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Embedded nonvolatile memory technologies, such as resistive random access memory (RRAM) and spin-transfer torque magnetic RAM (STT MRAM), are increasingly being researched for application in neuromorphic computing and hardware accelerators for artificial intelligence (AI). However, the stochastic write processes in these memory technologies affect their yield and need to be studied alongside process variations, which drastically increase the complexity of yield analysis using the Monte Carlo approach. Therefore, we propose an approach based on the Fokker&#x2013;Planck equation for modeling the stochastic write processes in STT MRAM and RRAM devices. Moreover, we show that our proposed approach can reproduce the experimental results for both STT-MRAM and RRAM devices.

A Fokker–Planck Approach for Modeling the Stochastic Phenomena in Magnetic and Resistive Random Access Memory Devices