KARAS, Pavel, David SVOBODA and Pavel ZEMČÍK. GPU Optimization of Convolution for Large 3-D Real Images. In Blanc-Talon, Jacques and Philips, Wilfried and Popescu, Dan and Scheunders, Paul and Zemcík, Pavel. Proceedings of the International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS’12). Neuveden: Springer Berlin / Heidelberg, 2012, p. 59-71. ISBN 978-3-642-33139-8. Available from: https://dx.doi.org/10.1007/978-3-642-33140-4_6. |
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@inproceedings{984851, author = {Karas, Pavel and Svoboda, David and Zemčík, Pavel}, address = {Neuveden}, booktitle = {Proceedings of the International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS’12)}, doi = {http://dx.doi.org/10.1007/978-3-642-33140-4_6}, editor = {Blanc-Talon, Jacques and Philips, Wilfried and Popescu, Dan and Scheunders, Paul and Zemcík, Pavel}, keywords = {gpu; convolution; 3-D; image processing}, howpublished = {tištěná verze "print"}, language = {eng}, location = {Neuveden}, isbn = {978-3-642-33139-8}, pages = {59-71}, publisher = {Springer Berlin / Heidelberg}, title = {GPU Optimization of Convolution for Large 3-D Real Images}, url = {http://dx.doi.org/10.1007/978-3-642-33140-4_6}, year = {2012} }
TY - JOUR ID - 984851 AU - Karas, Pavel - Svoboda, David - Zemčík, Pavel PY - 2012 TI - GPU Optimization of Convolution for Large 3-D Real Images PB - Springer Berlin / Heidelberg CY - Neuveden SN - 9783642331398 KW - gpu KW - convolution KW - 3-D KW - image processing UR - http://dx.doi.org/10.1007/978-3-642-33140-4_6 N2 - In this paper, we propose a method for computing convolution of large 3-D images with respect to real signals. The convolution is performed in a frequency domain using a convolution theorem. Due to properties of real signals, the algorithm can be optimized so that both time and the memory consumption are halved when compared to complex signals of the same size. Convolution is decomposed in a frequency domain using the decimation in frequency (DIF) algorithm. The algorithm is accelerated on a graphics hardware by means of the CUDA parallel computing model, achieving up to 10x speedup with a single GPU over an optimized implementation on a quad-core CPU. ER -
KARAS, Pavel, David SVOBODA and Pavel ZEMČÍK. GPU Optimization of Convolution for Large 3-D Real Images. In Blanc-Talon, Jacques and Philips, Wilfried and Popescu, Dan and Scheunders, Paul and Zemcík, Pavel. \textit{Proceedings of the International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS’12)}. Neuveden: Springer Berlin / Heidelberg, 2012, p.~59-71. ISBN~978-3-642-33139-8. Available from: https://dx.doi.org/10.1007/978-3-642-33140-4\_{}6.
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