How to Create and Configure GPU Droplets

Validated on 26 Sep 2024 • Last edited on 1 Oct 2024

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.

GPU Droplets have NVIDIA H100 GPUs in a single or 8 GPU configuration. They also come with two different kinds of storage: a boot disk for persistent data and a scratch disk for non-persistent data. Learn more about GPU Droplet plans and features.

We provide an AI/ML-ready image for GPU Droplets that has drivers and software from NVIDIA preinstalled. You can also create GPU Droplets with existing Droplet images, but you need to manually install drivers and other software to use the GPUs.

In general, you can manage GPU Droplets like non-GPU Droplets, but some features and requirements are specific to GPU Droplets:

Create GPU Droplets and choose the image, plan, datacenter, authentication method, and additional options.
Set up automatic mounting for the scratch disk on GPU Droplets.
Install the NVIDIA Data Center GPU Manager (DCGM) and DCGM Exporter to enable health monitoring, diagnostics, and process statistics for NVIDIA GPUs on GPU Droplets.
Enable jumbo frames, which are data packets with larger payloads than standard, on GPU Droplets.
This Community tutorial explains how to set up the NVIDIA container toolkit, run Docker for GPU workloads, and install Miniconda to manage Python environments on GPU Droplets.
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