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A parallel workload model and its implications for maui scheduling policies

  • Zhuo Liu*
  • , Aihua Liang
  • , Limin Xiao
  • *Corresponding author for this work
  • Beihang University

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

Abstract

We develop a workload model based on the logs of real workloads of the Linux cluster Atlas and a small IBM Blue Gene/L cluster at Lawrence Livermore National Laboratory (LLNL), and the 184-node IBM eServer pSeries 655/690 at the San Diego Supercomputer Center (SDSC). This model gives us insight into the performance of scheduling jobs on space-sharing parallel computers, provided by Maui. We find out that backfill queuing policies improve a lot of the system performance, and without reservation, the allocation policies do not have an obvious distance between each other.

Original languageEnglish
Title of host publicationICCMS 2010 - 2010 International Conference on Computer Modeling and Simulation
Pages384-389
Number of pages6
DOIs
StatePublished - 2010
Event2010 International Conference on Computer Modeling and Simulation, ICCMS 2010 - Sanya, China
Duration: 22 Jan 201024 Jan 2010

Publication series

NameICCMS 2010 - 2010 International Conference on Computer Modeling and Simulation
Volume2

Conference

Conference2010 International Conference on Computer Modeling and Simulation, ICCMS 2010
Country/TerritoryChina
CitySanya
Period22/01/1024/01/10

Keywords

  • Evaluation
  • Maui
  • Scheduling policy
  • Workload model

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