Replacement policy adaptable miss curve estimation for efficient cache partitioning

Byunghoon Lee, Kwangsu Kim, Eui Young Chung

Research output: Contribution to journalArticlepeer-review

Abstract

Cache replacement policies and cache partitioning are well-known cache management techniques which aim to eliminate inter- and intra-application contention caused by co-running applications, respectively. Since replacement policies can change applications’ behavior on a shared last-level cache, they have a massive impact on cache partitioning. Furthermore, cache partitioning determines the capacity allocated to each application affecting incorporated replacement policy. However, their interoperability has not been thoroughly explored. Since existing cache partitioning methods are tailored to specific replacement policies to reduce overheads for characterization of applications’ behavior, they may lead to suboptimal partitioning results when incorporated with the up-to-date replacement policies. In cache partitioning, miss curve estimation is a key component to relax this restriction which can reflect the dependency between a replacement policy and cache partitioning on partitioning decision. To tackle this issue, we propose a replacement policy adaptable miss curve estimation (RME) which estimates dynamic workload patterns according to any arbitrary replacement policy and to given applications with low overhead. In addition, RME considers asymmetry of miss latency by miss type, thus the impact of miss curve on cache partitioning can be reflected more accurately. The experimental results support the efficiency of RME and show that RME-based cache partitioning cooperated with high-performance replacement policies can minimize both inter- and intra-application interference successfully.

Original languageEnglish
Pages (from-to)445-457
Number of pages13
JournalIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Volume37
Issue number2
DOIs
Publication statusPublished - 2018 Feb

Bibliographical note

Funding Information:
Manuscript received January 17, 2017; revised March 29, 2017; accepted May 10, 2017. Date of publication June 6, 2017; date of current version January 19, 2018. This work was supported in part by the National Research Foundation of Korea under Grant 2016R1A2B4011799, and in part by the IT Research and Development Program of MOTIE/KEIT (Design technology development of ultralow voltage operating circuit and IP for smart sensor SoC) under Grant 10052716. This paper was recommended by Associate Editor T. Mitra. (Corresponding author: Eui-Young Chung.) The authors are with the School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, South Korea (e-mail: eychung@yonsei.ac.kr).

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering

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