Energy and Execution Time Comparison of Optical Flow Algorithms on SIMD and GPU Architectures

Abstract : This article presents and compares optimized implementations of two optical flow algorithms on several target boards comprising multi-core SIMD processors and GPUs. The two algorithms are Horn-Schunck (HS) and TV-L1, and have been chosen because they are both well-known, and because of their different computational complexity and accuracy. For both algorithms, we have made parallel optimized SIMD implementations , while HS has also been implemented on GPUs. For each algorithm, the comparison between the different versions and target boards is carried out in a two-dimensional fashion: in terms of computing speed-in order to achieve real-time computation-and in terms of energy consumption since we target embedded systems. The results show that for HS, the GPUs are the most efficient in both dimensions, able to process in real-time performances (25 frames per second) up to 8Mpix images for 0.35J per image, against 1.8Mpix images for 0.24J per image on CPU. The results also highlight the impact of optimizations on TV-L1: far slower than HS without optimization, it can almost match its performance after optimization on CPU, and can achieve real-time performances with 0.25J for 1.4Mpix images. We hope these results will help developers design optical flow embedded systems.
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Contributeur : Andrea Petreto <>
Soumis le : lundi 19 novembre 2018 - 18:16:57
Dernière modification le : samedi 16 mars 2019 - 02:01:52
Document(s) archivé(s) le : mercredi 20 février 2019 - 12:31:31


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  • HAL Id : hal-01925886, version 1



Andrea Petreto, Arthur Hennequin, Thomas Koehler, Thomas Romera, Yohan Fargeix, et al.. Energy and Execution Time Comparison of Optical Flow Algorithms on SIMD and GPU Architectures. Conference on Design and Architectures for Signal and Image Processing (Dasip 2018), Oct 2018, Porto, Portugal. 2018, 〈〉. 〈hal-01925886〉



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