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ubuntu22.04安装显卡、CUDA(含多个CUDA切换)、CUDNN、pytorch_ubuntu22安装cuda

作者：盐析白兔 | 2024-08-08 10:21:09

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ubuntu22安装cuda

一、显卡

「必须」更新软件列表和安装必要软件、依赖


sudo apt-get update #更新软件列表
     
sudo apt-get install g++
     
sudo apt-get install gcc
     
sudo apt-get install make

禁用 nouveau 驱动

ouveau是Ubuntu自带的显卡驱动，但他是核显，我这里想安装独显，就得把他禁掉

命令（cmd）

sudo gedit /etc/modprobe.d/blacklist.conf

（输入密码）

（自动打开的）文本，在末尾


# added
blacklist nouveau
blacklist lbm-nouveau
options nouveau modeset=0
alias nouveau off
alias lbm-nouveau off

ctrl+s 保存

更新重启


sudo update-initramfs –u
sudo reboot # 重启电脑

lsmod | grep nouveau  # 输出内容为空，则表示成功禁用

安装驱动

选择合适版本：官网查询，记住版本号xxx.yy

卸载之前的


sudo apt-get remove nvidia-*  # 卸载之前的
 
add-apt-repository ppa:graphics-drivers/ppa  # 更新显卡驱动的源
 
apt-get install nvidia-driver-xxx  # xxx是显卡版本，需要修改

检查
```
nvidia-smi
```
安装成功。

CUDA version :12.4 ——最大CUDA版本

二、CUDA

CUDA-显卡对应

pytorch 官网：CUDA11.8 12.1

安装依赖

sudo apt-get install freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libgl1-mesa-glx libglu1-mesa libglu1-mesa-dev

安装CUDA

CUDA 11.8
CUDA 12.1

一路选择下来，我最后选了runfile(local)，因为命令行少

第一行加sudo，能防止权限不够


# 11.8
sudo wget https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_520.61.05_linux.run
sudo sh cuda_11.8.0_520.61.05_linux.run


# 12.1
sudo wget https://developer.download.nvidia.com/compute/cuda/12.1.0/local_installers/cuda_12.1.0_530.30.02_linux.run
sudo sh cuda_12.1.0_530.30.02_linux.run

安装时的选择
1. continue
2. 写 accept
3. 不要driver：在driver处按enter
4. install
5. （如果有多个CUDA，会问你symlink改不改）: Yes
检查
```
nvcc -V
```

成功！

安装CUDA失败，重装该版本（希望用不上）

环境配置之cuda的卸载（ubuntu）_ubuntu卸载cuda-CSDN博客

切换CUDA（选读）

切换脚本

```
sudo vim switch-cuda.sh
```


#!/usr/bin/env bash
 
# Copyright (c) 2018 Patrick Hohenecker
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
 
# author:   Patrick Hohenecker <mail@paho.at>
# version:  2018.1
# date:     May 15, 2018
 
 
set -e
 
 
# ensure that the script has been sourced rather than just executed
if [[ "${BASH_SOURCE[0]}" = "${0}" ]]; then
    echo "Please use 'source' to execute switch-cuda.sh!"
    exit 1
fi
 
INSTALL_FOLDER="/usr/local"  # the location to look for CUDA installations at
TARGET_VERSION=${1}          # the target CUDA version to switch to (if provided)
 
# if no version to switch to has been provided, then just print all available CUDA installations
if [[ -z ${TARGET_VERSION} ]]; then
    echo "The following CUDA installations have been found (in '${INSTALL_FOLDER}'):"
    ls -l "${INSTALL_FOLDER}" | egrep -o "cuda-[0-9]+\\.[0-9]+$" | while read -r line; do
        echo "* ${line}"
    done
    set +e
    return
# otherwise, check whether there is an installation of the requested CUDA version
elif [[ ! -d "${INSTALL_FOLDER}/cuda-${TARGET_VERSION}" ]]; then
    echo "No installation of CUDA ${TARGET_VERSION} has been found!"
    set +e
    return
fi
 
# the path of the installation to use
cuda_path="${INSTALL_FOLDER}/cuda-${TARGET_VERSION}"
 
# filter out those CUDA entries from the PATH that are not needed anymore
path_elements=(${PATH//:/ })
new_path="${cuda_path}/bin"
for p in "${path_elements[@]}"; do
    if [[ ! ${p} =~ ^${INSTALL_FOLDER}/cuda ]]; then
        new_path="${new_path}:${p}"
    fi
done
 
# filter out those CUDA entries from the LD_LIBRARY_PATH that are not needed anymore
ld_path_elements=(${LD_LIBRARY_PATH//:/ })
new_ld_path="${cuda_path}/lib64:${cuda_path}/extras/CUPTI/lib64"
for p in "${ld_path_elements[@]}"; do
    if [[ ! ${p} =~ ^${INSTALL_FOLDER}/cuda ]]; then
        new_ld_path="${new_ld_path}:${p}"
    fi
done
 
# update environment variables
export CUDA_HOME="${cuda_path}"
export CUDA_ROOT="${cuda_path}"
export LD_LIBRARY_PATH="${new_ld_path}"
export PATH="${new_path}"
 
echo "Switched to CUDA ${TARGET_VERSION}."
 
set +e
return


# 保存，优先选1
:w !sudo tee %
 
:wq!


source switch-cuda.sh  # 查看拥有的CUDA版本
 
source switch-cuda.sh XX.X  # XX.X为版本号

三、CUDNN

选择合适版本：官网，下载tar（或者三个包）
单个包跳到3，
三个包点链接：ubuntu下的cudnn安装_cudnn安装 ubuntu-CSDN博客

解压


tar -xvf cudnn-linux-x86_64-8.9.6.50_cuda11-archive.tar.xz 
 
# 改文件名称
# 或者可以删掉文件名，然后把想解压的文件拖到命令窗口里，自动获取文件路径。都可以

进入文件夹，复制


cd cudnn-linux-x86_64-8.9.6.50_cuda11-archive/
 
sudo cp -d -r ./lib/* /usr/local/cuda-11.8/lib64/
sudo cp -r ./include/* /usr/local/cuda-11.8/include/

测试


sudo chmod a+r /usr/local/cuda-11.8/include/cudnn.h /usr/local/cuda-11.8/lib64/libcudnn*
 
cat /usr/local/cuda-11.8/include/cudnn_version.h | grep CUDNN_MAJOR -A 2

出现的三个数字==版本号

四、pytorch

官网：Start Locally | PyTorch

官网命令

pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

我用的conda xxx，没有conda用pip3 也行，据说pip3快

检查（依然在CMD）


python  # 如果报错，试python3
import torch
from torch.backends import  cudnn
print(cudnn.is_available())
print(torch.backends.cudnn.version())
print(torch.cuda.is_available())  # True，则gpu版本的pytorch安装成功
print(torch.zeros(1).cuda())