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.

PetersonMapping Polygranular Parallel Programs（P3）to Shared，Heterogeneous，High Performance Reconfigurable Computers（HPRC）摘要该项目旨在开发性能模型和映射算法作为设计基础设施的理论基础，以支持在共享，异构，高性能可重构计算机（HPRC）上执行的多粒度并行程序。 该项目将开发一个数学框架，用于表征在HPRC系统上执行的多粒度并行应用程序的性能。 此外，该项目还将研究计算效率高的方法，以最佳方式将应用程序映射到HPRC系统，从而大大提高HPRC和相关计算平台的设计自动化效率。 鉴于嵌入式系统和网格作为无处不在的计算基础的出现，该项目将专门解决与共享，该项目致力于新兴计算机系统体系结构领域，其更广泛的目标是提供有效利用当前和新兴硬件平台所需的理论性能建模和映射基础设施多粒度并行程序。 因此，该计划支持国家努力满足下一代计算需求的网格和嵌入式系统，包括片上系统。 HPRC平台的计算能力承诺显着的性能和成本改进的频谱的问题域，如图像处理和图形算法。