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June 30, 2022 09:01
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Instructions for CUDA v11.3 and cuDNN 8.2 installation on Ubuntu 20.04 for PyTorch 1.11
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#!/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 |
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