Si Microring Resonator Crossbar Array for On-Chip Inference and Training of the Optical Neural Network

作者：Shuhei Ohno, Rui Tang, Kasidit Toprasertpong, Shinichi Takagi, Mitsuru Takenaka · 发表于：ACS Photonics · 年份：2022 · DOI：10.1021/acsphotonics.1c01777 · 被引用次数：156 · 研究领域：Neural Networks and Reservoir Computing、Photonic and Optical Devices、Optical Network Technologies

High Resolution Image Download MS PowerPoint Slide Deep learning has been a powerful tool in various fields. Faced with the limits of the current electronics platform, optical neural networks (ONNs) based on Si programmable photonic integrated circuits (PICs) have attracted considerable attention as a novel deep-learning scheme with optical-domain matrix-vector multiplication (MVM). However, most of the proposed Si programmable PICs for ONNs have several drawbacks, such as low scalability, high power consumption, and lack of frameworks for training. To address these issues, we have proposed a microring resonator (MRR) crossbar array as a Si programmable PIC for an ONN. In this Article, we present a prototype of a fully integrated 4 × 4 MRR crossbar array for MVM and demonstrate a simple image classification task using this chip. Moreover, we propose on-chip backpropagation using the transpose matrix operation of the MRR crossbar array, enabling the on-chip training of the ONN. The proposed ONN scheme can establish a scalable, power-efficient deep-learning accelerator for both inference and training tasks.