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Cache replacement policy based on expected hit count

Vakil Ghahani, A ; Sharif University of Technology | 2018

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  1. Type of Document: Article
  2. DOI: 10.1109/LCA.2017.2762660
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2018
  4. Abstract:
  5. Memory-intensive workloads operate on massive amounts of data that cannot be captured by last-level caches (LLCs) of modern processors. Consequently, processors encounter frequent off-chip misses, and hence, lose significant performance potential. One of the components of a modern processor that has a prominent influence on the off-chip miss traffic is LLC's replacement policy. Existing processors employ a variation of least recently used (LRU) policy to determine the victim for replacement. Unfortunately, there is a large gap between what LRU offers and that of Belady's MIN, which is the optimal replacement policy. Belady's MIN requires selecting a victim with the longest reuse distance, and hence, is unfeasible due to the need for knowing the future. In this work, we observe that there exists a strong correlation between the expected number of hits of a cache block and the reciprocal of its reuse distance. Taking advantage of this observation, we improve the efficiency of last-level caches through a low-cost-yet-effective replacement policy. We suggest a hit-count based victim-selection procedure on top of existing low-cost replacement policies to significantly improve the quality of victim selection in last-level caches without commensurate area overhead. Our proposal offers 12.2 percent performance improvement over the baseline LRU in a multi-core processor and outperforms EVA, which is the state-of-the-art replacement policy. © 2017 IEEE
  6. Keywords:
  7. Belady's MIN ; Last-level cache ; Memory system ; Memory-intensive workload ; Correlation methods ; History ; Radiation detectors ; Last-level caches ; Memory systems ; Multi-core processing ; Prefetching ; Proposals ; Replacement policy ; Cache memory
  8. Source: IEEE Computer Architecture Letters ; Volume 17, Issue 1 , 2018 , Pages 64-67 ; 15566056 (ISSN)
  9. URL: https://ieeexplore.ieee.org/document/8070325