中容错，并在并行任务之间同步。这项研究研究了新的模型，该模型定位故障，提供可调的无故障开销，允许多种故障，实现层次恢复，并且与数据并行相关。 正在研究基础网络的故障建模。应用程序开发人员在这项工作中控制了粒度和无故障开销。中间件原型的性能和可伸缩性结果主要是通过与实用和学术兴趣的实际用例相关的紧凑应用来证明的。这项工作的影响范围从政府实验室中最大的超级计算机的用户到具有长期运行，关键时间应用程序的实用集群以及在“敌对”环境中的空间基础和其他并行处理，在这些环境中，故障频率比过去几年更频繁。 该项目正在生产可用的免费软件，该软件将在社区中广泛共享，并提供有关如何在学术界，工业和政府中编写更好的并行计划的指导。 该项目还提供了有关如何更新现有或遗留程序以使用正在练习的新功能的准则。