Efficient implementation of neural networks on Hypercube SIMD arrays
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Summary form only given, as follows. An efficient parallel implementation of neural networks on Hypercube SIMD arrays is presented. The authors show a mapping of a neural network having n nodes and e connections onto a Hypercube array having (n+e) processing elements such that each update step of the neural network can be performed in 8 log/sub 2/ (n+e)-3 steps by preprocessing the weight matrix. The technique is simple and efficient and can be used on current parallel machines such as the Connection Machine.<<ETX>>