Feedback-directed thread scheduling with memory considerations

Fengguang Song, Shirley Moore, Jack Dongarra

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

    Abstract

    This paper describes a novel approach to generate an optimized schedule to run threads on distributed shared memory (DSM) systems. The approach relies upon a binary instrumentation tool to automatically acquire the memory sharingrelationship between user-level threads by analyzing their memory trace. We introduce the concept of Affinity Graph to model the relationship. Expensive I/O for large trace files is completely eliminated by using an online graph creation scheme. We apply the technique of hierarchical graph partitioning and thread reordering to the affinity graph to determine an optimal thread schedule. We have performed experiments on an SGI Altix system. The experimental results show that our approach is able to reduce the totalexecution time by 10% to 38% for a variety of applications through the maximization of the data reuse within a single processor, minimization of the data sharing between processors, and a good load balance. Copyright 2007 ACM.
    Original languageEnglish
    Title of host publicationProceedings of the 16th International Symposium on High Performance Distributed Computing 2007, HPDC'07|Proc. Int. Symp. High Perform. Distrib. Comput.
    PublisherAssociation for Computing Machinery
    Pages97-106
    Number of pages9
    ISBN (Print)1595936734, 9781595936738
    DOIs
    Publication statusPublished - 2007
    Event16th International Symposium on High Performance Distributed Computing 2007, HPDC'07 and Co-Located Workshops - Monterey, CA
    Duration: 1 Jul 2007 → …

    Conference

    Conference16th International Symposium on High Performance Distributed Computing 2007, HPDC'07 and Co-Located Workshops
    CityMonterey, CA
    Period1/07/07 → …

    Keywords

    • Affinity graph
    • Distributed shared memory
    • Scientific applications
    • Shared-memory programming

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