Fine-grained Policy-driven I/O Sharing for Burst Buffers

Ed Karrels, Lei Huang, Yuhong Kan, Ishank Arora, Yinzhi Wang, Daniel S. Katz, William D. Gropp, Zhao Zhang

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

Abstract

A burst buffer is a common method to bridge the performance gap between the I/O needs of modern supercomputing applications and the performance of the shared file system on large-scale supercomputers. However, existing I/O sharing methods require resource isolation, offline profiling, or repeated execution that significantly limit the utilization and applicability of these systems. Here we present ThemisIO, a policy-driven I/O sharing framework for a remote-shared burst buffer: a dedicated group of I/O nodes, each with a local storage device. ThemisIO preserves high utilization by implementing opportunity fairness so that it can reallocate unused I/O resources to other applications. ThemisIO accurately and efficiently allocates I/O cycles among applications, purely based on real-time I/O behavior without requiring user-supplied information or offline-profiled application characteristics. ThemisIO supports a variety of fair sharing policies, such as user-fair, size-fair, as well as composite policies, e.g., group-then-user-fair. All these features are enabled by its statistical token design. ThemisIO can alter the execution order of incoming I/O requests based on assigned tokens to precisely balance I/O cycles between applications via time slicing, thereby enforcing processing isolation. Experiments using I/O benchmarks show that ThemisIO sustains 13.5-13.7% higher I/O throughput and 19.5-40.4% lower performance variation than existing algorithms. For real applications, ThemisIO significantly reduces the slowdown by 59.1-99.8% caused by I/O interference.

Original languageEnglish (US)
Title of host publicationSC '23: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
PublisherAssociation for Computing Machinery
ISBN (Electronic)9798400701092
DOIs
StatePublished - Nov 12 2023
Event2023 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2023 - Denver, United States
Duration: Nov 12 2023Nov 17 2023

Publication series

NameInternational Conference for High Performance Computing, Networking, Storage and Analysis, SC
ISSN (Print)2167-4329
ISSN (Electronic)2167-4337

Conference

Conference2023 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2023
Country/TerritoryUnited States
CityDenver
Period11/12/2311/17/23

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Software

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