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Performance of the crossbar memory array highly depends on the selector characteristics. In this paper, rigorous transient analyses are performed for a large-size crossbar memory array using novel NbO2-based selectors with a threshold switching behavior. To enable accurate and efficient array-level simulation, an electrostatic discharge-based compact model is employed to effectively describe the ${I}$ – ${V}$ characteristics of the selector. Multiple key design parameters of the selector are investigated, such as the threshold voltage, leakage current, and intrinsic switching speed. A sensitivity analysis is performed to evaluate the impact of hypothetical improvements in various selector parameters. In addition, the impacts of resistances of interconnect and memory element on the array-level access delay and energy dissipation are quantified. The results show that reducing the threshold voltage of selectors provides the most significant performance improvement, where up to 80% of the energy-delay product saving is observed if the threshold voltage is reduced by 50%. [ABSTRACT FROM AUTHOR]

Resistive switching memory (RRAM) relies on the voltage-driven formation/disruption of a conductive filament (CF) across a thin insulating layer. Due to the 1-D structure of the CF and discrete nature of defects, the set and reset states of the memory device generally display statistical variability from cycle to cycle. For projecting cell downscaling and designing improved programming operations, the variability as a function of the operation parameters, such as the maximum current in the set process and maximum voltage in the reset process, need to be evaluated and understood. This paper addresses set/reset variability, presenting statistical data for HfOx-based RRAM and introducing a physics-based Monte Carlo model for switching statistics. The model can predict the distribution of the set state as a function of the compliance (maximum) current during set and distribution of the reset state as a function of the stop (maximum) voltage during reset. Numerical modeling results are finally presented to provide additional insight into discrete fluctuation events. [ABSTRACT FROM AUTHOR]

The resistive random access memory (RRAM) crossbar array has been extensively studied as one of the most promising candidates for future high-density nonvolatile memory technology. However, some problems caused by circuit and device interaction, such as sneak leakage paths, result in limited array size and large power consumption, which degrade the array performance significantly. Thus, the analysis on circuit and device interaction issue is imperative. In this paper, a simulation method is developed to investigate the critical issues correlated with the interaction between devices and the circuit. The simulations show that a large off/on ratio of resistance states of RRAM is beneficial for large readout margin (i.e., array size). The existence of the selector connected in series with an RRAM device can eliminate the need for high Ron resistance, which is critical for the array consisted of only RRAM cells. The readout margin is more sensitive to the variation of Ron and is determined by the nonlinearity of the I–V characteristics of RRAM, whereas the nonlinear characteristics of the selector device are beneficial for a larger readout margin. An optimal design scheme for turn-on voltage and conductance of the selector is proposed based on the simulation. [ABSTRACT FROM PUBLISHER]