Parallelization of Cellular Neural Networks for Image Processing on Cluster Architectures
Abstract
In this paper a simple but effective approach for parallelization of cellular neural networks for image processing is developed. Digital gray-scale images were used to evaluate the program. The approach uses the SPMD model and is based on the structural data parallel approach. The process of parallelizing the algorithm employs HPF to generate an MPI-based program and the performance behavior was analyzed on two different cluster architectures.
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- Weishäupl, Thomas
- Schikuta, Erich
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Copyright Holders
- © 2003 IEEE <a href="http://dx.doi.org/10.1109/ICPPW.2003.1240370">Abstract</a>
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Shortfacts
Category |
Paper in Conference Proceedings or in Workshop Proceedings |
Event Title |
Workshop on High Performance Scientific and Engineering Computing with Applications (HPSECA-03) in conjunction with International Conference on Parallel Processing (ICPP-03) |
Divisions |
Workflow Systems and Technology |
Event Location |
Kaohsiung, Taiwan, ROC |
Event Type |
Conference |
Event Dates |
2003-10-06 |
Series Name |
Proceedings of the ICPP 2003 workshops |
Publisher |
IEEE Computer Society Press |
Date |
October 2003 |
Official URL |
http://www.pri.univie.ac.at/Publications/2003/Weis... |
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