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NVIDIA Exam NCA-AIIO Topic 2 Question 5 Discussion

Actual exam question for NVIDIA's NCA-AIIO exam
Question #: 5
Topic #: 2
[All NCA-AIIO Questions]

In your multi-tenant AI cluster, multiple workloads are running concurrently, leading to some jobs experiencing performance degradation. Which GPU monitoring metric is most critical for identifying resource contention between jobs?

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Suggested Answer: A

GPU Utilization Across Jobs is the most critical metric for identifying resource contention in a multi-tenant cluster. It shows how GPU resources are divided among workloads, revealing overuse or starvation via tools like nvidia-smi. Option B (temperature) indicates thermal issues, not contention. Option C (network latency) affects distributed tasks. Option D (memory bandwidth) is secondary. NVIDIA's DCGM supports this metric for contention analysis.


by Pamella at Jun 12, 2025, 12:33 AM

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Margret
1 months ago
GPU Temperature, huh? That's a good one. Maybe we can just put a bunch of fans in the server room and call it a day. Where's the fun in that?
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Laticia
42 minutes ago
User 2: I think Memory Bandwidth Utilization is also important to consider.
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Carissa
3 days ago
User 1: GPU Utilization Across Jobs is more critical for identifying resource contention.
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Reena
1 months ago
Network Latency? Really? Unless your jobs are all the way across the cluster, I don't see how that's going to help you identify resource contention. GPU Utilization is the way to go, folks.
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Tanja
1 months ago
I'm going with D, Memory Bandwidth Utilization. Gotta keep an eye on that memory pipeline, you know? Can't have jobs hogging all the bandwidth.
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Queenie
10 days ago
User 3: I see your point, but I still think D) Memory Bandwidth Utilization is the most critical. We can't overlook the memory pipeline.
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Lovetta
13 days ago
User 2: I agree with Lovetta, GPU utilization is key to identifying resource contention.
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Joni
29 days ago
User 1: I think A) GPU Utilization Across Jobs is more critical. We need to see how much each job is using the GPU.
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Angelica
2 months ago
I agree, GPU Utilization is the way to go. You can't optimize what you can't measure, am I right?
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Corrinne
1 months ago
I agree, GPU Utilization is the way to go. You can't optimize what you can't measure, am I right?
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Denae
1 months ago
A) GPU Utilization Across Jobs
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Selma
2 months ago
But what about Memory Bandwidth Utilization? That could also be important for identifying contention.
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Lucia
2 months ago
I agree with Celia, high GPU utilization across jobs can indicate resource contention.
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Celia
2 months ago
I think the most critical metric is GPU Utilization Across Jobs.
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Deandrea
2 months ago
GPU Utilization Across Jobs is definitely the key metric to look at. That's where the resource contention will show up first.
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Izetta
1 months ago
D) Memory Bandwidth Utilization could be another important metric to monitor.
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Georgeanna
1 months ago
B) GPU Temperature may also play a role in performance degradation.
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Sherell
2 months ago
A) GPU Utilization Across Jobs is crucial for identifying resource contention.
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