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Please use this identifier to cite or link to this item: http://hdl.handle.net/10198/7054

Título: An hybrid approach for the parallelization of a block iterative algorithm
Autor: Balsa, Carlos
Guivarch, Ronan
Ruiz, Daniel
Zenadi, Mohamed
Palavras-chave: Parallel and distributed computing
Performance analysis
Issue Date: 2010
Editora: Vecpar 2010
Citação: Balsa, Carlos; Guivarch, Ronan; Ruiz, Daniel; Zenadi, Mohamed (2010) - An hybrid approach for the parallelization of a block iterative algorithm. Vecpar 2010 - In 9th International Meeting on High Performance Computing for Computational Science. Berkeley, USA.
Resumo: The Cimmino method is a row projection method in which the original linear system is divided into subsystems. At every iteration, it computes one projection per subsystem and uses these projections to construct an approximation to the solution of the linear system. The usual parallelization strategy in block algorithms is to distribute the different blocks on the available processors. In this paper, we follow another approach where we do not perform explicitly this block distribution to processors within the code, but let the multi-frontal sparse solver MUMPS handle the data distribution and parallelism. The data coming from the subsystems defined by the block partition in the Block Cimmino method are gathered in an unique block diagonal sparse matrix which is analysed, distributed and factorized in parallel by MUMPS. Our target is to define a methodology for parallelism based only on the functionalities provided by general sparse solver libraries and how efficient this way of doing can be.
Arbitragem científica: yes
URI: http://hdl.handle.net/10198/7054
Versão do Editor: http://vecpar.fe.up.pt/2010/papers/25.php
Appears in Collections:DEMAT - Artigos em Proceedings Não Indexados ao ISI

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