Partition-Based Cache Replacement to Manage Shared L2 Caches

FANG Juan; WANG Jing; LI Chengyan; YAO Zhicheng; KE Weimao

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Article Navigation > Chinese Journal of Electronics > 2014 > 23(3): 464-467

FANG Juan, WANG Jing, LI Chengyan, et al., “Partition-Based Cache Replacement to Manage Shared L2 Caches,” Chinese Journal of Electronics, vol. 23, no. 3, pp. 464-467, 2014,

Citation:

FANG Juan, WANG Jing, LI Chengyan, et al., “Partition-Based Cache Replacement to Manage Shared L2 Caches,” Chinese Journal of Electronics, vol. 23, no. 3, pp. 464-467, 2014,

FANG Juan, WANG Jing, LI Chengyan, et al., “Partition-Based Cache Replacement to Manage Shared L2 Caches,” Chinese Journal of Electronics, vol. 23, no. 3, pp. 464-467, 2014,

Citation:

FANG Juan, WANG Jing, LI Chengyan, et al., “Partition-Based Cache Replacement to Manage Shared L2 Caches,” Chinese Journal of Electronics, vol. 23, no. 3, pp. 464-467, 2014,

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Partition-Based Cache Replacement to Manage Shared L2 Caches

1.
College of Computer Science, Beijing University of Technology, Beijing 100124, China;
2.
College of Information Engineering, Capital Normal University, Beijing 100048, China;
3.
College of Computing and Informatics, Drexel University, Chapel Hill, NC, USA

Funds: This work is supported by the National Natural Science Foundation of China (No.61202076, No.61202062) and the General Program of Science and Technology Development Project of the Beijing Municipal Education Commission (No.KM201210005022).

More Information

Corresponding author: WANG Jing
Received Date: 2014-01-01
Rev Recd Date: 2014-03-01
Publish Date: 2014-07-05

Abstract

Abstract

The Least recently used (LRU) replacement has been widely employed by on-chip shared caches. With the increase of cache associativity, the performance gap between LRU and theoretical optimal replacement algorithm is significant, motivating us to design alternative replacement algorithms to improve cache performance. We propose a Partition-based cache replacement (PCR) algorithm to manage multi-core shared L2 caches. PCR takes into consideration recency and frequency information of cache access, and cache resource interference among multiple competing applications. PCR is effective to filter out the less frequently reused blocks through a dynamic insertion/promotion policy based on the target partitions, and ensures that some fraction of the working set is retained in the cache to contribute to more hits. Our evaluation shows that PCR improves performance of an 8-core system by an average of 11.3% over LRU-based cache.
- Multi-core,
- Shared cache,
- Replacement algorithm,
- Cache partition

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References(15)

References

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