rapidsai/rapidsai-cloud-ml repository overview

⁠RAPIDS Cloud Machine Learning

RAPIDS is a suite of open-source libraries that bring GPU acceleration to data science pipelines. Users building cloud-based machine learning experiments can take advantage of this acceleration throughout their workloads to build models faster, cheaper, and more easily on the cloud platform of their choice. The cloud-ml-examples⁠ repository provides example notebooks and "getting started" code samples and this Docker repository provides a ready to run Docker container with RAPIDS and libraries/SDKs for AWS SageMaker, Azure ML and Google AI Platform.

NOTE: Review our prerequisites⁠ section to ensure your system meets the minimum requirements for RAPIDS.

⁠Current Version - RAPIDS v22.10

The RAPIDS images are based on nvidia/cuda⁠, and are intended to be drop-in replacements for the corresponding CUDA images in order to make it easy to add RAPIDS libraries while maintaining support for existing CUDA applications.

⁠Image Tag Naming Scheme

The tag naming scheme for RAPIDS images incorporates key platform details into the tag as shown below:

22.06-cuda11.5-base-ubuntu20.04-py3.9
 ^       ^    ^        ^         ^
 |       |    type     |         python version
 |       |             |
 |       cuda version  |
 |                     |
 RAPIDS version        linux version

⁠Prerequisites

• NVIDIA Pascal™ GPU architecture or better
• CUDA 11.0 - 11.5⁠ with a compatible NVIDIA driver
• Ubuntu 20.04 or CentOS 7
• Docker CE v18+
• nvidia-container-toolkit⁠

⁠More Information

Check out the RAPIDS HPO⁠ webpage for video tutorials and blog posts.

Please submit issues with the container to this GitHub repository: https://github.com/rapidsai/docker⁠

For issues with cloud-ml-examples file an issue in: https://github.com/rapidsai/cloud-ml-examples⁠