Large-scale neuromorphic optoelectronic computing with a reconfigurable diffractive processing unit
By Tiankuang Zhou, Xing Lin, Jiamin Wu, Yitong Chen, Hao Xie, Yipeng Li, Jingtao Fan, Huaqiang Wu, Lu Fang, Qionghai Dai. Nature Photonics, 2020
597 citations recorded by the source corpus.
There is an ever-growing demand for artificial intelligence. Optical processors, which compute with photons instead of electrons, can fundamentally accelerate the development of artificial intelligence by offering substantially improved computing performance. There has been long-term interest in optically constructing the most widely used artificial-intelligence architecture, that is, artificial neural networks, to achieve brain-inspired information processing at the speed of light. However, owing to restrictions in design flexibility and the accumulation of system errors, existing processor architectures are not reconfigurable and have limited model complexity and experimental performance. Here, we propose the reconfigurable diffractive processing unit, an optoelectronic fused computing architecture based on the diffraction of light, which can support different neural networks and achieve a high model complexity with millions of neurons. Along with the developed adaptive training approach to circumvent system errors, we achieved excellent experimental accuracies for high-speed image and video recognition over benchmark datasets and a computing performance superior to that of cutting-edge electronic computing platforms. Linear diffractive structures are by themselves passive systems but researchers here exploit the non-linearity of a photodetector to realize a reconfigurable diffractive ‘processing’ unit. High-speed image and video recognition is demonstrated.
Subfields: Artificial Intelligence, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/384c7150417d14f8e333718f595f7ebbe05df67d
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Citations in the corpus
- The physics of optical computing (2023, methodology): “[39, 70] both demonstrate the use of ∼5× 10(5) pixels to compute ∼5 × 10(5) scalar multiplications in parallel per pass of light through their optical setup.”
- Integrated electro-optics on thin-film lithium niobate (2024, unknown): “…current-controllable optical attenuators 150 , Mach-Zehnder interferometer meshes 151 , vertical-cavity surface-emitting laser arrays 152 , optical diffraction 153 , and in combination with communications 154 , further pushing the boundaries of computational accuracy, speed, and power consumption.”