Evaluation of Image Pixels Similarity Measurement Algorithm Accelerated on GPU with OpenACC

Authors

  • Ibrahim Mundher Abdulqader Centre for Telecommunication Research & Innovation (CeTRI), Faculty of Electronic & Computer Engineering, Universiti Teknikal Malaysia Melaka
  • Kim Chuan Lim Centre for Telecommunication Research & Innovation (CeTRI), Faculty of Electronic & Computer Engineering, Universiti Teknikal Malaysia Melaka

Keywords:

chi-square, OpenACC, pixel similarity measurement, tile and collapse clauses,

Abstract

OpenACC is a directive based parallel programming library that allows for the easy acceleration of existing C, C++ and Fortran based applications with minimal code modifications. By annotating the bottleneck causing a section of the code with OpenACC directives, the acceleration of the code can be simplified, leading for high portability of performance across different target Graphic Processing Units (GPUs). In this work, the portability of an implemented parallelizable chi-square based pixel similarity measurement algorithm has been evaluated on two consumer and professional grade GPUs. To our best knowledge, this is the first performance evaluation report that utilizes the OpenACC optimization clauses (collapse and tile) on different GPUs to process a less workload (low resolution image of 581x429 pixels) and a heavy workload (high resolution image of 4500 x 3500 pixels) to demonstrate the effectiveness and high portability of OpenACC.

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Published

2018-07-04

How to Cite

Abdulqader, I. M., & Lim, K. C. (2018). Evaluation of Image Pixels Similarity Measurement Algorithm Accelerated on GPU with OpenACC. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(2-6), 167–172. Retrieved from https://jtec.utem.edu.my/jtec/article/view/4390

Issue

Vol. 10 No. 2-6: Embracing The 4th Industrial Revolution: Innovation in Telecommunication, Electronic & Computer Engineering II

Section

Articles

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