Skip to Main content Skip to Navigation
Reports

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.
Document type :
Reports
Complete list of metadata

Cited literature [20 references]  Display  Hide  Download

https://hal.inria.fr/hal-00656457
Contributor : Marc Baboulin <>
Submitted on : Wednesday, February 29, 2012 - 11:27:57 AM
Last modification on : Thursday, July 8, 2021 - 3:48:19 AM
Long-term archiving on: : Wednesday, December 14, 2016 - 9:17:28 AM

File

RR-7854.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-00656457, version 3

Collections

Citation

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⟩

Share

Metrics

Record views

728

Files downloads

701