期刊
PARALLEL COMPUTING
卷 74, 期 -, 页码 118-135出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.parco.2017.11.006
关键词
MPI; CPU computing; Eigenvalue computation; Block-tridiagonal linear solvers
资金
- Agencia Estatal de Investigacion (AEI) [TIN2016-75985-P]
- European Commission ERDF funds
- Spanish Ministry of Education, Culture and Sport [FPU13-06655]
We consider the computation of a few eigenpairs of a generalized eigenvalue problen Ax = lambda Bx with block-tridiagonal matrices, not necessarily symmetric, in the context of Krylov methods. In this kind of computation, it is often necessary to solve a linear system of equations in each iteration of the eigensolver, for instance when B is not the identity matrix or when computing interior eigenvalues with the shift- and-invert spectral transformation. In this work, we aim to compare different direct linear solvers that can exploit the block-tridiagonal structure. Block cyclic reduction and the Spike algorithm are considered A parallel implementation based on MPI is developed in the context of the SLEPc library The use of GPU devices to accelerate local computations shows to be competitive for large block sizes. (C) 2017 Elsevier B.V. All rights reserved
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