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Title:
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Predicting the Best Mapping for Efficient Exploitation of Task and Data Parallelism
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Author:
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Guirado Fernández, Fernando; Ripoll, A.; Roig Mateu, Concepció; Yuan, X.; Luque, Emilio
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Notes:
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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.
This work was supported by the MCyT under contract 2001-2592 and partially sponsored by the Generalitat de Catalunya (G. de Rec. Consolidat 2001SGR-00218). |
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Rights:
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(c) Springer Verlag, 2003
info:eu-repo/semantics/restrictedAccess |
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Document type:
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article
publishedVersion |
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Published by:
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Springer Verlag
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