简述CUDA镜像构建

镜像需求

cuda-10.2

python-3.8

构建步骤

• base 镜像

可以随便找一个grpc的官法docker镜像

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• cuda 安装

在虚拟机上安装cuda会需要人为输入操作指令，而在docker上安装则可以直接通过yum，具体可参照Nvidia的[dockerfile](https://gitlab.com/nvidia/container-images/cuda/-/tree/master/dist/10.2/centos7), 注意repo中有三个镜像 `base`, `run`, `devel`, 这三个镜像是顺序依赖关系，如果想在一个dockerfile里搞定，就需要合并一下

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Dockerfile

FROM mirrors.****.com/grpc-python-compile\_linux3.1:0.1.7 as base



FROM base as base-amd64



ENV NVARCH x86\_64

ENV NVIDIA\_REQUIRE\_CUDA cuda>=10.2 brand=tesla,driver>=396,driver<397 brand=tesla,driver>=410,driver<411 brand=tesla,driver>=418,driver<419 brand=tesla,driver>=440,driver<441

ENV NV\_CUDA\_CUDART\_VERSION 10.2.89-1





RUN echo -e "[cuda]\nname=cuda\nbaseurl=https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86\_64\nenabled=1\ngpgcheck=1\ngpgkey=file:///etc/pki/rpm-gpg/RPM-GPG-KEY-NVIDIA" > /etc/yum.repos.d/cuda.repo

RUN echo -e "[nvidia-ml]\nname=nvidia-ml\nbaseurl=https://developer.download.nvidia.com/compute/machine-learning/repos/rhel7/x86\_64\nenabled=1\ngpgcheck=1\ngpgkey=file:///etc/pki/rpm-gpg/RPM-GPG-KEY-NVIDIA" >  /etc/yum.repos.d/nvidia-ml.repo







RUN NVIDIA\_GPGKEY\_SUM=d1be581509378368edeec8c1eb2958702feedf3bc3d17011adbf24efacce4ab5 && \

    curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/rhel7/${NVARCH}/7fa2af80.pub | sed '/^Version/d' > /etc/pki/rpm-gpg/RPM-GPG-KEY-NVIDIA && \

    echo "$NVIDIA\_GPGKEY\_SUM  /etc/pki/rpm-gpg/RPM-GPG-KEY-NVIDIA" | sha256sum -c --strict  -



ENV CUDA\_VERSION 10.2





RUN yum upgrade -y 

RUN yum install -y \

    cuda-cudart-10-2-${NV\_CUDA\_CUDART\_VERSION} \

    cuda-compat-10-2 \

    && ln -s cuda-10.2 /usr/local/cuda \

    && yum clean all \

    && rm -rf /var/cache/yum/\*



# nvidia-docker 1.0

RUN echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf && \

    echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf



ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:${PATH}

ENV LD\_LIBRARY\_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64



# nvidia-container-runtime

ENV NVIDIA\_VISIBLE\_DEVICES all

ENV NVIDIA\_DRIVER\_CAPABILITIES compute,utility



ENV NV\_CUDA\_LIB\_VERSION 10.2.89-1

ENV NV\_NVTX\_VERSION 10.2.89-1

ENV NV\_LIBNPP\_VERSION 10.2.89-1



ENV NV\_LIBCUBLAS\_PACKAGE\_NAME libcublas10

ENV NV\_LIBCUBLAS\_VERSION 10.2.2.89-1

ENV NV\_LIBCUBLAS\_PACKAGE ${NV\_LIBCUBLAS\_PACKAGE\_NAME}-${NV\_LIBCUBLAS\_VERSION}



ENV NV\_LIBNCCL\_PACKAGE\_NAME libnccl

ENV NV\_LIBNCCL\_PACKAGE\_VERSION 2.11.4-1

ENV NCCL\_VERSION 2.11.4

ENV NV\_LIBNCCL\_PACKAGE ${NV\_LIBNCCL\_PACKAGE\_NAME}-${NV\_LIBNCCL\_PACKAGE\_VERSION}+cuda10.2

RUN yum install -y \

    cuda-libraries-10-2-${NV\_CUDA\_LIB\_VERSION} \

    cuda-nvtx-10-2-${NV\_NVTX\_VERSION} \

    cuda-npp-10-2-${NV\_LIBNPP\_VERSION} \

    ${NV\_LIBCUBLAS\_PACKAGE} \

    ${NV\_LIBNCCL\_PACKAGE} 



ENV NV\_CUDA\_LIB\_VERSION 10.2.89-1

ENV NV\_NVPROF\_VERSION 10.2.89-1

ENV NV\_CUDA\_CUDART\_DEV\_VERSION 10.2.89-1

ENV NV\_NVML\_DEV\_VERSION 10.2.89-1



ENV NV\_LIBNPP\_DEV\_VERSION 10.2.89-1



ENV NV\_LIBCUBLAS\_DEV\_PACKAGE\_NAME libcublas-devel

ENV NV\_LIBCUBLAS\_DEV\_VERSION 10.2.2.89-1

ENV NV\_LIBCUBLAS\_DEV\_PACKAGE ${NV\_LIBCUBLAS\_DEV\_PACKAGE\_NAME}-${NV\_LIBCUBLAS\_DEV\_VERSION}



ENV NV\_LIBNCCL\_DEV\_PACKAGE\_NAME libnccl-devel

ENV NV\_LIBNCCL\_DEV\_PACKAGE\_VERSION 2.11.4-1

ENV NCCL\_VERSION 2.11.4

ENV NV\_LIBNCCL\_DEV\_PACKAGE ${NV\_LIBNCCL\_DEV\_PACKAGE\_NAME}-${NV\_LIBNCCL\_DEV\_PACKAGE\_VERSION}+cuda10.2



RUN yum install -y \

    make \

    cuda-nvml-dev-10-2-${NV\_NVML\_DEV\_VERSION} \

    cuda-command-line-tools-10-2-${NV\_CUDA\_LIB\_VERSION} \

    cuda-cudart-dev-10-2-${NV\_CUDA\_CUDART\_DEV\_VERSION} \

    cuda-libraries-dev-10-2-${NV\_CUDA\_LIB\_VERSION} \

    cuda-minimal-build-10-2-${NV\_CUDA\_LIB\_VERSION} \

    cuda-nvprof-10-2-${NV\_NVPROF\_VERSION} \

    cuda-npp-dev-10-2-${NV\_LIBNPP\_DEV\_VERSION} \

    ${NV\_LIBCUBLAS\_DEV\_PACKAGE} \

    ${NV\_LIBNCCL\_DEV\_PACKAGE} \

    && yum clean all \

    && rm -rf /var/cache/yum/\*





#RUN 执行以下命令

RUN yum install -y wget  && yum clean all





#WORKDIR 相当于cd

WORKDIR /usr/local/app

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