Flexible coscheduling: Mitigating load imbalance and improving utilization of heterogeneous resources

Eitan Frachtenberg, Dror G. Feitelson, Fabrizio Petrini, Juan Fernandez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

34 Scopus citations

Abstract

Fine-grained parallel applications require all their processes to run simultaneously on distinct processors to achieve good efficiency. This is typically accomplished by space slicing, wherein nodes are dedicated for the duration of the run, or by gang scheduling, wherein time slicing is coordinated across processors. Both schemes suffer from fragmentation, where processors are left idle because jobs cannot be packed with perfect efficiency. Obviously, this leads to reduced utilization and sub-optimal performance. Flexible coscheduling (FCS) solves this problem by monitoring each job's granularity and communication activity, and using gang scheduling only for those jobs that require it. Processes from other jobs, which can be scheduled without any constraints, are used as filler to reduce fragmentation. In addition, inefficiencies due to load imbalance and hardware heterogeneity are also reduced because the classification is done on a per-process basis. FCS has been fully implemented as part of the STORM resource manager, and shown to be competitive with gang scheduling and implicit coscheduling.

Original languageAmerican English
Title of host publicationProceedings - International Parallel and Distributed Processing Symposium, IPDPS 2003
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)0769519261, 9780769519265
DOIs
StatePublished - 2003
EventInternational Parallel and Distributed Processing Symposium, IPDPS 2003 - Nice, France
Duration: 22 Apr 200326 Apr 2003

Publication series

NameProceedings - International Parallel and Distributed Processing Symposium, IPDPS 2003

Conference

ConferenceInternational Parallel and Distributed Processing Symposium, IPDPS 2003
Country/TerritoryFrance
CityNice
Period22/04/0326/04/03

Bibliographical note

Publisher Copyright:
© 2003 IEEE.

Keywords

  • Cluster computing
  • Gang scheduling
  • Heterogeneous clusters
  • Job scheduling
  • Load balancing
  • Parallel architectures
  • STORM

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