Mapping Polygranular Parallel Processing to Shared, Heterogeneous, High-Performance Reconfigurable Computers

将多粒度并行处理映射到共享、异构、高性能可重构计算机

• 批准号: 0311500
• 负责人: Gregory Peterson
• 金额: $ 10.24万
• 依托单位: University of Tennessee Knoxville
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-08-15 至 2005-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0311500&HistoricalAwards=false
• 关键词: Mapping; Polygranular; Parallel; Processing; Shared

PetersonMapping Polygranular Parallel Programs (P3) to Shared, Heterogeneous, High Performance Reconfigurable Computers (HPRC)AbstractThe proposed project aims at the development of performance models and mapping algorithms as the theoretical foundation of a design infrastructure to support polygranular parallel programs executing on shared, heterogeneous, High Performance Reconfigurable Computers (HPRC). The project will develop a mathematical framework for characterizing the performance of polygranular parallel applications executing on HPRC systems. Moreover, the project will investigate computationally efficient approaches for optimally mapping applications to HPRC systems, providing dramatic improvement in design automation efficiency for HPRC and related computational platforms. Given the emergence of both embedded systems and the Grid as the basis for ubiquitous computing, the project will specifically address issues related to polygranular parallel application execution in a shared, heterogeneous environment.This project addresses the area of emerging computer systems architectures with the broader objective of providing the theoretic performance modeling and mapping infrastructure necessary to effectively exploit current and emerging hardware platforms with polygranular parallel programs. Hence, the program supports national efforts to meet next-generation computational needs with the grid and with embedded systems including system-on-chip. The computational capabilities of HPRC platforms promise significant performance and cost improvements for a spectrum of problem domains, such as image processing and graph algorithms.

PETSORMAPTIONMAPTION TORYPRALULALUL平行程序（P3）到共享的，异质的，高性能的可重构计算机（HPRC）摘要摘要该提出的项目旨在开发性能模型并将算法映射为设计基础架构的理论基础，以支持共享，高度兼容，高级绩效的共享平行程序，以支持共享的平行计划。 该项目将开发一个数学框架，用于表征HPRC系统执行的多元平行应用的性能。 此外，该项目将研究为HPRC系统最佳映射应用程序的计算高效方法，从而为HPRC和相关计算平台提供了设计自动化效率的显着提高。 鉴于嵌入式系统和网格作为无处不在计算的基础的出现，该项目将在共享的，异构的环境中特别解决与多晶平行应用执行相关的问题程序。 因此，该计划支持国家通过网格和嵌入式系统在内的芯片（包括芯片上系统的嵌入式系统）来满足下一代计算需求的努力。 HPRC平台的计算能力有助于对问题域（例如图像处理和图形算法）进行显着的性能和成本提高。