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

SHF：大型：协作研究：支持异构架构上的混合编程模型的统一运行时。

• 批准号: 1213056
• 负责人: Amitava Majumdar
• 金额: $ 38.22万
• 依托单位: University of California-San Diego
• 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=1213056&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次应用程序都是使用消息传递接口（MPI）编程模型编写的。其中一些应用程序运行在MPI+OpenMP模式下。 然而，使用MPI或MPI +OpenMP并保持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并行表示方式。 加速器引入了额外的编程模型：CUDA，OpenCL或OpenACC。 因此，新兴的异构体系结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的扩展API。 不幸的是，没有统一的运行时，提供最佳的性能和可扩展性，为所有这些混合编程模型的一系列应用程序的当前和下一代HEC系统。 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，它可以提供比其部分之和更大的好处？“一个协同和全面的研究计划，涉及计算机科学家从俄亥俄州州立大学（OSU）和俄亥俄州超级计算机中心（OSC）和计算科学家从得克萨斯州高级计算中心（TACC）和圣地亚哥超级计算机中心（SDSC），加州圣地亚哥大学（UCSD），提出了解决上述广泛的挑战与创新的解决方案。 该研讨会将专门解决以下挑战：1）对于一组千万亿次应用程序，使用混合编程模型的要求和限制是什么？ 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)候选的千万亿次应用程序如何重新设计以利用建议的统一运行时？ 以及5）所提出的方法可以实现什么样的好处（在性能、可扩展性和生产力方面）？ 这项研究将由一组应用程序驱动，这些应用程序来自已建立的NSF计算科学研究人员，他们在OSC，SDSC和OSU的Ranger和其他系统上运行大规模模拟。 所提出的设计将被集成到开源MVAPICH 2库中。 在TACC、SDSC和OSC建立的全国范围的培训和推广计划将用于传播这项研究的结果。