Reliability of CMOS Integrated Memristive HfO2 Arrays with Respect to Neuromorphic Computing

Abstract

CMOS integrated 4kbit 1T-1R memristive devices were examined in terms of device-to-device and pulse number dependent variability for the use in neuromorphic systems. Based on the variability of polycrystalline HfO2 based Resistive Random Access Memory (RRAM)devices, reliability issues for the implementation of stochastic learning rules are investigated. The switching variability of the memristive devices is demonstrated as a function of the voltage amplitude and pulse number. We demonstrate that the switching probability of the filamentary RRAM devices can emulate analog synaptic functionality. Finally, the endurance and retention characteristics of the memristive devices are analyzed to evaluate the performance and reliability of the cells used for neuromorphic computing.