Experimental Assessments of a AWGR Based Optical Switching Network for Distributed Reinforcement Learning Training

Abstract

An arrayed waveguide grating router based all-optical switching network is proposed to accelerate the communication phase of distributed reinforcement learning training. Experimental investigations validate 465ns worker-to-server latency with error-free communication at 0.9 traffic load.