Impact of Read Disturb on Multilevel RRAM based Inference Engine: Experiments and Model Prediction
Wonbo Shim, Yandong Luo, Jae-sun Seo, Shimeng Yu
Abstract
Different from the multilevel cell (MLC) memory where the crossover between tail bits matters, any drift of the conductance of the synaptic device induced by read disturb may aggregate, as the analog current is summed up along the column. In this work, we experimentally measured the conductance drift on 2-bit HfO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> RRAM array based on 1-transsitor-1-resistor (1T1R) test vehicle. The drift behavior of different states is modeled by vertical and lateral filament growth and saturation. The device model is incorporated into a VGG-like convolutional neural network algorithm for CIFAR-10 dataset. Read voltage should be minimized to 0.3V or below to maintain the inference accuracy.