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2015 | OriginalPaper | Buchkapitel

Modeling 1D Distributed-Memory Dense Kernels for an Asynchronous Multifrontal Sparse Solver

verfasst von : Patrick R. Amestoy, Jean-Yves L’Excellent, François-Henry Rouet, Wissam M. Sid-Lakhdar

Erschienen in: High Performance Computing for Computational Science -- VECPAR 2014

Verlag: Springer International Publishing

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Abstract

To solve sparse systems of linear equations, multifrontal methods rely on dense partial \(LU\) decompositions of so-called frontal matrices; we consider a parallel asynchronous setting in which several frontal matrices can be factored simultaneously. In this context, to address performance and scalability issues of acyclic pipelined asynchronous factorization kernels, we study models to revisit properties of left and right-looking variants of partial \(LU\) decompositions, study the use of several levels of blocking, before focusing on communication issues. The general purpose sparse solver MUMPS has been modified to implement the proposed algorithms and confirm the properties demonstrated by the models.

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Metadaten
Titel
Modeling 1D Distributed-Memory Dense Kernels for an Asynchronous Multifrontal Sparse Solver
verfasst von
Patrick R. Amestoy
Jean-Yves L’Excellent
François-Henry Rouet
Wissam M. Sid-Lakhdar
Copyright-Jahr
2015
DOI
https://doi.org/10.1007/978-3-319-17353-5_14