Multi-core portability abstraction

Martti Forsell, Mikko Hiivala

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

    2 Citations (Scopus)

    Abstract

    Application portability between different multicore architecture-parallel programming paradigm/tool pairs is a big problem nowadays leading often to a complete rewrite of an application when switching from an architecture-paradigm pair to another. This is caused by a wide variety of architectural properties requiring different optimization techniques for different architectures, typically hiding the essence of (parallel) computation defined by the application. In this paper, we introduce the Multi-Core Portability Abstraction (MCPA) simplifying portability and implementation of parallel applications making use of shared memory. It abstracts away typical architecture dependent effects caused by latency, synchronization, and partitioning and acts as an executable intermediate abstraction/reference implementation as well as a tool for analyzing the intrinsic parallelism of the application and relative goodness of architectures in executing it. We give a short application example with performance measurements
    Original languageEnglish
    Title of host publicationProceedings of the IEEE 26th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2012
    PublisherIEEE Institute of Electrical and Electronic Engineers
    Pages778-785
    ISBN (Print)978-1-4673-0974-5
    DOIs
    Publication statusPublished - 2012
    MoE publication typeNot Eligible
    Event26th International Parallel and Distributed Processing Symposium, IPDPSW 2012 - Shanghai, China
    Duration: 21 May 201225 May 2012
    Conference number: 26

    Conference

    Conference26th International Parallel and Distributed Processing Symposium, IPDPSW 2012
    Abbreviated titleIPDPSW 2012
    Country/TerritoryChina
    CityShanghai
    Period21/05/1225/05/12

    Keywords

    • Application portability
    • model of computation
    • multicore architectures
    • parallel computing
    • parallel programming

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