https://www.cyberciti.biz/faq/ubuntu-linux-install-nvidia-driver-latest-proprietary-driver/
https://blog.csdn.net/YPP0229/article/details/108939159
curl -d "user=学号&pass=密码" "10.3.8.211/login" apt update -y && apt upgrade -y apt-get update -y apt install tmux nano screen zsh -y
apt install dkms service lightdm stop systemctl disable lightdm add-apt-repository ppa:graphics-drivers/ppa apt-get update apt-cache search nvidia*
apt install nvidia-410 reboot nvidia-persistenced --persistence-mode
wget https://developer.download.nvidia.cn/compute/cuda/10. 0/secure/Prod/local_installers/cuda_10.0.130_410.48_l inux.run? V9wXUO1KBqX5IEaNjbvudEJlM1Yj2ZRvjvkGKX7d5wYyRCHiThHh- gizUwQx24qMjpiggRz1KcY9oFNVQCpUNNmXswsORB3UJMGK_PSCRK OvnkxGfGVifbgvz-B- htDVZzOPJQp3nzwsu50UevmCkjoyN8g6_J45tfrUjc8xIO19wWfu7 0LsiIn5A_A -O cuda_10.0.130_410.48_linux.run
chmod +x cuda_10.0.130_410.48_linux.run ./cuda_10.0.130_410.48_linux.run nano /etc/profile $ export PATH=$PATH:/usr/local/cuda-10.0/bin $ export LD_LIBRARY_PATH=/usr/local/cuda- 10.0/lib64:$LD_LIBRARY_PATH sudo apt-get install freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libgl1-mesa-glx libglu1-mesa libglu1-mesa-dev wget https://developer.download.nvidia.cn/compute/machine- learning/cudnn/secure/7.6.5.32/Production/10.0_201910 31/cudnn-10.0-linux-x64-v7.6.5.32.tgz?2R93GPI- OQyQOfK1oCEtLRNcWwqjQBsPZyauFPh_tfLro_AGk4KBd9- 3przJ_vfuLwT_5cn4aRJ7jMzONmbqiG32w- jQL11JOn7H2sP0Al8JJ9YD9WZZGA- aPcKJc9cL80dBWu5rO4xAkOIhF7_c70g9jG9AWVSddn5rcFEqN44q ZasHWmMb_mAM-RFEKZLcdMIgHCDywSKLdunK9pNZxu8- JrbifxEmrw -O cudnn-10.0-linux-x64-v7.6.5.32.tgz tar zxvf cudnn-10.0-linux-x64-v7.6.5.32.tgz -C . sudo cp cuda/include/cudnn.h /usr/local/cuda- 10.0/include sudo cp cuda/lib64/libcudnn* /usr/local/cuda- 10.0/lib64 sudo chmod a+r /usr/local/cuda-10.0/include/cudnn.h sudo chmod a+r /usr/local/cuda-10.0/lib64/libcudnn* sudo cp cuda/include/cudnn.h /usr/local/cuda- 10.1/include sudo cp cuda/lib64/libcudnn* /usr/local/cuda- 10.1/lib64 sudo chmod a+r /usr/local/cuda-10.1/include/cudnn.h sudo chmod a+r /usr/local/cuda-10.1/lib64/libcudnn* nvidia-persistenced --persistence-mode
apt-get update apt-get install docker.io curl -s -L https://nvidia.github.io/nvidia- docker/gpgkey | sudo apt-key add - distribution=$(. /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 sudo apt-get install nvidia-docker2 sudo pkill -SIGHUP dockerd sudo mkdir -p /home/docker sudo tee /etc/docker/daemon.json <<-'EOF' { "data-root": "/home/docker", "iptables": true, "ip-masq": false, "storage-driver": "overlay2", "runtimes": { "nvidia": { "path": "nvidia-container-runtime", "runtimeArgs": [] } }, "default-runtime": "nvidia", "registry-mirrors": [ "https://kfwkfulq.mirror.aliyuncs.com", "https://2lqq34jg.mirror.aliyuncs.com", "https://pee6w651.mirror.aliyuncs.com", "https://registry.docker-cn.com", "http://hub-mirror.c.163.com" ]
} EOF sudo systemctl enable docker && sudo systemctl start docker
sudo ufw disable apt install selinux-utils sudo setenforce 0 sudo nano /etc/selinux/config $ SELINUX=permissive sudo nano /etc/sysctl.conf $ net.ipv4.ip_forward = 1 #开启ipv4转发，允 许内置路由 #写入后执行如下命令生效： sudo sysctl -p sudo iptables -P FORWARD ACCEPT nano /etc/rc.local $ /usr/sbin/iptables -P FORWARD ACCEPT # exit 0上方写入 sudo swapoff -a nano /etc/sysctl.d/k8s.conf $ net.bridge.bridge-nf-call-ip6tables = 1 $ net.bridge.bridge-nf-call-iptables = 1 sudo sysctl --system
sudo apt-get update && sudo apt-get install -y apt- transport-https curl sudo curl -s https://mirrors.aliyun.com/kubernetes/apt/doc/apt- key.gpg | sudo apt-key add - sudo tee /etc/apt/sources.list.d/kubernetes.list <<- 'EOF'