目录windows安装cuda 安装激活环境 A 并安装 CUDA 11.8conda 安装cuda-toolkit参数说明安装CUDA各个历史版本下载https://developer.nvidia.com/cuda-toolkit-archivecudnn deb格式安装设置环境变量windows安装https://developer.nvidia.com/cuda-12-4-0-download-archivecuda_12.4.0_551.61_windows.exe在安装CUDA时选择自定义安装然后取消勾选Visual Studio Integration这一项其他保持默认继续安装。安装完成后CUDA本身就能正常工作不影响PyTorch使用。cuda 安装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/12.8.0/local_installers/cuda-repo-ubuntu2204-12-8-local_12.8.0-570.86.10-1_amd64.deb sudo dpkg -i cuda-repo-ubuntu2204-12-8-local_12.8.0-570.86.10-1_amd64.deb sudo cp /var/cuda-repo-ubuntu2204-12-8-local/cuda-*-keyring.gpg /usr/share/keyrings/ sudo apt-get update sudo apt-get -y install cuda-toolkit-12-8编辑 ~/.bashrc 或 ~/.zshrc加入 export PATH/usr/local/cuda-12.8/bin:$PATH export LD_LIBRARY_PATH/usr/local/cuda-12.8/lib64:$LD_LIBRARY_PATH 然后执行 source ~/.bashrc激活环境 A 并安装 CUDA 11.8bashconda activate env_a conda install -c nvidia/label/cuda-11.8.0 cuda-toolkit conda install -c nvidia/label/cuda-11.8.0 cudnn nvcc --version # 显示 11.8激活环境 B未安装 CUDA 或安装了其他版本conda activate env_b nvcc --version # 若未安装则提示命令不存在或显示其他版本如 12.2conda 安装cuda-toolkitconda install -c nvidia/label/cuda-12.4.0 cuda-toolkit conda install -c nvidia/label/cuda-12.1.0 cuda-toolkit配置清华源后可以安装成功,速度比较慢可能需要一个多小时。如果在环境里面安装的只对当前环境有效其他环境不能共享使用但是再安装速度可以加快。参数说明-c 是cache的意思缓存目录在别的conda环境安装速度回快很多。安装CUDA下载CUDA从https://developer.nvidia.com/cuda-downloads下载对应版本的cuda安装包我下载的是deblocal版各个历史版本下载https://developer.nvidia.com/cuda-toolkit-archive下载 runfile(local)sudo sh cuda_11.8.0_520.61.05_linux.run安装完成后重启一下cudnn deb格式安装wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004.pinsudo mv cuda-ubuntu2004.pin /etc/apt/preferences.d/cuda-repository-pin-600wget https://developer.download.nvidia.com/compute/cuda/12.1.0/local_installers/cuda-repo-ubuntu2004-12-1-local_12.1.0-530.30.02-1_amd64.debsudo dpkg -i cuda-repo-ubuntu2004-12-1-local_12.1.0-530.30.02-1_amd64.debsudo cp /var/cuda-repo-ubuntu2004-12-1-local/cuda-*-keyring.gpg /usr/share/keyrings/sudo apt-get updatesudo apt-get -y install cudawget https://developer.download.nvidia.com/compute/cuda/12.1.0/local_installers/cuda_12.1.0_530.30.02_linux.runsudo sh cuda_12.1.0_530.30.02_linux.runchmod x ./cudnn-local-repo-ubuntu2004-8.9.7.29_1.0-1_amd64.deb安装软件包使用以下命令开始安装.deb文件sudo dpkg -i /path/to/your_file.deb有时会有提示sudo cp /var/cudnn-local-repo-ubuntu2004-8.9.7.29/cudnn-local-CD2C2DD4-keyring.gpg /usr/share/keyrings/执行一下再执行sudo dpkg -i /runxxx.deb设置环境变量在打开的文件中加入如下两句话vim /etc/profileexport PATH/usr/local/cuda/bin:$PATH export LD_LIBRARY_PATH/usr/local/cuda/lib64:$LD_LIBRARY_PATH保存后使环境变量立即生效source /etc/profilecuda拷贝也可以cp -R /home/model-server/cuda-12.1 /mnt/envsexport PATH/mnt/envs//cuda-12.1/bin:$PATH
目录windows安装cuda 安装激活环境 A 并安装 CUDA 11.8conda 安装cuda-toolkit参数说明安装CUDA各个历史版本下载https://developer.nvidia.com/cuda-toolkit-archivecudnn deb格式安装设置环境变量windows安装https://developer.nvidia.com/cuda-12-4-0-download-archivecuda_12.4.0_551.61_windows.exe在安装CUDA时选择自定义安装然后取消勾选Visual Studio Integration这一项其他保持默认继续安装。安装完成后CUDA本身就能正常工作不影响PyTorch使用。cuda 安装wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-ubuntu2204.pin sudo mv cuda-ubuntu2204.pin /etc/apt/preferences.d/cuda-repository-pin-600 wget https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda-repo-ubuntu2204-12-8-local_12.8.0-570.86.10-1_amd64.deb sudo dpkg -i cuda-repo-ubuntu2204-12-8-local_12.8.0-570.86.10-1_amd64.deb sudo cp /var/cuda-repo-ubuntu2204-12-8-local/cuda-*-keyring.gpg /usr/share/keyrings/ sudo apt-get update sudo apt-get -y install cuda-toolkit-12-8编辑 ~/.bashrc 或 ~/.zshrc加入 export PATH/usr/local/cuda-12.8/bin:$PATH export LD_LIBRARY_PATH/usr/local/cuda-12.8/lib64:$LD_LIBRARY_PATH 然后执行 source ~/.bashrc激活环境 A 并安装 CUDA 11.8bashconda activate env_a conda install -c nvidia/label/cuda-11.8.0 cuda-toolkit conda install -c nvidia/label/cuda-11.8.0 cudnn nvcc --version # 显示 11.8激活环境 B未安装 CUDA 或安装了其他版本conda activate env_b nvcc --version # 若未安装则提示命令不存在或显示其他版本如 12.2conda 安装cuda-toolkitconda install -c nvidia/label/cuda-12.4.0 cuda-toolkit conda install -c nvidia/label/cuda-12.1.0 cuda-toolkit配置清华源后可以安装成功,速度比较慢可能需要一个多小时。如果在环境里面安装的只对当前环境有效其他环境不能共享使用但是再安装速度可以加快。参数说明-c 是cache的意思缓存目录在别的conda环境安装速度回快很多。安装CUDA下载CUDA从https://developer.nvidia.com/cuda-downloads下载对应版本的cuda安装包我下载的是deblocal版各个历史版本下载https://developer.nvidia.com/cuda-toolkit-archive下载 runfile(local)sudo sh cuda_11.8.0_520.61.05_linux.run安装完成后重启一下cudnn deb格式安装wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004.pinsudo mv cuda-ubuntu2004.pin /etc/apt/preferences.d/cuda-repository-pin-600wget https://developer.download.nvidia.com/compute/cuda/12.1.0/local_installers/cuda-repo-ubuntu2004-12-1-local_12.1.0-530.30.02-1_amd64.debsudo dpkg -i cuda-repo-ubuntu2004-12-1-local_12.1.0-530.30.02-1_amd64.debsudo cp /var/cuda-repo-ubuntu2004-12-1-local/cuda-*-keyring.gpg /usr/share/keyrings/sudo apt-get updatesudo apt-get -y install cudawget https://developer.download.nvidia.com/compute/cuda/12.1.0/local_installers/cuda_12.1.0_530.30.02_linux.runsudo sh cuda_12.1.0_530.30.02_linux.runchmod x ./cudnn-local-repo-ubuntu2004-8.9.7.29_1.0-1_amd64.deb安装软件包使用以下命令开始安装.deb文件sudo dpkg -i /path/to/your_file.deb有时会有提示sudo cp /var/cudnn-local-repo-ubuntu2004-8.9.7.29/cudnn-local-CD2C2DD4-keyring.gpg /usr/share/keyrings/执行一下再执行sudo dpkg -i /runxxx.deb设置环境变量在打开的文件中加入如下两句话vim /etc/profileexport PATH/usr/local/cuda/bin:$PATH export LD_LIBRARY_PATH/usr/local/cuda/lib64:$LD_LIBRARY_PATH保存后使环境变量立即生效source /etc/profilecuda拷贝也可以cp -R /home/model-server/cuda-12.1 /mnt/envsexport PATH/mnt/envs//cuda-12.1/bin:$PATH
