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.
|Titolo:||A parallel PDE-based numerical algorithm for computing the Optical Flow in hybrid systems|
|Autori interni:||GALLETTI, Ardelio|
|Data di pubblicazione:||2017|
|Rivista:||JOURNAL OF COMPUTATIONAL SCIENCE|
|Appare nelle tipologie:||1.1 Articolo in rivista|