SBIR/STTR Award attributes
Long term space missions can greatly benefit from neuromorphic processors enabling in-situ learning in the extreme environments in space. Photonic Tensor Cores provide extremely energy efficient and robust hardware for the computations required for neuromorphic processing. However, current technologies require the significant expenditure of energy, through resistive heaters or current injection diodes, to maintain the state of the neural network for inference. Here we describe a photonic accelerator technology that utilizes the learning from FLASH memory devices to enable non-volatile, 0 energy state retention for neuromorphic processors, enabling the possibility of reaching incredible inference efficiency of 1 femto-joule per operation ndash; a 3 order of magnitude improvement over todays GPUs.
