Simulation of neural networks on a massively parallel computer (DAP-510) using sparse matrix techniques

A parallel sparse matrix algorithm is proposed for the simulation of the modified Hopfield-Tank (MHT) network for solving the Traveling Salesman Problem (TSP). The MHT network using this sparse matrix algorithm has been implemented on a DAP-510, a massively parallel SIMD (single-instruction-steam, multiple-data-stream) computer consisting of 1024 processors. Problems of various sizes, ranging from eight cities up to 256 cities, have been simulated. The results show a very large speedup for the algorithm as compared with one using a standard dense matrix implementation.<
>