Revisiting I/O Behavior in Large-Scale Storage Systems: The Expected and the Unexpected

Large-scale applications typically spend a large fraction of their execution time performing I/O to a parallel storage system. How-ever, with rapid progress in compute and storage system stack of large-scale systems, it is critical to investigate and update our understanding of the I/O behavior of l...

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Vydáno v:SC19: International Conference for High Performance Computing, Networking, Storage and Analysis s. 1 - 13
Hlavní autoři: Patel, Tirthak, Byna, Suren, Lockwood, Glenn K., Tiwari, Devesh
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: ACM 17.11.2019
Témata:
High performance computing
Large-scale systems
Monitoring
Parallel processing
Processor scheduling
Production
ISSN:2167-4337
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Abstract Large-scale applications typically spend a large fraction of their execution time performing I/O to a parallel storage system. How-ever, with rapid progress in compute and storage system stack of large-scale systems, it is critical to investigate and update our understanding of the I/O behavior of large-scale applications. Toward that end, in this work, we monitor, collect and analyze a year worth of storage system data from a large-scale production parallel stor-age system. We perform temporal, spatial and correlative analysis of the system and uncover surprising patterns which defy existing assumptions and have important implications for future systems.
AbstractList Large-scale applications typically spend a large fraction of their execution time performing I/O to a parallel storage system. How-ever, with rapid progress in compute and storage system stack of large-scale systems, it is critical to investigate and update our understanding of the I/O behavior of large-scale applications. Toward that end, in this work, we monitor, collect and analyze a year worth of storage system data from a large-scale production parallel stor-age system. We perform temporal, spatial and correlative analysis of the system and uncover surprising patterns which defy existing assumptions and have important implications for future systems.
Author Patel, Tirthak
Lockwood, Glenn K.
Byna, Suren
Tiwari, Devesh
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  organization: Lawrence Berkeley National Laboratory,USA
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  organization: Lawrence Berkeley National Laboratory,USA
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  givenname: Devesh
  surname: Tiwari
  fullname: Tiwari, Devesh
  organization: Northeastern University,USA
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Snippet Large-scale applications typically spend a large fraction of their execution time performing I/O to a parallel storage system. How-ever, with rapid progress in...
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SubjectTerms High performance computing
Large-scale systems
Monitoring
Parallel processing
Processor scheduling
Production
Title Revisiting I/O Behavior in Large-Scale Storage Systems: The Expected and the Unexpected
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