fastmachinelearning/hls4ml
Machine learning on FPGAs using HLS
This project helps domain experts in fields like high-energy physics, quantum computing, or aerospace who need to process real-time data with extremely low latency. It takes machine learning models built with common frameworks and converts them into specialized firmware for FPGAs. The output is a highly optimized hardware implementation of your model, enabling rapid decision-making directly on hardware.
1,849 stars. Actively maintained with 9 commits in the last 30 days.
Use this if you need to deploy machine learning models for ultra-low-latency inference in specialized hardware environments like control systems or real-time monitoring.
Not ideal if your application does not require FPGA deployment or extreme real-time performance, or if you are focused on model training rather than inference.
Stars
1,849
Forks
530
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 12, 2026
Commits (30d)
9
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