Winner-Take-All Neural Network with Massively Optoelectronic Interconnections

Abstract

The increased interconnection density, bandwidth, nonlocality and fan-out-fan-in offered by optics over conventional electronic technologies make it a very attractive medium for a variety of application particularity in the field of communication system implementation for all types of computing engines is achieved. This is especially true for neural networks in which the demand for communication resources is extremely high. In this study, the implementation of a neural network that exploits an optical interconnect to perform a real task is described. A pnpn semiconductor device has been connected in parallel with a common load resistance for optical switching. When illuminated, only this device with maximum input will turn on. The voltages across the other devices drop and inhibit their switching ability. With suitable biasing, the winning device can be recall at any time. The result shows, a much faster response (<10ns) can be obtained from thyristors made of III-V compound semiconductors, because their carrier lifetime is considerably shorter than in silicon. With III-V photothyristor, it is possible to combine light emission (even lasing) and photothyristor action in the same unit.