A Survey of Techniques for Cache Partitioning in Multicore Processors

Author:

Mittal Sparsh1ORCID

Affiliation:

1. Oak Ridge National Laboratory

Abstract

As the number of on-chip cores and memory demands of applications increase, judicious management of cache resources has become not merely attractive but imperative. Cache partitioning, that is, dividing cache space between applications based on their memory demands, is a promising approach to provide capacity benefits of shared cache with performance isolation of private caches. However, naively partitioning the cache may lead to performance loss, unfairness, and lack of quality-of-service guarantees. It is clear that intelligent techniques are required for realizing the full potential of cache partitioning. In this article, we present a survey of techniques for partitioning shared caches in multicore processors. We categorize the techniques based on important characteristics and provide a bird’s eye view of the field of cache partitioning.

Funder

IIT Hyderabad

ORNL

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

Cited by 33 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Modelling centralised automotive E/E software architectures;Advanced Engineering Informatics;2024-01

2. Offline and Online Algorithms for Cache Allocation with Monte Carlo Tree Search and a Learned Model;2023 IEEE 41st International Conference on Computer Design (ICCD);2023-11-06

3. Divide&Content: A Fair OS-Level Resource Manager for Contention Balancing on NUMA Multicores;IEEE Transactions on Parallel and Distributed Systems;2023-11

4. A Survey of Memory-Centric Energy Efficient Computer Architecture;IEEE Transactions on Parallel and Distributed Systems;2023-10

5. ComCoS: Enhanced Cache Partitioning Technique for Integrated Modular Avionics;2023 26th Euromicro Conference on Digital System Design (DSD);2023-09-06

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3