Learn how to become an adopter, a contributor, and more.

RAPIDS is for everyone—users, adopters, and contributors. If you’re a data scientist, researcher, engineer, or developer using pandas, Dask, scikit-learn, or Spark on CPUs and looking for 50X end-to-end pipeline speedups at scale, look no further. Download RAPIDS and give us a run. The RAPIDS cuDF library is almost a drop-in, API-compatible, GPU-accelerated replacement for pandas and Dask (if you want to scale to multi-GPU and multi-node).

RAPIDS is also open sourced under the Apache 2.0 open-source license and is intended to be built upon and hardened in the community. While significant time and effort have been invested into making the platform usable and relevant, we need active contributors to help improve it and build its future.

Become a RAPIDS Adopter

RAPIDS features a highly GPU-optimized core dataframe and machine learning kernels that are perfect for adopters who are building high-performance databases, stream processing, machine learning applications, and more. RAPIDS handles the low-level GPU-accelerated NVIDIA® CUDA® code, so you can focus on integrating it with your solution. RAPIDS Python binding can be integrated into the solution as well. Adopters should announce their plans on our public channels. If approved, we’ll add a link to the project on the RAPIDS website.

Corporate Community Adopters

Become a RAPIDS Contributor

Contributors include anyone who helps improve the project—whether by reporting issues, adding documentation and examples, or contributing code. RAPIDS is built on open-source projects, fork our repositories from GitHub, start hacking, and open a pull request. Join us on Google Groups and let us know what you're working on.

Community Contributors