A Simulation Framework for Memristive Deep Learning Systems
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Updated
May 13, 2024 - Python
A Simulation Framework for Memristive Deep Learning Systems
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
A well-posed RRAM SPICE model implemented in Verilog-A, based on Stanford/ASU filamentary model, using code developed at UC Berkeley
Series of ReRAM characterization modules compatible with Keithley Semiconductor Characterization Systemsinstruments
Code and repository for RRAM RADAR programming method: https://doi.org/10.1109/TED.2021.3097975
Long Short-Term Memory Implementation Exploiting Passive RRAM Crossbar Array
NI RRAM programming in Python
Scripts to model functional experimental or other phenomena, such as neuronal/device spiking, or tip-sample interactions.
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