Instructions for CUDA v11.8 and cuDNN 8.7 installation on Ubuntu 22.04 for PyTorch 2.0.0

cuda_11.8_installation_on_Ubuntu_22.04

#!/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 purge nvidia* -y
sudo apt remove nvidia-* -y
sudo rm /etc/apt/sources.list.d/cuda*
sudo apt autoremove -y && sudo apt autoclean -y
sudo rm -rf /usr/local/cuda*

# system update
sudo apt update && sudo apt upgrade -y

# install other import packages
sudo apt 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

# find recommended driver versions for you
ubuntu-drivers devices

# install nvidia driver with dependencies
sudo apt install libnvidia-common-515 libnvidia-gl-515 nvidia-driver-515 -y

# reboot
sudo reboot now

# verify that the following command works
nvidia-smi

sudo wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-ubuntu2204.pin
sudo mv cuda-ubuntu2204.pin /etc/apt/preferences.d/cuda-repository-pin-600
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/3bf863cc.pub
sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/ /"

# Update and upgrade
sudo apt update && sudo apt upgrade -y

 # installing CUDA-11.8
sudo apt install cuda-11-8 -y

# setup your paths
echo 'export PATH=/usr/local/cuda-11.8/bin:$PATH' >> ~/.bashrc
echo 'export LD_LIBRARY_PATH=/usr/local/cuda-11.8/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc
source ~/.bashrc
sudo ldconfig

# install cuDNN v11.8
# First register here: https://developer.nvidia.com/developer-program/signup

CUDNN_TAR_FILE="cudnn-linux-x86_64-8.7.0.84_cuda11-archive.tar.xz"
sudo wget https://developer.download.nvidia.com/compute/redist/cudnn/v8.7.0/local_installers/11.8/cudnn-linux-x86_64-8.7.0.84_cuda11-archive.tar.xz
sudo tar -xvf ${CUDNN_TAR_FILE}
sudo mv cudnn-linux-x86_64-8.7.0.84_cuda11-archive cuda

# copy the following files into the cuda toolkit directory.
sudo cp -P cuda/include/cudnn.h /usr/local/cuda-11.8/include
sudo cp -P cuda/lib/libcudnn* /usr/local/cuda-11.8/lib64/
sudo chmod a+r /usr/local/cuda-11.8/lib64/libcudnn*

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

# install Pytorch (an open source machine learning framework)
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

For NVIDIA 50 Series 5060 - 5060 Ti - 5070 - 5070 Ti only the open versions of the drivers are supported.

When you install CUDA Toolkit via sudo apt install cuda-11-8 -y, it will also install the latest non-open driver which will conflict your driver installation. I edited the suggestion to be compatible with RTX 50 series:

GPU Driver - CUDA - cuDNN

Install the GPU Drivers

sudo apt purge nvidia* -y

sudo apt remove nvidia-* -y

sudo rm /etc/apt/sources.list.d/cuda*

sudo apt autoremove -y && sudo apt autoclean -y

sudo rm -rf /usr/local/cuda*

sudo apt update && sudo apt upgrade -y

sudo apt install g++ freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libglu1-mesa libglu1-mesa-dev

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

sudo apt update

ubuntu-drivers devices

sudo apt install libnvidia-common-@@@ libnvidia-gl-@@@ nvidia-driver-@@@-open -y

I used 575 for my GPU.

sudo reboot now

Verify Driver Installation

nvidia-smi

Install CUDA Toolkit

wget https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_520.61.05_linux.run

sudo sh cuda_11.8.0_520.61.05_linux.run --toolkit --silent --override

Add CUDA Environment Variables

echo 'export PATH=/usr/local/cuda-11.8/bin:$PATH' >> ~/.bashrc

echo 'export LD_LIBRARY_PATH=/usr/local/cuda-11.8/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc

source ~/.bashrc

Download cuDNN

wget https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-8.8.1.3_cuda11-archive.tar.xz

sudo tar -xvf cudnn-linux-x86_64-8.8.1.3_cuda11-archive.tar.xz

sudo mv cudnn-linux-x86_64-8.8.1.3_cuda11-archive cuda

Put cuDNN into CUDA files

sudo cp -P cuda/include/cudnn.h /usr/local/cuda-11.8/include

sudo cp -P cuda/lib/libcudnn* /usr/local/cuda-11.8/lib64/

sudo chmod a+r /usr/local/cuda-11.8/lib64/libcudnn*

I hope this helps let me know if you are having any troubles.

It worked with RTX 3090 on Ubuntu 22.04. Thanks, bro!