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PRODID:-//Microsoft Corporation//Outlook MIMEDIR//EN
VERSION:1.0
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DTSTART:20151117T231500Z
DTEND:20151118T010000Z
LOCATION:Level 4 - Lobby
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:ABSTRACT: We discuss a GPU solver for sparse or dense banded linear systems Ax=b, with A possibly nonsymmetric, sparse, and moderately large. The split and parallelize (SaP) approach seeks to partition the matrix A into P diagonal sub-blocks which are independently factored in parallel. The solution may choose to consider or to ignore the off-diagonal coupling blocks. This approach, along with the Krylov iterative methods that it preconditions, are implemented in the SaP::GPU solver, which runs entirely on the GPU except for several stages involved in preliminary row-column permutations. =0A=0ASaP::GPU compares well in terms of efficiency with three commonly used sparse direct solvers: PARDISO, SuperLU, and MUMPS. Compared to Intel's MKL, SaP::GPU proves to also be performant on dense banded systems that are close to being diagonally dominant. =0A=0ASaP::GPU is available open source under a permissive BSD3 license.
SUMMARY:A Splitting Approach for the Parallel Solution of Large Linear Systems on GPU Cards
PRIORITY:3
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