Incoherent photonic neuromorphic computing

Neuromorphic computing is emerging as a promising solution to address the ever-growing demand for computational power driven by artificial neural networks. We present a photonic hardware accelerator, implemented on the Silicon on Insulator platform, based on an incoherent crossbar array. We outline the system architecture and showcase live convolution processing using the photonic hardware accelerator. Furthermore, we integrate phase-change material which serves as a non-linear building block for a reconfigurable photonic neural network. We train the neural network for language classification.