Integrated photonic neuromorphic computing: opportunities and challenges

Abstract

Using photons in lieu of electrons to process information has been an exciting technological prospect for decades. Optical computing is gaining renewed enthusiasm, owing to the accumulated maturity of photonic integrated circuits and the pressing need for faster processing to cope with data generated by artificial intelligence. In neuromorphic photonics, the bosonic nature of light is exploited for high-speed, densely multiplexed linear operations, whereas the superior computing modalities of biological neurons are imitated to accelerate computations. Here, we provide an overview of recent advances in integrated synaptic optical devices and on-chip photonic neural networks focusing on the location in the architecture at which the optical to electrical conversion takes place. We present challenges associated with electro-optical conversions, implementations of optical nonlinearity, amplification and processing in the time domain, and we identify promising emerging photonic neuromorphic hardware. Neuromorphic photonics is an emerging computing platform that addresses the growing computational demands of modern society. We review advances in integrated neuromorphic photonics and discuss challenges associated with electro-optical conversions, implementations of nonlinearity, amplification and processing in the time domain.