The file paper.ps contains the CSRI technical report: 

Multiprocessor Scheduling for High-Variability Service Time Distributions

                                  by

                 Eric W. Parsons and Keneth C. Sevcik

presented at the Workshop on Job Scheduling Strategies for Parallel Processing
held in conjunction with IPPS '95, Santa Barbara, CA.  Reprinted in:

	Job Scheduling Strategies for Parallel Processing
	Lecture Notes in Computer Science, Vol. 949
	Dror G. Feitelson and Larry Rudolph (Eds.)

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This report was made available for anonymous ftp by: 

                         eparsons@cs.toronto.edu

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.