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

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    PID6112219.pdf
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    Final Accepted Manuscript
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    Author
    Savoie, Lee
    Lowenthal, David K.
    de Supinski, Bronis R.
    Mohror, Kathryn
    Jain, Nikhil
    Affiliation
    Univ Arizona, Dept Comp Sci
    Issue Date
    2019-09
    Keywords
    network contention
    quality of service
    MPI
    
    Metadata
    Show full item record
    Publisher
    IEEE
    Citation
    L. Savoie, D. K. Lowenthal, B. R. de Supinski, K. Mohror and N. Jain, "Mitigating Inter-Job Interference via Process-Level Quality-of-Service," 2019 IEEE International Conference on Cluster Computing (CLUSTER), Albuquerque, NM, USA, 2019, pp. 1-5, doi: 10.1109/CLUSTER.2019.8891007.
    Journal
    2019 IEEE INTERNATIONAL CONFERENCE ON CLUSTER COMPUTING (CLUSTER)
    Rights
    © 2019 IEEE.
    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. This sharing creates contention that can severely degrade performance. We investigate the use of Quality of Service (QoS) mechanisms to reduce the negative impacts of network contention. Our results show that careful use of QoS reduces the impact of contention for specific jobs, resulting in up to a 27% performance improvement. In some cases the impact of contention is completely eliminated. These improvements are achieved with limited negative impact to other jobs; any job that experiences performance loss typically degrades less than 5%, often much less. Our approach can help ensure that HPC machines maintain high throughput as per-node compute power continues to increase faster than network bandwidth.
    ISSN
    1552-5244
    DOI
    10.1109/cluster.2019.8891007
    Version
    Final accepted manuscript
    ae974a485f413a2113503eed53cd6c53
    10.1109/cluster.2019.8891007
    Scopus Count
    Collections
    UA Faculty Publications

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