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Computational Mechanics
Erschienen in: Computational Mechanics 1/2015

01.01.2015 | Original Paper

Impact of data distribution on the parallel performance of iterative linear solvers with emphasis on CFD of incompressible flows

verfasst von: M. Esmaily-Moghadam, Y. Bazilevs, A. L. Marsden

Erschienen in: Computational Mechanics | Ausgabe 1/2015

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Abstract

A parallel data structure that gives optimized memory layout for problems involving iterative solution of sparse linear systems is developed, and its efficient implementation is presented. The proposed method assigns a processor to a problem subdomain, and sorts data based on the shared entries with the adjacent subdomains. Matrix–vector-product communication overhead is reduced and parallel scalability is improved by overlapping inter-processor communications and local computations. The proposed method simplifies the implementation of parallel iterative linear equation solver algorithms and reduces the computational cost of vector inner products and matrix–vector products. Numerical results demonstrate very good performance of the proposed technique.
Vorheriger Artikel Multiscale modelling framework for the fracture of thin brittle polycrystalline films: application to polysilicon
Nächster Artikel Smoothed finite element method implemented in a resultant eight-node solid-shell element for geometrical linear analysis

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Metadaten
Titel
Impact of data distribution on the parallel performance of iterative linear solvers with emphasis on CFD of incompressible flows
verfasst von
M. Esmaily-Moghadam
Y. Bazilevs
A. L. Marsden
Publikationsdatum
01.01.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
Computational Mechanics / Ausgabe 1/2015
Print ISSN: 0178-7675
Elektronische ISSN: 1432-0924
DOI
https://doi.org/10.1007/s00466-014-1084-3

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