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Malleable scheduling for flows of jobs and applications to MapReduce

Author

Listed:
  • Viswanath Nagarajan

    (University of Michigan)

  • Joel Wolf

    (IBM T.J. Watson Research Center)

  • Andrey Balmin

    (Platfora Inc.)

  • Kirsten Hildrum

    (IBM T.J. Watson Research Center)

Abstract

This paper provides a unified family of algorithms with performance guarantees for malleable scheduling problems on flows. A flow represents a set of jobs with precedence constraints. Each job has a speedup function that governs the rate at which work is done on the job as a function of the number of processors allocated to it. In our setting, each speedup function is linear up to some job-specific processor maximum. A key aspect of malleable scheduling is that the number of processors allocated to any job is allowed to vary with time. The overall objective is to minimize either the total cost (minisum) or the maximum cost (minimax) of the flows. Our approach handles a very general class of cost functions, and in particular provides the first constant-factor approximation algorithms for total and maximum weighted completion time. Our motivation for this work was scheduling in MapReduce, and we also provide experimental evaluations that show good practical performance.

Suggested Citation

  • Viswanath Nagarajan & Joel Wolf & Andrey Balmin & Kirsten Hildrum, 2019. "Malleable scheduling for flows of jobs and applications to MapReduce," Journal of Scheduling, Springer, vol. 22(4), pages 393-411, August.
    • Handle: RePEc:spr:jsched:v:22:y:2019:i:4:d:10.1007_s10951-018-0576-y
    DOI: 10.1007/s10951-018-0576-y
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    References listed on IDEAS

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    1. Elisabeth Günther & Felix G. König & Nicole Megow, 2014. "Scheduling and packing malleable and parallel tasks with precedence constraints of bounded width," Journal of Combinatorial Optimization, Springer, vol. 27(1), pages 164-181, January.
    2. Robert McNaughton, 1959. "Scheduling with Deadlines and Loss Functions," Management Science, INFORMS, vol. 6(1), pages 1-12, October.
    3. M. Drozdowski & W. Kubiak, 1999. "Scheduling parallel tasks withsequential heads and tails," Annals of Operations Research, Springer, vol. 90(0), pages 221-246, January.
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    Cited by:

    1. Xiaohu Wu & Patrick Loiseau, 2024. "Algorithms for Scheduling Deadline-Sensitive Malleable Tasks," SN Operations Research Forum, Springer, vol. 5(2), pages 1-38, June.

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