- Tytuł:
- Studying OpenMP thread mapping for parallel linear algebra kernels on multicore system
- Autorzy:
-
Bylina, B.
Bylina, J. - Powiązania:
- https://bibliotekanauki.pl/articles/200778.pdf
- Data publikacji:
- 2018
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
computation performance
OpenMP standard
nonnegative matrix factorization
thread mapping
energy consumption
wydajność obliczeniowa
Standard OpenMP
nieujemna faktoryzacja macierzy
mapowanie
zużycie energii - Opis:
- Thread mapping is one of the techniques which allow for efficient exploiting of the potential of modern multicore architectures. The aim of this paper is to study the impact of thread mapping on the computing performance, the scalability, and the energy consumption for parallel dense linear algebra kernels on hierarchical shared memory multicore systems. We consider the basic application, namely a matrix-matrix product (GEMM), and two parallel matrix decompositions (LU and WZ). Both factorizations exploit parallel BLAS (basic linear algebra subprograms) operations, among others GEMM. We compare differences between various thread mapping strategies for these applications. Our results show that the choice of thread mapping has the measurable impact on the performance, the scalability, and energy consumption of the GEMM and two matrix factorizations.
- Źródło:
-
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2018, 66, 6; 981-990
0239-7528 - Pojawia się w:
- Bulletin of the Polish Academy of Sciences. Technical Sciences
- Dostawca treści:
- Biblioteka Nauki
Artykuł