RAPIDS is a collection of open source libraries from NVIDIA that provides machine learning and deep learning toolsets optimized to run on GPU. The goal of RAPIDS is to make it easy to harness GPU parallelism for accelerated processing and training tasks.
RAPIDS projects include the following:
For the full list of RAPIDS projects, check out RAPIDS on GitHub.
RAPIDS has a number of advantages:
Getting started with RAPIDS on Paperspace is easy. When you create a new notebook you should see the NVIDIA RAPIDS tile in the Recommended Runtimes. After you select the RAPIDS runtime, select a GPU instance and start your notebook!
By default this tile will pull the workspace located here: https://github.com/gradient-ai/RAPIDS.git.
If you would like to pull a different workspace into the RAPIDS container, we invite you to toggle the Advanced Options and enter an alternate workspace.
Once you've started up the notebook, you should see a number of examples waiting for you to try!
If you'd like to use a full version of JupyterLab, you can always swap over to a full JupyterLab instance by toggling the JupyterLab button in the sidebar.
You should now be up and running with NVIDIA RAPIDS on Paperspace Gradient.