Design of an integrated photonic convolution accelerator based on a cascaded array of microring resonators

Convolutional neural networks (CNNs) are a type of artificial neural networks (ANNs) that use the method of convoluting images with filter-kernels for object recognition and classification. More than 80% of the computation in CNNs is convolution which is rather difficult for traditional serial electronic computing architectures. To tackle this issue, photonic computation has harvested great attention due to its wide bandwidth and intrinsic parallelism. Here we propose an integrated photonic chip in order to accelerate convolution operations. The photonic chip consists of 144 microring resonators which can be programmed to perform arbitrary 9×16 matrix. The 9×16 matrix can be divided to 16 3×3 convolution kernels. Thus, the proposed chip is capable of processing 16 different 3×3 convolution operations simultaneously. The theory simulation results of the device design are demonstrated.