Hawk from Scratch

(Work in progress) Installing Hawk from Scratch

This guide will show you how to set up a basic system for testing and exploring Hawk, a live learning framework for discovering rare events. We will assume your hardware setup includes an NVIDIA GPU, although it may be possible to run CPU-only or with AMD mRoc. The current test rig we use at CMU is based around Intel Xeon CPUs with 12 cores @ 3.6 GHz, 32GB RAM, and a GTX1060 or better GPU.

We will be installing Ubuntu Server 20.04 (desktop might work but we have not tested it), the NVIDIA driver for your GPU, and various utilities needed to build and run Hawk. If you are running this on a laptop, you might want to use the regular nvidia-driver-535 instead.

# On a freshly installed Ubuntu Server 20.04 system
sudo apt install nvidia-driver-535-server nvidia-cuda-toolkit

If the installation seems to have worked, reboot your system and then run nvidia-smi to make sure we can see and communicate with the loaded kernel driver and that it has identified your GPU(s) correctly.

Now we can install some minimal dependencies we need to download the Hawk source and get a development environment configured.

sudo apt install git python3-pip python3-venv
pip install --user pipx
~/.local/bin/pipx ensurepath
. ~/.bashrc
pipx install poetry

Once this is done you should be able to obtain Hawk by cloning our GitHub repository:

git clone https://github.com/cmusatyalab/hawk.git
cd hawk/
poetry install -E scout -E home

Running the Hawk scout

At this point, Hawk has been installed and you can open a new terminal window and start a scout. Once started it will wait for a hawk_home instance to send it a new mission configuration.

cd ~/hawk/
poetry run hawk_scout