DocumentCode :
3325830
Title :
Parallelizing edge drawing algorithm on CUDA
Author :
Ozsen, Ozgur ; Topal, Cihan ; Akinlar, Cuneyt
fYear :
2012
fDate :
12-14 Jan. 2012
Firstpage :
79
Lastpage :
82
Abstract :
Parallel computing methods are very useful in speeding up algorithms that can be divided into independent subtasks. Traditional multi-processor architectures have limited use due to their high cost and difficulties of their use. Recently, Graphics Processor Units (GPUs) has opened up a new era for general purpose parallel computation. Among many GPU programming frameworks, Compute Unified Device Architecture (CUDA) seems to be the most widely used GPU architecture due to its low cost and ease of use. In this paper, we show how to implement our recently proposed novel edge segment detector, the Edge Drawing (ED) algorithm, in CUDA, and present performance studies demonstrating the performance gams in the CUDA architecture compared to a uniprocessor CPU implementation. The results show that a CUDA implementation improves the running time of ED by up to 12× and ED runs at an amazing blazing speed of about 1 ms on a 512×512 image. ED is run on different CUDA cards and the performance results are presented.
Keywords :
graphics processing units; image processing; parallel architectures; CUDA; GPU architecture; GPU programming frameworks; compute unified device architecture; edge drawing algorithm; general purpose parallel computation; graphics processor units; multiprocessor architectures; parallel computing; Decision support systems; CUDA; GPU programming; Parallel image processing; edge detection; real time;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Emerging Signal Processing Applications (ESPA), 2012 IEEE International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4673-0899-1
Type :
conf
DOI :
10.1109/ESPA.2012.6152450
Filename :
6152450
Link To Document :
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