Last active
August 11, 2020 06:14
-
-
Save ancabilloni/2ff2c393ab26bcb5446068071508cd97 to your computer and use it in GitHub Desktop.
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
# Instruction reference: https://www.tensorflow.org/install/gpu | |
# Add NVIDIA package repositories | |
# Add HTTPS support for apt-key | |
sudo apt-get install gnupg-curl | |
cd ~/Downloads | |
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_10.1.243-1_amd64.deb | |
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub | |
sudo dpkg -i cuda-repo-ubuntu1604_10.1.243-1_amd64.deb | |
sudo apt-get update | |
wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64/nvidia-machine-learning-repo-ubuntu1604_1.0.0-1_amd64.deb | |
sudo apt install ./nvidia-machine-learning-repo-ubuntu1604_1.0.0-1_amd64.deb | |
sudo apt-get update | |
# Install NVIDIA driver | |
# Issue with driver install requires creating /usr/lib/nvidia | |
sudo mkdir /usr/lib/nvidia | |
sudo apt-get install --no-install-recommends nvidia-418 | |
# Reboot. Check that GPUs are visible using the command: nvidia-smi | |
# Install development and runtime libraries (~4GB) | |
sudo apt-get install --no-install-recommends cuda-10-1 libcudnn7=7.6.4.38-1+cuda10.1 libcudnn7-dev=7.6.4.38-1+cuda10.1 |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment