Last active
November 16, 2024 10:21
-
-
Save Mahedi-61/2a2f1579d4271717d421065168ce6a73 to your computer and use it in GitHub Desktop.
Instructions for CUDA v11.8 and cuDNN 8.9.7 installation on Ubuntu 22.04 for PyTorch 2.1.2
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 | |
### 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 | |
# installing CUDA-11.8 | |
wget https://developer.download.nvidia.com/compute/cuda/repos/wsl-ubuntu/x86_64/cuda-keyring_1.0-1_all.deb | |
sudo dpkg -i cuda-keyring_1.0-1_all.deb | |
sudo apt-get update | |
sudo apt-get -y install cuda | |
# 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 v8.9.7 | |
# First register here: https://developer.nvidia.com/developer-program/signup | |
CUDNN_TAR_FILE="cudnn-linux-x86_64-8.9.7.29_cuda11-archive.tar.xz" | |
wget https://developer.nvidia.com/downloads/compute/cudnn/secure/8.9.7/local_installers/11.x/cudnn-linux-x86_64-8.9.7.29_cuda11-archive.tar.xz | |
tar -xvf ${CUDNN_TAR_FILE} | |
# copy the following files into the cuda toolkit directory. | |
sudo cp cudnn-*-archive/include/cudnn*.h /usr/local/cuda/include | |
$ sudo cp -P cudnn-*-archive/lib/libcudnn* /usr/local/cuda/lib64 | |
$ sudo chmod a+r /usr/local/cuda/include/cudnn*.h /usr/local/cuda/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 --index-url https://download.pytorch.org/whl/cu118 |
with this command :
$ sudo cp cudnn--archive/include/cudnn.h /usr/local/cuda/include
message error :
cp: cannot stat 'cudnn--archive/include/cudnn.h': No such file or directory
the same with the other commands :
$ sudo cp cudnn--archive/include/cudnn.h /usr/local/cuda/include
====> cp: cannot stat 'cudnn--archive/include/cudnn.h': No such file or directory
$sudo cp cudnn--archive/include/cudnn.h /usr/local/cuda/include
====> cp: cannot stat 'cudnn--archive/include/cudnn.h': No such file or directory
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
tar -xvf cudnn-linux-x86_64-8.9.7.29_cuda11-archive.tar.xz
xz: (stdin): File format not recognized
tar: Child returned status 1
tar: Error is not recoverable: exiting now
I get this error
I have my tar and xz installed