Laser & Photonics Review • Vol 16 • No 12
High‐Throughput Multichannel Parallelized Diffraction Convolutional Neural Network Accelerator
October 2022 • Zibo Hu, Shurui Li, Russell L. T. Schwartz, Maria Solyanik‐Gorgone, Mario Miscuglio, Puneet Gupta, Volker J. Sorger
Abstract Convolutional neural networks are paramount in image and signal processing, and are responsible for the majority of image recognition power consumption today, concentrated mainly in convolution computations. With convolution operations being computationally intensive, next‐generation hardware accelerators need to offer parallelization and high efficiency. Diffractive optics offers the promise of low‐latency, highly parallel convolution operations. However, thus far parallelism is only partially harvested,…