Parallelizing the Self-Organizing Feature Map on multiprocessor systems

Authors:
Chwan-Hwa Wu;Russel E. Hodges;Chia-Jiu Wang
Affiliations:
-;-;-
Venue:
Parallel Computing
Year:
1991

Citing 1
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Abstract

The Self-Organizing Feature Map (SOFM) proposed by Kohonen is a widely used vector quantization algorithm. A drawback of SOFM is the increase of computation time with an increase in the number of neurons. However, the inherent parallelism of SOFM allows parallel processing to speed up the computation. Parallel algorithms for implementing the Kohonen SOFM are presented in this paper. We have implemented the algorithms on a linear chain and a two-dimensional mesh of transputers. Significant speedup has been achieved. In addition, models to describe the performance of the algorithms are also presented. The performance of massively parallel systems is predicted from the models.