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

Lee Savoie, David K. Lowenthal, Bronis R. De Supinski, Kathryn Mohror, Nikhil Jain

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationProceedings - 2019 IEEE International Conference on Cluster Computing, CLUSTER 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728147345
StatePublished - Sep 2019
Event2019 IEEE International Conference on Cluster Computing, CLUSTER 2019 - Albuquerque, United States
Duration: Sep 23 2019Sep 26 2019

Publication series

NameProceedings - IEEE International Conference on Cluster Computing, ICCC
ISSN (Print)1552-5244


Conference2019 IEEE International Conference on Cluster Computing, CLUSTER 2019
Country/TerritoryUnited States


  • MPI
  • network contention
  • quality of service

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Signal Processing


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