Here we present a first multi-node/multi-GPU implementation of OpenCAL for grid-based high-performance numerical simulation. OpenCL and MPI have been adopted as low-level APIs for maximum portability and performance evaluated with respect to three different benchmarks, namely a Sobel edge detection filter, a Julia fractal generator, and the SciddicaT Cellular Automata model for fluid-flows simulation. Different hardware configurations of a dual-node test cluster have been considered, allowing for executions up to four GPUs. Optimal performance has been achieved in consideration of the compute/memory bound nature of both benchmarks and hardware configurations.
A first multi-GPU/multi-node implementation of the open computing abstraction layer
De Rango, Alessio;Spataro, Davide;Spataro, William;D'Ambrosio, Donato
2018-01-01
Abstract
Here we present a first multi-node/multi-GPU implementation of OpenCAL for grid-based high-performance numerical simulation. OpenCL and MPI have been adopted as low-level APIs for maximum portability and performance evaluated with respect to three different benchmarks, namely a Sobel edge detection filter, a Julia fractal generator, and the SciddicaT Cellular Automata model for fluid-flows simulation. Different hardware configurations of a dual-node test cluster have been considered, allowing for executions up to four GPUs. Optimal performance has been achieved in consideration of the compute/memory bound nature of both benchmarks and hardware configurations.File | Dimensione | Formato | |
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opencal-jcs-postprint.pdf
Open Access dal 23/09/2020
Descrizione: Versione editoriale disponibile al link https://www.sciencedirect.com/science/article/pii/S1877750318303922; DOI: 10.1016/j.jocs.2018.09.012
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