Kobusińska, Anna - ed. ; Hsu, Ching-Hsien - ed. ; Lin, Kwei-Jay - ed.
The aim of this paper is to investigate dense linear algebra algorithms on shared memory multicore architectures. The design and implementation of a parallel tiled WZ factorization algorithm which can fully exploit such architectures are presented. Three parallel implementations of the algorithm are studied. The first one relies only on exploiting multithreaded BLAS (basic linear algebra subprograms) operations. The second implementation, except for BLAS operations, employs the OpenMP standard to use the loop-level parallelism. The third implementation, except for BLAS operations, employs the OpenMP task directive with the depend clause. ; We report the computational performance and the speedup of the parallel tiled WZ factorization algorithm on shared memory multicore architectures for dense square diagonally dominant matrices. Then we compare our parallel implementations with the respective LU factorization from a vendor implemented LAPACK library. We also analyze the numerical accuracy. Two of our implementations can be achieved with near maximal theoretical speedup implied by Amdahl`s law.
Zielona Góra: Uniwersytet Zielonogórski
AMCS, volume 29, number 2 (2019) ; kliknij tutaj, żeby przejść
Biblioteka Uniwersytetu Zielonogórskiego
14 lip 2025
11 lip 2025
17
https://zbc.uz.zgora.pl/repozytorium/publication/100975
| Nazwa wydania | Data |
|---|---|
| The parallel tiled WZ factorization algorithm for multicore architectures | 14 lip 2025 |
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