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NVIDIA NCP-AII Exam - Topic 2 Question 8 Discussion

A team is validating a DGX BasePOD deployment. Using cmsh, they run a command to check GPU health across all nodes. What indicates that the system is ready for AI workloads?
C) All GPUs report Status_Health = OK and Health = OK for each device.
A) The command output is ignored if the system powers on without errors.
B) At least half of the GPUs report Status_Health = OK.
D) Only the head node's GPUs need to be healthy.

NVIDIA NCP-AII Exam - Topic 2 Question 8 Discussion

Actual exam question for NVIDIA's NCP-AII exam
Question #: 8
Topic #: 2
[All NCP-AII Questions]

A team is validating a DGX BasePOD deployment. Using cmsh, they run a command to check GPU health across all nodes. What indicates that the system is ready for AI workloads?

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Suggested Answer: C

In an NVIDIA DGX BasePOD or SuperPOD environment, 'Cluster Health' is a binary state: either the entire fabric and all compute resources are ready, or the cluster is considered degraded. Using the Bright Cluster Manager (BCM) shell (cmsh), administrators can aggregate telemetry from every node in the cluster. For a system to be considered 'Production Ready,' every single GPU across the multi-node deployment must report a status of Health = OK. This verification ensures that the hardware is communicating correctly over the PCIe bus, the NVLink fabric is initialized, and no ECC (Error Correction Code) memory errors are present. If even a single GPU in a 32-node cluster is unhealthy, collective communication libraries like NCCL may hang or experience significant performance penalties during 'All-Reduce' operations, as the entire job typically scales to the speed of the slowest/unhealthiest component. Therefore, seeing Status_Health = OK for every device is the mandatory exit criterion for the bring-up phase.


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Alesia
16 hours ago
I’m surprised that all GPUs need to be OK. Is that really necessary?
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Torie
6 days ago
No way, it has to be C. Anything less is just asking for trouble.
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King
11 days ago
Wait, only the head node's GPUs? That seems risky!
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Ty
2 months ago
I think B is enough, as long as half are good.
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Sabra
2 months ago
C is definitely the right answer. All GPUs need to be healthy!
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Stephanie
3 months ago
I feel like the head node's GPUs being healthy might not be enough for a full deployment, but I can't remember the specifics.
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Devora
3 months ago
If I recall correctly, the best practice is to ensure all GPUs report Status_Health = OK, but I could be mixing it up with another topic.
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Eden
3 months ago
I think I saw a similar question where it emphasized that all components need to be functional for optimal performance.
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Virgina
3 months ago
I remember something about checking GPU health, but I'm not sure if all GPUs need to be healthy or just a majority.
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