CUDA: Difference between revisions

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See [https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#ubuntu-installation CUDA Ubuntu Installation]
See [https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#ubuntu-installation CUDA Ubuntu Installation]
<syntaxhighlight lang="bash">
<syntaxhighlight lang="bash">
# Set UBUNTU_VERSION to 2004 or 2204
# Set UBUNTU_VERSION to 2004 or 2204 or 2404
UBUNTU_VERSION=$(lsb_release -sr | sed -e 's/\.//g')
UBUNTU_VERSION=$(lsb_release -sr | sed -e 's/\.//g')


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sudo apt install nvidia-driver-565
sudo apt install nvidia-driver-565


# Add NVIDIA package repositories
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-ubuntu${UBUNTU_VERSION}.pin
sudo mv cuda-ubuntu${UBUNTU_VERSION}.pin /etc/apt/preferences.d/cuda-repository-pin-600
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/3bf863cc.pub
sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/ /"


# Install cuda.
sudo apt install cuda
# Reboot and check that the drivers are working with nvidia-smi
sudo reboot
# Install cudnn if needed
sudo apt install libcudnn8 libcudnn8-dev
</syntaxhighlight>
</syntaxhighlight>


;Notes
;Notes
* For machine learning, use Anaconda or Docker's CUDA since different versions of TensorFlow and PyTorch require different CUDA versions.
* For machine learning, use Anaconda or Docker's CUDA since different versions of TensorFlow and PyTorch require different CUDA versions.
You may need to add <code>LD_LIBRARY_PATH&#x3D;/usr/local/cuda/lib64</code> to your environment variables.<br>
You can also do this in PyCharm.<br>
[[File:Pycharm LD LIBRARY PATH config.png| 200x200px]]
[[File:Pycharm LD LIBRARY PATH console config.png| 200x200px]]


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