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ubuntu安裝顯卡驅(qū)動和cuda教程

1. 卸載原始的驅(qū)動

#查看安裝的包
apt list --installed|grep -i nvidia
#卸載包
apt-get purge nvidia*

2. 下載新顯卡驅(qū)動

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

復(fù)制下載鏈接，在系統(tǒng)中用wget下載

#下載
wget https://cn.download.nvidia.cn/tesla/470.57.02/NVIDIA-Linux-x86_64-470.57.02.run
#安裝
sudo sh NVIDIA-Linux-x86_64-470.57.02.run

2.1 安裝顯卡驅(qū)動

3 安裝cuda

官網(wǎng)鏈接

選擇cuda版本，要和驅(qū)動的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

添加環(huán)境變量，將上圖中的建議加到.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
#添加路徑
export PATH=$PATH:/usr/local/cuda-11.4/bin
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-11.4/lib64
#使環(huán)境生效
source ~/.bashrc

查看nvcc -V

cudatoolkit

sudo apt install nvidia-cuda-toolkit

4. 安裝cudnn

安裝cudnn

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

wget https://developer.download.nvidia.cn/compute/machine-learning/cudnn/secure/8.2.2/11.4_07062021/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. 安裝anaconda

wget https://mirror.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-2021.05-Linux-x86_64.sh

添加環(huán)境變量

vim ~/.bashrc
export PATH="/usr/local/anaconda3/bin:$PATH"
source ~/.bashrc

替換anaconda源

"""更換清華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

測試安裝的tensorflow

import tensorflow as tf
print(tf.test.is_gpu_available())
tf.__version__
tf.__path__

上述報錯原因是cuda版本太高了，要選擇10.1版本

上述報錯原因是cudnn版本太高了，要選擇7.6.5版本

默認Python2調(diào)整為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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