NCP-AII Test Dumps: NVIDIA AI Infrastructure - NCP-AII Actual Exam Questions

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NVIDIA AI Infrastructure Sample Questions (Q76-Q81):

NEW QUESTION # 76
A DGX server reports degraded performance and storage alerts. How would you use NVSM and nvidia-smi to troubleshoot both system and GPU issues?

Answer: C

Explanation:
The correct approach is to use NVSM for platform-level health and storage status, and nvidia-smi -q for detailed GPU diagnostics. NVSM is the DGX system management utility designed to summarize server health across components such as storage, power, fans, thermals, alerts, and hardware subsystems. nvsm show health gives a fast overall health view, while nvsm show storage focuses on storage components and alerts.
nvidia-smi -q provides detailed GPU information, including temperature, power state, utilization, clocks, ECC status, driver details, and throttle reasons. This combination separates platform-level faults from GPU-level issues. lsblk can show block devices, but it does not provide DGX health interpretation or RAID/storage alert context. nvidia-smi -L only lists GPUs and does not diagnose degraded performance. nvsm --refresh, nvsm reset, and nvidia-smi --fix are not appropriate recovery commands for clearing or automatically repairing health problems. In NVIDIA AI infrastructure troubleshooting, administrators should collect health evidence first, identify whether the issue is storage, thermal, power, GPU, or firmware related, and then take targeted corrective action.


NEW QUESTION # 77
During East-West fabric validation on a 64-GPU cluster, an engineer runs all_reduce_perf and observes an algorithm bandwidth of 350 GB/s and bus bandwidth of 656 GB/s. What does this indicate about the fabric performance?

Answer: C


NEW QUESTION # 78
You are tasked with upgrading the NVIDIA driver on a Kubernetes node hosting GPU-accelerated A1 workloads. To minimize downtime and ensure a smooth transition, which sequence of steps should you follow?

Answer: D

Explanation:
Cordoning the node prevents new pods from being scheduled on it. After upgrading the driver and rebooting, uncordoning the node allows Kubernetes to resume scheduling workloads. Draining the node before upgrading can cause unnecessary downtime if pods are migrated before the upgrade process starts. The NVIDIA container toolkit must be compatible to the NVIDIA driver, but the upgrade sequence follows Option C steps.


NEW QUESTION # 79
You are deploying a new A1 inference service using Triton Inference Server on a multi-GPU system. After deploying the models, you observe that only one GPU is being utilized, even though the models are configured to use multiple GPUs. What could be the possible causes for this?

Answer: B,D

Explanation:
The 'instance_group' parameter in the model configuration dictates how Triton distributes the model across GPUs. Without proper configuration, it may default to a single GPIJ. CUDA MPS allows multiple CUDA applications (in this case, Triton inference processes) to share a single GPU, improving utilization. Insufficient CPU cores or non-optimized models could limit performance, but wouldn't necessarily restrict usage to a single GPIJ. While dissimilar GPIJs can affect performance, Triton will attempt to schedule across them if configured correctly.


NEW QUESTION # 80
You are running a distributed training job on a multi-GPU server. After several hours, the job fails with a NCCL (NVIDIA Collective Communications Library) error. The error message indicates a failure in inter-GPU communication. 'nvidia-smi' shows all GPUs are healthy. What is the MOST probable cause of this issue?

Answer: A,B

Explanation:
NCCL errors during inter-GPU communication often stem from configuration issues (B) or driver incompatibilities (E). Incorrect network interface or device affinity settings can prevent proper communication. Driver versions might not fully support the NCCL version being used. Reducing batch size (C) might alleviate symptoms but doesn't address the root cause. A faulty network cable (D) would likely cause broader network issues beyond NCCL. Downgrading NCCL (A) is a potential workaround but not the ideal first step.


NEW QUESTION # 81
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