Si microring resonator crossbar arrays for deep learning accelerator

Abstract

Abstract We propose Si microring resonator (MRR) crossbar arrays as a programmable nanophotonoic processor (PNP) for a deep learning accelerator. The proposed MRR crossbar array can perform multiply-accumulate (MAC) operation in an optical domain. We numerically reveal that an optical neural network (ONN) based on the proposed MRR crossbar arrays can be used for the pattern recognition task with a similar performance to that of an ONN based on cascaded Mach–Zehnder interferometers. We predict that the power consumption can be reduced by approximately tenfold. The small area of the MRR also contributes to the reduction in its chip size by a factor of 36. The fabricated test devices consisting of Si MRRs with phase shifters exhibited no significant crosstalk between neighboring MRRs and showed the feasibility of MAC operation. Photonic integrated circuit using the proposed MRR crossbar arrays is promising for large-scale and low-power PNP for deep learning.