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The Effect of Correlating Quantum Allocation and Job Size for Gang Scheduling

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Job Scheduling Strategies for Parallel Processing (JSSPP 1999)

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Abstract

Gang scheduling is an effective scheduling policy for multiprocessing workloads with significant interprocess synchronization and is in common use in real installations. In this paper we show that significant improvement in the job slowdown metric can be achieved simply by allocating a different number of quanta to different rows “control groups” depending on the number of processes belonging to jobs in a given row. Specifically, we show that allocating the number of quanta inversely proportionally to the number of processes per job in that row results in 20 – 50% smaller slowdowns without significantly affecting mean job response time. Incorporating these suggestions in to real schedulers would require the addition of only a few lines of simple code, hence this work should have an immediate practical impact.

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Author information

Authors and Affiliations

  1. Mathematics and Computer Science Department, University of Denver, Denver, CO 80208-0189

    Gaurav Ghare

  2. Mathematics and Computer Science Department, University of Denver, Denver, CO 80208-0189

    Scott T. Leutenegger

Authors
  1. Gaurav Ghare
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  2. Scott T. Leutenegger
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Editor information

Editors and Affiliations

  1. Institute of Computer Science, The Hebrew University of Jerusalem, 91904, Jerusalem, Israel

    Dror G. Feitelson

  2. Laboratory for Computer Science, MIT, Cambridge, MA, 02139, USA

    Larry Rudolph

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© 1999 Springer-Verlag Berlin Heidelberg

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Ghare, G., Leutenegger, S.T. (1999). The Effect of Correlating Quantum Allocation and Job Size for Gang Scheduling. In: Feitelson, D.G., Rudolph, L. (eds) Job Scheduling Strategies for Parallel Processing. JSSPP 1999. Lecture Notes in Computer Science, vol 1659. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47954-6_5

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  • DOI: https://doi.org/10.1007/3-540-47954-6_5

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66676-9

  • Online ISBN: 978-3-540-47954-3

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