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    Mitigating Inter-Job Interference via Process-Level Quality-of-Service

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    topc20.pdf
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    Final Accepted Manuscript
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    Author
    Savoie, Lee
    Lowenthal, David K.
    Supinski, Bronis R. de
    Mohror, Kathryn
    Jain, Nikhil
    Affiliation
    Department of Computer Science, The University of Arizona
    Issue Date
    2021-04
    Keywords
    High-performance computing
    network contention
    quality of service
    
    Metadata
    Show full item record
    Publisher
    Association for Computing Machinery (ACM)
    Citation
    Savoie, L., Lowenthal, D. K., Supinski, B. R. D., Mohror, K., & Jain, N. (2021). Mitigating Inter-Job Interference via Process-Level Quality-of-Service. ACM Transactions on Parallel Computing (TOPC), 8(1), 1-26.
    Journal
    ACM Transactions on Parallel Computing
    Rights
    © 2020 Association for Computing Machinery.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    Jobs on most high-performance computing (HPC) systems share the network with other concurrently executing jobs. Network sharing leads to contention that can severely degrade performance. This article investigates the use of Quality of Service (QoS) mechanisms to reduce the negative impacts of network contention. QoS allows users to manage resource sharing between network flows and to provide bandwidth guarantees to specific flows. Our results show that careful use of QoS reduces the impact of network contention for specific jobs, resulting in up to a 40% performance improvement. In some cases, it completely eliminates the impact of contention. It achieves these improvements with limited negative impact to other jobs; any job that experiences performance loss typically degrades less than 5%, and often much less. Our approach can help ensure that HPC machines maintain high levels of throughput as per-node compute power continues to increase faster than network bandwidth.
    ISSN
    2329-4949
    EISSN
    2329-4957
    DOI
    10.1145/3434397
    Version
    Final accepted manuscript
    Sponsors
    Lawrence Livermore National Laboratory
    ae974a485f413a2113503eed53cd6c53
    10.1145/3434397
    Scopus Count
    Collections
    UA Faculty Publications

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