docker.io/nvcr.io/nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04 linux/amd64

docker.io/nvcr.io/nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04 - 国内下载镜像源 浏览次数:95
好！下面是这个docker镜像的描述：

CUDA (Compute Unified Device Architecture) 是 NVIDIA 开发的一种用于加速 GPU 计算的编程框架。该镜像基于 NVIDIA 的 CUDA 环境，提供了一个完整的 CUDA 工具链，支持开发、调试和部署使用 CUDA 的应用程序。

本镜像包含以下组件：

  • CUDA Toolkit
  • NVIDIA Driver
  • nvidia-smi
  • 其他 NVIDIA 相关工具

该镜像支持多种操作系统，包括 Ubuntu、CentOS 和 Windows。它是开发和部署使用 CUDA 的应用程序的理想选择。

源镜像 docker.io/nvcr.io/nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04
国内镜像 swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04
镜像ID sha256:7d79b4fee2018c7b5b29f610d8f992319e3e5c69f80611e37b65f2c3885cf42d
镜像TAG 12.8.0-cudnn-devel-ubuntu22.04
大小 10.49GB
镜像源 docker.io
项目信息 Docker-Hub主页 🚀项目TAG 🚀
CMD
启动入口 /opt/nvidia/nvidia_entrypoint.sh
工作目录
OS/平台 linux/amd64
浏览量 95 次
贡献者
镜像创建 2025-01-26T23:14:33.027662541Z
同步时间 2025-03-18 02:03
更新时间 2025-03-31 12:10
环境变量
PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin NVARCH=x86_64 NVIDIA_REQUIRE_CUDA=cuda>=12.8 brand=unknown,driver>=470,driver<471 brand=grid,driver>=470,driver<471 brand=tesla,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=vapps,driver>=470,driver<471 brand=vpc,driver>=470,driver<471 brand=vcs,driver>=470,driver<471 brand=vws,driver>=470,driver<471 brand=cloudgaming,driver>=470,driver<471 brand=unknown,driver>=535,driver<536 brand=grid,driver>=535,driver<536 brand=tesla,driver>=535,driver<536 brand=nvidia,driver>=535,driver<536 brand=quadro,driver>=535,driver<536 brand=quadrortx,driver>=535,driver<536 brand=nvidiartx,driver>=535,driver<536 brand=vapps,driver>=535,driver<536 brand=vpc,driver>=535,driver<536 brand=vcs,driver>=535,driver<536 brand=vws,driver>=535,driver<536 brand=cloudgaming,driver>=535,driver<536 brand=unknown,driver>=550,driver<551 brand=grid,driver>=550,driver<551 brand=tesla,driver>=550,driver<551 brand=nvidia,driver>=550,driver<551 brand=quadro,driver>=550,driver<551 brand=quadrortx,driver>=550,driver<551 brand=nvidiartx,driver>=550,driver<551 brand=vapps,driver>=550,driver<551 brand=vpc,driver>=550,driver<551 brand=vcs,driver>=550,driver<551 brand=vws,driver>=550,driver<551 brand=cloudgaming,driver>=550,driver<551 brand=unknown,driver>=560,driver<561 brand=grid,driver>=560,driver<561 brand=tesla,driver>=560,driver<561 brand=nvidia,driver>=560,driver<561 brand=quadro,driver>=560,driver<561 brand=quadrortx,driver>=560,driver<561 brand=nvidiartx,driver>=560,driver<561 brand=vapps,driver>=560,driver<561 brand=vpc,driver>=560,driver<561 brand=vcs,driver>=560,driver<561 brand=vws,driver>=560,driver<561 brand=cloudgaming,driver>=560,driver<561 brand=unknown,driver>=565,driver<566 brand=grid,driver>=565,driver<566 brand=tesla,driver>=565,driver<566 brand=nvidia,driver>=565,driver<566 brand=quadro,driver>=565,driver<566 brand=quadrortx,driver>=565,driver<566 brand=nvidiartx,driver>=565,driver<566 brand=vapps,driver>=565,driver<566 brand=vpc,driver>=565,driver<566 brand=vcs,driver>=565,driver<566 brand=vws,driver>=565,driver<566 brand=cloudgaming,driver>=565,driver<566 NV_CUDA_CUDART_VERSION=12.8.57-1 CUDA_VERSION=12.8.0 LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=compute,utility NV_CUDA_LIB_VERSION=12.8.0-1 NV_NVTX_VERSION=12.8.55-1 NV_LIBNPP_VERSION=12.3.3.65-1 NV_LIBNPP_PACKAGE=libnpp-12-8=12.3.3.65-1 NV_LIBCUSPARSE_VERSION=12.5.7.53-1 NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-8 NV_LIBCUBLAS_VERSION=12.8.3.14-1 NV_LIBCUBLAS_PACKAGE=libcublas-12-8=12.8.3.14-1 NV_LIBNCCL_PACKAGE_NAME=libnccl2 NV_LIBNCCL_PACKAGE_VERSION=2.25.1-1 NCCL_VERSION=2.25.1-1 NV_LIBNCCL_PACKAGE=libnccl2=2.25.1-1+cuda12.8 NVIDIA_PRODUCT_NAME=CUDA NV_CUDA_CUDART_DEV_VERSION=12.8.57-1 NV_NVML_DEV_VERSION=12.8.55-1 NV_LIBCUSPARSE_DEV_VERSION=12.5.7.53-1 NV_LIBNPP_DEV_VERSION=12.3.3.65-1 NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-8=12.3.3.65-1 NV_LIBCUBLAS_DEV_VERSION=12.8.3.14-1 NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-8 NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-8=12.8.3.14-1 NV_CUDA_NSIGHT_COMPUTE_VERSION=12.8.0-1 NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-8=12.8.0-1 NV_NVPROF_VERSION=12.8.57-1 NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-8=12.8.57-1 NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev NV_LIBNCCL_DEV_PACKAGE_VERSION=2.25.1-1 NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.25.1-1+cuda12.8 LIBRARY_PATH=/usr/local/cuda/lib64/stubs NV_CUDNN_VERSION=9.7.0.66-1 NV_CUDNN_PACKAGE_NAME=libcudnn9-cuda-12 NV_CUDNN_PACKAGE=libcudnn9-cuda-12=9.7.0.66-1 NV_CUDNN_PACKAGE_DEV=libcudnn9-dev-cuda-12=9.7.0.66-1
镜像标签
9.7.0.66-1: com.nvidia.cudnn.version NVIDIA CORPORATION <cudatools@nvidia.com>: maintainer ubuntu: org.opencontainers.image.ref.name 22.04: org.opencontainers.image.version
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Docker拉取命令 无权限下载?点我修复 

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04  docker.io/nvcr.io/nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04

Containerd拉取命令 

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04  docker.io/nvcr.io/nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04

Shell快速替换命令 

sed -i 's#nvcr.io/nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04#' deployment.yaml

Ansible快速分发-Docker 

#ansible k8s -m shell -a 'docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04 && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04  docker.io/nvcr.io/nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04'

Ansible快速分发-Containerd 

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04 && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvcr.io/nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04  docker.io/nvcr.io/nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04'

镜像构建历史 


# 2025-01-27 07:14:33  1.10GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     ${NV_CUDNN_PACKAGE}     ${NV_CUDNN_PACKAGE_DEV}     && apt-mark hold ${NV_CUDNN_PACKAGE_NAME}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2025-01-27 07:14:33  0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=9.7.0.66-1
                        
# 2025-01-27 07:14:33  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2025-01-27 07:14:33  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2025-01-27 07:14:33  0.00B 设置环境变量 NV_CUDNN_PACKAGE_DEV
ENV NV_CUDNN_PACKAGE_DEV=libcudnn9-dev-cuda-12=9.7.0.66-1
                        
# 2025-01-27 07:14:33  0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn9-cuda-12=9.7.0.66-1
                        
# 2025-01-27 07:14:33  0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn9-cuda-12
                        
# 2025-01-27 07:14:33  0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=9.7.0.66-1
                        
# 2025-01-25 09:17:40  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
                        
# 2025-01-25 09:17:40  389.49KB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_DEV_PACKAGE_NAME} ${NV_LIBNCCL_DEV_PACKAGE_NAME} # buildkit
                        
# 2025-01-25 09:17:39  5.96GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     cuda-cudart-dev-12-8=${NV_CUDA_CUDART_DEV_VERSION}     cuda-command-line-tools-12-8=${NV_CUDA_LIB_VERSION}     cuda-minimal-build-12-8=${NV_CUDA_LIB_VERSION}     cuda-libraries-dev-12-8=${NV_CUDA_LIB_VERSION}     cuda-nvml-dev-12-8=${NV_NVML_DEV_VERSION}     ${NV_NVPROF_DEV_PACKAGE}     ${NV_LIBNPP_DEV_PACKAGE}     libcusparse-dev-12-8=${NV_LIBCUSPARSE_DEV_VERSION}     ${NV_LIBCUBLAS_DEV_PACKAGE}     ${NV_LIBNCCL_DEV_PACKAGE}     ${NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2025-01-25 09:17:39  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2025-01-25 09:17:39  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2025-01-25 09:17:39  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE
ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.25.1-1+cuda12.8
                        
# 2025-01-25 09:17:39  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.25.1-1
                        
# 2025-01-25 09:17:39  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.25.1-1
                        
# 2025-01-25 09:17:39  0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
                        
# 2025-01-25 09:17:39  0.00B 设置环境变量 NV_NVPROF_DEV_PACKAGE
ENV NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-8=12.8.57-1
                        
# 2025-01-25 09:17:39  0.00B 设置环境变量 NV_NVPROF_VERSION
ENV NV_NVPROF_VERSION=12.8.57-1
                        
# 2025-01-25 09:17:39  0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE
ENV NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-8=12.8.0-1
                        
# 2025-01-25 09:17:39  0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_VERSION
ENV NV_CUDA_NSIGHT_COMPUTE_VERSION=12.8.0-1
                        
# 2025-01-25 09:17:39  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE
ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-8=12.8.3.14-1
                        
# 2025-01-25 09:17:39  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-8
                        
# 2025-01-25 09:17:39  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=12.8.3.14-1
                        
# 2025-01-25 09:17:39  0.00B 设置环境变量 NV_LIBNPP_DEV_PACKAGE
ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-8=12.3.3.65-1
                        
# 2025-01-25 09:17:39  0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=12.3.3.65-1
                        
# 2025-01-25 09:17:39  0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=12.5.7.53-1
                        
# 2025-01-25 09:17:39  0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=12.8.55-1
                        
# 2025-01-25 09:17:39  0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=12.8.57-1
                        
# 2025-01-25 09:17:39  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.8.0-1
                        
# 2025-01-27 07:06:37  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2025-01-27 07:06:37  2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
                        
# 2025-01-27 07:06:37  3.06KB 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
                        
# 2025-01-27 07:06:37  263.00KB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_PACKAGE_NAME} ${NV_LIBNCCL_PACKAGE_NAME} # buildkit
                        
# 2025-01-27 07:06:37  3.13GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     cuda-libraries-12-8=${NV_CUDA_LIB_VERSION}     ${NV_LIBNPP_PACKAGE}     cuda-nvtx-12-8=${NV_NVTX_VERSION}     libcusparse-12-8=${NV_LIBCUSPARSE_VERSION}     ${NV_LIBCUBLAS_PACKAGE}     ${NV_LIBNCCL_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2025-01-27 07:06:37  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2025-01-27 07:06:37  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.25.1-1+cuda12.8
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.25.1-1
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.25.1-1
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-12-8=12.8.3.14-1
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=12.8.3.14-1
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-8
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=12.5.7.53-1
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-12-8=12.3.3.65-1
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=12.3.3.65-1
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=12.8.55-1
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.8.0-1
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2025-01-27 07:06:37  17.29KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 PATH
ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2025-01-27 07:06:37  46.00B 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf     && echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf # buildkit
                        
# 2025-01-27 07:06:37  203.16MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     cuda-cudart-12-8=${NV_CUDA_CUDART_VERSION}     cuda-compat-12-8     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=12.8.0
                        
# 2025-01-27 07:06:37  10.60MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     gnupg2 curl ca-certificates &&     curl -fsSLO https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/${NVARCH}/cuda-keyring_1.1-1_all.deb &&     dpkg -i cuda-keyring_1.1-1_all.deb &&     apt-get purge --autoremove -y curl     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2025-01-27 07:06:37  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2025-01-27 07:06:37  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=12.8.57-1
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand
ENV NVIDIA_REQUIRE_CUDA=cuda>=12.8 brand=unknown,driver>=470,driver<471 brand=grid,driver>=470,driver<471 brand=tesla,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=vapps,driver>=470,driver<471 brand=vpc,driver>=470,driver<471 brand=vcs,driver>=470,driver<471 brand=vws,driver>=470,driver<471 brand=cloudgaming,driver>=470,driver<471 brand=unknown,driver>=535,driver<536 brand=grid,driver>=535,driver<536 brand=tesla,driver>=535,driver<536 brand=nvidia,driver>=535,driver<536 brand=quadro,driver>=535,driver<536 brand=quadrortx,driver>=535,driver<536 brand=nvidiartx,driver>=535,driver<536 brand=vapps,driver>=535,driver<536 brand=vpc,driver>=535,driver<536 brand=vcs,driver>=535,driver<536 brand=vws,driver>=535,driver<536 brand=cloudgaming,driver>=535,driver<536 brand=unknown,driver>=550,driver<551 brand=grid,driver>=550,driver<551 brand=tesla,driver>=550,driver<551 brand=nvidia,driver>=550,driver<551 brand=quadro,driver>=550,driver<551 brand=quadrortx,driver>=550,driver<551 brand=nvidiartx,driver>=550,driver<551 brand=vapps,driver>=550,driver<551 brand=vpc,driver>=550,driver<551 brand=vcs,driver>=550,driver<551 brand=vws,driver>=550,driver<551 brand=cloudgaming,driver>=550,driver<551 brand=unknown,driver>=560,driver<561 brand=grid,driver>=560,driver<561 brand=tesla,driver>=560,driver<561 brand=nvidia,driver>=560,driver<561 brand=quadro,driver>=560,driver<561 brand=quadrortx,driver>=560,driver<561 brand=nvidiartx,driver>=560,driver<561 brand=vapps,driver>=560,driver<561 brand=vpc,driver>=560,driver<561 brand=vcs,driver>=560,driver<561 brand=vws,driver>=560,driver<561 brand=cloudgaming,driver>=560,driver<561 brand=unknown,driver>=565,driver<566 brand=grid,driver>=565,driver<566 brand=tesla,driver>=565,driver<566 brand=nvidia,driver>=565,driver<566 brand=quadro,driver>=565,driver<566 brand=quadrortx,driver>=565,driver<566 brand=nvidiartx,driver>=565,driver<566 brand=vapps,driver>=565,driver<566 brand=vpc,driver>=565,driver<566 brand=vcs,driver>=565,driver<566 brand=vws,driver>=565,driver<566 brand=cloudgaming,driver>=565,driver<566
                        
# 2025-01-27 07:06:37  0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
                        
# 2024-09-12 00:25:18  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2024-09-12 00:25:17  77.86MB 
/bin/sh -c #(nop) ADD file:ebe009f86035c175ba244badd298a2582914415cf62783d510eab3a311a5d4e1 in / 
                        
# 2024-09-12 00:25:16  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.version=22.04
                        
# 2024-09-12 00:25:16  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.ref.name=ubuntu
                        
# 2024-09-12 00:25:16  0.00B 
/bin/sh -c #(nop)  ARG LAUNCHPAD_BUILD_ARCH
                        
# 2024-09-12 00:25:16  0.00B 
/bin/sh -c #(nop)  ARG RELEASE

镜像信息 

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            "NV_CUDA_CUDART_VERSION=12.8.57-1",
            "CUDA_VERSION=12.8.0",
            "LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
            "NVIDIA_VISIBLE_DEVICES=all",
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}

更多版本

docker.io/nvcr.io/nvidia/cuda:11.8.0-cudnn8-devel-ubuntu22.04

linux/amd64 docker.io9.74GB2024-08-28 18:20
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docker.io/nvcr.io/nvidia/cuda:12.4.1-cudnn-devel-ubuntu22.04

linux/amd64 docker.io8.29GB2025-01-18 00:08
239

docker.io/nvcr.io/nvidia/cuda:12.8.0-cudnn-devel-ubuntu22.04

linux/amd64 docker.io10.49GB2025-03-18 02:03
94