NUMA-ICTM: A Parallel Version of ICTM Exploiting Memory Placement Strategies for NUMA Machines

Marcio Bastos Castro 1 Luiz Gustavo Fernandes 2, * Christiane Pousa Ribeiro 1, 3, * Jean-François Mehaut 1 M. Aguiar
* Auteur correspondant
1 MESCAL - Middleware efficiently scalable
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
2 PUCRS - Pontifícia Universidade Católica do Rio Grande do Sul [Porto Alegre]
3 LIG - Laboratoire d'Informatique de Grenoble
Abstract : In geophysics, the appropriate subdivision of a region into segments is extremely important. ICTM (interval categorizer tesselation model) is an application that categorizes geographic regions using information extracted from satellite images. The categorization of large regions is a computational intensive problem, what justifies the proposal and development of parallel solutions in order to improve its applicability. Recent advances in multiprocessor architectures lead to the emergence of NUMA (non-uniform memory access) machines. In this work, we present NUMA-ICTM: a parallel solution of ICTM for NUMA machines. First, we parallelize ICTM using OpenMP. After, we improve the OpenMP solution using the MAI (memory affinity interface) library, which allows a control of memory allocation in NUMA machines. The results show that the optimization of memory allocation leads to significant performance gains over the pure OpenMP parallel solution.
Type de document :
Communication dans un congrès
Proceedings of the 10th International Workshop on Parallel and Distributed Scientific and Engineering Computing (PDSEC), 2009, Roma, Italy. IEEE, pp.1-8, 2009, 〈10.1109/IPDPS.2009.5161155〉
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https://hal.inria.fr/hal-00788917
Contributeur : Arnaud Legrand <>
Soumis le : vendredi 15 février 2013 - 13:46:24
Dernière modification le : jeudi 11 octobre 2018 - 08:48:02

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Marcio Bastos Castro, Luiz Gustavo Fernandes, Christiane Pousa Ribeiro, Jean-François Mehaut, M. Aguiar. NUMA-ICTM: A Parallel Version of ICTM Exploiting Memory Placement Strategies for NUMA Machines. Proceedings of the 10th International Workshop on Parallel and Distributed Scientific and Engineering Computing (PDSEC), 2009, Roma, Italy. IEEE, pp.1-8, 2009, 〈10.1109/IPDPS.2009.5161155〉. 〈hal-00788917〉

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