Yahia Said

Work place: Laboratory of Electronics and Microelectronics (EμE), Faculty of Sciences of Monastir University of Monastir, 5000, TUNISIA



Research Interests: Computer systems and computational processes, Computer Architecture and Organization, Embedded System, Processor Design, Image Compression, Image Manipulation, Image Processing, Data Structures and Algorithms


Yahia SAID received the Master„s Degree in Micro-electronics from Faculty of Science of Monastir, Tunisia in 2010. Since 2011, he has been working as a Research Scientist at the Laboratory of Electronics & Micro-electronics, Faculty of Science of Monastir where he prepares his thesis. His areas of interest include Embedded Processor, Embedded System, Image and Video Processing, and HW/SW Co-design.

Author Articles
Efficient 2D Convolution Filters Implementations on Graphics Processing Unit Using NVIDIA CUDA

By Mouna Afif Yahia Said Mohamed Atri

DOI: https://doi.org/10.5815/ijigsp.2018.08.01, Pub. Date: 8 Aug. 2018

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.

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