ubuntu安装显卡驱动和cuda教程

目录

1. 卸载原始的驱动2. 下载新显卡驱动2.1 安装显卡驱动3 安装cuda

查看nvcc -V

cudatoolkit



4. 安装cudnn5. 安装anaconda


添加环境变量替换anaconda源查看tensorflow版本

测试安装的tensorflow

写在最前面：

最新的版本不一定是好的，合适的才是最好的，建议cuda10.1+cudnn7.6.5

1. 卸载原始的驱动

#查看安装的包

apt list –installed|grep -i nvidia

#卸载包

apt-get purge nvidia*

2. 下载新显卡驱动

https://www.nvidia.cn/Download/index.aspx?lang=cn

复制下载链接，在系统中用wget下载

#下载

wget https://cn.download.nvidia.cn/tesla/470.57.02/NVIDIA-Linux-x86_64-470.57.02.run

#安装

sudo sh NVIDIA-Linux-x86_64-470.57.02.run

2.1 安装显卡驱动

3 安装cuda

官网链接

选择cuda版本，要和驱动的cuda版本一致

wget https://developer.nvidia.com/compute/cuda/10.0/Prod/local_installers/cuda_10.0.130_410.48_linux

sudo sh cuda_10.0.130_410.48_linux

添加环境变量，将上图中的建议加到.bashrc文件中

Please make sure that

          PATH includes /usr/local/cuda-11.4/bin

          LD_LIBRARY_PATH includes /usr/local/cuda-11.4/lib64, or,

                   add /usr/local/cuda-11.4/lib64 to /etc/ld.so.conf and run ldconfig as root

vim ~/.bashrc

#添加路径

export PATH=$PATH:/usr/local/cuda-11.4/bin

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-11.4/lib64

#使环境生效

source ~/.bashrc

查看nvcc -V

cudatoolkit

sudo apt install nvidia-cuda-toolkit

4. 安装cudnn

安装cudnn

https://developer.nvidia.com/rdp/cudnn-download

wget https://developer.download.nvidia.cn/compute/machine-learning/cudnn/secure/8.2.2/11.4_07062022/Ubuntu18_04-x64/libcudnn8_8.2.2.26-1%2Bcuda11.4_amd64.deb?aJLLhXbzztwE4iizwf68uvg1s73kk4KKBGqv6B0UkO9HhnOhOsGHlyo1Br5CWc0nAIJLmc6C5SkLYqbdQqdZBoAdcVQgBTmWKXJXigR7roUeXd0VIKUuM57UKWMp3BUQgr6SQ4kkGnRRtUJ5mJt

dpkg -i libcudnn8_8.2.2.26-1+cuda11.4_amd64.deb

5. 安装anaconda

wget https://mirror.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-2022.05-Linux-x86_64.sh

添加环境变量

vim ~/.bashrc

export PATH=”/usr/local/anaconda3/bin:$PATH”

source ~/.bashrc

替换anaconda源

“””更换清华conda源”””

conda config –add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/

conda config –add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/

conda config –set show_channel_urls yes

conda config –add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch/

查看tensorflow版本

pip install tensorflow-gpu==2.2.0 -i https://pypi.tuna.tsinghua.edu.cn/simple

测试安装的tensorflow

import tensorflow as tf

print(tf.test.is_gpu_available())

tf.__version__

tf.__path__

上述报错原因是cuda版本太高了，要选择10.1版本

上述报错原因是cudnn版本太高了，要选择7.6.5版本

默认Python2调整为Python3

apt-get install python3.7

sudo update-alternatives –install /usr/bin/python python /usr/bin/python2 100

sudo update-alternatives –install /usr/bin/python python /usr/bin/python3 150

sudo apt install python3-pip

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