DigitalOcean Droplets are Linux-based virtual machines (VMs) that run on top of virtualized hardware. Each Droplet you create is a new server you can use, either standalone or as part of a larger, cloud-based infrastructure.
We strongly recommend creating GPU Droplets using our AI/ML-ready image. This image has NVIDIA drivers and software preinstalled and configured to help you get started.
The AI/ML-ready image is based on Ubuntu 22.04 and includes:
nvidia-container-toolkit=1.71.0cuda-keyring_1.1-1cuda-drivers-535cuda-toolkit-12-1bzip2 (8 GPU Droplets only)MLNX_OFED_LINUX-23.10-1.1.9.0-ubuntu22.04-x86_64 (8 GPU Droplets only)nvidia-fabricmanager-535 (8 GPU Droplets only)You can choose this image when you create a GPU Droplet from the control panel or specify it by slug name (gpu-h100x1-base for single GPU Droplets, gpu-h100x8-base for 8 GPU Droplets) when creating a GPU Droplet from the API or doctl.
GPU Droplets also work with other Droplet images (stock Linux images, backups, snapshots, and so on) but you need to manually install drivers and other software to use your Droplet’s GPUs.
If you have additional software you want to use across multiple GPU Droplets, one option is to start with our AI-ML-ready image, install any additional software, and then take a snapshot of the Droplet. You can then create additional GPU Droplets based off that snapshot.
For manual setup, on Debian-based systems like Ubuntu, you can install the CUDA drivers and toolkit as well as the NVIDIA Container Toolkit with APT.
On 8 GPU Droplets, our image installs a few additional things that require more configuration, as noted above. We recommend following NVIDIA’s installation documentation for Fabric Manager and NVIDIA’s documentation on Mellanox OFED for manual configuration.