| Texto completo | |
| Autor(es): |
Carastan-Santos, Danilo
;
Martins-, David C., Jr.
;
Song, Siang W.
;
Rozante, Luiz C. S.
;
de Camargo, Raphael Y.
Número total de Autores: 5
|
| Tipo de documento: | Artigo Científico |
| Fonte: | CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE; v. 31, n. 18, p. 12-pg., 2019-09-25. |
| Resumo | |
We present a hybrid exact algorithm for the Minimal Hitting Set (MHS) Enumeration Problem for highly heterogeneous CPU-GPU-MIC platforms. With several techniques that permit an efficient exploitation of each architecture, low communication cost, and effective load balancing, we were able to enumerate MHSs for large instances in reasonable time, achieving good performance and scalability. We obtained speedups of up to 25.32 in comparison with using two six-core CPUs and we also enumerated MHSs for instances with tens of thousands of variables in less than 5 hours. We also evaluated our algorithm with a real-world driven dataset, and with a large CPU-GPU cluster, we unprecedentedly enumerated in parallel large minimal hitting sets of this dataset in less than 8 hours. These results reinforce the statement that heterogeneous clusters of CPUs, GPUs, and MICs can be used efficiently for high-performance computing. (AU) | |
| Processo FAPESP: | 14/50937-1 - INCT 2014: da Internet do Futuro |
| Beneficiário: | Fabio Kon |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |
| Processo FAPESP: | 13/26644-1 - Modelos de programação e algoritmos para a execução eficiente de aplicações paralelas em aglomerados heterogêneos |
| Beneficiário: | Raphael Yokoingawa de Camargo |
| Modalidade de apoio: | Auxílio à Pesquisa - Regular |
| Processo FAPESP: | 15/24485-9 - Internet do futuro aplicada a cidades inteligentes |
| Beneficiário: | Fabio Kon |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |
| Processo FAPESP: | 15/01587-0 - Armazenagem, modelagem e análise de sistemas dinâmicos para aplicações em e-Science |
| Beneficiário: | João Eduardo Ferreira |
| Modalidade de apoio: | Auxílio à Pesquisa - Programa eScience e Data Science - Temático |