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RECAP: Region-Aware Cache Partitioning

机译:RECAP:区域感知缓存分区

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In recent years, high performance computing systems have obtained more processing cores and share a last level cache (LLC). However, as their number grows, the core-to-way ratio in the LLC increases, presenting problems to existing cache partitioning techniques which require more ways than cores. Furthermore, effective energy management of the LLC becomes increasingly important due to its size. This paper proposes a Region Aware Cache Partitioning (RECAP), an LLC energy-saving scheme for high-performance, many-core processors. RECAP partitions the data within the cache into shared and private regions. Applications only access the ways containing the data that they require, realising dynamic energy savings. Any ways that are not within the shared or private regions can be turned off to save static energy. We evaluate our scheme using an 8-core CMP running multi-programmed workloads and show that it achieves 17% dynamic and 13% static energy savings in the shared LLC with a 15% performance gain. Across our multi-threaded applications, we achieve 17% dynamic and 41% static energy savings with no impact on performance.
机译:近年来,高性能计算系统已经获得了更多的处理核心,并共享最后一级缓存(LLC)。但是,随着它们数量的增加,LLC中的核心/通道比率增加,给现有的缓存分区技术带来了问题,该技术需要比核心更多的方法。此外,由于LLC的规模,有效的能源管理变得越来越重要。本文提出了一种区域感知缓存分区(RECAP),一种针对高性能,多核处理器的LLC节能方案。 RECAP将缓存中的数据划分为共享区域和专用区域。应用程序仅访问包含其所需数据的方式,从而实现了动态节能。可以关闭不在共享或私有区域内的任何方式以节省静态能量。我们使用运行多程序工作负载的8核CMP评估了我们的方案,结果表明,该方案在共享LLC中实现了17%的动态能耗和13%的静态能耗节省,而性能却提高了15%。在我们的多线程应用程序中,我们实现了17%的动态能耗和41%的静态能耗节省,并且不影响性能。

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