Hybrid static–dynamic selection of implementation alternatives in heterogeneous environments
Impacto
Scholar |
Otros documentos de la autoría: del Río Astorga, David; Dolz, Manuel F.; Fernández Muñoz, Javier; García Blas, Javier
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Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7036
comunitat-uji-handle3:10234/8620
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https://doi.org/10.1007/s11227-017-2147-y |
Metadatos
Título
Hybrid static–dynamic selection of implementation alternatives in heterogeneous environmentsFecha de publicación
2019-09Editor
SpringerCita bibliográfica
DEL RIO ASTORGA, D., et al. Hybrid static–dynamic selection of implementation alternatives in heterogeneous environments. The Journal of Supercomputing, 2019, 75.8: 4098-4113.Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://link.springer.com/article/10.1007/s11227-017-2147-yVersión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
With the emergence of heterogeneous architectures, developing parallel software has become an increasingly complex task. The ability of using multiple devices in a single application, such as CPUs, accelerators, or ... [+]
With the emergence of heterogeneous architectures, developing parallel software has become an increasingly complex task. The ability of using multiple devices in a single application, such as CPUs, accelerators, or coprocessors, has turned the implementation and optimization tasks into a challenging process, which comes along with a variety of difficulties. The inherent complexities of the parallel algorithm, its multiple implementations, and the mapping possibilities onto one of the available processors are just examples of how intricate these tasks can become. To alleviate these issues, this paper proposes a hybrid static–dynamic selector to better exploit resources provided by heterogeneous systems. Specifically, this framework generates at compile time a decision tree based on historical information for selecting the implementation that performs best at run-time. To evaluate the benefits of this approach, we analyze the performance with two use cases: the general matrix–matrix multiplication and an image processing medical application. The experimental results demonstrate that our proposed selector enhances performance and minimizes efforts needed to tune applications. We proved that our solution improves from 10 to 24% the overall application performance in comparison with other similar approach. [-]
Proyecto de investigación
EU Project ICT 644235 “RePhrase: REfactoring Parallel Heterogeneous Resource-Aware Applications” ; Spanish Ministerio de Economía y Competitividad, Project TIN2016-79637-P “Towards Unification of HPC and Big Data Paradigms”Derechos de acceso
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