Direct inference with hls4ml
hls4ml is a Python package developed by the Fast Machine Learning Lab. It's primary purpose is to create firmware implementations of machine learning (ML) models to be run on FPGAs. The package interfaces with a high-level synthesis (HLS) backend (i.e. Xilinx Vivado HLS) to transpile the ML model into hardware description language (HDL). The primary hls4ml documentation, including API reference pages, is located here.
The main hls4ml tutorial code is kept on GitHub. Users are welcome to walk through the notebooks at their own pace. There is also a set of slides linked to the README.
That said, there have been several cases where the hls4ml developers have given live demonstrations and tutorials. Below is a non-exhaustive list of tutorials given in the last few years (newest on top).
| Workshop/Conference | Date | Links |
| 23rd Virtual IEEE Real Time Conference | August 03, 2022 | Indico |
| 2022 CMS ML Town Hall | July 22, 2022 | Contribution Link |
| a3d3 hls4ml @ Snowmass CSS 2022: Tutorial | July 21, 2022 | Slides, Recording, JupyterHub |
| Fast Machine Learning for Science Workshop | December 3, 2020 | Indico, Slides, GitHub, Interactive Notebooks |
| hls4ml @ UZH ML Workshop | November 17, 2020 | Indico, Slides |
| ICCAD 2020 | November 5, 2020 | https://events-siteplex.confcats.io/iccad2022/wp-content/uploads/sites/72/2021/12/2020_ICCAD_ConferenceProgram.pdf, GitHub |
| 4th IML Workshop | October 19, 2020 | Indico, Slides, Instructions, Notebooks, Recording |
| 22nd Virtual IEEE Real Time Conference | October 15, 2020 | Indico, Slides, Notebooks |
| 30th International Conference on Field-Programmable Logic and Applications | September 4, 2020 | Program |
| hls4ml tutorial @ CERN | June 3, 2020 | Indico, Slides, Notebooks |
| Fast Machine Learning | September 12, 2019 | Indico |
| 1st Real Time Analysis Workshop, Université Paris-Saclay | July 16, 2019 | Indico, Slides, Autoencoder Tutorial |