Optoelectronic neural-network scheduler for packet switches

A novel, to our knowledge, type of packet scheduler that could significantly outperform current state-of-the-art schedulers is presented. The operation and the design of such a scheduler are discussed, and a fully operational experimental implementation is described. The scheduler uses a neural network in a winner-take-all strategy to optimize decisions on the throughput of both a crossbar and a banyan switching fabric. The problems of high interconnection density are solved by use of a free-space optical interconnect that exploits diffractive optical techniques to generate the required interconnection patterns and weights.