Parallel self-organization map using multiple stimuli

We propose a parallel SOM algorithm to speedup the fundamental SOM calculation using parallel computer environments. In the parallel SOM algorithm synaptic weights are updated in parallel corresponding to multiple stimuli (inputs). Parallelism in the proposed algorithm is based on the analogy of the biological neural networks in which neurons respond to the stimuli in parallel. Performance is evaluated by implementing the newly developed performance simulator in a personal computer-cluster under the message passing interface library (MPI) environment. A speedup ratio of about 5.0 is achieved with 8 processors (personal computers) when the width of the neighborhood function is less than 5% of the total number of neurons in the SOM network