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A class of communication-avoiding algorithms for solving general dense linear systems on CPU/GPU parallel machines

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 for these solvers on current hybrid multicore-GPU parallel machines.
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https://hal.inria.fr/hal-00656457
Contributor : Marc Baboulin Connect in order to contact the contributor
Submitted on : Wednesday, February 29, 2012 - 11:27:57 AM
Last modification on : Wednesday, October 26, 2022 - 8:16:05 AM
Long-term archiving on: : Wednesday, December 14, 2016 - 9:17:28 AM

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  • HAL Id : hal-00656457, version 3

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Marc Baboulin, Simplice Donfack, Jack Dongarra, Laura Grigori, Adrien Rémy, et al.. A class of communication-avoiding algorithms for solving general dense linear systems on CPU/GPU parallel machines. [Research Report] RR-7854, INRIA. 2012. ⟨hal-00656457v3⟩

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