In this paper, we propose a fine-to-coarse parallelization strategy in order to exploit, in a case study, a parallel hybrid architecture. We consider the Optical Flow numerical problem, modelled by partial differential equations, and implement a parallel multilevel software. Our hybrid software solution is a smart combination between codes on Graphic Processor Units (GPUs) and standard scientific parallel computing libraries on a cluster. Numerical experiments, on real satellite image sequences coming from a large dataset in a big data scenario, together with application profiling, highlight good results in terms of performance for the proposed approach.

A parallel PDE-based numerical algorithm for computing the Optical Flow in hybrid systems / Cuomo, Salvatore; DE MICHELE, Pasquale; Galletti, Ardelio; Marcellino, Livia. - In: JOURNAL OF COMPUTATIONAL SCIENCE. - ISSN 1877-7503. - (2017). [10.1016/j.jocs.2017.03.011]

A parallel PDE-based numerical algorithm for computing the Optical Flow in hybrid systems

CUOMO, SALVATORE;DE MICHELE, PASQUALE;GALLETTI, ARDELIO;MARCELLINO, LIVIA
2017

Abstract

In this paper, we propose a fine-to-coarse parallelization strategy in order to exploit, in a case study, a parallel hybrid architecture. We consider the Optical Flow numerical problem, modelled by partial differential equations, and implement a parallel multilevel software. Our hybrid software solution is a smart combination between codes on Graphic Processor Units (GPUs) and standard scientific parallel computing libraries on a cluster. Numerical experiments, on real satellite image sequences coming from a large dataset in a big data scenario, together with application profiling, highlight good results in terms of performance for the proposed approach.
2017
A parallel PDE-based numerical algorithm for computing the Optical Flow in hybrid systems / Cuomo, Salvatore; DE MICHELE, Pasquale; Galletti, Ardelio; Marcellino, Livia. - In: JOURNAL OF COMPUTATIONAL SCIENCE. - ISSN 1877-7503. - (2017). [10.1016/j.jocs.2017.03.011]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/675166
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