Vultr Cloud GPU Troubleshooting

Updated on February 1, 2024
Vultr Cloud GPU Troubleshooting header image

There's no need to install any drivers on a Vultr Cloud GPU. Licensed NVIDIA drivers and the CUDA Toolkit are preinstalled by cloud-init when you deploy our standard images.

Please check these troubleshooting FAQs before opening a support ticket if you have driver or license problems with a Cloud GPU server.

How can I verify the GPU drivers are installed?

See if the drivers loaded:

$ sudo lsmod nvidia

The two most common reasons they may not load are:

  • The installer did not run
  • A kernel update ran after the driver installation finished.

Installer did not run

To find out if the installer ran during deployment, test if this file exists:

$ sudo ls /opt/nvidia/driver/linux_nvidia_client.run

If the file does not exist, please open a support ticket.

Fix a conflicting kernel update

If /opt/nvidia/drivers/linux_nvidia_client.run exists and the drivers aren't loaded, then a kernel update is possibly blocking the drivers. Try re-running the installer to resolve the conflict. After this, the NVIDIA drivers should correctly recognize the new kernel and load.

$ sudo chmod +x /opt/nvidia/driver/linux_nvidia_client.run
$ sudo /opt/nvidia/driver/linux_nvidia_client.run --ui=none --no-questions

How do I verify the NVIDIA license is installed properly?

The Cloud GPU will not run if the license file is missing or corrupt. Normally, cloud-init uses Vultr's vendor-data to install the license file during deployment. If your Cloud GPU isn't working properly, please verify the license file exists:

$ sudo ls /etc/nvidia/gridd.conf

If the file is missing, or you believe it is corrupt, please open a support ticket.

How do I install drivers in a custom operating system?

If you want to use an operating system that isn't offered by Vultr, please install cloud-init in your custom OS. It will automatically install the drivers and libraries using Vultr's vendor-data.

How do I reinstall or upgrade PyTorch?

PyTorch supports several different installation methods, which you'll find documented on their website. We recommend using Anaconda to install PyTorch in most cases. To get started with PyTorch, you can deploy our ready-to-run Anaconda and Miniconda Marketplace apps.

What CUDA versions does Vultr support?

Vultr Talon Cloud GPUs are compatible with CUDO version 11.3 or later.