Coarse-Grain Optimization and Code Generation for Embedded Multicore Systems

Abstract : As processors and systems-on-chip increasingly become multicore, parallel programming remains a difficult, time-consuming and complicated task. End users who are not parallel programming experts have a need to exploit such processors and architectures, using state of the art fourth generation of high programming languages, like Scilab or MATLAB. The ALMA toolset addresses this problem by receiving Scilab code as input and produces parallel code for embedded multiprocessor systems on chip, using platform quasi-agnostic optimisations. In this paper, coarse grain parallelism extraction and optimization issues as well as parallel code generation for the ALMA toolset are discussed.
Type de document :
Communication dans un congrès
16th Euromicro Conference on Digital System Design (DSD), Sep 2013, Santander, Spain. pp.379-386, 2013, 〈10.1109/DSD.2013.48〉
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https://hal.inria.fr/hal-00921459
Contributeur : François Charot <>
Soumis le : vendredi 20 décembre 2013 - 14:28:27
Dernière modification le : mercredi 16 mai 2018 - 11:23:26

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George Goulas, Christos Valouxis, Panayiotis Alefragis, Nikolaos Voros, Oliver Oey, et al.. Coarse-Grain Optimization and Code Generation for Embedded Multicore Systems. 16th Euromicro Conference on Digital System Design (DSD), Sep 2013, Santander, Spain. pp.379-386, 2013, 〈10.1109/DSD.2013.48〉. 〈hal-00921459〉

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