An Adaptive Demotion Policy with Considering Temporal Locality

M. Hasegawa, J. Tada
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Abstract

In the upper-level caches like as L1 caches, the temporal locality mainly affects the performance of the caches. Although the Adaptive Demotion Policy (ADP) can achieve the performance improvement at the upper-level caches compared to the conventional hardware suitable replacement policies, the most recently used block will be evicted when all the blocks in the accessed set have the same priority value. Hence, there is a possibility of decreasing the performance of the cache by spoiling the temporal locality. To avoid this problem, this paper proposes a cache replacement policy which focuses on preventing the eviction of the most recently used block, and the policy is called Adaptive Demotion Policy with considering Temporal Locality (ADPTL). At a cache hit, if the priority values of all the blocks in the accessed set except the hit block are the highest value, the ADPTL decreases these priority values by one. This operation prevents the eviction of the most recently used block. The performance evaluation shows that the ADPTL achieves the reduction of the cache misses and the IPC improvement at the L1 caches compared to the LRU policy and the ADP.
考虑时间局部性的自适应降格策略
在诸如L1缓存这样的上层缓存中,时间局部性主要影响缓存的性能。虽然与传统的硬件合适替换策略相比,自适应降级策略(ADP)可以实现上层缓存的性能改进,但是当访问集中的所有块具有相同的优先级值时,最近使用的块将被驱逐。因此,有可能通过破坏时间局部性来降低缓存的性能。为了避免这一问题,本文提出了一种以防止最近使用的块被移除为重点的缓存替换策略,该策略被称为考虑时间局域性的自适应降级策略(ADPTL)。在缓存命中时,如果访问集中除命中块外的所有块的优先级值都是最高的,则ADPTL将这些优先级值降低1。此操作可防止最近使用的块被删除。性能评估表明,与LRU策略和ADP相比,ADPTL在L1缓存上实现了缓存丢失的减少和IPC的提高。
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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