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Author:

Fang, Juan (Fang, Juan.) (Scholars:方娟) | Li, Cheng-Yan (Li, Cheng-Yan.) | Wang, Shuai (Wang, Shuai.) | Yao, Zhi-Cheng (Yao, Zhi-Cheng.)

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Abstract:

LRU has been widely used in single-core processor, while Chip Multi-Processors (CMP) employ a large Last-Level Cache (LLC) which is shared among the multiple cores. With the increasement of the LLC capacity and associativity, and the grows of working set of multicore's applications, the performance gap between the LRU and the theoretical optimal replacement algorithms gets wider and wider. This paper proposes an Average partition LRU algorithm based on Frequency (ALRU-F). The algorithm has maintained the working set at Cache and drive out the ignore block. Also, a Cache line stealing strategy is proposed to realize a Block partition LRU replacement algorithm based on Frequency (BLRU-F). The result of experiments shows that comparing to the traditional LRU algorithm, the proposed ALRU-F algorithm reduces the miss rate by 26.59%, and improves the Instruction Per Clock (IPC) by 13.59% with little change of power consumption. Comparing to the traditional LRU and BLRU-F algorithms, the proposed algorithm reduces the Cache miss rate by 33.72% and improves the IPC by 16.59%.

Keyword:

Cache memory Multiprocessing systems Partitions (building)

Author Community:

  • [ 1 ] [Fang, Juan]College of Computer Science, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Li, Cheng-Yan]College of Computer Science, Beijing University of Technology, Beijing 100124, China
  • [ 3 ] [Wang, Shuai]College of Computer Science, Beijing University of Technology, Beijing 100124, China
  • [ 4 ] [Yao, Zhi-Cheng]College of Computer Science, Beijing University of Technology, Beijing 100124, China

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Source :

Journal of Electronics and Information Technology

ISSN: 1009-5896

Year: 2014

Issue: 5

Volume: 36

Page: 1229-1234

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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