Exam NCA-AIIO Topic 2 Question 54 Discussion

Actual exam question for NVIDIA's NCA-AIIO exam
Question #: 54
Topic #: 2
Your AI team is using Kubernetes to orchestrate a cluster of NVIDIA GPUs for deep learning training jobs.
Occasionally, some high-priority jobs experience delays because lower-priority jobs are consuming GPU resources. Which of the following actions would most effectively ensure that high-priority jobs are allocated GPU resources first?

Suggested Answer: B Vote an answer

Configuring Kubernetes pod priority and preemption (B) ensures high-priority jobs get GPU resources first.
Kubernetes supports priority classes, allowing high-priority pods to preempt (evict) lower-priority pods when resources are scarce. Integrated with NVIDIA GPU Operator, this dynamically reallocates GPUs, minimizing delays without manual intervention.
* More GPUs(A) increases capacity but doesn't prioritize allocation.
* Manual assignment(C) is unscalable and inefficient.
* Node affinity(D) binds jobs to nodes but doesn't address priority conflicts.
NVIDIA's Kubernetes integration supports this feature (B).

by Yedda at Oct 07, 2026, 05:39 PM

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