docker.io/nvidia/cuda:11.6.2-cudnn8-devel-ubuntu18.04 linux/arm64

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvidia/cuda:11.6.2-cudnn8-devel-ubuntu18.04-linuxarm64
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvidia/cuda:11.6.2-cudnn8-devel-ubuntu18.04-linuxarm64  docker.io/nvidia/cuda:11.6.2-cudnn8-devel-ubuntu18.04

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvidia/cuda:11.6.2-cudnn8-devel-ubuntu18.04-linuxarm64
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvidia/cuda:11.6.2-cudnn8-devel-ubuntu18.04-linuxarm64  docker.io/nvidia/cuda:11.6.2-cudnn8-devel-ubuntu18.04

Shell快速替换命令

sed -i 's#nvidia/cuda:11.6.2-cudnn8-devel-ubuntu18.04#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvidia/cuda:11.6.2-cudnn8-devel-ubuntu18.04-linuxarm64#' 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/nvidia/cuda:11.6.2-cudnn8-devel-ubuntu18.04-linuxarm64 && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvidia/cuda:11.6.2-cudnn8-devel-ubuntu18.04-linuxarm64  docker.io/nvidia/cuda:11.6.2-cudnn8-devel-ubuntu18.04'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvidia/cuda:11.6.2-cudnn8-devel-ubuntu18.04-linuxarm64 && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nvidia/cuda:11.6.2-cudnn8-devel-ubuntu18.04-linuxarm64  docker.io/nvidia/cuda:11.6.2-cudnn8-devel-ubuntu18.04'

镜像构建历史

# 2022-12-17 09:22:57  2.75GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=arm64 /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
                        
# 2022-12-17 09:22:57  0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=8.4.0.27
                        
# 2022-12-17 09:22:57  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2022-12-17 09:22:57  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-12-17 09:22:57  0.00B 设置环境变量 NV_CUDNN_PACKAGE_DEV
ENV NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.4.0.27-1+cuda11.6
                        
# 2022-12-17 09:22:57  0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn8=8.4.0.27-1+cuda11.6
                        
# 2022-12-17 09:22:57  0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
                        
# 2022-12-17 09:22:57  0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=8.4.0.27
                        
# 2022-12-15 04:49:18  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
                        
# 2022-12-15 04:49:18  358.16KB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=arm64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_DEV_PACKAGE_NAME} ${NV_LIBNCCL_DEV_PACKAGE_NAME} # buildkit
                        
# 2022-12-15 04:49:16  2.39GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=arm64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     cuda-cudart-dev-11-6=${NV_CUDA_CUDART_DEV_VERSION}     cuda-command-line-tools-11-6=${NV_CUDA_LIB_VERSION}     cuda-minimal-build-11-6=${NV_CUDA_LIB_VERSION}     cuda-libraries-dev-11-6=${NV_CUDA_LIB_VERSION}     cuda-nvml-dev-11-6=${NV_NVML_DEV_VERSION}     ${NV_NVPROF_DEV_PACKAGE}     ${NV_LIBNPP_DEV_PACKAGE}     libcusparse-dev-11-6=${NV_LIBCUSPARSE_DEV_VERSION}     ${NV_LIBCUBLAS_DEV_PACKAGE}     ${NV_LIBNCCL_DEV_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2022-12-15 04:49:16  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2022-12-15 04:49:16  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-12-15 04:49:16  0.00B 设置环境变量 NV_NVPROF_DEV_PACKAGE
ENV NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-6=11.6.124-1
                        
# 2022-12-15 04:49:16  0.00B 设置环境变量 NV_NVPROF_VERSION
ENV NV_NVPROF_VERSION=11.6.124-1
                        
# 2022-12-15 04:49:16  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE
ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-6=11.9.2.110-1
                        
# 2022-12-15 04:49:16  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=11.9.2.110-1
                        
# 2022-12-15 04:49:16  0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-6
                        
# 2022-12-15 04:49:16  0.00B 设置环境变量 NV_LIBNPP_DEV_PACKAGE
ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-6=11.6.3.124-1
                        
# 2022-12-15 04:49:16  0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=11.6.3.124-1
                        
# 2022-12-15 04:49:16  0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=11.7.2.124-1
                        
# 2022-12-15 04:49:16  0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=11.6.55-1
                        
# 2022-12-15 04:49:16  0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=11.6.55-1
                        
# 2022-12-15 04:49:16  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.6.2-1
                        
# 2022-12-15 04:38:58  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2022-12-15 04:38:58  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2022-12-15 04:38:58  2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
                        
# 2022-12-15 04:38:58  3.04KB 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
                        
# 2022-12-15 04:38:58  253.20KB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=arm64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_PACKAGE_NAME} ${NV_LIBNCCL_PACKAGE_NAME} # buildkit
                        
# 2022-12-15 04:38:57  1.66GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=arm64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     cuda-libraries-11-6=${NV_CUDA_LIB_VERSION}     ${NV_LIBNPP_PACKAGE}     cuda-nvtx-11-6=${NV_NVTX_VERSION}     libcusparse-11-6=${NV_LIBCUSPARSE_VERSION}     ${NV_LIBCUBLAS_PACKAGE}     ${NV_LIBNCCL_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2022-12-15 04:38:57  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2022-12-15 04:38:57  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-12-15 04:38:57  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-11-6=11.9.2.110-1
                        
# 2022-12-15 04:38:57  0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=11.9.2.110-1
                        
# 2022-12-15 04:38:57  0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-6
                        
# 2022-12-15 04:38:57  0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=11.7.2.124-1
                        
# 2022-12-15 04:38:57  0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-11-6=11.6.3.124-1
                        
# 2022-12-15 04:38:57  0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=11.6.3.124-1
                        
# 2022-12-15 04:38:57  0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=11.6.124-1
                        
# 2022-12-15 04:38:57  0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.6.2-1
                        
# 2022-12-15 04:32:59  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2022-12-15 04:32:59  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2022-12-15 04:32:59  16.05KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
                        
# 2022-12-15 04:32:59  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2022-12-15 04:32:59  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
                        
# 2022-12-15 04:32:59  46.00B 执行命令并创建新的镜像层
RUN |1 TARGETARCH=arm64 /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
                        
# 2022-12-15 04:32:59  1.44MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=arm64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     cuda-cudart-11-6=${NV_CUDA_CUDART_VERSION}     ${NV_CUDA_COMPAT_PACKAGE}     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2022-12-15 04:32:11  0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=11.6.2
                        
# 2022-12-15 04:32:11  14.75MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=arm64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends     gnupg2 curl ca-certificates &&     curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/${NVARCH}/3bf863cc.pub | apt-key add - &&     echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/${NVARCH} /" > /etc/apt/sources.list.d/cuda.list &&     apt-get purge --autoremove -y curl     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2022-12-15 04:32:11  0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
                        
# 2022-12-15 04:32:11  0.00B 定义构建参数
ARG TARGETARCH
                        
# 2022-12-15 04:32:11  0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=11.6.55-1
                        
# 2022-12-15 04:32:11  0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA
ENV NVIDIA_REQUIRE_CUDA=cuda>=11.6
                        
# 2022-12-15 04:32:11  0.00B 设置环境变量 NVARCH
ENV NVARCH=sbsa
                        
# 2022-12-09 09:46:44  0.00B 
/bin/sh -c #(nop)  CMD ["bash"]
                        
# 2022-12-09 09:46:43  56.66MB 
/bin/sh -c #(nop) ADD file:eb8b2914800b2ed866666fbff73c8234f4ac2a5ef01743d6fea0984230c2f464 in / 
                        
                    

镜像信息

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