os-hxfan/BayesNN_FPGA
FPGA-based hardware acceleration for dropout-based Bayesian Neural Networks.
This project offers a way to significantly speed up complex machine learning models called Bayesian Neural Networks, especially those used for making predictions with uncertainty. It takes your existing Bayesian Neural Network models and processes them using specialized hardware (FPGAs) to deliver faster results. This tool is for machine learning engineers or researchers who need to deploy high-performance, uncertainty-aware AI models in real-time or resource-constrained environments.
No commits in the last 6 months.
Use this if you are a machine learning engineer or researcher looking to accelerate the inference speed of your Bayesian Neural Networks on FPGA hardware, particularly for applications requiring efficient uncertainty quantification.
Not ideal if you are looking for a plug-and-play solution for general machine learning acceleration without specific interest in Bayesian Neural Networks or FPGA deployment.
Stars
27
Forks
2
Language
Python
License
MIT
Category
Last pushed
Aug 15, 2023
Commits (30d)
0
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