Perspective: Uniform switching of artificial synapses for large-scale neuromorphic arrays

Abstract

Resistive random-Access memories are promising analog synaptic devices for efficient bio-inspired neuromorphic computing arrays. Here we first describe working principles for phase-change random-Access memory, oxide random-Access memory, and conductive-bridging random-Access memory for artificial synapses. These devices could allow for dense and efficient storage of analog synapse connections between CMOS neuron circuits. We also discuss challenges and opportunities for analog synaptic devices toward the goal of realizing passive neuromorphic computing arrays. Finally, we focus on reducing spatial and temporal variations, which is critical to experimentally realize powerful and efficient neuromorphic computing systems.