Parallelization of Cellular Neural Networks for Image Processing on Cluster Architectures

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.

• Type: Conference
• Year: 2003
• Where: ICPPW
• Authors: Thomas Weishäupl, Erich Schikuta
• Keywords: Cellular Neural Networks, Data Parallel Approach, Digital Gray-scale Images, Distributed And Parallel Computing, ICPPW 2003