PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #23
You are training a deep learning model for semantic image segmentation with reduced training time. While using a Deep Learning VM Image, you receive the following error: The resource…
The correct answer is B. Ensure that the required GPU is available in the selected region. The error indicates that the specified GPU type is unavailable in the chosen region or zone, preventing the VM from being provisioned.
Question
Options
- AEnsure that you have GPU quota in the selected region.
- BEnsure that the required GPU is available in the selected region.
- CEnsure that you have preemptible GPU quota in the selected region.
- DEnsure that the selected GPU has enough GPU memory for the workload.
How the community answered
(47 responses)- A2% (1)
- B89% (42)
- C6% (3)
- D2% (1)
Why each option
The error indicates that the specified GPU type is unavailable in the chosen region or zone, preventing the VM from being provisioned.
GPU quota issues typically result in a "quota exceeded" error, indicating capacity limits rather than the non-existence of the resource itself.
The error message "The resource 'projects/deeplearning-platforn/zones/europe-west4-c/acceleratorTypes/nvidia-tesla-k80' was not found" explicitly states that the requested GPU type is not available in the specified zone. To resolve this, one must verify GPU availability in the selected region or zone before provisioning the Deep Learning VM.
Preemptible GPU quota relates to a specific pricing model and capacity type, not the fundamental availability of the GPU hardware in the selected location.
GPU memory capacity affects workload execution after the GPU is provisioned, but it does not prevent the resource from being found or allocated initially.
Concept tested: GPU availability in Google Cloud regions/zones
Source: https://cloud.google.com/compute/docs/gpus/gpu-regions-zones
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