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[General] Detailed NCP-AII Study Dumps, Reliable NCP-AII Learning Materials

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【General】 Detailed NCP-AII Study Dumps, Reliable NCP-AII Learning Materials

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NVIDIA AI Infrastructure Sample Questions (Q297-Q302):NEW QUESTION # 297
You are configuring a switch port connected to a host in an NCP-AII environment. The host is running RoCEv2. To optimize performance and prevent packet loss, which flow control mechanism should you enable on the switch port?
  • A. Priority Flow Control (PFC) or 802.1 Qbb, specifically for the traffic class associated with RoCEv2.
  • B. TCP flow control.
  • C. Simple Network Management Protocol (SNMP).
  • D. None; flow control is not needed with RoCEv2.
  • E. Spanning Tree Protocol (STP).
Answer: A
Explanation:
Priority Flow Control (PFC), also known as 802.1Qbb, is the appropriate flow control mechanism for RoCEv2. RoCEv2 is a lossless Ethernet protocol, and PFC allows you to enable flow control on specific traffic classes, preventing packet loss in congested situations. By enabling PFC specifically for the traffic class carrying RoCEv2 traffic, you ensure that high-priority A1 training data is delivered reliably without being affected by congestion on other parts of the network.

NEW QUESTION # 298
When deploying BlueField OS using PXE boot, which of the following files on the PXE server is responsible for specifying the kernel, initrd, and device tree files to be loaded by the client?
  • A. pxelinux.cfg/default
  • B. dhcpd .conf
  • C. /boot/grub/grub.cfg
  • D. tftpboot/lpxelinux.0
  • E. tftpboot/pxelinux.0
Answer: A
Explanation:
The 'pxelinux.cfg/default' file (or a similar configuration file based on the client's MAC address or IP address) contains the configuration directives for the PXE bootloader, including specifying the kernel, initrd, and device tree files. 'dhcpd.conf is for DHCP server configuration, 'pxelinux.ff is the PXE bootloader itself, and '/boot/grub/grub.cfg' is a GRUB configuration file, usually on the client's disk.

NEW QUESTION # 299
What is the primary function of the NVIDIA Container Toolkit, and how does it facilitate the use of GPUs within containerized environments? (Multiple Answers)
  • A. It enables monitoring of GPU utilization within containers.
  • B. It automatically installs the necessary NVIDIA drivers inside the container.
  • C. It manages the lifecycle of containers running GPU-accelerated workloads.
  • D. It allows containers to access and utilize NVIDIA GPUs by injecting the necessary drivers and libraries into the container runtime environment.
  • E. It provides a set of command-line tools for managing NVIDIA drivers on the host system.
Answer: A,D
Explanation:
The NVIDIA Container Toolkit allows containers to access and utilize NVIDIA GPUs by injecting the necessary drivers and libraries into the container runtime environment and It enables monitoring of GPU utilization within containers. While it requires proper drivers to be installed, the toolkit does not manage host drivers directly. The NVIDIA container toolkit relies on container runtimes, and container runtimes manage the container lifecycle. The container toolkit does not automatically install drivers inside containers.

NEW QUESTION # 300
You are tasked with selecting transceivers for a new NVIDIA Quantum-2 InfiniBand switch deployment. The primary requirement is to minimize power consumption while maintaining 400Gbps bandwidth over short distances (up to 50 meters). Which transceiver type would offer the BEST power efficiency in this scenario?
  • A. QSFP-DD LR8
  • B. QSFP-DD SR8
  • C. QSFP-DD DR4
  • D. QSFP-DD AOC
  • E. QSFP-DD SR4
Answer: E
Explanation:
SR4 transceivers are known for their relatively low power consumption compared to other 400GbE transceiver types. This is because they use a simpler modulation scheme and shorter reach, requiring less power for signal amplification and processing. LR8 and DR4 are designed for longer distances and consume more power. AOCs, while convenient, are not typically the most power-efficient option. SR8 may consume slightly higher power than SR4 but provides better performance in certain scenarios.

NEW QUESTION # 301
You are deploying a multi-GPU server for deep learning training. After installing the GPUs, the system boots, but 'nvidia-smi' only detects one GPU. The motherboard has multiple PCle slots, all of which are physically capable of supporting GPUs. What is the most probable cause?
  • A. The system BIOS/UEFI is not configured to enable all PCle slots or the PCle lanes are not allocated correctly. Check the BIOS/IJEFI settings to enable all slots and configure the PCle lane allocation (e.g., x16/x8/x8).
  • B. The other GPUs are not properly seated in their PCle slots. Reseat the GPUs and ensure they are securely connected.
  • C. The NVIDIA drivers are not installed correctly or are incompatible with the GPUs. Reinstall the drivers and ensure they are compatible with the specific GPU model and CUDA version.
  • D. The other GPUs are faulty and need to be replaced. Test each GPU individually to confirm their functionality.
  • E. The power supply is not providing enough power to all GPIJs. Upgrade to a higher wattage power supply.
Answer: A
Explanation:
Incorrect BIOS/UEFI settings are the most likely cause when GPUs are physically present but not detected. The BIOS controls PCle lane allocation and slot enabling. Reseating GPUs is a good first step, but if the BIOS is misconfigured, it won't resolve the issue. Insufficient power is also a possibility, but BIOS configuration is more common in initial setup.

NEW QUESTION # 302
......
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