Title :
Parallelization of cellular neural networks for image processing on cluster architectures
Author :
Weishäupl, Thomas ; Schikuta, Erich
Author_Institution :
Dept. of Comput. Sci. & Bus. Informatics, Vienna Univ., Austria
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 (single-program multiple-data) model and is based on the structural data parallel approach (Schikuta et al, 1996). 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.
Keywords :
cellular neural nets; data models; image processing; message passing; parallel programming; workstation clusters; MPI-based program; SPMD model; cellular neural networks; cluster architectures; digital gray-scale images; image processing; parallelization; single-program multiple-data; structural data parallel approach; Algorithm design and analysis; Cellular neural networks; Computer architecture; Image analysis; Image motion analysis; Image processing; Neural networks; Performance analysis; Signal analysis; Signal processing algorithms;
Conference_Titel :
Parallel Processing Workshops, 2003. Proceedings. 2003 International Conference on
Print_ISBN :
0-7695-2018-9
DOI :
10.1109/ICPPW.2003.1240370