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

TL;DR

This paper introduces a Fokker-Planck equation-based model to analyze stochastic write processes in RRAM and STT-MRAM devices, providing a more efficient alternative to Monte Carlo simulations for yield analysis in neuromorphic computing applications.

Contribution

The paper presents a novel Fokker-Planck approach to model stochastic phenomena in RRAM and STT-MRAM, capturing experimental results and improving analysis efficiency.

Findings

Successfully reproduces experimental results for RRAM and STT-MRAM.

Offers a computationally efficient alternative to Monte Carlo simulations.

Enhances understanding of stochastic write processes in non-volatile memories.

Abstract

Embedded non-volatile 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 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-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.