NCP-AIO Exam Dumps | You are deploying an AI workload on a Kubernetes cluster that requires access to GPUs for training deep

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EMC.NCP-AIO.v2025-12-03.q29
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Question 1/29

You are deploying an AI workload on a Kubernetes cluster that requires access to GPUs for training deep learning models. However, the pods are not able to detect the GPUs on the nodes.
What would be the first step to troubleshoot this issue?

A. Verify that the NVIDIA GPU Operator is installed and running on the cluster.

B. Ensure that all pods are using the latest version of TensorFlow or PyTorch.

C. Check if the nodes have sufficient memory allocated for AI workloads.

D. Increase the number of CPU cores allocated to each pod to ensure better resource utilization.

Correct Answer: A

Comprehensive and Detailed Explanation From Exact Extract:
The first step in troubleshooting Kubernetes pods that cannot detect GPUs is to verify whether theNVIDIA GPU Operatoris properly installed and running. The GPU Operator manages the installation and configuration of all NVIDIA GPU components in the cluster, including drivers, device plugins, and monitoring tools. Without it, pods will not have access to GPU resources. Ensuring correct installation and operational status of the GPU Operator is essential before checking application-level versions or resource allocations.

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