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[General] Pass4sure NCP-AII Exam Prep | NCP-AII Test Questions Fee

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【General】 Pass4sure NCP-AII Exam Prep | NCP-AII Test Questions Fee

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NVIDIA AI Infrastructure Sample Questions (Q242-Q247):NEW QUESTION # 242
You're managing a cluster of servers with BlueField-2 DPUs. One server is experiencing intermittent network connectivity issues. You suspect a problem with the DPU's firmware. Which of the following is the MOST reliable method to determine the CURRENT firmware version of the BlueField-2 DPIJ?
  • A. Examine the '/proc/driver/mlx4_core/versiorf file.
  • B. Check the system logs for firmware-related messages during boot.
  • C. Use the 'mst status' command to query the device status and firmware version.
  • D. Query the DPIJ's BMC (Baseboard Management Controller) via IPMI or Redfish.
  • E. Run 'ethtool -i on a network interface associated with the DPIJ.
Answer: C
Explanation:
'mst status' is the most reliable method. This command, part of the Mellanox OFED tools, is specifically designed to query the status of Mellanox devices, including the DPLJ, and accurately reports the firmware version. While other methods might provide clues, 'mst statuS is the definitive source of truth.

NEW QUESTION # 243
You have a GPU-intensive application that requires the latest features of CUDA 12. However, your host system's NVIDIA driver is only compatible with CUDA 11.8. What steps can you take to enable your application to use CUDA 12 within a Docker container, without upgrading the host driver?
  • A. Use a Docker image based on 'nvidia/cuda:12.0-base-ubuntu20.04'. The NVIDIA Container Toolkit will automatically handle the driver compatibility between the host and the container.
  • B. Downgrade the application to use CUDA 11.8 to match the host's driver version.
  • C. Mount the CUDA 12 libraries from a separate Docker volume into the container and configure the accordingly.
  • D. Upgrade the NVIDIA driver on the host system to the latest version compatible with CUDA 12.
  • E. Install CUDA 12 inside the Docker container and set the 'CUDA DRIVER VERSION' environment variable to match the host driver version.
Answer: A
Explanation:
The NVIDIA Container Toolkit enables compatibility between the host driver and the CUDA version within the container (B). Using a Docker image based on will allow your application to leverage CUDA 12 features. Upgrading the host driver (A) is an option but not necessary and may introduce other compatibility issues. Setting (C) is not a standard or reliable approach. Mounting CUDA libraries from a volume (D) is complex and might not resolve driver version mismatches. Downgrading the application (E) avoids the problem but sacrifices access to CUDA 12 features. Because NVIDIA ensures a degree of backwards compatibility, the newer toolkit in the container can often work with an older driver on the host.

NEW QUESTION # 244
You are installing eight NVIDIAAIOO GPUs in a server designed for maximum performance. The server supports NVLink. Which of the following actions will BEST improve the inter-GPU communication bandwidth?
  • A. Only installing four of the eight GPUs to reduce the total number of connections needed.
  • B. Ensuring the GPUs are placed in slots that support NVLink bridges and that the bridges are properly installed.
  • C. Using a standard PCIe riser card for all GPUs.
  • D. Installing the GPUs in PCIe Gen3 slots instead of PCIe Gen4 slots.
  • E. Disabling NVLink in the BIOS/UEFI settings.
Answer: B
Explanation:
NVLink provides significantly higher bandwidth than PCle for inter-GPIJ communication. Installing the GPUs in slots that support NVLink and properly installing the NVLink bridges will enable this faster communication. PCle Gen4 is better than Gen3. Riser cards don't improve communication bandwidth. Disabling NVLink negates its benefits. Removing GPUs reduces overall performance.

NEW QUESTION # 245
You are tasked with installing the NGC CLI on a host that does not have direct internet access. You have downloaded the NGC CLI package to a local repository. Which of the following steps are required to successfully install and configure the NGC CLI in this offline environment?
  • A. Run 'ngc config set' to configure the API key, pointing to a local configuration file.
  • B. Configure the NGC CLI to point to your local package repository by setting the environment variable.
  • C. Only copying the whl file is sufficient, NGC CLI dependencies are always local
  • D. Transfer the NGC CLI package to the host and install it using 'pip install .whl'.
  • E. Manually download and install all dependencies of the NGC CLI package using 'pip install --no-index --find-links=/path/to/dependencies .whl'.
Answer: A,B,D,E
Explanation:
In an offline environment, you need to install the package locally (A), configure the CLI to know where to find the package (B), manually install dependencies (C), and configure the API key (D). Option E is wrong because dependencies must be handled manually in the offline environment.

NEW QUESTION # 246
You have a server with two NVIDIA GPUs connected via NVLink. You want to verify that NVLink is functioning correctly. Which command(s) or tool(s) can you use to check the NVLink status and bandwidth?
  • A. 'nvidia-smi nvlink -statue
  • B. 'nvidia-settings' (GUI tool)
  • C. nvcc -version'
  • D. 'nvidia-smi topo -m'
  • E. Ispci'
Answer: A,D
Explanation:
'nvidia-smi nvlink -statuS provides a direct overview of the NVLink status, including link speed and errors. 'nvidia-smi topo shows the topology of the GPUs and how they are connected, including NVLink connections. 'Ispci' lists PCl devices but doesn't provide NVLink- specific information. 'nvcc -version' checks the CUDA compiler version. 'nvidia-settings' is a GUI tool that can display some information, but it's less precise than 'nvidia-smr for NVLink status.

NEW QUESTION # 247
......
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