Efficient virtual memory for big memory servers

Author:

Basu Arkaprava1,Gandhi Jayneel1,Chang Jichuan2,Hill Mark D.1,Swift Michael M.1

Affiliation:

1. University of Wisconsin-Madison, Madison, WI

2. Hewlett-Packard Laboratories, Palo Alto, CA

Abstract

Our analysis shows that many "big-memory" server workloads, such as databases, in-memory caches, and graph analytics, pay a high cost for page-based virtual memory. They consume as much as 10% of execution cycles on TLB misses, even using large pages. On the other hand, we find that these workloads use read-write permission on most pages, are provisioned not to swap, and rarely benefit from the full flexibility of page-based virtual memory. To remove the TLB miss overhead for big-memory workloads, we propose mapping part of a process's linear virtual address space with a direct segment , while page mapping the rest of the virtual address space. Direct segments use minimal hardware---base, limit and offset registers per core---to map contiguous virtual memory regions directly to contiguous physical memory. They eliminate the possibility of TLB misses for key data structures such as database buffer pools and in-memory key-value stores. Memory mapped by a direct segment may be converted back to paging when needed. We prototype direct-segment software support for x86-64 in Linux and emulate direct-segment hardware. For our workloads, direct segments eliminate almost all TLB misses and reduce the execution time wasted on TLB misses to less than 0.5%.

Funder

Google

University of Wisconsin-Madison

Division of Computer and Network Systems

Publisher

Association for Computing Machinery (ACM)

Cited by 42 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. QUIC is not Quick Enough over Fast Internet;Proceedings of the ACM Web Conference 2024;2024-05-13

2. FASTA: Revisiting Fully Associative Memories in Computer Microarchitecture;IEEE Access;2024

3. Affinity Alloc: Taming Not-So Near-Data Computing;56th Annual IEEE/ACM International Symposium on Microarchitecture;2023-10-28

4. HugeGPT: Storing Guest Page Tables on Host Huge Pages to Accelerate Address Translation;2023 32nd International Conference on Parallel Architectures and Compilation Techniques (PACT);2023-10-21

5. Operand-Oriented Virtual Memory Support for Near-Memory Processing;IEEE Transactions on Computers;2023-08-01

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