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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| Veröffentlicht in: | SC19: International Conference for High Performance Computing, Networking, Storage and Analysis S. 1 - 13 |
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| Sprache: | Englisch |
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17.11.2019
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| 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. |
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| 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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| 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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