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Performance Metrics and Models for Shared Cache

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Abstract

Performance metrics and models are prerequisites for scientific understanding and optimization. This paper introduces a new footprint-based theory and reviews the research in the past four decades leading to the new theory. The review groups the past work into metrics and their models in particular those of the reuse distance, metrics conversion, models of shared cache, performance and optimization, and other related techniques.

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Authors and Affiliations

  1. Department of Computer Science, University of Rochester, Rochester, NY, 14627-0226, U.S.A.

    Chen Ding, Xiaoya Xiang, Bin Bao & Hao Luo

  2. School of Electronics Engineering and Computer Science, Peking University, Beijing, 100871, China

    Ying-Wei Luo & Xiao-Lin Wang

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  1. Chen Ding
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  2. Xiaoya Xiang
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Correspondence to Chen Ding.

Additional information

The work is partially supported by the National Natural Science Foundation of China (NSFC) under Grant No. 61232008, the NSFC Joint Research Fund for Overseas Chinese Scholars and Scholars in Hong Kong and Macao under Grant No. 61328201, the National Science Foundation of USA under Contract Nos. CNS-1319617, CCF-1116104, CCF-0963759, an IBM CAS Faculty Fellowship and a research grant from Huawei. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the funding organizations.

Xiang has graduated and is now working at Twitter Inc. Bao has graduated and is now working at Quacomm Inc.

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Ding, C., Xiang, X., Bao, B. et al. Performance Metrics and Models for Shared Cache. J. Comput. Sci. Technol. 29, 692–712 (2014). https://doi.org/10.1007/s11390-014-1460-7

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  • DOI: https://doi.org/10.1007/s11390-014-1460-7

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