Neural network design of a banyan network controller

The algorithm for choosing nonblocking sets of data cells from the queues can significantly affect the throughput and queuing behavior. The authors present an algorithm that is shown to have maximum throughput. This algorithm is reduced on a banyan network to a constraint satisfaction problem by using an equivalence approach. To gain the required computational speed, the massive parallelism of neural networks is used. A neural network design using multiple overlapping winner-take-all circuits is defined. This is shown to be stable and to result only in nonblocking sets of data cells. An efficient interface between the neural network and the queue is also defined. The performance of the banyan with a neural network controller is compared to a noninternal-blocking switch with various controllers. The banyan is within a factor of two of the nonblocking switch.<
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