A Prototype 3D Optically Interconnected Neural Network

GöKçe Yayla, Sadik C. Esener, Ashok V. Krishnamoorthy, Gary C. Marsden

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


We report the implementation of a prototype three-dimensional (3D) optoelectronic neural network that combines free-space optical interconnects with silicon-VLSI-based optoelectronic circuits. The prototype system consists of a 16-node input, 4-neuron hidden, and a single-neuron output layer, where the denser input-to-hidden-layer connections are optical. The input layer uses PLZT light modulators to generate optical outputs which are distributed over an optoelectronic neural network chip through space-invariant holographic optical interconnects. Optical interconnections provide negligible fan-out delay and allow compact, purely on-chip electronic H-tree type fan-in structure. The small prototype system achieves a measured 8-bit electronic fan-in precision and a calculated maximum speed of 640 million interconnections per second. The system was tested using synaptic weights learned off system and was shown to distinguish any vertical line from any horizontal one in an image of 4/spl times/4 pixels. New, more efficient light detector and small-area analog synapse circuits and denser optoelectronic neuron layouts are proposed to scale up the system. A high-speed, feed-forward optoelectronic synapse implementation density of up to 10/sup 4//cm/sup 2/ seems feasible using new synapse design. A scaling analysis of the system shows that the optically interconnected neural network implementation can provide higher fan-in speed and lower power consumption characteristics than a purely electronic, crossbar-based neural network implementation.

Original languageEnglish (US)
Pages (from-to)1749-1762
Number of pages14
JournalProceedings of the IEEE
Issue number11
StatePublished - Nov 1994
Externally publishedYes

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering


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