SHF:Large:Collaborative Research:Unified Runtime for Supporting Hybrid Programming Models on Heterogeneous Architecture

SHF：大型：协作研究：支持异构架构上混合编程模型的统一运行时

• 批准号: 1213057
• 负责人: William Barth
• 金额: $ 37.19万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-07-01 至 2016-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1213057&HistoricalAwards=false
• 关键词: SHF; Large; Collaborative; Research; Unified

Most of the traditional High-End Computing (HEC) applications andcurrent petascale applications are written using the Message PassingInterface (MPI) programming model. Some of these applications are runin MPI+OpenMP mode. However, it can be very difficult to use MPI orMPI+OpenMP and maintain performance for applications which demonstrateirregular and dynamic communication patterns. The Partitioned GlobalAddress Space (PGAS) programming model presents a flexible way forthese applications to express parallelism. Accelerators introduceadditional programming models: CUDA, OpenCL or OpenACC. Thus, theemerging heterogeneous architectures require support for varioushybrid programming models: MPI+OpenMP, MPI+PGAS, and MPI+PGAS+OpenMPwith extended APIs for multiple levels of parallelism. Unfortunately,there is no unified runtime which delivers the best performance andscalability for all of these hybrid programming models for a range ofapplications on current and next-generation HEC systems. This leadsto the following broad challenge: "Can a unified runtime for hybridprogramming model be designed which can provide benefits that aregreater than the sum of its parts?"A synergistic and comprehensive research plan, involving computerscientists from The Ohio State University (OSU) and Ohio SupercomputerCenter (OSC) and computational scientists from the Texas AdvancedComputing Center (TACC) and San Diego Supercomputer Center (SDSC),University of California San Diego (UCSD), is proposed to address theabove broad challenge with innovative solutions. The investigatorswill specifically address the following challenges: 1) What are therequirements and limitations of using hybrid programming models for aset of petascale applications? 2) What features and mechanisms areneeded in a unified runtime? 3) How can the unified runtime andassociated extension to programming model APIs be designed andimplemented? 4) How can candidate petascale applications beredesigned to take advantage of proposed unified runtime? and 5) Whatkind of benefits (in terms of performance, scalability andproductivity) can be achieved by the proposed approach? The researchwill be driven by a set of applications from established NSFcomputational science researchers running large scale simulations onRanger and other systems at OSC, SDSC and OSU. The proposed designswill be integrated into the open-source MVAPICH2 library. Theestablished national-scale training and outreach programs at TACC,SDSC and OSC will be used to disseminate the results of this research.

大多数传统的高端计算（HEC）应用程序和当前的千万亿级应用程序都是使用消息传递接口（MPI）编程模型编写的。其中一些应用程序在 MPI+OpenMP 模式下运行。 然而，使用 MPI 或 MPI+OpenMP 并保持表现出不规则和动态通信模式的应用程序的性能可能非常困难。 分区全局地址空间 (PGAS) 编程模型为这些应用程序提供了一种灵活的方式来表达并行性。 加速器引入了额外的编程模型：CUDA、OpenCL 或 OpenACC。 因此，新兴的异构架构需要支持各种混合编程模型：MPI+OpenMP、MPI+PGAS 和 MPI+PGAS+OpenMP，并具有用于多级并行性的扩展 API。 不幸的是，没有统一的运行时可以为当前和下一代 HEC 系统上的一系列应用程序的所有这些混合编程模型提供最佳性能和可扩展性。 这导致了以下广泛的挑战：“能否为混合编程模型设计一个统一的运行时，其所带来的好处大于各部分之和？”一项协同且全面的研究计划，涉及俄亥俄州立大学 (OSU) 和俄亥俄州的计算机科学家超级计算机中心 (OSC) 以及来自德克萨斯高级计算中心 (TACC) 和圣地亚哥超级计算机中心 (SDSC)、加州大学圣地亚哥分校 (UCSD) 的计算科学家提出通过创新解决上述广泛挑战解决方案。 研究人员将具体解决以下挑战：1）对一组千万亿级应用程序使用混合编程模型有哪些要求和限制？ 2）统一运行时需要哪些特性和机制？ 3）如何设计和实现统一的运行时和相关的编程模型API扩展？ 4) 如何重新设计候选千万级应用程序以利用建议的统一运行时？ 5) 通过所提出的方法可以实现哪些好处（在性能、可扩展性和生产力方面）？ 该研究将由美国国家科学基金会 (NSF) 计算科学研究人员的一系列应用程序推动，这些研究人员在 OSC、SDSC 和 OSU 的 Ranger 和其他系统上运行大规模模拟。 拟议的设计将集成到开源 MAPICH2 库中。 TACC、SDSC 和 OSC 已建立的国家级培训和推广计划将用于传播这项研究成果。