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Instructions for CUDA v12.2 and cuDNN 8.7 installation on Ubuntu 20.04 for PyTorch 2.0.0
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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. | |
#### alternative 1 | |
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* | |
#### alternative 2 (if installed via runfile): | |
sudo /usr/local/cuda-11.8/bin/cuda-uninstaller | |
# 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-535 libnvidia-gl-535 nvidia-driver-535 -y | |
# reboot | |
sudo reboot now | |
# verify that the following command works | |
nvidia-smi | |
# download and prepare the cuda repository | |
(follow this page: https://developer.nvidia.com/cuda-12-2-2-download-archive?target_os=Linux&target_arch=x86_64&Distribution=Ubuntu&target_version=20.04&target_type=runfile_local) | |
## install using runfile: | |
wget https://developer.download.nvidia.com/compute/cuda/12.2.2/local_installers/cuda_12.2.2_535.104.05_linux.run | |
sudo sh cuda_12.2.2_535.104.05_linux.run | |
# setup your paths | |
echo 'export PATH="/usr/local/cuda-12.2/bin${PATH:+:${PATH}}"' >> ~/.bashrc | |
echo 'export LD_LIBRARY_PATH="/usr/local/cuda-12.2/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}"' >> ~/.bashrc | |
source ~/.bashrc | |
sudo ldconfig | |
# install cuDNN v 9.0.0 | |
# First register here: https://developer.nvidia.com/developer-program/signup | |
wget https://developer.download.nvidia.com/compute/cudnn/9.0.0/local_installers/cudnn-local-repo-ubuntu2004-9.0.0_1.0-1_amd64.deb | |
sudo dpkg -i cudnn-local-repo-ubuntu2004-9.0.0_1.0-1_amd64.deb | |
sudo cp /var/cudnn-local-repo-ubuntu2004-9.0.0/cudnn-*-keyring.gpg /usr/share/keyrings/ | |
sudo apt-get update | |
sudo apt-get -y install cudnn-cuda-12 | |
## legacy (manual cudnn installation) | |
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 | |
cat /usr/include/x86_64-linux-gnu/cudnn_version_v9.h | |
# install Pytorch (an open source machine learning framework) | |
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118 |
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