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https://github.com/Xilinx/logicnets
https://github.com/Xilinx/logicnets
Last synced: 6 days ago
JSON representation
- Host: GitHub
- URL: https://github.com/Xilinx/logicnets
- Owner: Xilinx
- License: apache-2.0
- Created: 2021-03-15T21:52:34.000Z (over 3 years ago)
- Default Branch: master
- Last Pushed: 2024-06-12T11:12:39.000Z (5 months ago)
- Last Synced: 2024-08-02T09:27:20.853Z (3 months ago)
- Language: Python
- Size: 96.7 KB
- Stars: 80
- Watchers: 7
- Forks: 26
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
- Authors: AUTHORS.rst
Awesome Lists containing this project
- awesome-opensource-hardware - logicnets
README
# LogicNets: Co-Designed Neural Networks and Circuits for Extreme-Throughput Applications
LogicNets is a methodology for designing, training and deploying sparse,
quantized neural networks based on hardware building blocks.
They are able to achieve extremely high throughput and low latency on Xilinx FPGAs.
## Description
This project provides a set of library components and examples to help you design,
train and deploy your own LogicNets networks.
Note, this is considered to be an \'alpha\' release: expect API changes and issues.
You can learn more about LogicNets from [this paper](https://arxiv.org/abs/2004.03021), or from the following YouTube videos:
* [10-minute presentation at DATE'21](https://www.youtube.com/watch?v=xtWySQ-ehRw)
* [20-minute presentation at FPL'20](https://www.youtube.com/watch?v=qCyK5v84jpI)
## Prerequisites
- [Python\>=3](https://www.python.org/)
- [PyTorch](https://pytorch.org/)
- [Brevitas](https://github.com/Xilinx/brevitas)
- [Verilator](https://www.veripool.org/wiki/verilator)
- [PyVerilator](https://github.com/csail-csg/pyverilator)
- [oh-my-xilinx](https://bitbucket.org/maltanar/oh-my-xilinx/)
- [Vivado Design
Suite](https://www.xilinx.com/products/design-tools/vivado.html)
## Installation
There are two main ways to install LogicNets:
1. Using [docker](https://www.docker.com/) (recommended)
2. Manually (advanced)
### Docker Installation
Follow the steps below to install LogicNets within a `docker` container:
1. Install [Vivado Design Suite](https://www.xilinx.com/products/design-tools/vivado.html)
1. Install [docker](https://www.docker.com/).
1. Clone the LogicNets repository using: `git clone [email protected]:Xilinx/logicnets.git`
1. Create an environment variable `VIVADO_SETTINGS_FILE` which points to the `settings64.sh` in your Vivado installation (e.g., `export VIVADO_SETTINGS_FILE=/path/to/Vivado/settings64.sh`)
1. (Optional): Set your `XILINXD_LICENSE_FILE` or `LM_LICENSE_FILE` variables to point to a specific license server
1. Run `./docker/run-docker.sh` from the root directory of the LogicNets repository
1. (Optional): Copy your Vivado license file over to the running docker container
You are now ready to run an example, browse to `/workspace/logicnets/examples/jet_substructure/` and start training a LogicNets network!
Note, a license is not required to run any of the provided examples.
### Manual Installation
A manual installation is not recommended for beginners.
We will only provide limited support for people wishing to pursue a manual installation.
People wanting to pursue a manual installation may want to look at the LogicNets Dockerfile,
as this contains details for a full environmental setup (including the installation of dependencies of dependencies).
The basic steps for a manual installation are as follows:
1. Install [Vivado Design Suite](https://www.xilinx.com/products/design-tools/vivado.html)
1. Install `oh-my-xilinx` by cloning this [repository](https://bitbucket.org/maltanar/oh-my-xilinx.git) and creating the environment variable `OHMYXILINX` which points to its root directory (e.g., `export OHMYXILINX=/path/to/oh-my-xilinx`)
* `oh-my-xilinx` requires `zsh`, on Ubuntu, this can be installed as follows: `sudo apt-get install zsh`
1. Install `Nitro-Parts-lib-Xilinx` by cloning this [repository](https://github.com/dirjud/Nitro-Parts-lib-Xilinx.git) and creating the environment variable `NITROPARTSLIB` which points to its root directory (e.g., `export NITROPARTSLIB=/path/to/Nitro-Parts-lib-Xilinx`)
1. Install `verilator`, on Ubuntu, this can be done as follows: `sudo apt-get install verilator build-essential`
1. Install `python3`, `pytorch`, `brevitas` and `pyverilator` using `conda` and/or `pip` or your preferred method
1. Install `logicnets` using: `pip install --upgrade git+https://github.com/Xilinx/logicnets.git`
Alternatively, instead of the last step you can clone the LogicNets repository and install as follows:
```bash
pip install .
```
Note, to install the dependencies for all the examples, you can run the following:
```bash
pip install .[example-all]
```
## Examples
Currently, we have the following examples, located in `./examples/`:
* [Jet substructure classification](examples/jet_substructure/)
* [Network intrusion detection](examples/cybersecurity/)
More examples coming soon.
## Documentation
Documentation site coming soon.
## Citation
If you find this work useful for your research, please consider citing
[our paper](https://arxiv.org/abs/2004.03021) from FPL'20 below:
```bibtex
@inproceedings{umuroglu2020logicnets,
author = {Umuroglu, Yaman and Akhauri, Yash and Fraser, Nicholas J and Blott, Michaela},
booktitle = {Proceedings of the International Conference on Field-Programmable Logic and Applications},
title = {LogicNets: Co-Designed Neural Networks and Circuits for Extreme-Throughput Applications},
year = {2020},
pages = {291-297},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
month = {sep}
}
```