igozhang

——

    CentOS82配置深度学习环境

    Env:
    Cent82 Nvidia3090GTX 显卡
    安装基础包
    yum install -y yum-utils \
      device-mapper-persistent-data \
      lvm2
    设置稳定仓库
    yum-config-manager \
        --add-repo \
        https://mirrors.aliyun.com/docker-ce/linux/centos/docker-ce.repo
    
    安装Docker Engine - Community
    yum -y install docker-ce docker-ce-cli containerd.io
    
    systemctl start docker
    systemctl enable docker
    
    安装显卡驱动
    yum -y install pkg-config gcc gcc-c++ kernel-devel kernel-headers dkms epel-release
    
    禁用 nouveau
    grub2-editenv - set "$(grub2-editenv - list | grep kernelopts) nouveau.modeset=0"
    echo -e "blacklist nouveau\noptions nouveau modeset=0" > /etc/modprobe.d/blacklist.conf
    验证: 重启后
    lsmod |grep nouveau
    
    yum -y update
    
    # grep nvidia /etc/modprobe.d/* /lib/modprobe.d/*
    注释掉这行才能安装
    /lib/modprobe.d/dist-blacklist.conf:blacklist nvidiafb
    
    带内核路径
    ./NVIDIA-Linux-x86_64-470.57.02.run --kernel-source-path=/usr/src/kernels/4.18.0-305.10.2.el8_4.x86_64 -k $(uname -r)
    
    安装cuda
    # ./cuda_11.4.1_470.57.02_linux.run
    Accept ->install
    
    export PATH=/usr/local/cuda-11.4/bin:$PATH
    export LD_LIBRARY_PATH=/usr/local/cuda-11.4/lib64:$LD_LIBRARY_PATH
    export CUDA_HOME=/usr/local/cuda
    
    nvcc -V
    
    安装cudnn
    tar -xf cudnn-11.4-linux-x64-v8.2.2.26.tgz
    cp cuda/include/cudnn*.h /usr/local/cuda-11.4/include
    cp cuda/lib64/libcudnn* /usr/local/cuda-11.4/lib64/
    chmod a+r /usr/local/cuda-11.4/include/cudnn*.h /usr/local/cuda-11.4/lib64/libcudnn*
    验证:
    cat /usr/local/cuda/include/cudnn_version.h | grep CUDNN_MAJOR -A 2
    
    给用户添加docker组
    useradd igo;
    passwd igo
    # cat /etc/group | grep docker
    docker:x:985:
    usermod -aG docker igo
    usermod -aG wheel  igo 添加sudo组
    newgrp docker
    
    配置完可以 跑 google_bert 3dmark benchmark 测试性能
    

    MP3