nvidia驱动安装
网络不好时，最好配置一个国内的ubantu源,此次安装Ubantu20.04.4 sudo add-apt-repository ppa:graphics-drivers/ppa sudo apt update sudo apt upgrade 使用ubuntu-drivers工具检测可用的NVIDIA驱动，并安装推荐的驱动： ubuntu-drivers devices sudo ubuntu-drivers autoinstall
nvidia-smi
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CUDA
nvida驱动的作用是让电脑识别显卡，因为你安装的显卡是nvida的，所以安装他家的驱动
而CUDA是深度学习平台，让C++开发者可以通过CUDA平台使用显卡，对应的深度学习库为CUDNN
pytorch是个平台，给python开发者使用的,cuda就对应pytorch
ubantu22.04版下载
https://developer.nvidia.com/cuda-12-4-0-download-archive?target_os=Linux&target_arch=x86_64&Distribution=Ubuntu
cudnn
https://developer.nvidia.cn/cudnn
参考
https://blog.csdn.net/qq_44862915/article/details/136337934
https://blog.csdn.net/QDU_zty/article/details/136584139?utm_medium=distribute.pc_relevant.none-task-blog-2~default~baidujs_baidulandingword~default-4-136584139-blog-136337934.235^v43^pc_blog_bottom_relevance_base9&spm=1001.2101.3001.4242.3&utm_relevant_index=7
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ubantu22.04版下载
https://developer.nvidia.com/cuda-12-4-0-download-archive?target_os=Linux&target_arch=x86_64&Distribution=Ubuntu
wget https://developer.download.nvidia.com/compute/cuda/12.4.0/local_installers/cuda_12.4.0_550.54.14_linux.runsudo sh cuda_12.4.0_550.54.14_linux.run sudo sh cuda_12.4.0_550.54.14_linux.run 注意WSL中的ubuntu与直接安装在电脑/服务器上的ubuntu是有区别的 
历史版本 https://developer.nvidia.com/cuda-toolkit-archive 可以执行nvidia-smi查看对应的CUDA版本 # nvidia-smi Fri Nov 1 20:40:46 2024 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 555.52.01 Driver Version: 555.99 CUDA Version: 12.5 | |-----------------------------------------+------------------------+----------------------+ sudo apt install dkms wget https://developer.download.nvidia.com/compute/cuda/12.4.0/local_installers/cuda_12.4.0_550.54.14_linux.run sudo sh cuda_12.4.0_550.54.14_linux.run https://developer.nvidia.com/cuda-12-5-1-download-archive wget https://developer.download.nvidia.com/compute/cuda/12.5.1/local_installers/cuda_12.5.1_555.42.06_linux.run sudo sh cuda_12.5.1_555.42.06_linux.run 
export PATH=/usr/local/cuda-12.5/bin:$PATH export LD_LIBRARY_PATH=/usr/local/cuda-12.5/lib64:$LD_LIBRARY_PATH export CUDA_HOME=/usr/local/cuda wget https://developer.download.nvidia.com/compute/cuda/12.6.2/local_installers/cuda_12.6.2_560.35.03_linux.run run的方式，只需要执行一个文件就可以了 如果是deb的方式，则需要执行一系列类型下面的操作 wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-ubuntu2204.pin sudo mv cuda-ubuntu2204.pin /etc/apt/preferences.d/cuda-repository-pin-600 wget https://developer.download.nvidia.com/compute/cuda/12.4.0/local_installers/cuda-repo-ubuntu2204-12-4-local_12.4.0-550.54.14-1_amd64.deb sudo dpkg -i cuda-repo-ubuntu2204-12-4-local_12.4.0-550.54.14-1_amd64.deb sudo cp /var/cuda-repo-ubuntu2204-12-4-local/cuda-*-keyring.gpg /usr/share/keyrings/ sudo apt-get update sudo apt-get -y install cuda-toolkit-12-4
export PATH=/usr/local/cuda-12.4/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-12.4/lib64:$LD_LIBRARY_PATH
$ ll /usr/local/cuda
lrwxrwxrwx 1 root root 22 5月 9 15:40 /usr/local/cuda -> /etc/alternatives/cuda/
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https://developer.nvidia.com/cudnn-downloads 
wget https://developer.download.nvidia.com/compute/cudnn/9.1.1/local_installers/cudnn-local-repo-ubuntu2204-9.1.1_1.0-1_amd64.deb sudo dpkg -i cudnn-local-repo-ubuntu2204-9.1.1_1.0-1_amd64.deb sudo cp /var/cudnn-local-repo-ubuntu2204-9.1.1/cudnn-*-keyring.gpg /usr/share/keyrings/ sudo apt-get update sudo apt-get -y install cudnn https://docs.nvidia.com/ https://docs.nvidia.com/deeplearning/cudnn/latest/ To install for CUDA 11, perform the above configuration but install the CUDA 11 specific package: sudo apt-get -y install cudnn-cuda-11 To install for CUDA 12, perform the above configuration but install the CUDA 12 specific package: sudo apt-get -y install cudnn-cuda-12 如果之前单独安装过CUDA12，那么再执行下面的命令，它会提示已经安装过CUDA12 sudo apt-get -y install cudnn9-cuda-12 xt@ai:/opt/soft$ sudo apt-get -y install cudnn9-cuda-12 Reading package lists... Done Building dependency tree... Done Reading state information... Done cudnn9-cuda-12 is already the newest version (9.1.1.17-1). cudnn9-cuda-12 set to manually installed. The following packages were automatically installed and are no longer required: libwpe-1.0-1 libwpebackend-fdo-1.0-1 Use 'sudo apt autoremove' to remove them. 0 upgraded, 0 newly installed, 0 to remove and 14 not upgraded. 运行示例 https://docs.nvidia.com/deeplearning/cudnn/latest/installation/build-run-cudnn.html |
https://developer.nvidia.com/cuda-12-4-0-download-archive?target_os=Linux&target_arch=x86_64&Distribution=WSL-Ubuntu&target_version=2.0&target_type=deb_local wget https://developer.download.nvidia.com/compute/cuda/repos/wsl-ubuntu/x86_64/cuda-wsl-ubuntu.pin sudo mv cuda-wsl-ubuntu.pin /etc/apt/preferences.d/cuda-repository-pin-600 wget https://developer.download.nvidia.com/compute/cuda/12.4.0/local_installers/cuda-repo-wsl-ubuntu-12-4-local_12.4.0-1_amd64.deb sudo dpkg -i cuda-repo-wsl-ubuntu-12-4-local_12.4.0-1_amd64.deb sudo cp /var/cuda-repo-wsl-ubuntu-12-4-local/cuda-*-keyring.gpg /usr/share/keyrings/ sudo apt-get update sudo apt-get -y install cuda-toolkit-12-4 xt@qisan:/opt/soft$ ll /usr/local/cuda lrwxrwxrwx 1 root root 22 May 9 17:04 /usr/local/cuda -> /etc/alternatives/cuda/ xt@qisan:/opt/soft$ ll /usr/local/cuda cuda/ cuda-12/ cuda-12.4/ |
https://developer.nvidia.com/cudnn-downloads 没有针对WSL-Ubantu的cudnn版本，只有针对Ubantu的 |
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参考