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Numrering	Referens	Omslagsbild	Hitta
1.	Myllykoski, Mirko, 1988-, et al. (författare) On solving separable block tridiagonal linear systems using a GPU implementation of radix-4 PSCR method 2018 Ingår i: Journal of Parallel and Distributed Computing. - : Elsevier. - 0743-7315 .- 1096-0848. ; 115, s. 56-66 Tidskriftsartikel (refereegranskat)abstract Partial solution variant of the cyclic reduction (PSCR) method is a direct solver that can be applied to certain types of separable block tridiagonal linear systems. Such linear systems arise, e.g., from the Poisson and the Helmholtz equations discretized with bilinear finite-elements. Furthermore, the separability of the linear system entails that the discretization domain has to be rectangular and the discretization mesh orthogonal. A generalized graphics processing unit (GPU) implementation of the PSCR method is presented. The numerical results indicate up to 24-fold speedups when compared to an equivalent CPU implementation that utilizes a single CPU core. Attained floating point performance is analyzed using roofline performance analysis model and the resulting models show that the attained floating point performance is mainly limited by the off-chip memory bandwidth and the effectiveness of a tridiagonal solver used to solve arising tridiagonal subproblems. The performance is accelerated using off-line autotuning techniques.

Myllykoski, Mirko, 1988-, et al. (författare)
On solving separable block tridiagonal linear systems using a GPU implementation of radix-4 PSCR method
2018
Ingår i: Journal of Parallel and Distributed Computing. - : Elsevier. - 0743-7315 .- 1096-0848. ; 115, s. 56-66
Tidskriftsartikel (refereegranskat)abstract
- Partial solution variant of the cyclic reduction (PSCR) method is a direct solver that can be applied to certain types of separable block tridiagonal linear systems. Such linear systems arise, e.g., from the Poisson and the Helmholtz equations discretized with bilinear finite-elements. Furthermore, the separability of the linear system entails that the discretization domain has to be rectangular and the discretization mesh orthogonal. A generalized graphics processing unit (GPU) implementation of the PSCR method is presented. The numerical results indicate up to 24-fold speedups when compared to an equivalent CPU implementation that utilizes a single CPU core. Attained floating point performance is analyzed using roofline performance analysis model and the resulting models show that the attained floating point performance is mainly limited by the off-chip memory bandwidth and the effectiveness of a tridiagonal solver used to solve arising tridiagonal subproblems. The performance is accelerated using off-line autotuning techniques.

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