Novel synaptic memory device for neuromorphic computing

Abstract

This report discusses the electrical characteristics of two-terminal synaptic memory devices capable of demonstrating an analog change in conductance in response to the varying amplitude and pulse-width of the applied signal. The devices are based on Mn doped HfO2 material. The mechanism behind reconfiguration was studied and a unified model is presented to explain the underlying device physics. The model was then utilized to show the application of these devices in speech recognition. A comparison between a 20[emsp14]nm [times] 20[emsp14]nm sized synaptic memory device with that of a state-of-the-art VLSI SRAM synapse showed ~10[times] reduction in area and >106 times reduction in the power consumption per learning cycle.