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CUDA

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Logo for CUDA

Description

CUDA is a parallel computing platform and programming model that enables dramatic increases in computing performance by harnessing the power of the NVIDIA GPUs.

Publisher

NVIDIA

Latest Tag

11.8.0-devel-ubuntu22.04

Modified

December 1, 2022

Compressed Size

2.19 GB

Multinode Support

No

Multi-Arch Support

Yes

11.8.0-devel-ubuntu22.04 (Latest) Scan Results

Linux / arm64

Linux / amd64

NVIDIA CUDA

CUDA is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers can dramatically speed up computing applications by harnessing the power of GPUs.

The CUDA Toolkit from NVIDIA provides everything you need to develop GPU-accelerated applications. The CUDA Toolkit includes GPU-accelerated libraries, a compiler, development tools and the CUDA runtime.

The CUDA container images provide an easy-to-use distribution for CUDA supported platforms and architectures.

End User License Agreements

The images are governed by the following NVIDIA End User License Agreements. By pulling and using the CUDA images, you accept the terms and conditions of these licenses. Since the images may include components licensed under open-source licenses such as GPL, the sources for these components are archived here.

NVIDIA Deep learning Container License

To view the NVIDIA Deep Learning Container license, click here

Documentation

For more information on CUDA, including the release notes, programming model, APIs and developer tools, visit the CUDA documentation site.

Announcement

NEW: Cuda Image Support Policy

We are changing the terms for how long we support published CUDA images to NGC and Docker Hub. Please review the NEW CUDA image support policy here.

Deprecated: "latest" tag

The "latest" tag for CUDA, CUDAGL, and OPENGL images has been deprecated on NGC and Docker Hub.

With the removal of the latest tag, the following use case will result in the "manifest unknown" error:

$ docker pull nvidia/cuda
Error response from daemon: manifest for nvidia/cuda:latest not found: manifest unknown: manifest
unknown

This is not a bug.

Overview of Images

Three flavors of images are provided:

  • base: Includes the CUDA runtime (cudart)
  • runtime: Builds on the base and includes the CUDA math libraries, and NCCL. A runtime image that also includes cuDNN is available.
  • devel: Builds on the runtime and includes headers, development tools for building CUDA images. These images are particularly useful for multi-stage builds.

The Dockerfiles for the images are open-source and licensed under 3-clause BSD. For more information see the Supported Tags section below.

NVIDIA Container Toolkit

The NVIDIA Container Toolkit for Docker is required to run CUDA images.

For CUDA 10.0, nvidia-docker2 (v2.1.0) or greater is recommended. It is also recommended to use Docker 19.03.

How to report a problem

Read NVIDIA Container Toolkit Frequently Asked Questions to see if the problem has been encountered before.

After it has been determined the problem is not with the NVIDIA runtime, report an issue at the CUDA Container Image Issue Tracker.

Supported tags

Supported tags are updated to the latest CUDA and cuDNN versions. These tags are also periodically updated to fix CVE vulnerabilities.

For a full list of supported tags, click here.

LATEST CUDA 11.8.0

Visit OpenSource @ Nvidia for the GPL sources of the packages contained in the CUDA base image layers.

ubuntu22.04 [arm64, x86_64]

ubuntu20.04 [arm64, x86_64]

ubuntu18.04 [x86_64]

ubi8 [arm64, ppc64le, x86_64]

ubi7 [x86_64]

rockylinux8 [x86_64]

centos7 [x86_64]

WARNING: POSSIBLE MISSING IMAGE TAGS

The Cuda image tags for centos7 and 8 may be missing on NGC and Docker Hub. Centos upstream images often fail security scans required by Nvidia before publishing images. Please check https://gitlab.com/nvidia/container-images/cuda/-/issues for any security notices!

Unsupported tags

A list of tags that are no longer supported can be found here

Source of this description

This Readme is located in the doc directory of the CUDA Container Image source repository. (history)