Total Ionizing Dose Effects on Multistate HfOₓ-Based RRAM Synaptic Array

Abstract

Emerging nonvolatile memories (eNVMs) have demonstrated satisfactory accuracy on various applications in deep learning. Characterized by high density and low leakage power consumption, resistive random access memory (RRAM) becomes very attractive in synaptic devices for deep neural networks (DNNs). RRAM-based synaptic devices include both analog and discrete versions. Unlike analog RRAM synapses which suffer from nonlinearity, discrete but multistate RRAM synapses are better suited for neural network hardware implementation. In this article, the multistate operation in RRAM arrays has been proposed as a synaptic device for DNN inference. Four-state conductance has been achieved in HfO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> -based RRAM synaptic arrays. The impact of total ionizing dose (TID) on the multistate behavior of HfO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> -based RRAM is investigated by irradiating a one-transistor-one-resistor (1T1R) 64-kb array with CMOS peripheral decoding circuitry fabricated at the 90-nm technology node with Co-60 gamma rays ( <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">60</sup> Co γ-ray irradiation).