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Multiprocessor scheduling for high-variability service time distributions

  • Eric W. Parsons
  • Kenneth C. Sevcik
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 949)

Abstract

Many disciplines have been proposed for scheduling and processor allocation in multiprogrammed multiprocessors for parallel processing. These have been, for the most part, designed and evaluated for workloads having relatively low variability in service demand. But with reports that variability in service demands at high performance computing centers can actually be quite high, these disciplines must be reevaluated. In this paper, we examine the performance of two well-known static scheduling disciplines, and propose preemptive versions of these that offer much better mean response times when the variability in service demand is high. We argue that, in systems in which dynamic repartitioning in applications is expensive or impossible, these preemptive disciplines are well suited for handling high variability in service demand.

Keywords

Service Demand Service Time Distribution Multiprocessor Schedule Partition Size Short Remain Processing Time 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Eric W. Parsons
    • 1
  • Kenneth C. Sevcik
    • 1
  1. 1.Computer Systems Research InstituteUniversity of TorontoCanada

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