How to Create Gradient GPU Droplets
Create GPU Droplets and choose the image, plan, datacenter, authentication method, and additional options.
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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.
How to Use GPU Droplets
In general, you can manage GPU Droplets like non-GPU Droplets, but some features and requirements are specific to GPU Droplets:
How to Use the Scratch Disk on Gradient GPU Droplets
Set up automatic mounting for the scratch disk on GPU Droplets.
How to Enable GPU Metrics on Gradient GPU Droplets with DCGM
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.
How to Enable Jumbo Frames on Gradient GPU Droplets
Enable jumbo frames, which are data packets with larger payloads than standard, on GPU Droplets.
Gradient 1-Click Models
1-Click Models let you deploy third-party generative AI models on GPU Droplets with no additional setup or configuration.
How to Use NVIDIA Container Tools and Miniconda with 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.
GPU Droplets vs Bare Metal GPUs
Bare metal GPUs and GPU Droplets both provide GPU-based compute resources tailored to AI/ML workloads, but they’re each suited for different use cases. Learn more about the difference between bare metal GPUs and GPU Droplets:
Gradient Bare Metal GPUs vs GPU Droplets
Learn the difference between Gradient Bare Metal GPUs and GPU Droplets to choose the product that suits your use case.