GCP error: Quota 'GPUS_ALL_REGIONS' exceeded. Limit: 0.0 globally

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Resolving GCP Quota 'GPUS_ALL_REGIONS' Exceeded Errors

Hero image for GCP error: Quota 'GPUS_ALL_REGIONS' exceeded. Limit: 0.0 globally

Learn how to diagnose and resolve the 'GPUS_ALL_REGIONS' quota exceeded error in Google Cloud Platform, preventing GPU resource allocation.

Encountering a Quota 'GPUS_ALL_REGIONS' exceeded. Limit: 0.0 globally error can be a frustrating roadblock when trying to provision GPU-enabled virtual machines on Google Cloud Platform (GCP). This error indicates that your project does not have the necessary quota to create GPU instances, either because the quota is set to zero or you've exhausted your allocated limit. This article will guide you through understanding why this error occurs and provide a step-by-step solution to request a quota increase.

Understanding GPU Quotas in GCP

GCP implements quotas to prevent unforeseen spikes in resource usage, protect the platform from abuse, and manage resource availability. For GPUs, there are typically two main types of quotas:

  1. Regional GPU Quotas: These quotas apply to specific GPU types within a particular region (e.g., NVIDIA_TESLA_T4 in us-central1).
  2. Global GPU Quotas (GPUS_ALL_REGIONS): This is an overarching quota that limits the total number of GPUs you can provision across all regions in your project, regardless of type. The error GPUS_ALL_REGIONS exceeded with a limit of 0.0 means your project currently has no global allowance for GPUs.
flowchart TD
    A[Attempt to Create GPU VM] --> B{Check Regional Quota?}
    B -- Yes --> C{Regional Quota Available?}
    C -- No --> D[Regional Quota Exceeded Error]
    B -- No --> E{Check Global Quota (GPUS_ALL_REGIONS)?}
    E -- Yes --> F{Global Quota Available?}
    F -- No --> G[GPUS_ALL_REGIONS Exceeded Error]
    F -- Yes --> H[VM Provisioned Successfully]
    C -- Yes --> H

GCP GPU VM Provisioning Quota Check Flow

Why is the Limit 0.0?

A 0.0 limit for GPUS_ALL_REGIONS is common for new GCP projects or projects that haven't previously requested GPU resources. Google Cloud often sets initial GPU quotas to zero to ensure responsible resource allocation and to prevent misuse. To use GPUs, you must explicitly request an increase for this quota. This process involves submitting a request to Google Cloud, which they will review based on your project's history, billing status, and justification for the GPU usage.

Requesting a Quota Increase

The only way to resolve the GPUS_ALL_REGIONS exceeded error with a 0.0 limit is to request a quota increase through the Google Cloud Console. This process is straightforward but requires a clear justification for your GPU usage.

1. Navigate to the Quotas Page

In the Google Cloud Console, go to IAM & Admin > Quotas. You can also search for 'Quotas' in the search bar.

2. Filter for GPU Quotas

On the Quotas page, use the filters to narrow down your search. Set Service to 'Compute Engine API' and Metric to 'GPUs (all regions)'. You might also want to filter by 'Limit Name' and search for GPUS_ALL_REGIONS.

3. Request Quota Increase

Locate the GPUS_ALL_REGIONS quota. It will likely show a current limit of 0.0. Select the checkbox next to it and click the EDIT QUOTAS button at the top of the page.

4. Fill Out the Quota Increase Form

A form will appear. You'll need to:

  • New limit: Specify the desired new limit (e.g., 1 or 2 for a small number of GPUs).
  • Request description: Provide a detailed justification for why you need the GPU quota. Explain your use case (e.g., 'machine learning training', 'scientific simulations', 'rendering'), the type of GPUs you plan to use, and why the current limit is insufficient. Be as specific as possible.
  • Contact information: Ensure your contact details are correct.

5. Submit and Await Approval

Review your request and click Submit Request. Google Cloud will review your request, which can take anywhere from a few hours to a few business days. You will receive an email notification regarding the status of your request.

gcloud compute quotas describe --project=<YOUR_PROJECT_ID> --format=json

# Example output (truncated):
# [
#   {
#     "limit": "0.0",
#     "metric": "gpus_all_regions",
#     "name": "projects/<PROJECT_NUMBER>/regions/global/quotas/gpus_all_regions",
#     "owner": "compute-engine",
#     "usage": "0.0"
#   },
#   ...
# ]

Checking current GPU quotas using gcloud CLI