Research Initiation Award: Compilation of Data-Parallel Programs for Scalable Shared-Address Space Multiprocessors

研究启动奖：可扩展共享地址空间多处理器数据并行程序的编译

• 批准号: 9309054
• 负责人: David Hudak
• 金额: $ 5.08万
• 依托单位: Ohio Northern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-09-01 至 1997-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9309054&HistoricalAwards=false
• 关键词: Research; Initiation; Award; Compilation; Data

9309054 Hudak Shared-address distributed-memory massively parallel processing (MPP) system offer the simplicity of a single address space while maintaining the potential for teraflops performance. However, to obtain reasonable efficiency on these systems, the programmer or compiler must specify and appropriate distribution of work and data among the processors and the physically distributed memories. This project will address the problem of determining the optimal distributions for a given parallel application. Ongoing research in compilation for MPP's has yielded a collection of techniques for the specification of work and data distributions for individual data-parallel loops. This project will combine those techniques with flow-graph representations of data-parallel programs to generate code which specifics the creation and alteration of work and data distributions. The distributions will be designed maximum efficiency across program constructs for altering the flow of control of a program, such as conditional statements (e.g., if statements) and procedure calls. The research will lead to the development of a software system named DPF+, a new system that will analyze an partition data- parallel programs as well as provide an efficient environment for object-oriented data-parallel programming. Data parallel program can be built from user-defined objects, with the DFT+ compiler automatically tuning each object's procedures for high performance on an existing shared-address spaced multiprocessor system. This research will greatly increase the usability of MPPs, the portability of parallel programs and the performance level achieved by users. ***

9309054 Hudak共享地址分布式存储器大规模并行处理（MPP）系统提供了单一地址空间的简单性，同时保持了万亿次浮点运算性能的潜力。 然而，为了在这些系统上获得合理的效率，程序员或编译器必须在处理器和物理分布的存储器之间指定和适当地分配工作和数据。 这个项目将解决为给定的并行应用程序确定最佳分布的问题。 正在进行的MPP编译研究已经产生了一系列技术，用于规范单个数据并行循环的工作和数据分布。 这个项目将联合收割机结合这些技术与流图表示的数据并行程序，以产生代码，具体的创建和更改的工作和数据分布。 分布将被设计为跨程序构造的最大效率，用于改变程序的控制流，诸如条件语句（例如，if语句）和过程调用。 本文的研究工作将有助于开发一个名为DPF+的软件系统，该系统将分析一个分区的数据并行程序，并为面向对象的数据并行程序设计提供一个有效的环境。 数据并行程序可以从用户定义的对象，DFT+编译器自动调整每个对象的程序，在现有的共享地址空间的多处理器系统的高性能。 该研究将大大提高并行程序的可用性、可移植性和用户可达到的性能水平。 ***