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http://hdl.handle.net/20.500.12222/141| Título : | A differential evolution algorithm parallel implementation in a GPU |
| Autor(es) : | Gerardo Abel Laguna-Sanchez, 0000-0001-5145-1248 |
| Autor(es) sin ID: | Olguín Carbajal, M.; Cruz Cortés, N.; Barrón Fernández, R.; Cadena Martínez, R. |
| Fecha de publicación : | 2016 |
| Tipo de resultado Científico: | article |
| Materia o Disciplina: | INGENIERÍA Y TECNOLOGÍA |
| Palabras clave: | Multithreading; Parallel Programming; GPU; Differential Evolution and Fine Grain |
| Descripción : | The computational power of a Graphics Processing Unit (GPU), relative to a single CPU, presents a promising alternative to write parallel codes in an efficient and economical way. Differential Evolution (DE) algorithm is a global optimization based on bio-inspired heuristic. DE has a good performance, low computational complexity and need few parameters. This article presents parallel implementation of this population-based heuristic, implemented on a NVIDIA GPU device with multi-thread support and using CUDA as the model of parallel programming for these case. Our goal is to give some insights about GPU’s parallel programming by a simple and almost straightforward parallel code, and compare the performance of DE algorithm running on a multithreading GPU. This work shows that with a parallel code and a NVIDIA GPU not only the execution time is reduced but also the convergence behavior to the global optimum may be changed in a significant manner with respect the original sequential code. |
| Editor: | JATIT |
| URI : | http://hdl.handle.net/20.500.12222/141 |
| Condiciones de licencia: | https://creativecommons.org/licenses/by-nc-nd/4.0/ |
| Fuente: | Journal of Theoretical and Applied Information Technology (JATIT) (2) vol.86 (2016) ISSN: 1992-8645 |
| Aparece en las colecciones: | Artículos Científicos |
Ficheros en este ítem:
| Fichero | Descripción | Tamaño | Formato | |
|---|---|---|---|---|
| 000017.pdf | 12 páginas | 844.12 kB | Adobe PDF | Visualizar/Abrir |
| 000017.xml | 1.21 MB | XML | Visualizar/Abrir |
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