Instructions for CUDA v11.3 and cuDNN 8.2 installation on Ubuntu 20.04 for PyTorch 1.11

cuda_11.3_installation_on_Ubuntu_20.04

#!/bin/bash

### steps ####
# verify the system has a cuda-capable gpu
# download and install the nvidia cuda toolkit and cudnn
# setup environmental variables
# verify the installation
###

## install tools for lspci, ubuntu-drivers, add-apt-repository
sudo apt install pciutils ubuntu-drivers-common software-properties-common

### to verify your gpu is cuda enable check
lspci | grep -i nvidia

### If you have previous installation remove it first. 
sudo apt-get purge nvidia*
sudo apt remove nvidia-*
sudo rm /etc/apt/sources.list.d/cuda*
sudo apt-get autoremove && sudo apt-get autoclean
sudo rm -rf /usr/local/cuda*

# system update
sudo apt-get update
sudo apt-get upgrade

# install other import packages
sudo apt-get install gcc g++ freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libglu1-mesa libglu1-mesa-dev

## Check if nivida driver installed， NOTICE： if installed, no need to reinstall again
nvidia-smi
cat /proc/driver/nvidia/version

# first get the PPA repository driver
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt update

# check capable driver version- **NOTICE: choose the driver with "recommended" **
ubuntu-drivers devices

```
modalias : pci:v000010DEd00002208sv00001462sd0000389Bbc03sc00i00
vendor   : NVIDIA Corporation
driver   : nvidia-driver-510-server - distro non-free
driver   : nvidia-driver-470 - distro non-free
driver   : nvidia-driver-470-server - distro non-free
driver   : nvidia-driver-510 - distro non-free recommended
driver   : xserver-xorg-video-nouveau - distro free builtin
```

# install nvidia driver with dependencies, for me is 510
sudo apt install libnvidia-common-510
sudo apt install libnvidia-gl-510
sudo apt install nvidia-driver-510

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004.pin
sudo mv cuda-ubuntu2004.pin /etc/apt/preferences.d/cuda-repository-pin-600
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/3bf863cc.pub
sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/ /"
sudo apt-get update

 # installing CUDA-11.3
sudo apt install cuda-11-3 

# setup your paths
echo 'export PATH=/usr/local/cuda-11.3/bin:$PATH' >> ~/.bashrc
echo 'export LD_LIBRARY_PATH=/usr/local/cuda-11.3/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc
source ~/.bashrc
sudo ldconfig

# install cuDNN v11.3
# First register here: https://developer.nvidia.com/developer-program/signup

# https://developer.nvidia.com/rdp/cudnn-download -> choose Local Installer for Linux x86_64 (Tar) 
CUDNN_TAR_FILE="cudnn.tar.xz"
wget https://developer.nvidia.com/compute/machine-learning/cudnn/secure/8.2.1.32/11.3_06072021/cudnn-11.3-linux-x64-v8.2.1.32.tgz
tar -xvf ${CUDNN_TAR_FILE}

# copy the following files into the cuda toolkit directory.
sudo cp -P cudnn/include/cudnn.h /usr/local/cuda-11.3/include
sudo cp -P cudnn/lib/libcudnn* /usr/local/cuda-11.3/lib64/
sudo chmod a+r /usr/local/cuda-11.3/lib64/libcudnn*

# install nccl https://developer.nvidia.com/nccl/nccl-download choose correspoding nccl version
# install
wget url
tar -xvf nccl.txz

# copy
sudo cp -P nccl/include/* /usr/local/cuda-11.3/include/
sudo cp -P nccl/lib/libnccl* /usr/local/cuda-11.3/lib64/
sudo chmod a+r /usr/local/cuda-11.3/lib64/libncc*

# Finally, to verify the installation, check
nvidia-smi
nvcc -V

# install Pytorch (an open source machine learning framework)
pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu113