Simulation and Modeling of MRAM for On-Chip Learning

Electrical Engineering

Team 12

Selin Bakkaloglu, Jonathan Rossman, Caidyn Spickler, Elliot Word

Summary

Synthesizing multiple forms of Magnetic Random Access Memory (MRAM) devices using Object Oriented Micromagnetic Framework (OOMMF) and HSPICE to create an optimal form of memory for on-chip AI computations. Our project models, simulates, and analyzes STT, SOT, and SAS MRAM devices to evaluate switching behavior, energy efficiency, and stability.

Video

Research poster

Sponsor

Advisor

Portrait of Deliang Fan

Deliang Fan

Associate Professor

School of Electrical, Computer and Energy Engineering

[email protected]