FREE PDF 2025 NVIDIA NCP-AII: FANTASTIC EXAM NVIDIA AI INFRASTRUCTURE LAB QUESTIONS

Free PDF 2025 NVIDIA NCP-AII: Fantastic Exam NVIDIA AI Infrastructure Lab Questions

Free PDF 2025 NVIDIA NCP-AII: Fantastic Exam NVIDIA AI Infrastructure Lab Questions

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Tags: Exam NCP-AII Lab Questions, Dumps NCP-AII Guide, NCP-AII New Test Materials, Exam NCP-AII Revision Plan, NCP-AII Vce Test Simulator

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NVIDIA AI Infrastructure Sample Questions (Q264-Q269):

NEW QUESTION # 264
You're troubleshooting a DGX-I server exhibiting performance degradation during a large-scale distributed training job. 'nvidia-smu shows all GPUs are detected, but one GPU consistently reports significantly lower utilization than the others. Attempts to reschedule orkloads to that GPU frequently result in CUDA errors. Which of the following is the MOST likely cause and the BEST initial roubleshooting step?

  • A. Power supply unit (PSU) overload, causing reduced power delivery to that GPU; monitor PSU load and check PSU specifications.
  • B. A driver issue affecting only one GPU; reinstall NVIDIA drivers completely.
  • C. A software bug in the training script utilizing that specific GPU's resources inefficiently; debug the training script.
  • D. Insufficient cooling in the server rack; verify adequate airflow and cooling capacity for the rack.
  • E. A hardware fault with the GPU, potentially thermal throttling or memory issues; run 'nvidia-smi -i -q' to check temperatures, power limits, and error counts.

Answer: E

Explanation:
While all options are possibilities, the consistently lower utilization and CUDA errors point strongly to a hardware fault. Running nvidia-smi -i -q' provides detailed telemetry data, including temperature, power limits, and ECC error counts, which are crucial for diagnosing GPU hardware issues.


NEW QUESTION # 265
You've installed a DGX A100 server During the initial hardware validation, you observe that one of the GPUs is consistently reporting lower performance compared to the others. Which troubleshooting steps should you take, in the CORRECT order, to diagnose the problem?

  • A. 1. Check the power supply connections. 2. Check GPU temperature. 3. Reseat the GPIJ. 4. Run GPU diagnostics.
  • B. 1. Check GPU temperature. 2. Reseat the GPU. 3. Run GPU diagnostics. 4. Update the GPU driver.
  • C. 1. Reseat the GPU. 2. Check GPU temperature. 3. Update the GPU driver. 4. Run GPU diagnostics.
  • D. 1. Run GPU diagnostics. 2. Reseat the GPIJ. 3. Check GPU temperature. 4. Update the GPU driver.
  • E. 1. Update the GPU driver. 2. Run GPU diagnostics. 3. Check GPU temperature. 4. Reseat the GPIJ.

Answer: B

Explanation:
Checking temperature is crucial first to avoid damaging the GPU if it's overheating. Reseating addresses potential connectivity issues. Running diagnostics identifies hardware faults. Updating the driver should be done after hardware checks to ensure the card isn't faulty.


NEW QUESTION # 266
A GPU in your AI server consistently overheats during inference workloads. You've ruled out inadequate cooling and software bugs.
Running 'nvidia-smi' shows high power draw even when idle. Which of the following hardware issues are the most likely causes?

  • A. Insufficient system RAM.
  • B. A BIOS setting that is overvolting the GPU.
  • C. Incorrectly seated GPU in the PCle slot, leading to poor power delivery.
  • D. Degraded thermal paste between the GPU die and the heatsink.
  • E. A failing voltage regulator module (VRM) on the GPU board, causing excessive power leakage.

Answer: C,D,E

Explanation:
Degraded thermal paste loses its ability to conduct heat effectively. A failing VRM can cause excessive power draw and heat generation. An incorrectly seated GPU can cause instability and poor power delivery, leading to overheating. Overvolting in BIOS will definitely cause overheating. While insufficient RAM can cause performance issues, it is less likely to lead to overheating.


NEW QUESTION # 267
You are upgrading an AI server with new NVIDIAA800 GPUs and require 400GbE connectivity. After installing the new QSFP-DD transceivers and connecting the fiber cables, the link does not come up. You suspect a polarity issue. Assuming you are using MPO/MTP connectors, which of the following steps would BEST help diagnose and rectify a potential polarity mismatch? (Choose TWO)

  • A. Use an Optical Time Domain Reflectometer (OTDR) to verify cable integrity.
  • B. Replace the QSFP-DD transceivers with known working units.
  • C. Use a fiber optic polarity tester to confirm correct TX/RX mapping through the entire cable assembly.
  • D. Consult the cable manufacturer's documentation to verify the MPO/MTP key orientation and pinout configuration and ensure it aligns with the transceiver requirements.
  • E. Swap the transmit (TX) and receive (RX) fibers at one end of the connection.

Answer: C,D

Explanation:
Polarity issues often arise with MPO/MTP connectors. Consulting the cable documentation to verify the key orientation is critical. A fiber optic polarity tester can definitively confirm the TX/RX mapping. Swapping fibers manually isn't recommended due to potential damage. OTDR checks cable integrity, but not polarity. Replacing transceivers is a troubleshooting step, but addressing polarity first is more efficient.


NEW QUESTION # 268
You are monitoring a server with 8 GPUs used for deep learning training. You observe that one of the GPUs reports a significantly lower utilization rate compared to the others, even though the workload is designed to distribute evenly. 'nvidia-smi' reports a persistent "XID 13" error for that GPU. What is the most likely cause?

  • A. An incorrect CUDA version installed.
  • B. Insufficient system memory preventing data transfer to that GPU.
  • C. The GPU's compute mode is set to 'Exclusive Process'.
  • D. A driver bug causing incorrect workload distribution.
  • E. A hardware fault within the GPU, such as a memory error or core failure.

Answer: E

Explanation:
XID 13 errors in 'nvidia-smi' typically indicate a hardware fault within the GPU. Driver bugs or memory issues would likely cause different error codes or system instability across multiple GPUs. CUDA version mismatch might prevent the application from running altogether, but is less likely to lead to a specific XID error on a single GPU. Exclusive Process mode will lead to it being used by a different process but not necessarily cause that XID error.


NEW QUESTION # 269
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