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 [12]. 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.
Citation:
Thomas Weish?upl, Erich Schikuta, "Parallelization of Cellular Neural Networks for Image Processing on Cluster Architectures," icppw, pp.191, 2003 International Conference on Parallel Processing Workshops (ICPPW'03), 2003