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arXiv · 2101.12356

Soliton crystal Kerr microcombs for high-speed, scalable optical neural networks at 10 GigaOPs/s

Xingyuan Xu·Mengxi Tan·David J. Moss
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Abstract

Optical artificial neural networks (ONNs) have significant potential for ultra-high computing speed and energy efficiency. We report a new approach to ONNs based on integrated Kerr micro-combs that is programmable, highly scalable and capable of reaching ultra-high speeds, demonstrating the building block of the ONN, a single neuron perceptron, by mapping synapses onto 49 wavelengths to achieve a single-unit throughput of 11.9 Giga-OPS at 8 bits per OP, or 95.2 Gbps. We test the perceptron on handwritten-digit recognition and cancer-cell detection, achieving over 90% and 85% accuracy, respectively. By scaling the perceptron to a deep learning network using off the shelf telecom technology we can achieve high throughput operation for matrix multiplication for real-time massive data processing.

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Xingyuan Xu, Mengxi Tan, David J. Moss. 2021-01-29. Soliton crystal Kerr microcombs for high-speed, scalable optical neural networks at 10 GigaOPs/s. https://doi.org/10.23919/mwp48676.2020.9314409

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