Fast and stable switching between states is one of the key factors for the success resistive random access memory (RRAM) development. In an array, wide reset efficiency variation in RRAM cells is found to link to the characteristics of its low frequency noise (LFN) in bit-cell current. Through Monte Carlo simulation on randomly placing conductive filaments (CF), LFN characteristics correspond to the densities of the CF in the RRAM film. Further correlations between LFN features and the reset efficiency are found. In addition, CF topography are found to change after long term cycling tests. A trimming process is proposed to minimize the impacts of stochastic CF generation, leading to increase reset speed.INDEX TERMS Variability, resistive random access memory, low frequency noise, Monte Carlo simulation, conductive filament.