CUDA: Difference between revisions

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* 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=/usr/local/cuda/lib64</code> to your environment variables.<br>
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>
You can also do this in PyCharm.<br>
[[File:Pycharm LD LIBRARY PATH config.png| 200x200px]]
[[File:Pycharm LD LIBRARY PATH config.png| 200x200px]]

Revision as of 21:20, 6 July 2022

Installation

Ubuntu

CUDA Toolkit

Details

See CUDA Ubuntu Installation

# Set UBUNTU_VERSION to 2004 or 2204
UBUNTU_VERSION=$(lsb_release -sr | sed -e 's/\.//g')

# 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 NVIDIA driver and cuda.
sudo apt install nvidia-driver-515 cuda
# Reboot and check that the drivers are working with nvidia-smi
sudo reboot

# Install cudnn
sudo apt install libcudnn8 libcudnn8-dev
Notes
  • 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 LD_LIBRARY_PATH=/usr/local/cuda/lib64 to your environment variables.
You can also do this in PyCharm.

GCC Versions

nvcc sometimes only supports older gcc/g++ versions.
To make it use those by default, create the following symlinks:

  • sudo ln -s /usr/bin/gcc-6 /usr/local/cuda/bin/gcc
  • sudo ln -s /usr/bin/g++-6 /usr/local/cuda/bin/g++

Alternatively, you can use -ccbin and point to your gcc:

-ccbin /usr/local/cuda/bin/gcc

References