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Efficient distributed workstealing via matchmaking

Published:27 February 2016Publication History
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Abstract

Many classes of high-performance applications and combinatorial problems exhibit large degree of runtime load variability. One approach to achieving balanced resource use is to over decompose the problem on fine-grained tasks that are then dynamically balanced using approaches such as workstealing. Existing work stealing techniques for such irregular applications, running on large clusters, exhibit high overheads due to potential untimely interruption of busy nodes, excessive communication messages and delays experienced by idle nodes in finding work due to repeated failed steals. We contend that the fundamental problem of distributed work-stealing is of rapidly bringing together work producers and consumers. In response, we develop an algorithm that performs timely, lightweight and highly efficient matchmaking between work producers and consumers which results in accurate load balance. Experimental evaluations show that our scheduler is able to outperform other distributed work stealing schedulers, and to achieve scale beyond what is possible with current approaches.

References

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  • Published in

    cover image ACM SIGPLAN Notices
    ACM SIGPLAN Notices  Volume 51, Issue 8
    PPoPP '16
    August 2016
    405 pages
    ISSN:0362-1340
    EISSN:1558-1160
    DOI:10.1145/3016078
    Issue’s Table of Contents
    • cover image ACM Conferences
      PPoPP '16: Proceedings of the 21st ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
      February 2016
      420 pages
      ISBN:9781450340922
      DOI:10.1145/2851141

    Copyright © 2016 ACM

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 27 February 2016

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