Optically Connected Multiprocessors For Simulating Artificial Neural Networks

Joydeep Ghosh; Kai Hwang

doi:10.1117/12.944094

3 May 1988 Optically Connected Multiprocessors For Simulating Artificial Neural Networks

Joydeep Ghosh, Kai Hwang

Proceedings Volume 0882, Neural Network Models for Optical Computing; (1988) https://doi.org/10.1117/12.944094
Event: 1988 Los Angeles Symposium: O-E/LASE '88, 1988, Los Angeles, CA, United States

Abstract

This paper investigates the architectural requirements in simulating large neural networks using a highly parallel multiprocessor with distributed memory and optical interconnects. First, we model the structure of a neural network and the functional behavior of individual cells. These models are used to estimate the volume of messages that need to be exchanged among physical processors to simulate the weighted connections of the neural network. The distributed processor/memory organization is tailored to an electronic implementation for greater versatility and flexibility. Optical interconnects are used to satisfy the interprocessor communication bandwidth demands. The hybrid implementation attempts to balance the processing, memory and bandwidth demands in simulating asynchronous, value-passing models for cooperative parallel computation with self-learning capabilities.

Citation Download Citation

Joydeep Ghosh and Kai Hwang "Optically Connected Multiprocessors For Simulating Artificial Neural Networks", Proc. SPIE 0882, Neural Network Models for Optical Computing, (3 May 1988); https://doi.org/10.1117/12.944094

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