International Journal of Image, Graphics and Signal Processing (IJIGSP)
IJIGSP Vol. 10, No. 8, 8 Aug. 2018
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Efficient 2D Convolution Filters Implementations on Graphics Processing Unit Using NVIDIA CUDA
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Author(s)
Mouna Afif
1,*
Yahia Said
1
Mohamed Atri
1
Index Terms
Convolution algorithms, Sobel filter, Gaussian Blur, CUDA, GPU, CPU
Abstract
Convolution algorithms present a key component and a significant step in image processing field. Despite their high arithmetic complexity, these algorithms are widely used because of their great importance for extracting image properties and features. Convolution algorithms require significant computing time, for that we propose a GPU acceleration of these algorithms by using the programming language CUDA presented by NVIDIA. Since these algorithms consume a lot of computing power, we understand the impact of the implementation of this type of algorithm on the acceleration of processing. GPU implementation present a suitable path to achieve better results than other implementation , for that optimizing time consuming time consuming of applications became an increasingly important task in many research areas. The goal of this work is to try to boost convolution algorithms execution time by adopting GPU implementations to accelerate treatments and to achieve real time constraints.
Cite This Paper
Mouna Afif, Yahia Said, Mohamed Atri, " Efficient 2D Convolution Filters Implementations on Graphics Processing Unit Using NVIDIA CUDA ", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.10, No.8, pp. 1-8, 2018. DOI: 10.5815/ijigsp.2018.08.01
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