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;D'Ambrosio, Donato
2018

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.
Complex systems modeling; GPGPU computing; Grid based numerical modelling; MPI; OpenCL; Theoretical Computer Science; Computer Science (all); Modeling and Simulation
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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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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11770/288777
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