This repository includes the Resistive Random Access Memory (RRAM) Compiler which is designed in the context of the research project of Dimitris Antoniadis (PG Taught Student) at Imperial College London

RRAM resistive switching behavior evaluation and prediction, based on fabrication conditions. Applied Machine learning\Deep learning models to predict SET voltage distribution in Honey-based RRAM devices. Simulating the basic operations of RRAM crossbars in image classification tasks, investigating the robustness of in situ vs. ex situ training.