Simon Cao
Mary Gates Research Scholar
Winter 2022
Project
Modeling and Simulation of Resistive Random Access Memories Using High-Performance Computing Tools
The resistive random-access memory (RRAM) is a promising candidate for next-generation nonvolatile memory (NVM). This technology is considered one of the most standout emerging memory technologies due to its potential high storage density, fast access speed, low power consumption, and low cost. If the technology is well-understood, it could significantly change the memory industry and trigger more advancement in computing and, thus, the scientific field. The research project’s main focus would be the theoretical modeling and simulations of the properties and behaviors of the conductive filament in the resistive random access memories using high-performance computing (HPC) resources at the University of Washington. More simulations will be done to understand further the physical principles behind two configurations: unipolar RRAM and bipolar RRAM. In unipolar RRAM, the voltage to reset and set the memory cell has the same polarity, while in bipolar RRAM, the voltage to reset and set has reverse polarity. While some of the theoretical models are still not complete, these simulations might help understand the phenomenon and shed some light on future modeling.