专属域名
文档搜索
轩辕助手
Run助手
邀请有礼
返回顶部
快速返回页面顶部
收起
收起工具栏
轩辕镜像 官方专业版
轩辕镜像 官方专业版轩辕镜像 官方专业版官方专业版
首页个人中心搜索镜像

交易
充值流量我的订单
工具
提交工单镜像收录一键安装
Npm 源Pip 源Homebrew 源
帮助
常见问题
其他
关于我们网站地图

官方QQ群: 1072982923

热门搜索:openclaw🔥nginx🔥redis🔥mysqlopenjdkcursorweb2apimemgraphzabbixetcdubuntucorednsjdk
cuda

nvidia/cuda

NVIDIA 官方容器镜像

英伟达在GitLab仓库(gitlab.com/nvidia/cuda)提供的CUDA(并行计算平台)和cuDNN(深度神经网络加速库)镜像,为开发者提供了预配置的开发环境,支持高效进行并行计算应用开发、深度学习模型训练及推理任务,确保了环境的一致性和部署的便捷性,是构建基于英伟达GPU加速应用的重要资源。

2.0千 次收藏下载次数: 0状态:社区镜像维护者:NVIDIA 官方容器镜像仓库类型:镜像最近更新:26 天前
轩辕镜像,加速的不只是镜像。点击查看
版本下载
轩辕镜像,加速的不只是镜像。点击查看

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

CUDA Container Support Policy

CUDA image container tags have a lifetime. The tags will be deleted Six Months after the last supported "Tesla Recommended Driver" has gone end-of-life OR a newer update release has been made for the same CUDA version.

Please see CUDA Container Support Policy for more information.

Breaking changes are announced on Gitlab Issue #209.

Cuda Repo Signing Key has Changed!

This may present itself as the following errors.

debian:

Reading package lists... Done
W: GPG error: http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64  InRelease: The following signatures couldn't be verified because the public key is not available: NO_PUBKEY A4B469963BF863CC
W: The repository 'http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64  InRelease' is not signed.
N: Data from such a repository can't be authenticated and is therefore potentially dangerous to use.
N: See apt-secure(8) manpage for repository creation and user configuration details.

RPM:

warning: /var/cache/dnf/cuda-fedora32-x86_64-d60aafcddb176bf5/packages/libnvjpeg-11-1-11.3.0.105-1.x86_64.rpm: Header V4 RSA/SHA512 Signature, key ID d42d0685: NOKEY
cuda-fedora32-x86_64                                                                                  23 kB/s | 1.6 kB     00:00
Importing GPG key 0x7FA2AF80:
 Userid     : "cudatools <cudatools@nvidia.com>"
 Fingerprint: AE09 FE4B BD22 3A84 B2CC FCE3 F60F 4B3D 7FA2 AF80
 From       : https://developer.download.nvidia.com/compute/cuda/repos/fedora32/x86_64/7fa2af80.pub
Is this ok [y/N]: y
Key imported successfully
Import of key(s) didn't help, wrong key(s)?
Public key for libnvjpeg-11-1-11.3.0.105-1.x86_64.rpm is not installed. Failing package is: libnvjpeg-11-1-11.3.0.105-1.x86_64
 GPG Keys are configured as: https://developer.download.nvidia.com/compute/cuda/repos/fedora32/x86_64/7fa2af80.pub
The downloaded packages were saved in cache until the next successful transaction.
You can remove cached packages by executing 'dnf clean packages'.
Error: GPG check FAILED

Updated images will be pushed out over the next few days containing the new repo key. Please follow progress using the links below:

  • [***]
  • [***]

Multi-arch image manifests are now LIVE for all supported CUDA container image versions

It is now possible to build CUDA container images for all supported architectures using Docker Buildkit in one step. See the example script below.

The deprecated image names nvidia/cuda-arm64 and nvidia/cuda-ppc64le will remain available, but no longer supported.

The following product pages still exist but will no longer be supported:

  • https://hub.docker.com/r/nvidia/cuda-ppc64le
  • https://hub.docker.com/r/nvidia/cuda-arm64

The following gitlab repositories will be archived:

  • [***]

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. Some images may also include TensorRT.
  • 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 https://github.com/NVIDIA/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 https://github.com/NVIDIA/nvidia-docker/wiki/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, cuDNN, and TensorRT versions. These tags are also periodically updated to fix CVE vulnerabilities.

For a full list of supported tags, click here.

LATEST CUDA 13.2.0

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

ubuntu24.04 [arm64, x86_64]

  • 13.2.0-cudnn-runtime-ubuntu24.04 (13.2.0/ubuntu2404/runtime/cudnn/Dockerfile)
  • 13.2.0-runtime-ubuntu24.04 (13.2.0/ubuntu2404/runtime/Dockerfile)
  • 13.2.0-cudnn-devel-ubuntu24.04 (13.2.0/ubuntu2404/devel/cudnn/Dockerfile)
  • 13.2.0-devel-ubuntu24.04 (13.2.0/ubuntu2404/devel/Dockerfile)
  • 13.2.0-base-ubuntu24.04 (13.2.0/ubuntu2404/base/Dockerfile)

ubuntu22.04 [arm64, x86_64]

  • 13.2.0-cudnn-runtime-ubuntu22.04 (13.2.0/ubuntu2204/runtime/cudnn/Dockerfile)
  • 13.2.0-runtime-ubuntu22.04 (13.2.0/ubuntu2204/runtime/Dockerfile)
  • 13.2.0-cudnn-devel-ubuntu22.04 (13.2.0/ubuntu2204/devel/cudnn/Dockerfile)
  • 13.2.0-devel-ubuntu22.04 (13.2.0/ubuntu2204/devel/Dockerfile)
  • 13.2.0-base-ubuntu22.04 (13.2.0/ubuntu2204/base/Dockerfile)

ubi9 [arm64, x86_64]

  • 13.2.0-cudnn-runtime-ubi9 (13.2.0/ubi9/runtime/cudnn/Dockerfile)
  • 13.2.0-runtime-ubi9 (13.2.0/ubi9/runtime/Dockerfile)
  • 13.2.0-cudnn-devel-ubi9 (13.2.0/ubi9/devel/cudnn/Dockerfile)
  • 13.2.0-devel-ubi9 (13.2.0/ubi9/devel/Dockerfile)
  • 13.2.0-base-ubi9 (13.2.0/ubi9/base/Dockerfile)

ubi8 [arm64, x86_64]

  • 13.2.0-cudnn-runtime-ubi8 (13.2.0/ubi8/runtime/cudnn/Dockerfile)
  • 13.2.0-runtime-ubi8 (13.2.0/ubi8/runtime/Dockerfile)
  • 13.2.0-cudnn-devel-ubi8 (13.2.0/ubi8/devel/cudnn/Dockerfile)
  • 13.2.0-devel-ubi8 (13.2.0/ubi8/devel/Dockerfile)
  • 13.2.0-base-ubi8 (13.2.0/ubi8/base/Dockerfile)

ubi10 [arm64, x86_64]

  • 13.2.0-cudnn-runtime-ubi10 (13.2.0/ubi10/runtime/cudnn/Dockerfile)
  • 13.2.0-runtime-ubi10 (13.2.0/ubi10/runtime/Dockerfile)
  • 13.2.0-cudnn-devel-ubi10 (13.2.0/ubi10/devel/cudnn/Dockerfile)
  • 13.2.0-devel-ubi10 (13.2.0/ubi10/devel/Dockerfile)
  • 13.2.0-base-ubi10 (13.2.0/ubi10/base/Dockerfile)

suse16 [arm64, x86_64]

  • 13.2.0-runtime-suse16 (13.2.0/suse16/runtime/Dockerfile)
  • 13.2.0-devel-suse16 (13.2.0/suse16/devel/Dockerfile)
  • 13.2.0-base-suse16 (13.2.0/suse16/base/Dockerfile)

rockylinux9 [arm64, x86_64]

  • 13.2.0-cudnn-runtime-rockylinux9 (13.2.0/rockylinux9/runtime/cudnn/Dockerfile)
  • 13.2.0-runtime-rockylinux9 (13.2.0/rockylinux9/runtime/Dockerfile)
  • 13.2.0-cudnn-devel-rockylinux9 (13.2.0/rockylinux9/devel/cudnn/Dockerfile)
  • 13.2.0-devel-rockylinux9 (13.2.0/rockylinux9/devel/Dockerfile)
  • 13.2.0-base-rockylinux9 (13.2.0/rockylinux9/base/Dockerfile)

rockylinux8 [arm64, x86_64]

  • 13.2.0-cudnn-runtime-rockylinux8 (13.2.0/rockylinux8/runtime/cudnn/Dockerfile)
  • 13.2.0-runtime-rockylinux8 (13.2.0/rockylinux8/runtime/Dockerfile)
  • 13.2.0-cudnn-devel-rockylinux8 (13.2.0/rockylinux8/devel/cudnn/Dockerfile)
  • 13.2.0-devel-rockylinux8 (13.2.0/rockylinux8/devel/Dockerfile)
  • 13.2.0-base-rockylinux8 (13.2.0/rockylinux8/base/Dockerfile)

rockylinux10 [arm64, x86_64]

  • 13.2.0-cudnn-runtime-rockylinux10 (13.2.0/rockylinux10/runtime/cudnn/Dockerfile)
  • 13.2.0-runtime-rockylinux10 (13.2.0/rockylinux10/runtime/Dockerfile)
  • 13.2.0-cudnn-devel-rockylinux10 (13.2.0/rockylinux10/devel/cudnn/Dockerfile)
  • 13.2.0-devel-rockylinux10 (13.2.0/rockylinux10/devel/Dockerfile)
  • 13.2.0-base-rockylinux10 (13.2.0/rockylinux10/base/Dockerfile)

oraclelinux9 [arm64, x86_64]

  • 13.2.0-cudnn-runtime-oraclelinux9 (13.2.0/oraclelinux9/runtime/cudnn/Dockerfile)
  • 13.2.0-runtime-oraclelinux9 (13.2.0/oraclelinux9/runtime/Dockerfile)
  • 13.2.0-cudnn-devel-oraclelinux9 (13.2.0/oraclelinux9/devel/cudnn/Dockerfile)
  • 13.2.0-devel-oraclelinux9 (13.2.0/oraclelinux9/devel/Dockerfile)
  • 13.2.0-base-oraclelinux9 (13.2.0/oraclelinux9/base/Dockerfile)

oraclelinux8 [arm64, x86_64]

  • 13.2.0-cudnn-runtime-oraclelinux8 (13.2.0/oraclelinux8/runtime/cudnn/Dockerfile)
  • 13.2.0-runtime-oraclelinux8 (13.2.0/oraclelinux8/runtime/Dockerfile)
  • 13.2.0-cudnn-devel-oraclelinux8 (13.2.0/oraclelinux8/devel/cudnn/Dockerfile)
  • 13.2.0-devel-oraclelinux8 (13.2.0/oraclelinux8/devel/Dockerfile)
  • 13.2.0-base-oraclelinux8 (13.2.0/oraclelinux8/base/Dockerfile)

opensuse15 [x86_64]

  • 13.2.0-cudnn-runtime-opensuse15 (13.2.0/opensuse15/runtime/cudnn/Dockerfile)
  • 13.2.0-runtime-opensuse15 (13.2.0/opensuse15/runtime/Dockerfile)
  • 13.2.0-cudnn-devel-opensuse15 (13.2.0/opensuse15/devel/cudnn/Dockerfile)
  • 13.2.0-devel-opensuse15 (13.2.0/opensuse15/devel/Dockerfile)
  • 13.2.0-base-opensuse15 (13.2.0/opensuse15/base/Dockerfile)

azl3 [arm64, x86_64]

  • 13.2.0-runtime-azl3 (13.2.0/azl3/runtime/Dockerfile)
  • 13.2.0-devel-azl3 (13.2.0/azl3/devel/Dockerfile)
  • 13.2.0-base-azl3 (13.2.0/azl3/base/Dockerfile)

amzn2023 [arm64, x86_64]

  • 13.2.0-runtime-amzn2023 (13.2.0/amzn2023/runtime/Dockerfile)
  • 13.2.0-devel-amzn2023 (13.2.0/amzn2023/devel/Dockerfile)
  • 13.2.0-base-amzn2023 (13.2.0/amzn2023/base/Dockerfile)

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)

Deployment & Usage Documentation

NVIDIA CUDA 镜像 Docker 容器化部署全流程

CPU 像“全能但慢的多面手”,适合处理逻辑复杂但数据量小的任务;GPU 像“成千上万的小工人”,擅长同时处理大量重复、简单的计算。CUDA 就是连接开发者与 GPU 能力的“桥梁”,让 GPU 能脱离显卡驱动,直接为科学计算、AI 训练、数据处理等任务服务。

Read More

查看更多 cuda 相关镜像 →

rocker/cuda logo

rocker/cuda

rocker
集成NVIDIA CUDA库的Rocker镜像,提供R语言环境下的GPU加速计算支持,基于rocker-org/rocker-versioned2项目构建。
10 次收藏5万+ 次下载
14 天前更新
okteto/cuda logo

okteto/cuda

okteto
暂无描述
172 次下载
1 年前更新
openeuler/cuda logo

openeuler/cuda

openeuler
官方CUDA Docker镜像,基于openEuler构建,提供异构计算平台,通过分层API和高级库助力快速构建基于NVIDIA GPU的高性能计算应用和AI服务,免费使用且无用户速率限制。
650 次下载
7 个月前更新
vistart/cuda logo

vistart/cuda

vistart
基于NVIDIA官方Dockerfile构建的CUDA镜像,使用清华源,集成CUDA、CUDNN、NCCL、TensorRT等组件,支持多种Ubuntu版本,每周更新,提供Docker Hub和阿里云香港节点双存储。
17 次收藏5万+ 次下载
4 年前更新
gpuci/cuda logo

gpuci/cuda

gpuci
用于填补空白并补充nvidia/cuda的CUDA镜像
5万+ 次下载
4 年前更新
tobycheese/cuda logo

tobycheese/cuda

tobycheese
基于Ubuntu 18.04的Docker镜像,集成CUDA 9.0和cuDNN 7,解决Nvidia未提供旧版CUDA与新版Ubuntu组合的问题,适用于依赖CUDA 9.0的应用场景。
2 次收藏1万+ 次下载
7 年前更新

轩辕镜像配置手册

探索更多轩辕镜像的使用方法,找到最适合您系统的配置方式

Docker 配置

登录仓库拉取

通过 Docker 登录认证访问私有仓库

专属域名拉取

无需登录使用专属域名

K8s Containerd

Kubernetes 集群配置 Containerd

K3s

K3s 轻量级 Kubernetes 镜像加速

Dev Containers

VS Code Dev Containers 配置

Podman

Podman 容器引擎配置

Singularity/Apptainer

HPC 科学计算容器配置

其他仓库配置

ghcr、Quay、nvcr 等镜像仓库

Harbor 镜像源配置

Harbor Proxy Repository 对接专属域名

Portainer 镜像源配置

Portainer Registries 加速拉取

Nexus 镜像源配置

Nexus3 Docker Proxy 内网缓存

系统配置

Linux

在 Linux 系统配置镜像服务

Windows/Mac

在 Docker Desktop 配置镜像

MacOS OrbStack

MacOS OrbStack 容器配置

Docker Compose

Docker Compose 项目配置

NAS 设备

群晖

Synology 群晖 NAS 配置

飞牛

飞牛 fnOS 系统配置镜像

绿联

绿联 NAS 系统配置镜像

威联通

QNAP 威联通 NAS 配置

极空间

极空间 NAS 系统配置服务

网络设备

爱快路由

爱快 iKuai 路由系统配置

宝塔面板

在宝塔面板一键配置镜像

需要其他帮助?请查看我们的 常见问题Docker 镜像访问常见问题解答 或 提交工单

镜像拉取常见问题

使用与功能问题

配置了专属域名后,docker search 为什么会报错?

docker search 限制

Docker Hub 上有的镜像,为什么在轩辕镜像网站搜不到?

站内搜不到镜像

机器不能直连外网时,怎么用 docker save / load 迁镜像?

离线 save/load

docker pull 拉插件报错(plugin v1+json)怎么办?

插件要用 plugin install

WSL 里 Docker 拉镜像特别慢,怎么排查和优化?

WSL 拉取慢

轩辕镜像安全吗?如何用 digest 校验镜像没被篡改?

安全与 digest

第一次用轩辕镜像拉 Docker 镜像,要怎么登录和配置?

新手拉取配置

错误码与失败问题

docker pull 提示 manifest unknown 怎么办?

manifest unknown

docker pull 提示 no matching manifest 怎么办?

no matching manifest(架构)

镜像已拉取完成,却提示 invalid tar header 或 failed to register layer 怎么办?

invalid tar header(解压)

Docker pull 时 HTTPS / TLS 证书验证失败怎么办?

TLS 证书失败

Docker pull 时 DNS 解析超时或连不上仓库怎么办?

DNS 超时

Docker 拉取出现 410 Gone 怎么办?

410 Gone 排查

出现 402 或「流量用尽」提示怎么办?

402 与流量用尽

Docker 拉取提示 UNAUTHORIZED(401)怎么办?

401 认证失败

遇到 429 Too Many Requests(请求太频繁)怎么办?

429 限流

docker login 提示 Cannot autolaunch D-Bus,还算登录成功吗?

D-Bus 凭证提示

为什么会出现「单层超过 20GB」或 413,无法加速拉取?

413 与超大单层

账号 / 计费 / 权限

轩辕镜像免费版和专业版有什么区别?

免费版与专业版区别

轩辕镜像支持哪些 Docker 镜像仓库?

支持的镜像仓库

镜像拉取失败还会不会扣流量?

失败是否计费

麒麟 V10 / 统信 UOS 提示 KYSEC 权限不够怎么办?

KYSEC 拦截脚本

如何在轩辕镜像申请开具发票?

申请开票

怎么修改轩辕镜像的网站登录和仓库登录密码?

修改登录密码

如何注销轩辕镜像账户?要注意什么?

注销账户

配置与原理类

写了 registry-mirrors,为什么还是走官方或仍然报错?

mirrors 不生效

怎么用 docker tag 去掉镜像名里的轩辕域名前缀?

去掉域名前缀

如何拉取指定 CPU 架构的镜像(如 ARM64、AMD64)?

指定架构拉取

用轩辕镜像拉镜像时快时慢,常见原因有哪些?

拉取速度原因

查看全部问题→

用户好评

来自真实用户的反馈,见证轩辕镜像的优质服务

用户头像

oldzhang

运维工程师

Linux服务器

5

"Docker访问体验非常流畅,大镜像也能快速完成下载。"

轩辕镜像
NVIDIA 官方容器镜像
...
nvidia/cuda
博客公告Docker 镜像公告与技术博客
热门镜像查看热门 Docker 镜像推荐
一键安装一键安装 Docker 并配置镜像源
镜像拉取问题咨询请 提交工单,官方技术交流群:1072982923。轩辕镜像所有镜像均来源于原始仓库,本站不存储、不修改、不传播任何镜像内容。
镜像拉取问题咨询请提交工单,官方技术交流群:。轩辕镜像所有镜像均来源于原始仓库,本站不存储、不修改、不传播任何镜像内容。
商务合作:点击复制邮箱
©2024-2026 源码跳动
商务合作:点击复制邮箱Copyright © 2024-2026 杭州源码跳动科技有限公司. All rights reserved.