Nested OpenMP Parallelization of a Hierarchical Data Clustering Algorithm

Panagiotis Hadjidoukas 1 Laurent Amsaleg 2
2 TEXMEX - Multimedia content-based indexing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : This paper presents a high performance parallel implementation of a hierarchical data clustering algorithm. The OpenMP programming model, either enhanced with our lightweight runtime support or through its tasking model, deals with the high irregularity of the algorithm and allows for efficient exploitation of the inherent loop-level nested parallelism. Thorough experimental evaluation demonstrates the performance scalability of our parallelization and the effective utilization of computational resources, which results in a clustering approach able to provide high quality clustering of very large datasets.
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Article dans une revue
Parallel Processing Letters, World Scientific Publishing, 2010, 20 (2), pp.187-208. 〈http://www.worldscinet.com/ppl/20/preserved-docs/2002/S0129626410000144.pdf〉. 〈10.1142/S0129626410000144〉
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https://hal.inria.fr/inria-00514758
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Soumis le : vendredi 3 septembre 2010 - 09:02:16
Dernière modification le : jeudi 11 janvier 2018 - 06:20:10

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Panagiotis Hadjidoukas, Laurent Amsaleg. Nested OpenMP Parallelization of a Hierarchical Data Clustering Algorithm. Parallel Processing Letters, World Scientific Publishing, 2010, 20 (2), pp.187-208. 〈http://www.worldscinet.com/ppl/20/preserved-docs/2002/S0129626410000144.pdf〉. 〈10.1142/S0129626410000144〉. 〈inria-00514758〉

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