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Convolution of large 3D images on GPU and its decomposition

Pavel Karas, David Svoboda
Centre for Biomedical Image Analysis, Faculty of Informatics, Masaryk University, Botanicka 68a, Brno, Czech republic
EURASIP Journal on Advances in Signal Processing, ISSN 1687-6172, vol. 2011, no. 1, 2011

@article{karas2011convolution,

   title={Convolution of Large 3D Images on GPU and its Decomposition},

   author={Karas, P. and Svoboda, D.},

   year={2011}

}

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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.
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