基于缓存的可重构计算的性能和能力

Andrew Putnam, S. Eggers, Dave Bennett, E. Dellinger, J. Mason, Henry Styles, P. Sundararajan, Ralph Wittig
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引用次数: 33

摘要

多缓存是一种有效支持商用fpga缓存的内存架构。它为高性能计算(HPC)开发人员提供了比当前CPU平台更高的内存性能和更低的功耗,同时又不会牺牲他们熟悉的基于c语言的编程环境,从而促进了FPGA编程。Many-cache在FGPA的小型独立内存之上创建多个多银行缓存,每个缓存针对应用程序中的特定数据结构或内存区域,每个缓存针对访问它的内存操作进行定制。这些缓存由黑猩猩的C-to- fpga编译器从C源代码自动生成。本文对构建多缓存的黑猩猩编译器进行了分析和优化。对黑猩猩生成的FPGA的架构评估表明,与仅cpu执行相同的源代码相比,FPGA的性能优势为7.8倍(几何平均值),FPGA的功耗平均减少4.1倍,因此每瓦性能也更高,几何平均值为21.3倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance and power of cache-based reconfigurable computing
Many-cache is a memory architecture that efficiently supports caching in commercially available FPGAs. It facilitates FPGA programming for high-performance computing (HPC) developers by providing them with memory performance that is greater and power consumption that is less than their current CPU platforms, but without sacrificing their familiar, C-based programming environment. Many-cache creates multiple, multi-banked caches on top of an FGPA's small, independent memories, each targeting a particular data structure or region of memory in an application and each customized for the memory operations that access it. The caches are automatically generated from C source by the CHiMPS C-to-FPGA compiler. This paper presents the analyses and optimizations of the CHiMPS compiler that construct many-cache caches. An architectural evaluation of CHiMPS-generated FPGAs demonstrates a performance advantage of 7.8x (geometric mean) over CPU-only execution of the same source code, FPGA power usage that is on average 4.1x less, and consequently performance per watt that is also greater, by a geometric mean of 21.3x.
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