Computational Failure Analysis of Resistive RAM Used as a Synapse in a Convolutional Neural Network for Image Classification

Abstract

Various NVM technologies are being explored for neuromorphic system realization, including resistive RAM, ferroelectric RAM, phase change RAM, spin transfer torque RAM, and NAND flash. This article discusses the potential of RRAM for such applications and evaluates key performance and reliability metrics in the context of neural network image classification. The authors conclude that the accuracy-power tradeoff may be further improved using alternative material stacks and multi-layer dielectrics so as to achieve better control of the oxygen vacancy or metallic filamentation process that governs RRAM switching characteristics.