一种节能数据预取的自适应滤波机制

Xianglei Dang, Xiaoyin Wang, Dong Tong, Zichao Xie, Lingda Li, Keyi Wang
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引用次数: 3

摘要

数据预取应用于嵌入式处理器中,减少数据预取的能量浪费是提高处理器能效的关键。本文提出了一种自适应预取滤波(APF)机制,以减少无用预取造成的带宽和能量浪费以及缓存污染。APF记录发出预取的预取受害者地址对,并收集每个地址对中哪个地址首先被处理器访问的信息,以指导过滤新生成的无用预取。同时,记录过滤后的预取,建立反馈机制,避免过滤有用的预取。实验结果表明,APF平均减少了53.81%的无用预取,减少了5.28%的有用预取,从而减少了59.92%的内存访问带宽消耗和6.19%的L2缓存能量。APF还通过减少无用的预取带来的缓存污染来提高几个程序的性能,从而获得2.12%的平均性能提升。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An adaptive filtering mechanism for energy efficient data prefetching
As data prefetching is used in embedded processors, it is crucial to reduce the wasted energy for improving the energy efficiency. In this paper, we propose an adaptive prefetch filtering (APF) mechanism to reduce the wasted bandwidth and energy as well as the cache pollution caused by useless prefetches. APF records the prefetch-victim address pairs of issued prefetches and collects information about which address in each pair is first accessed by the processor to guide the filtering of new generated useless prefetches. Meanwhile, filtered prefetches are recorded for building the feedback mechanism to avoid filtering useful prefetches. Experimental results demonstrate that APF reduces useless prefetches by an average of 53.81% with a mere 5.28% reduction of useful prefetches, thus reducing the memory access bandwidth consumption by 59.92% and the L2 cache energy by 6.19%. APF also improves the performance of several programs by reducing the cache pollution incurred by useless prefetches, thus gaining an average performance improvement of 2.12%.
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