sudo apt update && sudo apt upgradesudo apt autoremove nvidia* --purgeubuntu-drivers devicesYou will install the NVIDIA driver whose version is tagged with recommended
sudo ubuntu-drivers autoinstallMy recommended version is 525, adapt to yours
sudo apt install nvidia-driver-525rebootafter restart verify that the following command works
nvidia-smisudo apt update && sudo apt upgradesudo apt install nvidia-cuda-toolkitnvcc --versionYou can download cuDNN file here. You will need an Nvidia account. Select the cuDNN version for the appropriate CUDA version, which is the version that appears when you run:
nvcc --versionsudo apt install ./<filename.deb>
sudo cp /var/cudnn-<something>.gpg /usr/share/keyrings/My cuDNN version is 8, adapt the following to your version:
sudo apt update
sudo apt install libcudnn8
sudo apt install libcudnn8-dev
sudo apt install libcudnn8-samplessudo apt-get install python3-pip
sudo pip3 install virtualenv
virtualenv -p py3.10 venv
source venv/bin/activatepip3 install torch torchvision torchaudioimport torch
print(torch.cuda.is_available()) # should be True
t = torch.rand(10, 10).cuda()
print(t.device) # should be CUDAGo to Nvidia webiste here. Select latest TensorRT version that matches your CUDA version and download the DEB file.
sudo apt install ./<filename.deb>
sudo apt update
sudo apt install tensorrtVerify that the trtexec utility is present.
whereis trtexec # should be trtexec: /usr/src/tensorrt/bin/trtexec
/usr/src/tensorrt/bin/trtexec
Also maybe someone of you would also like to install a custom ffmpeg with the correct codecs. This took me quiet a while to bring it to work. It was tested on ubuntu 22.04
This was for testing so the ansible tasks are not rly perfect but works. Also you should be able to easily copy paste the commands manually in the shell.