GPU support

Use GPU-backed VMs in GCP sandboxes for AI, ML, and other hardware-accelerated labs.

GPU support lets you run hardware-accelerated labs in GCP sandboxes. Use it for model training, inference, rendering, and other workloads that do not perform well on CPU-only hosts.

GPU support is available by request. Contact your Instruqt Customer Success team to enable it for your organisation.

GPU support builds on the standard GCP project flow. If you have not added a GCP project to a sandbox before, start with GCP projects.

What's supported

• GPU types: NVIDIA T4 and P4

• VM instance family: N1

• Limit: Up to 2 GPU-backed VMs per GCP project

Supported regions

Region	Location
europe-west1	Europe (Belgium)
us-central1	US (Iowa)
asia-southeast1	Asia-Pacific (Singapore)

GPUs are only available in these regions. When you attach a GPU, unsupported regions are removed from the selector.

Before you begin

• GPU support must be enabled for your organisation.

• Your track or sandbox preset must already include a GCP project.

• Add the Cloud Client if learners need the GCP console or gcloud.

Example track

Use this example as a starting point:

• Play it: GCP project – GPU VM

• Source: instruqt/examples – gcp-project-gpu-vm

You won't be able to play this track unless GPU support is enabled for your workspace. You can still browse the source files to get a feel for how the sandbox is put together.

Configure a GPU-backed VM

1

Add a GCP project

Add a GCP cloud account with these values:

Setting	Value
Services	Compute Engine API (compute.googleapis.com)
Regions	Europe (Belgium), US (Iowa), Asia-Pacific (Singapore)
User roles	Viewer, IAP-secured Tunnel User
Admin roles	Compute Admin, IAP Tunnel User

In the web UI, click + Add a cloud account and select Google.

2

Add the Cloud Client container

Add the Instruqt Cloud Client container so learners can access the GCP console and gcloud:

gcr.io/instruqt/cloud-client:2

3

Attach a GPU to the VM

When you add a VM to the GCP project, select:

• an N1 instance type

• a T4 or P4 GPU

Each GCP project supports up to two GPU-backed VMs.

Your sandbox is now configured for GPU workloads. Play the track and confirm startup time and behaviour before publishing.

Startup time and availability

GPU capacity is allocated on a best-effort basis. Startup depends on available hardware in a supported GCP region.

• Typical startup time: 5 to 9 minutes

• HotStarts: Supported

GPU availability depends on current GCP capacity. Startup can take longer during busy periods. Test ahead of live or time-sensitive sessions.

Costs

GPU usage is billed in addition to standard cloud account costs. Your Customer Success team will confirm pricing when GPU support is enabled for your organisation.

Related pages

• GCP projects

• GCP IAM Permissions

• Cloud Client

• Securing your cloud accounts