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Ubuntu 装机经验

Ubuntu 装机经验

作者: Apples_3d38 | 来源:发表于2018-05-13 12:06 被阅读0次

    Ubuntu 装机经验

    显卡配置

    sudo apt-get remove --purge nvidia*
    sudo add-apt-repository ppa:graphics-drivers
    sudo apt-get update
    # 此处使用显卡为 Titan X,由于查不到合适得驱动故使用老版本
    sudo apt-get install nvidia-375
    

    安装Cuda

    sudo dpkg -i cuda-repo-ubuntu1704-9-0-local_9.0.176-1_amd64.deb
    sudo apt-get update
    sudo apt-get install cuda
    

    安装Nvidia Docker

    # install docker-ce
    sudo apt-get update
    
    # Install packages to allow apt to use a repository over HTTPS:
    sudo apt-get install \
        apt-transport-https \
        ca-certificates \
        curl \
        software-properties-common
    
    # Add Docker’s official GPG key:
    curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
    
    # Verify that you now have the key with the fingerprint 9DC8 5822 9FC7 DD38 854A E2D8 8D81 803C 0EBF CD88, by searching for the last 8 characters of the fingerprint.
    sudo apt-key fingerprint 0EBFCD88
    
    sudo add-apt-repository \
       "deb [arch=amd64] https://download.docker.com/linux/ubuntu \
       $(lsb_release -cs) \
       stable"
    sudo apt-get update
    sudo apt-get install docker-ce
    
    # nvidia-docker
    # If you have nvidia-docker 1.0 installed: we need to remove it and all existing GPU containers
    docker volume ls -q -f driver=nvidia-docker | xargs -r -I{} -n1 docker ps -q -a -f volume={} | xargs -r docker rm -f
    sudo apt-get purge -y nvidia-docker
    
    # Add the package repositories
    curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | \
      sudo apt-key add -
    distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
    curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | \
      sudo tee /etc/apt/sources.list.d/nvidia-docker.list
    sudo apt-get update
    
    # Install nvidia-docker2 and reload the Docker daemon configuration
    sudo apt-get install -y nvidia-docker2
    sudo pkill -SIGHUP dockerd
    
    # Test nvidia-smi with the latest official CUDA image
    # 此处使用镜像以加速
    docker run --runtime=nvidia --rm registry.docker-cn.com/nvidia/cuda nvidia-smi
    

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