PaSTeL : Parallel Runtime and Algorithms for Small Datasets

Brice Videau 1 Erik Saule 1 Jean-François Méhaut 2
2 MESCAL - Middleware efficiently scalable
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : In this document, we put forward PaSTeL, an engine dedicated to parallel algorithms. PaSTeL offers both a programming model, to build parallel algorithms and an execution model based on work-stealing. Special care has been taken on using optimized thread activation and synchronization mechanisms. In order to illustrate the use of PaSTeL a subset of the STL's algorithms was implemented, which were also used on performance experiments. PaSTeL's performance is evaluated on a laptop computer using two cores, but also on a 16 cores platform. PaSTeL shows better performance than other implementations of the STL, especially on small datasets.
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Rapport
[Research Report] RR-6650, INRIA. 2008, pp.20
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Dernière modification le : jeudi 11 janvier 2018 - 06:21:39
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Brice Videau, Erik Saule, Jean-François Méhaut. PaSTeL : Parallel Runtime and Algorithms for Small Datasets. [Research Report] RR-6650, INRIA. 2008, pp.20. 〈inria-00322158v2〉

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