Get Started

The RAPIDS data science framework is a collection of libraries for running end-to-end data science pipelines completely on the GPU. The interaction is designed to have a familiar look and feel to working in Python, but utilizes optimized NVIDIA® CUDA® primitives and high-bandwidth GPU memory under the hood. Below are some links to help getting started with the RAPIDS libraries.

Installation Tool

RAPIDS.AI

Contains a configurator tool to help you choose between the various methods for installing RAPIDS.

10 Minutes to cuDF and Dask-cuDF

cuDF Post

Modeled after 10 Minutes to Pandas, this is a short introduction to cuDF that is geared mainly for new users.

RAPIDS Spark Examples

GitHub Repo

A repo for Spark related utilities and examples using the RAPIDS Accelerator, including ETL, ML/DL, etc.

Our Collection of Example Notebooks

GitHub Repo

A GitHub repository with our introductory examples of XGBoost, cuML demos, cuGraph demos, and more.

Our Extended Collection of Example Notebooks

GitHub Repo

A GitHub repository with examples of XGBoost, cuML demos, cuGraph demos, and more.