OPTIMAL REPARTITIONING DECISION POLICY.

David M. Nicol, Paul F. Reynolds

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

Abstract

The automated partitioning of simulations for parallel execution is a timely research problem. A simulation's run-time performance depends heavily on the nature of the inputs the simulation responds to. Consequently, a simulation's run-time behavior is generally too complex to analytically predict, and partitioning algorithms must be statistically based; they base their partitioning decisions on the simulation's observed behavior. Simulations which are partitioned statistically are vulnerable to radical changes in the run-time dynamic repartitioning decision policy which detects change in a simulation's run-time behavior and reacts to this change. The decision policy optimally balances the costs and potential benefits of repartitioning a running simulation.

Original languageEnglish (US)
Title of host publicationWinter Simulation Conference Proceedings
PublisherIEEE
Pages493-497
Number of pages5
ISBN (Print)0911801073, 9780911801071
DOIs
StatePublished - 1985
Externally publishedYes

Publication series

NameWinter Simulation Conference Proceedings
ISSN (Print)0275-0708

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Safety, Risk, Reliability and Quality
  • Chemical Health and Safety
  • Applied Mathematics

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