SimBrain – Neuromorphic Simulation Framework
Electrical Engineering
Team 35
Lucien Roberson, Chiraz Barhoumi, Sabryna Henze, Bryan Matos, Dennis Hoang
Summary
Compares traditional and spiking neural networks under realistic hardware conditions. Using IBM’s AIHWKIT simulator, the project measures how analog device imperfections such as RRAM read noise and conductance drift affect model performance. The goal is to quantify the real-world tradeoffs of running neural networks on energy-efficient neuromorphic hardware using a controlled comparison framework.
Demo Day Zoom link: https://asu.zoom.us/j/2984187484