Szczegóły publikacji
Opis bibliograficzny
Towards efficient GPGPU Cellular Automata model implementation using persistent active cells / Paweł RENC, Tomasz Pęcak, Alessio De Rango, William Spataro, Giuseppe Mendicino, Jarosław WĄS // Journal of Computational Science ; ISSN 1877-7503. — 2022 — vol. 59 art. no. 101538, s. 1–10. — Bibliogr. s. 9–10, Abstr. — Publikacja dostępna online od: 2022-01-10. — P. Renc - dod. afiliacja: Sano, Centre for Computational Medicine, Kraków
Autorzy (6)
- AGHRenc Paweł
- AGHPęcak Tomasz
- de Rango Alessio
- Spataro William
- Mendicino Giuseppe
- AGHWąs Jarosław
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 138902 |
|---|---|
| Data dodania do BaDAP | 2022-03-03 |
| Tekst źródłowy | URL |
| DOI | 10.1016/j.jocs.2021.101538 |
| Rok publikacji | 2022 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Czasopismo/seria | Journal of Computational Science |
Abstract
Natural complex phenomena simulation relies on the application of advanced numerical models. Nevertheless, due to their inherent temporal and spatial computational complexity, efficient parallel computing algorithms are required in order to speed up simulation execution times. In this paper, we apply the Nvidia CUDA architecture to the simulation of a groundwater hydrological model based on the Cellular Automata formalism. Different implementations, using different memory access patterns and optimizations, regarding the application of persistent active cells (i.e., once a cell is activated, it remains such throughout a simulation), are presented and evaluated. The obtained results have demonstrated the full suitability of the approach in speeding up simulation times, thus resulting in a valid support for complex system modeling.
