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Instructions for CUDA v11.3 and cuDNN 8.2 installation on Ubuntu 20.04 for PyTorch 1.11
#!/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
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
CUDNN_TAR_FILE="cudnn-11.3-linux-x64-v8.2.1.32.tgz"
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 -xzvf ${CUDNN_TAR_FILE}
# copy the following files into the cuda toolkit directory.
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)
pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu113
@addy1997
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addy1997 commented Jun 26, 2022

I am wondering whether these work for installing cuda 11.3 on ubuntu 22.04 also?

@saravananpsg
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saravananpsg commented Jul 1, 2022

Will it work for nvidia-server on ubuntu 20.04 server ?

install nvidia driver with dependencies

sudo apt install libnvidia-common-470-server
sudo apt install libnvidia-gl-470-server
sudo apt install nvidia-driver-470-server

@initialneil
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initialneil commented Jul 3, 2022

Will it work for nvidia-server on ubuntu 20.04 server ?

install nvidia driver with dependencies

sudo apt install libnvidia-common-470-server sudo apt install libnvidia-gl-470-server sudo apt install nvidia-driver-470-server

@saravananpsg It's works for server. I tested. I also changed 470 to 515 to support 3090.

@jackkolb
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jackkolb commented Jul 22, 2022

I also had to change the version from 470 to 515 for a 1070 TI.

sudo apt install libnvidia-common-515
sudo apt install libnvidia-gl-515
sudo apt install nvidia-driver-515

After installing, if nvidia-smi gives a kernel/client version mismatch error, reboot.

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