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CCF-SHF: CSR: Small: Compilation for Multi-core Processors with Limited Local Memories

CCF-SHF：CSR：小型：本地内存有限的多核处理器的编译

基本信息

批准号：
0916652
负责人：
Aviral Shrivastava
金额：
$ 50万
依托单位：
Arizona State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2009
资助国家：
美国
起止时间：
2009-08-01 至 2014-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=0916652&HistoricalAwards=false
关键词：
CCF SHF CSR Small Compilation

项目摘要

Multi-core processors provide the only way to continue improving peak performance without much increase in the power consumption. However, there are serious challenges not only in expressing all the parallelism in the application, but also in exploiting the available parallelism by efficient application management on modern multi-core architectures. These challenges are only compounded by the trend of the absence of memory virtualization in the hardware, that is observed in futuristic processors, like the IBM Cell, and the Intel experimental 80-core processor. Memory management cannot be supported in hardware, because cache coherency protocols do not scale to 100s or 1000s of cores, and also because memory management in hardware consumes significant energy. Memory management in software can exploit application and data characteristics to reduce the overhead, however, it increases the burden of the application programmer. This project aims to develop tools and techniques to automatically manage the limited local memories present in each of the cores of a multi-core processor. In addition to power-efficient execution, the main objective of the project is to relieve the application programmer of the burden of carefully crafting the application, dividing and mapping it onto the cores to ensure its correct execution and portability.

多核处理器提供了在不增加功耗的情况下继续提高峰值性能的唯一方法。然而，不仅在表达应用程序中的所有并行性方面存在严重的挑战，而且在现代多核架构上通过有效的应用程序管理来利用可用的并行性方面也存在严重的挑战。这些挑战只是由于硬件中缺乏内存虚拟化的趋势而加剧，这在未来的处理器中观察到，如IBM Cell和英特尔实验性80核处理器。硬件无法支持内存管理，因为高速缓存一致性协议无法扩展到100或1000个核心，并且还因为硬件中的内存管理消耗大量能量。软件中的内存管理可以充分利用应用程序和数据的特性来减少开销，但同时也增加了应用程序员的负担。该项目旨在开发工具和技术来自动管理多核处理器的每个核心中存在的有限本地内存。除了高能效执行之外，该项目的主要目标是减轻应用程序员精心制作应用程序的负担，将其划分并映射到核心上，以确保其正确执行和可移植性。