세트별 재사용 정보 기반 쓰래싱 저항 캐쉬 관리 기법
Reuse Information based Thrashing Resistant Cache Management Scheme
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In recent computing systems, LRU replacement policy has been widely used because it can be simply implemented and applicable to most programs. However, if the working set size of the program is bigger than the actual cache size, LRU replacement policy may occur thrashing problem. Thrashing problem means that cache blocks are consistently replaced without re-referencing in the cache. This paper proposes a new cache management scheme to solve the thrashing problem in the second-level cache. The proposed scheme measures per set reuse frequency using EAF structure to find thrashing sets. When the cache miss occurs, it tests whether the address of the missed block is stored or not. If the address of the missed block is stored, it means that the recently evicted block is re-requested, so the reuse frequency is predicted high. In this case, the corresponding counter of the set is increased. When the counter value is bigger than the threshold value, we assume that the corresponding set shows high reuse frequency. The proposed scheme assigns the set with high reuse frequency to the additional small size cache to keep the blocks in the cache for a long time. Our experimental results show that the proposed scheme improves the IPC by 3.81% on average.
Abstract
In recent computing systems, LRU replacement policy has been widely used because it can be simply implemented and applicable to most programs. However, if the working set size of the program is bigger than the actual cache size, LRU replacement policy may occur thrashing problem. Thrashing problem means that cache blocks are consistently replaced without re-referencing in the cache. This paper proposes a new cache management scheme to solve the thrashing problem in the second-level cache. The proposed scheme measures per set reuse frequency using EAF structure to find thrashing sets. When the cache miss occurs, it tests whether the address of the missed block is stored or not. If the address of the missed block is stored, it means that the recently evicted block is re-requested, so the reuse frequency is predicted high. In this case, the corresponding counter of the set is increased. When the counter value is bigger than the threshold value, we assume that the corresponding set shows high reuse frequency. The proposed scheme assigns the set with high reuse frequency to the additional small size cache to keep the blocks in the cache for a long time. Our experimental results show that the proposed scheme improves the IPC by 3.81% on average.
참고문헌 (12)
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