Introduction

This blog post is an attempt to simplify the process of setting up of an environment for cuML development. If your environment already has docker and you have access to building images and running containers using them, then the Dockerfile shipped with cuML repo is the easiest way to get started.

Pre-reqs

  1. Install the cuda toolkit
  2. Download the bash script from the github gist here and save it as rapids-setup.
  3. ~10-15GB of free disk-space.

Instructions

Run the bash script to install cuML and its dependencies. Recommended approach is to use anaconda. This script installs all the needed dependencies in a stand-alone folder and thus does not need root access.

bash ./rapids-setup installCuml

At the end, it prints a couple of environment variables to be set in your bash terminal. Execute them and you should now be ready to run tests and develop!