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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Published in:Procedia computer science Vol. 9; pp. 17 - 26
Main Authors: Baboulin, Marc, Donfack, Simplice, Dongarra, Jack, Grigori, Laura, Rémy, Adrien, Tomov, Stanimire
Format: Journal Article
Language:English
Published: Elsevier B.V 2012
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ISSN:1877-0509, 1877-0509
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Abstract 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.
AbstractList 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.
Author Baboulin, Marc
Rémy, Adrien
Dongarra, Jack
Grigori, Laura
Donfack, Simplice
Tomov, Stanimire
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  surname: Tomov
  fullname: Tomov, Stanimire
  email: tomov@eecs.utk.edu
  organization: University of Tennessee, USA
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crossref_primary_10_15803_ijnc_4_1_131
crossref_primary_10_1016_j_jcp_2017_12_028
crossref_primary_10_3390_mca26030052
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Keywords linear system solvers
dense linear algebra libraries
LU factorization
communication-avoiding algorithms
hybrid multicore/GPU computing
Language English
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SubjectTerms communication-avoiding algorithms
dense linear algebra libraries
hybrid multicore/GPU computing
linear system solvers
LU factorization
Title A Class of Communication-avoiding Algorithms for Solving General Dense Linear Systems on CPU/GPU Parallel Machines
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