License: 
Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagRep.11.7.16
URN: urn:nbn:de:0030-drops-155891
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2021/15589/
Carns, Philip ;
Kunkel, Julian ;
Mohror, Kathryn ;
Schulz, Martin
Weitere Beteiligte (Hrsg. etc.): Philip Carns and Julian Kunkel and Kathryn Mohror and Martin Schulz
Understanding I/O Behavior in Scientific and Data-Intensive Computing (Dagstuhl Seminar 21332)
Abstract
Two key changes are driving an immediate need for deeper understanding of I/O workloads in high-performance computing (HPC): applications are evolving beyond the traditional bulk-synchronous models to include integrated multistep workflows, in situ analysis, artificial intelligence, and data analytics methods; and storage systems designs are evolving beyond a two-tiered file system and archive model to complex hierarchies containing temporary, fast tiers of storage close to compute resources with markedly different performance properties. Both of these changes represent a significant departure from the decades-long status quo and require investigation from storage researchers and practitioners to understand their impacts on overall I/O performance. Without an in-depth understanding of I/O workload behavior, storage system designers, I/O middleware developers, facility operators, and application developers will not know how best to design or utilize the additional tiers for optimal performance of a given I/O workload. The goal of this Dagstuhl Seminar was to bring together experts in I/O performance analysis and storage system architecture to collectively evaluate how our community is capturing and analyzing I/O workloads on HPC systems, identify any gaps in our methodologies, and determine how to develop a better in-depth understanding of their impact on HPC systems. Our discussions were lively and resulted in identifying critical needs for research in the area of understanding I/O behavior. We document those discussions in this report.
BibTeX - Entry
@Article{carns_et_al:DagRep.11.7.16,
author = {Carns, Philip and Kunkel, Julian and Mohror, Kathryn and Schulz, Martin},
title = {{Understanding I/O Behavior in Scientific and Data-Intensive Computing (Dagstuhl Seminar 21332)}},
pages = {16--75},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2021},
volume = {11},
number = {7},
editor = {Carns, Philip and Kunkel, Julian and Mohror, Kathryn and Schulz, Martin},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2021/15589},
URN = {urn:nbn:de:0030-drops-155891},
doi = {10.4230/DagRep.11.7.16},
annote = {Keywords: I/O performance measurement, Understanding user I/O patterns, HPC I/O, I/O characterization}
}
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Keywords: |
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I/O performance measurement, Understanding user I/O patterns, HPC I/O, I/O characterization |
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Collection: |
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DagRep, Volume 11, Issue 7 |
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Issue Date: |
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2021 |
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Date of publication: |
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22.12.2021 |
