Efficient multi-grained wear leveling for inodes of persistent memory file systems

Chaoshu Yang, Duo Liu, Runyu Zhang, Xianzhang Chen, Shun Nie, Fengshun Wang, Qingfeng Zhuge, Edwin H.M. Sha

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

Existing persistent memory file systems usually store inodes in fixed locations, which ignores the external and internal imbalanced wears of inodes on the persistent memory (PM). Therefore, the PM for storing inodes can be easily damaged. Existing solutions achieve low accuracy of wear-leveling with high-overhead data migrations. In this paper, we propose a Lightweight and Multi-grained Wear-leveling Mechanism, called LMWM, to solve these problems. We implement the proposed LMWM in Linux kernel based on NOVA, a typical persistent memory file system. Compared with MARCH, the state-of-theart wear-leveling mechanism for inode table, experimental results show that LMWM can improve 2.5× lifetime of PM and 1.12× performance, respectively.

Original languageEnglish
Title of host publication2020 57th ACM/IEEE Design Automation Conference, DAC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781450367257
DOIs
StatePublished - Jul 2020
Event57th ACM/IEEE Design Automation Conference, DAC 2020 - Virtual, San Francisco, United States
Duration: 20 Jul 202024 Jul 2020

Publication series

NameProceedings - Design Automation Conference
Volume2020-July
ISSN (Print)0738-100X

Conference

Conference57th ACM/IEEE Design Automation Conference, DAC 2020
Country/TerritoryUnited States
CityVirtual, San Francisco
Period20/07/2024/07/20

Keywords

  • File system
  • Inode management
  • Persistent memory
  • Wear leveling

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