Free NVIDIA NCA-AIIO Actual Exam Questions - Question 12 Discussion
Question No. 12
You have deployed an AI training job on a GPU cluster, but the training time has not decreased as
expected after adding more GPUs. Upon further investigation, you observe that the GPU utilization is
low, and the CPU utilization is very high. What is the most likely cause of this issue?
expected after adding more GPUs. Upon further investigation, you observe that the GPU utilization is
low, and the CPU utilization is very high. What is the most likely cause of this issue?
Select one option, then reveal solution.
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Shoaib B.
2026-02-12
Yeah, I’m with D too. If the CPUs are maxed out, the GPUs end up waiting for data instead of training. Adding GPUs won’t help if the bottleneck is before the data even reaches them. It’s basically a pipeline issue—preprocessing or loading needs to be sped up or parallelized to see any GPU utilization gains.
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Ethan B.
2026-01-30
Maybe D, since high CPU and low GPU usage often means the GPUs are waiting on data. If the CPUs are busy preprocessing, that would explain the slowdown despite adding GPUs.
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Ahmed Q.
2026-01-25
Makes sense that CPUs are overloaded, so they can’t feed data fast enough to GPUs. Definitely D here.
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Sarah E.
2026-01-16
It’s D. CPU bottleneck in data preprocessing slowing down GPUs.
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