High-Performance Computation of Bézier Surfaces on Parallel and Heterogeneous PlatformsReport as inadecuate




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International Journal of Parallel Programming

pp 1–28

First Online: 12 May 2017Received: 18 December 2016Accepted: 25 April 2017DOI: 10.1007-s10766-017-0506-1

Cite this article as: Palomar, R., Gómez-Luna, J., Cheikh, F.A. et al. Int J Parallel Prog 2017. doi:10.1007-s10766-017-0506-1

Abstract

Bézier surfaces are mathematical tools employed in a wide variety of applications. Some works in the literature propose parallelization strategies to improve performance for the computation of Bézier surfaces. These approaches, however, are mainly focused on graphics applications and often are not directly applicable to other domains. In this work, we propose a new method for the computation of Bézier surfaces, together with approaches to efficiently map the method onto different platforms CPUs, discrete and integrated GPUs. Additionally, we explore CPU–GPU cooperation mechanisms for computing Bézier surfaces using two integrated heterogeneous systems with different characteristics. An exhaustive performance evaluation—including different data-types, rendering and several hardware platforms—is performed. The results show that our method achieves speedups as high as 3.12x double-precision and 2.47x single-precision on CPU, and 3.69x double-precision and 13.14x single-precision on GPU compared to other methods in the literature. In heterogeneous platforms, the CPU–GPU cooperation increases the performance up to 2.09x with respect to the GPU-only version. Our method and the associated parallelization approaches can be easily employed in domains other than computer-graphics e.g., image registration, bio-mechanical modeling and flow simulation, and extended to other Bézier formulations and Bézier constructions of higher order than surfaces.

KeywordsBézier surfaces GPU computing Parallel computing Computer-graphics Heterogeneous computing This work was supported by the European Economic Area EEA Grants NILS 004-2BBRR, the Research Council of Norway through the Hypercept project No. 221073, The Intervention Centre, Oslo University Hospital Norway, The Ministry of Education of Spain TIN2013-42253P and Junta de Andalucía of Spain TIC-1692.





Author: Rafael Palomar - Juan Gómez-Luna - Faouzi A. Cheikh - Joaquín Olivares-Bueno - Ole J. Elle

Source: https://link.springer.com/







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