SpecPMT: Speculative Logging for Resolving Crash Consistency Overhead of Persistent Memory

被引：1
|
作者：
Ye, Chencheng [1 ,4 ]
Xu, Yuanchao [2 ]
Shen, Xipeng [2 ]
Sha, Yan [1 ,4 ]
Liao, Xiaofei [1 ,4 ]
Jin, Hai [1 ,4 ]
Solihin, Yan [3 ]
机构：
[1] Huazhong Univ Sci & Technol, Wuhan, Hubei, Peoples R China
[2] North Carolina State Univ, Raleigh, NC USA
[3] Univ Cent Florida, Orlando, FL 32816 USA
[4] Huazhong Univ Sci & Technol, Natl Engn Res Ctr Big Data Technol & Syst, Serv Comp Technol & Syst Lab, Cluster & Grid Comp Lab,Sch Comp Sci & Technol, Wuhan, Peoples R China
来源：
PROCEEDINGS OF THE 28TH ACM INTERNATIONAL CONFERENCE ON ARCHITECTURAL SUPPORT FOR PROGRAMMING LANGUAGES AND OPERATING SYSTEMS, VOL 2, ASPLOS 2023 | 2023年
基金：
美国国家科学基金会; 中国国家自然科学基金;
关键词：
persistent memory; transaction; logging; microarchitecture; HARDWARE TRANSACTIONAL MEMORY; EFFICIENT; SUPPORT; LOGTM;
D O I：
10.1145/3575693.3575696
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Crash consistency overhead is a long-standing barrier to the adoption of byte-addressable persistent memory in practice. Despite continuous progress, persistent transactions for crash consistency still incur a 5.6x slowdown, making persistent memory prohibitively costly in practical settings. This paper introduces speculative logging, a new method that forgoes most memory fences and reduces data persistence overhead by logging data values early. This technique enables a novel persistent transaction model, speculatively persistent memory transactions (SpecPMT). Our evaluation shows that SpecPMT reduces the execution time overheads of persistent transactions substantially to just 10%.
引用
收藏
页码：762 / 777
页数：16
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