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HUNTER: Releasing Persistent Memory Write Performance with A Novel PM-DRAM Collaboration Architecture

  • Yanqi Pan
  • , Yifeng Zhang
  • , Wen Xia*
  • , Xiangyu Zou
  • , Cai Deng
  • *Corresponding author for this work
  • School of Computer Science and Technology, Harbin Institute of Technology
  • Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies

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

Abstract

We present HUNTER, a POSIX-compliant persistent memory (PM) file system that fully releases PM's write performance. Compared to state-of-the-art ones, HUNTER proposes a novel PM-DRAM collaboration architecture to significantly eliminate/reduce software overheads in the write path. Expensive in-PM metadata are updated asynchronously to hide their performance penalties. Furthermore, in-PM metadata/data are laid out separately for locality awareness, enabling collaboration with asynchronous architecture. HUNTER also adopts several lightweight in-DRAM allocators/indexes to manage PM efficiently.Experimental results suggest that HUNTER achieves 2.0-3.4× write bandwidth compared to state-of-the-art PM file systems in write-intensive workloads and shows similar write bandwidth compared to bare PM.

Original languageEnglish
Title of host publication2023 60th ACM/IEEE Design Automation Conference, DAC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350323481
DOIs
StatePublished - 2023
Externally publishedYes
Event60th ACM/IEEE Design Automation Conference, DAC 2023 - San Francisco, United States
Duration: 9 Jul 202313 Jul 2023

Publication series

NameProceedings - Design Automation Conference
Volume2023-July
ISSN (Print)0738-100X

Conference

Conference60th ACM/IEEE Design Automation Conference, DAC 2023
Country/TerritoryUnited States
CitySan Francisco
Period9/07/2313/07/23

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