Nanophotonics | |
Opportunities for integrated photonic neural networks | |
article | |
Pascal Stark1  Folkert Horst1  Roger Dangel1  Jonas Weiss1  Bert Jan Offrein1  | |
[1] IBM Research – Zurich | |
关键词: integrated optics; optical signal processing; photonic neural networks; photonic reservoir computing; | |
DOI : 10.1515/nanoph-2020-0297 | |
学科分类:社会科学、人文和艺术(综合) | |
来源: De Gruyter | |
【 摘 要 】
Photonics offers exciting opportunities for neuromorphic computing. This paper specifically reviews the prospects of integrated optical solutions for accelerating inference and training of artificial neural networks. Calculating the synaptic function, thereof, is computationally very expensive and does not scale well on state-of-the-art computing platforms. Analog signal processing, using linear and nonlinear properties of integrated optical devices, offers a path toward substantially improving performance and power efficiency of these artificial intelligence workloads. The ability of integrated photonics to operate at very high speeds opens opportunities for time-critical real-time applications, while chip-level integration paves the way to cost-effective manufacturing and assembly.
【 授权许可】
CC BY
【 预 览 】
Files | Size | Format | View |
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RO202107200003212ZK.pdf | 1579KB | download |