Devirtualizing Memory in Heterogeneous Systems

Author:

Haria Swapnil1,Hill Mark D.1,Swift Michael M.1

Affiliation:

1. University of Wisconsin-Madison, Madison, WI, USA

Abstract

Accelerators are increasingly recognized as one of the major drivers of future computational growth. For accelerators, shared virtual memory (VM) promises to simplify programming and provide safe data sharing with CPUs. Unfortunately, the overheads of virtual memory, which are high for general-purpose processors, are even higher for accelerators. Providing accelerators with direct access to physical memory (PM) in contrast, provides high performance but is both unsafe and more difficult to program. We propose Devirtualized Memory (DVM) to combine the protection of VM with direct access to PM. By allocating memory such that physical and virtual addresses are almost always identical (VA==PA), DVM mostly replaces page-level address translation with faster region-level Devirtualized Access Validation (DAV). Optionally on read accesses, DAV can be overlapped with data fetch to hide VM overheads. DVM requires modest OS and IOMMU changes, and is transparent to the application. Implemented in Linux 4.10, DVM reduces VM overheads in a graph-processing accelerator to just 1.6% on average. DVM also improves performance by 2.1X over an optimized conventional VM implementation, while consuming 3.9X less dynamic energy for memory management. We further discuss DVM's potential to extend beyond accelerators to CPUs, where it reduces VM overheads to 5% on average, down from 29% for conventional VM.

Funder

National Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Software

Reference37 articles.

1. Junwhan Ahn Sungpack Hong Sungjoo Yoo Onur Mutlu and Kiyoung Choi. 2015. A Scalable Processing-in-memory Accelerator for Parallel Graph Processing Proceedings of the 42Nd Annual International Symposium on Computer Architecture (ISCA). 10.1145/2749469.2750386 Junwhan Ahn Sungpack Hong Sungjoo Yoo Onur Mutlu and Kiyoung Choi. 2015. A Scalable Processing-in-memory Accelerator for Parallel Graph Processing Proceedings of the 42Nd Annual International Symposium on Computer Architecture (ISCA). 10.1145/2749469.2750386

2. AMD I/O Virtualization Technology (IOMMU) Specification;AMD.;Revision,2016

3. The NAS parallel benchmarks---summary and preliminary results

4. Translation caching

5. Efficient virtual memory for big memory servers

Cited by 4 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. A survey on hardware accelerators: Taxonomy, trends, challenges, and perspectives;Journal of Systems Architecture;2022-08

2. Improving Address Translation in Multi-GPUs via Sharing and Spilling aware TLB Design;MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture;2021-10-17

3. Morrigan: A Composite Instruction TLB Prefetcher;MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture;2021-10-17

4. MEG;ACM Transactions on Reconfigurable Technology and Systems;2020-10

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