A voting-based working set assessment scheme for dynamic cache resizing mechanisms

Masayuki Sato, Ryusuke Egawa, H. Takizawa, Hiroaki Kobayashi
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引用次数: 7

Abstract

Considering the trade-off between performance and power consumption has become significantly important in multi-core processor design. Under this situation, one promising approach is to employ a power-aware dynamic cache partitioning mechanism. This mechanism individually manages activation of each cache way, and exclusively allocates the minimum number of required ways to each thread. In the mechanism, an appropriate number of ways for a thread is decided based on locality assessment. However, sampling results of cache accesses that are used for locality assessment are disturbed by exceptional behaviors of cache accesses, which happen in a very short period. Such sampling results may change locality assessment results to ones that are not along with the overall trend in a long access-sampling period. These assessment results will excessively adapt the cache to exceptional behaviors, and deteriorate energy efficiency. To avoid such excessive adaptation by the exceptional behaviors, this paper proposes a voting-based working set assessment scheme, in which the number of activated ways is adjusted based on majority voting of locality assessment of several short sampling periods. By using the majority voting, the proposed scheme can identify the periods including exceptional behaviors, and ignore the assessment results of these periods. As a result, the proposed scheme makes the cache resizing mechanism more stable and robust. The experimental results indicate that the proposed scheme can reduce energy consumption by up to 24%, and 10% on an average without significant performance degradation in multi-thread execution on a 2-core CMP.
一种基于投票的动态缓存调整机制的工作集评估方案
在多核处理器设计中,考虑性能和功耗之间的权衡已经变得非常重要。在这种情况下,一种有希望的方法是采用功率感知动态缓存分区机制。该机制单独管理每种缓存方式的激活,并专门为每个线程分配最少数量的所需方式。在该机制中,基于局部性评估确定线程的适当路径数。然而,用于局部性评估的缓存访问采样结果会受到缓存访问异常行为的干扰,这些异常行为发生在很短的时间内。这样的采样结果可能会使局部评价结果在较长的访问采样周期内与总体趋势不一致。这些评估结果会使缓存过度适应异常行为,从而降低能源效率。为了避免这种异常行为的过度适应,本文提出了一种基于投票的工作集评估方案,该方案根据几个短采样周期的局部评估的多数投票来调整激活方式的数量。该方案采用多数表决的方法,可以识别包含异常行为的时间段,而忽略这些时间段的评估结果。因此,该方案使缓存大小调整机制更加稳定和健壮。实验结果表明,该方案在2核CMP上的多线程执行中,可以减少高达24%的能耗,平均减少10%的能耗,而不会显著降低性能。
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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