Opt Lett. 2022 Nov 15;47(22):5977-5980. doi: 10.1364/OL.477624.
We propose and experimentally demonstrate a simple and energy-efficient photonic convolutional accelerator based on a monolithically integrated multi-wavelength distributed feedback semiconductor laser using the superimposed sampled Bragg grating structure. The photonic convolutional accelerator operates at 44.48 GOPS for one 2 × 2 kernel with a convolutional window vertical sliding stride of 2 and generates 100 images of real-time recognition. Furthermore, a real-time recognition task on the MNIST database of handwritten digits with a prediction accuracy of 84% is achieved. This work provides a compact and low-cost way to realize photonic convolutional neural networks.
我们提出并实验演示了一种基于采用叠加取样布拉格光栅结构的单片集成多波长分布式反馈半导体激光器的简单且节能的光子卷积加速器。该光子卷积加速器在卷积窗口垂直滑动步长为 2 时，针对一个 2×2 核的操作速度为 44.48GOPS，可实时生成 100 张识别图像。此外，还实现了手写数字 MNIST 数据库的实时识别任务，预测准确率达到 84%。这项工作提供了一种紧凑且低成本的方法来实现光子卷积神经网络。
