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IEEE Microwave Photonics Conf 2020 perceptron ieee tech.pdf (672.79 kB)

Kerr microcombs based on soliton crystals for high-speed, scalable optical neural networks

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posted on 11.11.2020, 15:34 by David Moss
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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Email Address of Submitting Author

dmoss@swin.edu.au

ORCID of Submitting Author

0000-0001-5195-1744

Submitting Author's Institution

swinburne university of technology

Submitting Author's Country

Australia

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