Distributed S-Net: Cluster and grid computing without the hassle

C. Grelck, Jukka Julku, F. Penczek

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    6 Citations (Scopus)

    Abstract

    S-Net is a declarative coordination language and component technology primarily aimed at modern multi-core/many-core chip architectures. It builds on the concept of stream processing to structure dynamically evolving networks of communicating asynchronous components, which themselves are implemented using a conventional language suitable for the application domain. We present the design and implementation of Distributed S-Net, a conservative extension of S-Net aimed at distributed memory architectures ranging from many-core chip architectures with hierarchical memory organisations to more traditional clusters of workstations, supercomputers and grids. Three case studies illustrate how to use Distributed S-Net to implement different models of parallel execution. Runtimes obtained on a workstation cluster demonstrate how Distributed S-Net allows programmers with little or no background in parallel programming to make effective use of distributed memory architectures with minimal programming effort
    Original languageEnglish
    Title of host publicationProceedings
    Subtitle of host publication12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012
    PublisherIEEE Institute of Electrical and Electronic Engineers
    Pages410-418
    ISBN (Print)978-0-7695-4691-9, 978-1-4673-1395-7
    DOIs
    Publication statusPublished - 2012
    MoE publication typeNot Eligible
    Event12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012 - Ottawa, ON, Canada
    Duration: 13 May 201216 May 2012

    Conference

    Conference12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012
    Abbreviated titleCCGrid 2012
    CountryCanada
    CityOttawa, ON
    Period13/05/1216/05/12

    Keywords

    • Cluster computing
    • component coordination
    • message passing
    • stream processing

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