A Class of Communication-avoiding Algorithms for Solving General Dense Linear Systems on CPU/GPU Parallel Machines

We study several solvers for the solution of general linear systems where the main objective is to reduce the communication overhead due to pivoting. We first describe two existing algorithms for the LU factorization on hybrid CPU/GPU architectures. The first one is based on partial pivoting and the...

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Vydáno v:Procedia computer science Ročník 9; s. 17 - 26
Hlavní autoři: Baboulin, Marc, Donfack, Simplice, Dongarra, Jack, Grigori, Laura, Rémy, Adrien, Tomov, Stanimire
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 2012
Témata:
communication-avoiding algorithms
dense linear algebra libraries
hybrid multicore/GPU computing
linear system solvers
LU factorization
linear system solvers
dense linear algebra libraries
LU factorization
communication-avoiding algorithms
hybrid multicore/GPU computing
ISSN:1877-0509, 1877-0509
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Shrnutí:We study several solvers for the solution of general linear systems where the main objective is to reduce the communication overhead due to pivoting. We first describe two existing algorithms for the LU factorization on hybrid CPU/GPU architectures. The first one is based on partial pivoting and the second uses a random preconditioning of the original matrix to avoid pivoting. Then we introduce a solver where the panel factorization is performed using a communication-avoiding pivoting heuristic while the update of the trailing submatrix is performed by the GPU. We provide performance comparisons and tests on accuracy for these solvers on current hybrid multicore-GPU parallel machines.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2012.04.003