Decoupled Fused Cache

Author:

Vasilakis Evangelos1,Papaefstathiou Vassilis2,Trancoso Pedro1,Sourdis Ioannis1

Affiliation:

1. Chalmers University of Technology, Gothenburg, Sweden

2. Foundation for Research and Technology Hellas (FORTH), Heraklion, Greece

Abstract

DRAM caches have shown excellent potential in capturing the spatial and temporal data locality of applications capitalizing on advances of 3D-stacking technology; however, they are still far from their ideal performance. Besides the unavoidable DRAM access to fetch the requested data, tag access is in the critical path, adding significant latency and energy costs. Existing approaches are not able to remove these overheads and in some cases limit DRAM cache design options. For instance, caching DRAM cache tags adds constant latency to every access; accessing the DRAM cache using the TLB calls for OS support and DRAM cachelines as large as a page; reusing the last-level cache (LLC) tags to access the DRAM cache limits LLC performance as it requires indexing the LLC using higher-order address bits. In this article, we introduce Decoupled Fused Cache , a DRAM cache design that alleviates the cost of tag accesses by fusing DRAM cache tags with the tags of the on-chip LLC without affecting LLC performance. In essence, the Decoupled Fused Cache relies in most cases on the LLC tag access to retrieve the required information for accessing the DRAM cache while avoiding additional overheads. Compared to current DRAM cache designs of the same cacheline size, Decoupled Fused Cache improves system performance by 6% on average and by 16% to 18% for large cacheline sizes. Finally, Decoupled Fused Cache reduces DRAM cache traffic by 18% and DRAM cache energy consumption by 7%.

Funder

ECOSCALE

MECCA

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Information Systems,Software

Cited by 10 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. Object Fingerprint Cache for Heterogeneous Memory System;IEEE Transactions on Computers;2023-09-01

2. Baryon: Efficient Hybrid Memory Management with Compression and Sub-Blocking;2023 IEEE International Symposium on High-Performance Computer Architecture (HPCA);2023-02

3. RHPM: Using Relative Hotness to Guide Page Migration for Hybrid Memory Systems;IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems;2022

4. Improving the Performance of Block-based DRAM Caches Via Tag-Data Decoupling;IEEE Transactions on Computers;2021-11-01

5. Performance Evaluation of Intel Optane Memory for Managed Workloads;ACM Transactions on Architecture and Code Optimization;2021-06

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