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[Hardware] Quiz 2026 NVIDIA NCP-AII: Trustable Unlimited NVIDIA AI Infrastructure Exam Prac

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【Hardware】 Quiz 2026 NVIDIA NCP-AII: Trustable Unlimited NVIDIA AI Infrastructure Exam Prac

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NVIDIA AI Infrastructure Sample Questions (Q289-Q294):NEW QUESTION # 289
You are replacing a faulty NVIDIA Tesla V 100 GPU in a server. After physically installing the new GPU, the system fails to recognize it. You've verified the power connections and seating of the card. Which of the following steps should you take next to troubleshoot the issue?
  • A. Check if the new GPU requires a different driver version than the currently installed one and update if needed.
  • B. Disable and re-enable the GPU slot in the system BIOS.
  • C. Update the system BIOS and BMC firmware to the latest versions.
  • D. Immediately RMA the new GPU as it is likely defective.
  • E. Reinstall the operating system to ensure proper driver installation.
Answer: A,C
Explanation:
After verifying the physical installation, the next steps are to ensure the system's firmware is up-to-date and that the correct drivers are installed. Older BIOS/BMC firmware may not properly recognize newer GPUs, and incorrect drivers will prevent the GPU from functioning correctly. RMAing the new GPU or reinstalling the OS prematurely are inefficient troubleshooting steps. The system BIOS may have an option to disable and enable the GPU slot, but that would be rare.

NEW QUESTION # 290
You are installing four NVIDIAAIOO GPUs in a server, and after installation, you observe that the PCle link speed for one of the GPUs is running at x8 instead of the expected x16. What could be the POSSIBLE causes for this reduced PCle link speed?
  • A. The PCle slot is only wired for x8 speed.
  • B. The CPU does not have enough PCle lanes to support all GPUs at x16.
  • C. All of the above
  • D. The GPU is faulty.
  • E. The BIOS/UEFI is configured to limit the PCle link speed for that slot.
Answer: C
Explanation:
A reduced PCle link speed can result from multiple factors: a faulty GPU, insufficient PCle lanes from the CPU, the physical wiring of the PCle slot, or a BIOS/IJEFI configuration limiting the speed. All these are potentially viable cause. Thus answer E is correct.

NEW QUESTION # 291
You're configuring a BlueField-3 DPU-based server for high-performance storage. You want to utilize NVMe-oF (NVMe over Fabrics) to access remote NVMe SSDs. What is the primary benefit of using a BlueField DPU in this NVMe-oF setup compared to a traditional server with a standard NIC?
  • A. BlueField DPU eliminates the need for a separate NVMe-oF target server.
  • B. BlueField DPU allows hot-swapping of NVMe SSDs without interrupting the NVMe-oF connection.
  • C. BlueField DPU automatically configures the NVMe-oF target without any manual intervention.
  • D. BlueField DPU provides built-in hardware encryption for all NVMe-oF traffic.
  • E. BlueField DPU offloads the NVMe-oF protocol processing, reducing CPU overhead on the host server.
Answer: E
Explanation:
The key advantage of using a BlueField DPU in an NVMe-oF setup is its ability to offload the NVMe-oF protocol processing. This significantly reduces the CPU overhead on the host server, allowing it to dedicate more resources to other tasks. While some DPUs might offer features like hardware encryption, the primary benefit is protocol offload.

NEW QUESTION # 292
You are setting up a new A1 server with multiple NVIDIA GPUs for deep learning workloads. You need to install the NVIDIA Container Toolkit. After installing the necessary packages using your distribution's package manager, what is the most crucial next step to ensure proper integration with Docker?
  • A. Restart the Docker daemon (e.g., 'systemctl restart docker'
  • B. Manually create vetc/docker/daemon.json' and add 'nvidia' as a default runtime.
  • C. Reboot the server to load the new kernel modules.
  • D. Run 'nvidia-smr to verify GPU detection. This automatically configures the container runtime.
  • E. Run 'nvidia-ctk runtime configure -runtime=docker' .
Answer: E
Explanation:
The 'nvidia-ctk runtime configure -runtime=docker' command is essential to configure Docker to use the NVIDIA Container Runtime. This integrates the NVIDIA drivers and libraries within the Docker environment, allowing containers to access the GPUs. While restarting Docker is often helpful, 'nvidia-ctk' performs the necessary configuration steps. Rebooting is not always necessary after just installing a package, and manually editing 'daemon.json' is generally not the recommended approach. 'nvidia-smi' simply reports the status of the GPUs, it doesn't configure the runtime.

NEW QUESTION # 293
You are setting up network fabric ports for hosts in an NVIDIA-Certified Professional A1 Infrastructure (NCP-AII) environment. You need to configure Jumbo Frames to improve network throughput. What is the typical MTU (Maximum Transmission Unit) size you would set on the network interfaces and switches, and why?
  • A. 1500 bytes, as it's the default and compatible with most networks.
  • B. Any MTU size between 1500 and 9000 bytes; the specific value doesn't matter.
  • C. 576 bytes, the minimum MTU size required by IPv4.
  • D. 9000 bytes, also known as Jumbo Frames, reduces overhead and improves throughput for large data transfers.
  • E. 65535 bytes, the theoretical maximum MTU size, for maximum performance.
Answer: D
Explanation:
For optimal performance in an A1 training environment, Jumbo Frames (MTU of 9000 bytes) are recommended. Increasing the MTU reduces the number of packets required to transmit a given amount of data, thereby reducing processing overhead and improving overall throughput. While technically larger MTUs are possible, 9000 is the standard for Jumbo Frames.

NEW QUESTION # 294
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