Efficient resource management applied to master-worker applications

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    Abstract

    We investigate the problem arising in scheduling parallel applications that follow a master-worker paradigm in order to maximize both resource efficiency and application performance. Based on the results obtained in a previous simulation study, we have derived a self-adjusting strategy that can be used to dynamically adjust the number of processors allocated to the application. The effectiveness of the proposed strategy has been assessed in two different scenarios: first, we implemented and tested this strategy on a cluster of homogeneous workstations. Secondly, we extended the self-adjusting strategy to be applied on heterogeneous clusters. We assessed the effectiveness of our strategy using an image-thinning application as a practical example of master-worker application. © 2003 Elsevier Inc. All rights reserved.
    Original languageEnglish
    Pages (from-to)767-773
    JournalJournal of Parallel and Distributed Computing
    Volume64
    Issue number6
    DOIs
    Publication statusPublished - 1 Jan 2004

    Keywords

    • Image thinning
    • Master-worker applications
    • Non-dedicated clusters
    • Resource management
    • Scheduling

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