Predicting the best mapping for efficient exploitation of task and data parallelism

Fernando Guirado, Ana Ripoll, Concepció Roig, Xiao Yuan, Emilio Luque

    Research output: Contribution to journalArticleResearchpeer-review

    2 Citations (Scopus)

    Abstract

    The detection and exploitation of different kinds of parallelism, task parallelism and data parallelism often leads to efficient parallel programs. This paper presents a simulation environment to predict the best mapping for the execution of message-passing applications on distributed systems. Using this environment, we evaluate the performance of an image processing application for the different parallelizing alternatives, and we propose the ways to improve its performance. © Springer-Verlag 2003.
    Original languageEnglish
    Pages (from-to)218-223
    JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume2790
    Publication statusPublished - 1 Dec 2004

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