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I/O Optimizations Based on Workload Characteristics for Parallel File Systems

  • Bing Wei
  • , Limin Xiao*
  • , Bingyu Zhou
  • , Guangjun Qin
  • , Baicheng Yan
  • , Zhisheng Huo
  • *Corresponding author for this work
  • Beihang University

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

Abstract

Parallel file systems usually provide a unified storage solution, which fails to meet specific application needs. In this paper, we propose an extended file handle scheme to address this problem. It allows the file systems to specify optimizations for individual file or directory based on workload characteristics. One case study shows that our proposed approach improves the aggregate throughput of large files and small files by up to 5% and 30%, respectively. To further improve the access performance of small files in parallel file systems, we also propose a new metadata-based small file optimization method. The experimental results show that the aggregate throughput of small files can be effectively improved through our method.

Original languageEnglish
Title of host publicationNetwork and Parallel Computing - 16th IFIP WG 10.3 International Conference, NPC 2019, Proceedings
EditorsXiaoxin Tang, Quan Chen, Pradip Bose, Weiming Zheng, Jean-Luc Gaudiot
PublisherSpringer
Pages305-310
Number of pages6
ISBN (Print)9783030307080
DOIs
StatePublished - 2019
Event16th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2019 - Hohhot, China
Duration: 23 Aug 201924 Aug 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11783 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2019
Country/TerritoryChina
CityHohhot
Period23/08/1924/08/19

Keywords

  • Extended file handle
  • Parallel file systems
  • Small file optimizations
  • Workload characteristics

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