KARAS, Pavel and David SVOBODA. Convolution of Large 3D Images on GPU and its Decomposition. EURASIP Journal on Advances in Signal Processing. NEW YORK (USA): HINDAWI PUBLISHING CORPORATION, 2011, vol. 2011, No 120, p. 1-12. ISSN 1687-6172. Available from: https://dx.doi.org/10.1186/1687-6180-2011-120. |
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@article{950226, author = {Karas, Pavel and Svoboda, David}, article_location = {NEW YORK (USA)}, article_number = {120}, doi = {http://dx.doi.org/10.1186/1687-6180-2011-120}, keywords = {convolution; decomposition; fft; gpu; dif; 3D}, language = {eng}, issn = {1687-6172}, journal = {EURASIP Journal on Advances in Signal Processing}, title = {Convolution of Large 3D Images on GPU and its Decomposition}, url = {http://asp.eurasipjournals.com/content/2011/1/120}, volume = {2011}, year = {2011} }
TY - JOUR ID - 950226 AU - Karas, Pavel - Svoboda, David PY - 2011 TI - Convolution of Large 3D Images on GPU and its Decomposition JF - EURASIP Journal on Advances in Signal Processing VL - 2011 IS - 120 SP - 1-12 EP - 1-12 PB - HINDAWI PUBLISHING CORPORATION SN - 16876172 KW - convolution KW - decomposition KW - fft KW - gpu KW - dif KW - 3D UR - http://asp.eurasipjournals.com/content/2011/1/120 L2 - http://asp.eurasipjournals.com/content/2011/1/120 N2 - In this paper we propose a method for computing convolution of large 3D images. The convolution is performed in a frequency domain using a convolution theorem. The algorithm is accelerated on a graphic card by means of the CUDA parallel computing model. Convolution is decomposed in a frequency domain using the DIF (decimation in frequency) algorithm. We pay attention to keeping our approach efficient in terms of both time and memory consumption and also in terms of memory transfers between CPU and GPU which have a significant influence on overall computational time. We also study the implementation on multiple GPUs and compare the results between the multi-GPU and multi-CPU implementations. ER -
KARAS, Pavel and David SVOBODA. Convolution of Large 3D Images on GPU and its Decomposition. \textit{EURASIP Journal on Advances in Signal Processing}. NEW YORK (USA): HINDAWI PUBLISHING CORPORATION, 2011, vol.~2011, No~120, p.~1-12. ISSN~1687-6172. Available from: https://dx.doi.org/10.1186/1687-6180-2011-120.
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