HIGH NCP-AII QUALITY - EXAM NCP-AII VCE

High NCP-AII Quality - Exam NCP-AII Vce

High NCP-AII Quality - Exam NCP-AII Vce

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Tags: High NCP-AII Quality, Exam NCP-AII Vce, Reliable NCP-AII Test Review, Reliable NCP-AII Exam Price, NCP-AII Questions Answers

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Exam NCP-AII Vce & Reliable NCP-AII Test Review

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NVIDIA AI Infrastructure Sample Questions (Q206-Q211):

NEW QUESTION # 206
You are deploying a cloud-native AI inference service using Kubernetes and NVIDIA GPUs. You need to ensure that GPU resources are efficiently allocated and monitored. Which of the following approaches is MOST effective for achieving this within the Kubernetes environment?

  • A. Using the NVIDIA Device Plugin for Kubernetes to advertise GPU resources and utilizing resource requests and limits to schedule pods on nodes with available GPUs.
  • B. Overcommitting GPU resources and relying on the Kubernetes scheduler to handle potential out-of-memory (OOM) errors.
  • C. Deploying a dedicated monitoring agent on each node to track GPU utilization and manually adjusting pod resource requests based on these metrics.
  • D. Relying solely on Kubernetes' default CPU and memory resource requests and limits, assuming GPU usage will be implicitly managed.
  • E. Manually assigning specific GPU devices to pods using hostPath volumes and environment variables.

Answer: A

Explanation:
The NVIDIA Device Plugin for Kubernetes is specifically designed to advertise GPU resources to the Kubernetes scheduler, enabling efficient allocation and utilization. Resource requests and limits ensure pods are scheduled on nodes with sufficient GPU capacity, preventing resource contention and 00M errors. Options A, C, D, and E are either ineffective, manual, or potentially lead to instability.


NEW QUESTION # 207
You are troubleshooting a network performance issue in your NCP-AII environment. After running 'ibstat' on a host, you see the following output for one of the InfiniBand ports:

What does the 'LMC: 0' indicate, and what are the implications for network performance?

  • A. LMC: 0 indicates that Link Aggregation (LAG) is not enabled on this port, meaning only a single link is being used for communication.
  • B. LMC : 0 is the default and expected value; it has no impact on performance.
  • C. LMC: 0 indicates that the link is down and not functioning correctly.
  • D. LMC : 0 indicates that the Subnet Manager is not running correctly.
  • E. LMC : 0 indicates the port is operating at the lowest possible speed.

Answer: A

Explanation:
LMC (Link Mask Capability) indicates the level of link aggregation enabled. LMC: 0 means that link aggregation is disabled. This means that only one link is being used for communication, which could limit the overall bandwidth and potentially create a bottleneck if multiple GPUs are trying to communicate through that single link. Higher LMC values indicate that multiple links are aggregated together to increase bandwidth.


NEW QUESTION # 208
After installing a new NVIDIA GPU, you attempt to run a CUDA application, but you encounter the following error: 'CUDA error: CUDA driver version is insufficient for CUDA runtime version'. You have verified the driver and CUDA toolkit are installed. What is the MOST likely reason for this error, and how do you resolve it?

  • A. The CUDA runtime libraries are missing from the system path. Add them to the PATH variable.
  • B. The CUDA VISIBLE DEVICES environment variable is not set correctly.
  • C. The CUDA toolkit is too old. Update the CIJDA toolkit.
  • D. The NVIDIA driver is too old for the CUDA toolkit. Update the NVIDIA driver to a version that supports the CUDA toolkit.
  • E. The GPU is not compatible with the CUDA toolkit. Install a different GPIJ.

Answer: D

Explanation:
This error indicates an incompatibility between the driver and the CUDA toolkit. The most common reason is an outdated driver. The driver must be at least as new as the CUDA toolkit's minimum required driver version. CUDA VISIBLE DEVICES relates to GPU selection, not driver version.


NEW QUESTION # 209
Consider the following scenario: You have a BlueField-2 DPU installed in a server. You are trying to establish RDMA (Remote Direct Memory Access) communication between the DPU and another server. However, the RDMA connection fails. Which of the following is the most crucial factor to verify in this scenario?

  • A. That the TCP window size is properly tuned for high-bandwidth communication.
  • B. That the correct MTU (Maximum Transmission Unit) is configured on the network interfaces involved in the RDMA connection.
  • C. That the clocks on both servers are synchronized using NTP (Network Time Protocol).
  • D. That the power supply to the DPU is providing sufficient wattage.
  • E. That the appropriate RDMA kernel modules (e.g., , 'ib_uverbs) are loaded on both the DPUand the remote server.

Answer: E

Explanation:
For RDMA to function correctly, the necessary kernel modules must be loaded on both ends of the connection. These modules provide the core functionality for RDMA communication. While MTU and other network settings are important, the absence of the RDMA modules will prevent the connection from being established in the first place. Clock synchronization and TCP window size are less directly related to the initial RDMA connection failure. Power supply issues would likely manifest in other ways.


NEW QUESTION # 210
You are configuring network fabric ports for NVIDIA GPUs in a server. The GPUs are connected to the network via PCIe. What is the primary factor that determines the maximum achievable bandwidth between the GPUs and the network?

  • A. The amount of system RAM.
  • B. The speed of the system's hard drives or SSDs.
  • C. The PCIe generation and number of lanes connecting the GPUs to the network adapter (e.g., PCIe 4.0 x16).
  • D. The clock speed of the CPU.
  • E. The color of the Ethernet cables.

Answer: C

Explanation:
The PCIe generation (e.g., PCIe 4.0, PCIe 5.0) and the number of lanes (e.g., x8, x16) directly determine the maximum theoretical bandwidth available between the GPUs and the network adapter. Higher PCIe generations and more lanes provide greater bandwidth. For example, PCIe 4.0 x16 offers significantly more bandwidth than PCIe 3.0 x8. All other options are either irrelevant or have a negligible impact on this particular bottleneck.


NEW QUESTION # 211
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