marcelwa/ls4ai
Hack4Her: Logic Synthesis for AI
This project helps embedded systems engineers and hardware designers understand how to convert neural network models into hardware descriptions. It takes a trained neural network model as input and generates Verilog code, which can then be simulated to verify its behavior on hardware. The ideal user is someone involved in designing custom hardware for AI applications.
No commits in the last 6 months.
Use this if you need to translate an AI model into a format suitable for hardware implementation and want to simulate its behavior.
Not ideal if you are looking for a high-level AI development framework or do not work with hardware description languages like Verilog.
Stars
10
Forks
—
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jun 13, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/marcelwa/ls4ai"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
fastmachinelearning/hls4ml
Machine learning on FPGAs using HLS
alibaba/TinyNeuralNetwork
TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework.
KULeuven-MICAS/zigzag
HW Architecture-Mapping Design Space Exploration Framework for Deep Learning Accelerators
fastmachinelearning/hls4ml-tutorial
Tutorial notebooks for hls4ml
doonny/PipeCNN
An OpenCL-based FPGA Accelerator for Convolutional Neural Networks