Ubuntu 22.04 下安装cuda、cuDNN的过程。

一、检查是否安装nvidia显卡

通过命令lspci | grep -i nvidia 查看是否安装nvidia显卡，如果有输出则说明系统有nvidia显示。
输出如下：

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00:05.0 3D controller: NVIDIA Corporation GP102GL [Tesla P40] (rev a1)

二、安装NVIDIA显卡的官方驱动

  1. 增加官方的apt源

    从NVIDIA官网CUDA下载页面获取apt源。

    1710495677496.jpg

    如上图所示的界面，选择Linux –> x86_64 –> Ubuntu –> 22.04 –> deb(network),
    具体的系统架构，根据真实系统进行选择。可以得到具体的安装命令。

  2. 执行安装命令

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    wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
    sudo dpkg -i cuda-keyring_1.1-1_all.deb
    sudo apt-get update

  3. 获取可用驱动程序

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    ubuntu-drivers devices

    输出信息为：

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    == /sys/devices/pci0000:00/0000:00:02.0/0000:04:00.0 ==
    modalias : pci:v000010DEd00001B38sv000010DEsd000011D9bc03sc02i00
    vendor   : NVIDIA Corporation
    model    : GP102GL [Tesla P40]
    driver   : nvidia-driver-515 - third-party non-free
    driver   : nvidia-driver-545 - third-party non-free
    driver   : nvidia-driver-525 - third-party non-free
    driver   : nvidia-driver-535-server - distro non-free
    driver   : nvidia-driver-470 - distro non-free
    driver   : nvidia-driver-520 - third-party non-free
    driver   : nvidia-driver-525-server - distro non-free
    driver   : nvidia-driver-535 - third-party non-free
    driver   : nvidia-driver-550 - third-party non-free recommended
    driver   : nvidia-driver-470-server - distro non-free
    driver   : nvidia-driver-418-server - distro non-free
    driver   : nvidia-driver-450-server - distro non-free
    driver   : nvidia-driver-390 - distro non-free
    driver   : xserver-xorg-video-nouveau - distro free builtin

    找前面为driver，后面为recommend 的记录。
    上面的输出结果为：nvidia-driver-550

  4. 安装驱动

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    sudo apt install nvidia-driver-550

    安装完成后，重启电脑

  5. 查看驱动是否安装成功

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    nvidia-smi

    输出结果如下显示有一块显卡:

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    +-----------------------------------------------------------------------------------------+
    | NVIDIA-SMI 550.54.14              Driver Version: 550.54.14      CUDA Version: 12.4     |
    |-----------------------------------------+------------------------+----------------------+
    | GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
    | Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
    |                                         |                        |               MIG M. |
    |=========================================+========================+======================|
    |   0  Tesla P40                      Off |   00000000:00:05.0 Off |                    0 |
    | N/A   28C    P8             11W /  250W |       0MiB /  23040MiB |      0%      Default |
    |                                         |                        |                  N/A |
    +-----------------------------------------+------------------------+----------------------+

    +-----------------------------------------------------------------------------------------+
    | Processes:                                                                              |
    |  GPU   GI   CI        PID   Type   Process name                              GPU Memory |
    |        ID   ID                                                               Usage      |
    |=========================================================================================|
    |  No running processes found                                                             |
    +-----------------------------------------------------------------------------------------+

三、安装cuda、cuDNN

可以参考cuda官网
与cuDNN官网

下面是已经设置过官方源(在本文第二部分已经设置过官方源)后的执行过程：

  1. 执行安装命令

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    sudo apt-get -y install cuda
    sudo apt-get -y install cudnn

  2. 配置环境变量并验证

    bash环境下，通过命令cat >> .bashrc << EOF逐行输入以下文本

    zsh环境下，通过命令cat >> .zshrc << EOF逐行输入以下文本

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    export CUDA_HOME=/usr/local/cuda
    export LD_LIBRARY_PATH=\$CUDA_HOME/lib64\${LD_LIBRARY_PATH:+:\${LD_LIBRARY_PATH}}
    export PATH=\$CUDA_HOME/bin\${PATH:+:\${PATH}}
    EOF

    首次配置完环境变量后通过source .bashrc或source .zshrc命令使环境变量生效。

    配置完环境变量后，通过命令nvcc -V检查cuda版本，输出结果如下所示：

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    nvcc: NVIDIA (R) Cuda compiler driver
    Copyright (c) 2005-2024 NVIDIA Corporation
    Built on Tue_Feb_27_16:19:38_PST_2024
    Cuda compilation tools, release 12.4, V12.4.99
    Build cuda_12.4.r12.4/compiler.33961263_0

  3. 验证与测试

    • 安装必要的依赖
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    sudo apt-get install libfreeimage3 libfreeimage-dev
    • 编译测试代码
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    cd ~
    cp -r /usr/src/cudnn_samples_v9 ./
    cd cudnn_samples_v9/mnistCUDNN
    make clean && make
    • 运行测试代码
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    ./mnistCUDNN

    如果cudnn安装成功会显示如下信息：

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    Test passed!