A dataflow processing element for neural network simulation

Neural networks can be easily represented by macro dataflow graphs. Dataflow machines are thus suitable for simulation of these networks. In this paper, neural computing hardware considerations are first addressed. The architecture of a new argument-fetch dataflow processor dedicated to neural computing is then described. Backpropagation and Hopfield networks are transformed into dataflow graphs and simulated on the machine. Excellent performance results have been achieved.