Last active
March 12, 2024 02:29
-
-
Save mcvarer/30041141c8fe70ea5fe13f839330bc5a to your computer and use it in GitHub Desktop.
CUDA 11.2 Installation on Ubuntu 18.04
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
#!/bin/bash | |
## This gist contains instructions about cuda v11.2 and cudnn 8.1 installation in Ubuntu 18.04 for PyTorch | |
############################################################################################# | |
##### forked by : https://gist.github.com/Mahedi-61/2a2f1579d4271717d421065168ce6a73 ######## | |
############################################################################################# | |
### steps #### | |
# verify the system has a cuda-capable gpu | |
# download and install the nvidia cuda toolkit and cudnn | |
# setup environmental variables | |
# verify the installation | |
### | |
### 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* | |
### to verify your gpu is cuda enable check | |
lspci | grep -i nvidia | |
### gcc compiler is required for development using the cuda toolkit. to verify the version of gcc install enter | |
gcc --version | |
# 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-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub | |
echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 /" | sudo tee /etc/apt/sources.list.d/cuda.list | |
sudo apt-get update | |
# installing CUDA-11.2 | |
sudo apt-get -o Dpkg::Options::="--force-overwrite" install cuda-11-2 cuda-drivers | |
# 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 | |
# install cuDNN v8.1 | |
CUDNN_TAR_FILE="cudnn-11.2-linux-ppc64le-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-ppc64le-v8.1.1.33.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* | |
# Finally, to verify the installation, check | |
nvidia-smi | |
nvcc -V | |
# install PyTorch (an open source machine learning framework) | |
pip install torch==1.7.1+cu110 torchvision==0.8.2+cu110 torchaudio==0.7.2 -f https://download.pytorch.org/whl/torch_stable.html |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
For the download link (which is forbidden), I had to create an NVIDIA account (free), manually download and then
tar -xzvf cudnn-11.2-linux-ppc64le-v8.1.1.33.tgz
. After copying cuDNN library files into the CUDA toolkit, I would recommend rebooting since there might be a "driver mismatch" error fornvidia-smi
. Following reboot, everything looks great! Thanks!