OxRRAM-Based Analog in-Memory Computing for Deep Neural Network Inference: A Conductance Variability Study

Analog in-memory compute (AiMC) is a promising approach to efficiently process deep neural networks (DNNs). Due to its small size and nonvolatility, oxide resistive random access memory (OxRRAM) is being considered as a memory device to map neural network weights in AiMC systems. However, OxRRAM conductance variability can have a severe impact on neural network accuracy. This variability depends o...