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Publication
DRC 2024
Conference paper
Read Noise Analysis in Analog Conductive-Metal-Oxide/HfOxReRAM Devices
Abstract
Analog in-memory computing with resistive memory devices is a compelling alternative to conventional digital von Neumann computers [1]. Recent advancements in learning algorithms and hardware optimizations have enabled the utilization of ReRAM technology for deep neural network training purposes [2], in addition to inference. Specifically, ReRAM devices based on Conductive-Metal-Oxide (CMO)/HfOx stacks exhibit lower programming stochasticity and finer conductance updates [3], [4]. The physical explanation of the enhanced device performance is still debated. Previous reports have attributed it to multiple filament switching [5], or to oxygen content modulation in the CMO region above a single filament [6]. To maximize the potential of this technology for both inference and training applications, a comprehensive understanding of the intrinsic sources of noise is required. Prior research on nanometer-scale devices has demonstrated noise properties being dependent on device resistance, frequency, and applied voltage [7], [8]. In particular, low-frequency noise measurements offer valuable insights into the electronic transport and noise-generating mechanisms. This study investigates read noise in CMO/HfOx ReRAM devices and compares it with other systems.