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Author:

Fang, Juan (Fang, Juan.) (Scholars:方娟) | Cheng, Yan-Jin (Cheng, Yan-Jin.) | Cai, Min (Cai, Min.) | Chang, Ze-Qing (Chang, Ze-Qing.)

Indexed by:

CPCI-S

Abstract:

In recent years, high performance computing systems have obtained more processing cores and shared a last level cache (LLC). Now, the problem to the existing cache partitioning techniques is that they give each core the number of cache ways according to their need, these schemes have the potential to realize significant performance increases, yet for most part they do not consider LLC energy saving. In this paper, we design and realize a multi-processing processor monitor. Through a utility monitor we calculate the number of hits and misses when allocate different cache ways to each application. In other words, we use utility monitors to track the access by each core to characterize each thread's use of the cache. Dynamically give each core the number of ways based on the performance to achieve its highest utilization. On gem5, we run Parsec benchmarks as our multi-threaded application. We output the numbers of misses for all possible number of ways, and find the number of associativity to achieve its highest utilization. By analysing experimental results, cache miss rate decreases with the increasing of the cache capacity.

Keyword:

Shared cache Multicore Cache partitioning

Author Community:

  • [ 1 ] [Fang, Juan]Beijing Univ Technol, Coll Comp Sci, Beijing, Peoples R China
  • [ 2 ] [Cheng, Yan-Jin]Beijing Univ Technol, Coll Comp Sci, Beijing, Peoples R China
  • [ 3 ] [Cai, Min]Beijing Univ Technol, Coll Comp Sci, Beijing, Peoples R China
  • [ 4 ] [Chang, Ze-Qing]Beijing Univ Technol, Coll Comp Sci, Beijing, Peoples R China

Reprint Author's Address:

  • 方娟

    [Fang, Juan]Beijing Univ Technol, Coll Comp Sci, Beijing, Peoples R China

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Source :

PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATION AND SENSOR NETWORKS (WCSN 2016)

ISSN: 2352-538X

Year: 2016

Volume: 44

Page: 561-565

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 10

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