A novel cache replacement policy via dynamic adaptive insertion and re-reference prediction

Xi Zhang*, Chongmin Li, Zhenyu Liu, Haixia Wang, Dongsheng Wang, Takeshi Ikenaga

*この研究の対応する著者

研究成果: Article査読

3 被引用数 (Scopus)

抄録

Previous research illustrates that LRU replacement policy is not efficient when applications exhibit a distant re-reference interval. Recently RRIP policy is proposed to improve the performance for such kind of workloads. However, the lack of access recency information in RRIP confuses the replacement policy to make the accurate prediction. To enhance the robustness of RRIP for recency-friendly workloads, we propose an Dynamic Adaptive Insertion and Re-reference Prediction (DAI-RRP) policy which evicts data based on both re-reference prediction value and the access recency information. DAI-RRP makes adaptive adjustment on insertion position and prediction value for different access patterns, which makes the policy robust across different workloads and different phases. Simulation results show that DAI-RRP outperforms LRU and RRIP. For a single-core processor with a 1MB 16-way set last-level cache (LLC), DAIRRP reduces CPI over LRU and Dynamic RRIP by an average of 8.1% and 2.7% respectively. Evaluations on quad-core CMP with a 4MBshared LLC show that DAI-RRP outperforms LRU and Dynamic RRIP (DRRIP) on the weighted speedup metric by an average of 8.1% and 15.7% respectively. Furthermore, compared to LRU, DAI-RRP consumes the similar hardware for 16-way cache, or even less hardware for high-associativity cache. In summary, the proposed policy is practical and can be easily integrated into existing hardware approximations of LRU.

本文言語English
ページ(範囲)468-476
ページ数9
ジャーナルIEICE Transactions on Electronics
E94-C
4
DOI
出版ステータスPublished - 2011 4

ASJC Scopus subject areas

  • 電子材料、光学材料、および磁性材料
  • 電子工学および電気工学

フィンガープリント

「A novel cache replacement policy via dynamic adaptive insertion and re-reference prediction」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル