An OpenCL-based parallel acceleration of aSobel edge detection algorithm Using IntelFPGA technology

Authors

  • Abedalmuhdi Almomany Department of Computer Engineering, Yarmouk University, Irbid-Jordan https://orcid.org/0000-0002-5922-6106
  • Ahmad Al-Omari Department of Biomedical systems and Bioinformatics Engineering, Yarmouk University, Irbid, Jordan
  • Amin Jarrah Department of Computer Engineering, Yarmouk University, Irbid, Jordan
  • Mohammed Tawalbeh Information Technology & Communications Center, Jordan University of Science and Technology, Irbid, Jordan
  • Amin Alqudah Department of Computer Engineering, Yarmouk University, Irbid, Jordan

DOI:

https://doi.org/10.18489/sacj.v32i1.749

Keywords:

FPGA, Reconfigurable computing, Parallel processing, Edge detection, OpenCL, Image processing, Hardware solution

Abstract

This paper examines the feasibility of using commercial out-of-the-box Reconfigurable Field Programmable Gate Array (FPGA) technology and the OpenCL framework to create efficient Sobel edge-detection implementation, which is considered a fundamental part in the field of image and video processing. The revised proposed approach was created at a high level of abstraction and executed on high commodity Intel FPGA platform. This was performed in a manner that was designed to allow the high-level compiler/synthesis tool to manipulate a task a parallelism model. The most promising FPGA and the naive implementations were compared to their single-core CPU software equivalents while manipulating local-memory, pipelining, loop unrolling, vectorization, internal channels mechanisms and memory coalescing to provide a much more effective hardware design. The run-time and the power consumption attributes were estimated for each implementation. The proposed FPGA based implementations were found to have significantly better runtime and power consumption with approximately up to 37 folds of improvement in the whole execution/transfer time, and up to 53 folds of improvement in energy consumption when compared to a specific single-core CPU based implementation.

Author Biography

Abedalmuhdi Almomany, Department of Computer Engineering, Yarmouk University, Irbid-Jordan

PH.D Computer Engineering

Published

2020-07-22

Issue

Section

Research Papers (general)