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RAPIDS Cloud Machine Learning

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Description

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.

Publisher

NVIDIA

Latest Tag

21.06-cuda11.0-base-ubuntu18.04

Modified

November 8, 2022

Compressed Size

4.27 GB

Multinode Support

No

Multi-Arch Support

No

21.06-cuda11.0-base-ubuntu18.04 (Latest) Scan Results

Linux / amd64

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 v0.19

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:

0.19-cuda11.0-base-ubuntu18.04-py3.8
 ^       ^    ^        ^         ^
 |       |    type     |         python version
 |       |             |
 |       cuda version  |
 |                     |
 RAPIDS version        linux version

Prerequisites

  • NVIDIA Pascalâ„¢ GPU architecture or better
  • CUDA 10.2/11.0 with a compatible NVIDIA driver
  • Ubuntu 16.04/18.04 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

License

By pulling and using the container, you accept the terms and conditions of this End User License Agreement.