Optimal Footprint Symbiosis in Shared Cache

Xiaolin Wang, Yechen Li, Yingwei Luo, Xiameng Hu, Jacob Brock, C. Ding, Zhenlin Wang
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引用次数: 15

Abstract

On multicore processors, applications are run sharing the cache. This paper presents online optimization to collocate applications to minimize cache interference to maximize performance. The paper formulates the optimization problem and solution, presents a new sampling technique for locality analysis and evaluates it in an exhaustive test of 12,870 cases. For locality analysis, previous sampling was two orders of magnitude faster than full-trace analysis. The new sampling reduces the cost by another two orders of magnitude. The best prior work improves co-run performance by 56% on average. The new optimization improves it by another 29%. When sampling and optimization are combined, the paper shows that it takes less than 0.1 second analysis per program to obtain a co-run that is within 1.5% of the best possible performance.
共享缓存中的最优内存占用共生
在多核处理器上,应用程序运行时共享缓存。本文提出了在线优化配置应用程序,以减少缓存干扰,最大限度地提高性能。本文提出了优化问题及其求解方法,提出了一种新的局部分析抽样技术,并通过对12870例的穷举测试对其进行了评价。对于局部性分析,以前的采样比全迹分析快两个数量级。新的采样方法将成本又降低了两个数量级。最好的先前工作平均提高了56%的协同运行性能。新的优化又提高了29%。当采样和优化相结合时,论文表明,每个程序只需不到0.1秒的分析就可以获得在最佳性能的1.5%以内的共同运行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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