research-article

Using file system counters in modelling parallel I/O architectures

Authors:

Salem El Sayed,

Matthias Bolten,

Dirk PleiterAuthors Info & Claims

ACM SIGOPS Operating Systems Review, Volume 50, Issue 2

Pages 37 - 46

https://doi.org/10.1145/3041710.3041716

Published: 30 January 2017 Publication History

Abstract

Keeping compute and I/O performance balanced is a major challenge for future cost-efficient HPC systems. Several architectural concepts and new technologies allow to address this challenge, however at the price of higher complexity. As a result, the need emerges to simulate these architectural concepts and new technologies to predict their impact on the overall performance. In this paper we propose a particular approach to explore the design space using event simulation models that take I/O server-side performance counters as input. In this way large quantities of real-life data measured over a large number of applications can be used to explore architectural modifications. We apply our approach using data collected by a GPFS file system serving a petascale Blue Gene/P installation.

References

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Digital Library

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Cited By

Brown KXu TIwabuchi KSato KMoody AMohror KJain NBhatele ASchulz MPearce RGokhale MMatsuoka S(2017)Accelerating Big Data Infrastructure and Applications (Ongoing Collaboration)2017 IEEE 37th International Conference on Distributed Computing Systems Workshops (ICDCSW)10.1109/ICDCSW.2017.74(343-347)Online publication date: Jun-2017
https://doi.org/10.1109/ICDCSW.2017.74

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Published In

cover image ACM SIGOPS Operating Systems Review

ACM SIGOPS Operating Systems Review Volume 50, Issue 2

Special Topics

December 2016

45 pages

ISSN:0163-5980

DOI:10.1145/3041710

Editors:
Jeanna Neefe Matthews
Clarkson University, Potsdam, NY
,
Thomas Bressoud
Denison University, Granville, OH

Issue’s Table of Contents

Copyright © 2017 Copyright is held by the owner/author(s).

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 30 January 2017

Published in SIGOPS Volume 50, Issue 2

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Cited By

Brown KXu TIwabuchi KSato KMoody AMohror KJain NBhatele ASchulz MPearce RGokhale MMatsuoka S(2017)Accelerating Big Data Infrastructure and Applications (Ongoing Collaboration)2017 IEEE 37th International Conference on Distributed Computing Systems Workshops (ICDCSW)10.1109/ICDCSW.2017.74(343-347)Online publication date: Jun-2017
https://doi.org/10.1109/ICDCSW.2017.74

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