Ubuntu安装Nvidia Driver、CUDA、CUDNN

安装Nvidia Driver

lspci | grep -i nvidia

sudo apt update
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt udpate

ubuntu-drivers devices
sudo apt install nvidia-driver-<version>

sudo reboot

nvidia-smi
nvidia-smi -L

安装CUDA

# 下载
# https://developer.nvidia.com/cuda-toolkit-archive

# 选择 CUDA Toolkit 10.1 (Feb 2019)
# https://developer.nvidia.com/cuda-10.1-download-archive-base
# Linux -> x86_64 -> Ubuntu -> 18.04 -> runfile(local)
# https://developer.nvidia.com/compute/cuda/10.1/Prod/local_installers/cuda_10.1.105_418.39_linux.run

# 安装

# 添加环境变量
export PATH=/usr/local/cuda-10.1/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-10.1/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}


# 验证
cd /usr/local/cuda-10.1/samples/1_Utilities/deviceQuery
sudo make
./deviceQuery
# Result = PASS

安装CUDNN

# https://developer.nvidia.com/cudnn-archive

# 老版本下载
# https://developer.nvidia.com/rdp/cudnn-archive

# 选择 Download cuDNN v7.5.1 (April 22, 2019), for CUDA 10.1
# 选择 cuDNN Library for Linux
# https://developer.nvidia.com/compute/machine-learning/cudnn/secure/v7.5.1/prod/10.1_20190418/cudnn-10.1-linux-x64-v7.5.1.10.tgz

# 选择 cuDNN Code Samples and User Guide for Ubuntu18.04 (Deb)
# https://developer.nvidia.com/compute/machine-learning/cudnn/secure/v7.5.1/prod/10.1_20190418/Ubuntu18_04-x64/libcudnn7-doc_7.5.1.10-1%2Bcuda10.1_amd64.deb

# 安装 
sudo cp cuda/include/cudnn.h /usr/local/cuda/include
sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64
sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn*

# 查看版本
cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2
# cat /usr/local/cuda/include/cudnn_version.h | grep CUDNN_MAJOR -A 2

# 测试
dpkg-deb --extract libcudnn7-doc_7.5.1.10-1+cuda10.1_amd64.deb libcudnn

cd libcudnn/usr/src/cudnn_samples_v7/mnistCUDNN
make 
./mnistCUDNN
# 不会卡死，并且最后是 Test passed!