| Revista: | Journal of applied research and technology |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000380500 |
| ISSN: | 1665-6423 |
| Autores: | Lin, Chih-Sheng1 Hsieh, Chih-Wei2 Chang, Hsi-Ya2 Hsiung, Pao-Ann1 |
| Instituciones: | 1National Chung Cheng University, Department of Computer Science and Information Engineering, Chaiyi. Taiwán 2National Center for High-Performance Computing, Hsinchu. Taiwán |
| Año: | 2014 |
| Periodo: | Dic |
| Volumen: | 12 |
| Número: | 6 |
| Paginación: | 1176-1186 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Experimental, aplicado |
| Resumen en inglés | Recently, heterogeneous system architectures are becoming mainstream for achieving high performance and power efficiency. In particular, many-core graphics processing units (GPUs) now play an important role for computing in heterogeneous architectures. However, for application designers, computational workload still needs to be distributed to heterogeneous GPUs manually and remains inefficient. In this paper, we propose a mixed integer non-linear programming (MINLP) based method for efficient workload distribution on heterogeneous GPUs by considering asymmetric capabilities of GPUs for various applications. Compared to the previous methods, the experimental results show that our proposed method improves performance and balance up to 33% and 116%, respectively. Moreover, our method only requires a few overhead while achieving high performance and load balancing |
| Disciplinas: | Ciencias de la computación |
| Palabras clave: | Programación, Unidades de procesamiento gráfico, Balance de carga, Programación mixta entera no lineal |
| Keyword: | Computer science, Programming, Graphic processing units, Load balance, Mixed-integer nonlinear programming |
| Texto completo: | Texto completo (Ver HTML) |
