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Are User Runtime Estimates Inherently Inaccurate?

  • Cynthia Bailey Lee
  • Yael Schwartzman
  • Jennifer Hardy
  • Allan Snavely
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3277)

Abstract

Computer system batch schedulers typically require information from the user upon job submission, including a runtime estimate. Inaccuracy of these runtime estimates, relative to the actual runtime of the job, has been well documented and is a perennial problem mentioned in the job scheduling literature. Typically users provide these estimates under circumstances where their job will be killed after the provided amount of time elapses. Also, users may be unaware of the potential benefits of providing accurate estimates, such as increased likelihood of backfilling. This study examines user behavior when the threat of job killing is removed, and when a tangible reward for accuracy is provided. We show that under these conditions, about half of users provide an improved estimate, but there is not a substantial improvement in the overall average accuracy.

Keywords

Kill Time Actual Runtime Runtime Estimate Scheduler Performance Average Slowdown 
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 2005

Authors and Affiliations

  • Cynthia Bailey Lee
    • 1
    • 2
  • Yael Schwartzman
    • 1
  • Jennifer Hardy
    • 1
  • Allan Snavely
    • 1
    • 2
  1. 1.San Diego Supercomputer CenterUniversity of California, San DiegoLa JollaUSA
  2. 2.Department of Computer Science and EngineeringUniversity of California, San DiegoLa JollaUSA

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