At GTC Europe in Munich Germany, NVIDIA announced RAPIDS, a suite of open-source software libraries for executing end-to-end data science and analytics pipelines entirely on GPUs.
RAPIDS aims to accelerate the entire data science pipeline including data loading, ETL, model training, and inference. This will enable more productive, interactive, and exploratory workflows.
The RAPIDS libraries are written in Python, and built on Apache Arrow. The software is being developed as open source software in partnership with enterprises globally.
RAPIDS is now available as a container image on NVIDIA GPU Cloud (NGC) and Docker Hub for use on-premises or on public cloud services such as AWS, Azure, and GCP. The RAPIDS source code is also available on github. Visit the RAPIDS site for more information.
For a walk through of how to download the RAPIDS container, run it, visit the original post on the NVIDIA Developer Blog.
Related resources
- DLI course: Accelerating End-to-End Data Science Workflows
- GTC session: Accelerate Data Science in Python with RAPIDS (Spring 2023)
- GTC session: Accelerating Your Prototypes with NVIDIA RAPIDS and Friends* (Spring 2023)
- Webinar: RAPIDS: Next-Gen Data Science with NVIDIA
- Webinar: Accelerating Data Science Workflows with RAPIDS
- Webinar: NVIDIA HPC Accelerated Compute Software for Capital Markets
About the Authors
