A principled approach for selecting block I/O traces

Omkar Desai, Seungmin Shin, Eunji Lee, Bryan S. Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present IOTAP, a tool that analyzes and profiles block I/O traces. IOTAP computes the (dis)similarities among a set of workloads and sets a guideline for selecting a subset of traces for benchmarking. By doing so, we avoid experimentally running all workloads or, even worse, arbitrarily selecting a subset that skews the results. We demonstrate the usefulness of IOTAP by comparing its results with experiments on real SSDs, achieving a high correlation of 0.92 for an NVMe SSD.

Original languageEnglish (US)
Title of host publicationHotStorage 2022 - Proceedings of the 2022 14th ACM Workshop on Hot Topics in Storage and File Systems
PublisherAssociation for Computing Machinery, Inc
Pages52-58
Number of pages7
ISBN (Electronic)9781450393997
DOIs
StatePublished - Jun 27 2022
Event14th ACM Workshop on Hot Topics in Storage and File Systems, HotStorage 2022 - Virtual, Online, United States
Duration: Jun 27 2022Jun 28 2022

Publication series

NameHotStorage 2022 - Proceedings of the 2022 14th ACM Workshop on Hot Topics in Storage and File Systems

Conference

Conference14th ACM Workshop on Hot Topics in Storage and File Systems, HotStorage 2022
Country/TerritoryUnited States
CityVirtual, Online
Period6/27/226/28/22

Keywords

  • workload analysis

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems
  • Software

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