Instructions for CUDA v11.3 and cuDNN 8.1 installation on Ubuntu 20.04 for Pytorch 1.10

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
###

### 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 g++ freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libglu1-mesa libglu1-mesa-dev

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

# install nvidia driver with dependencies
sudo apt install libnvidia-common-470
sudo apt install libnvidia-gl-470
sudo apt install nvidia-driver-470

sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/7fa2af80.pub
echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64 /" | sudo tee /etc/apt/sources.list.d/cuda.list
sudo apt-get update

 # installing CUDA-11.3
sudo apt install cuda-11-3 (with pytorch 1.10.0)

# setup your paths
echo 'export PATH=/usr/local/cuda-11.2/bin:$PATH' >> ~/.bashrc
echo 'export LD_LIBRARY_PATH=/usr/local/cuda-11.2/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc
source ~/.bashrc
sudo ldconfig

# https://developer.nvidia.com/rdp/cudnn-archive
# install cuDNN v11.2
# For downloading cuDNN v11.2 you have to be regeistered here https://developer.nvidia.com/developer-program/signup

# CUDNN_TAR_FILE="cudnn-11.2-linux-x64-v8.1.1.33.tgz"
# wget https://developer.nvidia.com/compute/machine-learning/cudnn/secure/8.1.1.33/11.2_20210301/cudnn-11.2-linux-x64-v8.1.1.33.tgz

CUDNN_TAR_FILE="cudnn-11.3-linux-x64-v8.2.0.53.tgz"
# wget https://developer.nvidia.com/compute/machine-learning/cudnn/secure/8.2.0.53/11.3_04222021/cudnn-11.3-linux-x64-v8.2.0.53.tgz
tar -xzvf ${CUDNN_TAR_FILE}

# copy the following files into the cuda toolkit directory.
# sudo cp -P cuda/include/cudnn.h /usr/local/cuda-11.2/include
# sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda-11.2/lib64/
# sudo chmod a+r /usr/local/cuda-11.2/lib64/libcudnn*
sudo cp -P cuda/include/cudnn.h /usr/local/cuda-11.3/include
sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda-11.3/lib64/
sudo chmod a+r /usr/local/cuda-11.3/lib64/libcudnn*

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

# install Pytorch (an open source machine learning framework)
# pip install torch==1.10.0 torchvision==0.11.0 torchaudio==0.10.0
conda install pytorch==1.10.0 torchvision==0.11.0 torchaudio==0.10.0 cudatoolkit=11.3 -c pytorch -c conda-forge