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NCP-AII시험덤프데모, NCP-AII인기덤프문제

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퍼펙트한 NCP-AII시험덤프데모 덤프데모문제

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최신 NVIDIA-Certified Professional NCP-AII 무료샘플문제 (Q118-Q123):

질문 # 118
You encounter an error during the BlueField OS flashing process using 'bfboot: 'ERROR: Could not detect a BlueField device'. Which of the following steps is MOST likely to resolve the issue?

A. Update the 'bfboot' utility to the latest version. Older versions may have compatibility issues.
B. Install the Mellanox OFED drivers on the host system. These drivers are required for 'bfboot' to function correctly.
C. Ensure the BlueField device is powered on and properly connected to the host system via PCIe.
D. Verify that the correct PCIe slot is being used. Some systems may have specific slots designated for SmartNICs.
E. Check the systems BIOS/UEFI to confirm that SR-IOV is enabled.

정답：C

설명：
The most basic and common cause of this error is a physical connection issue. Ensuring the device is powered and connected is the first step. While other options might be relevant in specific scenarios, connectivity is the most probable cause.

질문 # 119
You're deploying a new cluster with multiple NVIDIAAIOO GPUs per node. You want to ensure optimal inter-GPU communication performance using NVLink. Which of the following configurations are critical for achieving maximum NVLink bandwidth?

A. The NVIDIA driver must be configured to enable NVLink; it is disabled by default.
B. All GPUs within a node must be the same model and have identical firmware versions.
C. GPUs should be physically installed in slots that maximize direct NVLink connections based on the server's architecture.
D. The server must use a specific CPU model to leverage NVLink capabilities.
E. The motherboard must support PCle Gen5 to maximize NVLink bandwidth.

정답：B,C

설명：
For optimal NVLink performance, several conditions must be met. GPUs of the same model and firmware ensure compatibility and prevent performance bottlenecks. Physical placement is critical; GPUs must be installed in slots that maximize direct NVLink connections, as defined by the server's architecture and documentation. While PCle Gen5 is beneficial for overall system performance, it does not directly impact NVLink bandwidth. NVLink is typically enabled by default. Some CPU models may be preferable, but it's the motherboard's NVLink topology that is more important.

질문 # 120
Consider this Python code snippet used for loading data for a deep learning model:

Assuming the images are stored on a remote file system accessed over NFS, and training is slow due to I/O bottlenecks, which change to the 'DataLoader' would MOST directly improve performance?

A. Implement multithreaded data loading inside _getitem
B. Decrease 'num workers' to 1.
C. Increase 'num_workers' to a value equal to the number of CPU cores on each training node.
D. Set in the DataLoader.
E. Increase 'batch_size' significantly (e.g., to 256).

정답：C

설명：
Explanation: Increasing 'num_workerS allows the DataLoader to load data in parallel, which can help to overcome the I/O bottleneck when using NFS. Setting it to the number of CPU cores on each training node often yields the best performance. Increasing 'batch_size' helps, but it has diminishing returns if I/O is the primary bottleneck. Decreasing 'num_workers' will worsen the bottleneck. Primarily improves GPU memory transfer performance, not I/O performance from NFS. Multithreading inside _getitem is more complex and can lead to contention if not implemented carefully.

질문 # 121
You have configured two lg.10gb MIG instances on an NVIDIAA100 GPU. You are running a deep learning training job on one instance and want to ensure that it cannot consume resources from the other MIG instance. Which mechanism ensures isolation between the two MIG instances at the hardware level?

A. MIG hardware partitioning
B. vGPIJ scheduling
C. CUDA Multi-Process Service (MPS)
D. Kubernetes resource quotas
E. cgroups

정답：A

설명：
MIG (Multi-lnstance GPU) provides hardware-level partitioning of the GPU. This means that each MIG instance has dedicated compute, memory, and memory bandwidth resources, ensuring strong isolation between the instances. CUDA MPS allows multiple processes to share a single GPU, but does not provide isolation. vGPU scheduling is for virtualized environments. Kubernetes resource quotas provide resource limits at the container orchestration level but do not provide hardware-level isolatiom Cgroups is a Linux kernel feature to limit, account, and isolate resource usage (CPU, memory, disk I/O, network, etc.) of process groups. It is often used in conjunction with containerization technologies such as Docker, but does not directly influence the MIG hardware partitioning.

질문 # 122
You are installing four NVIDIAAIOO GPUs into a server designed for AI training. The server motherboard has multiple PCIe Gen4 x16 slots. However, the server's power supply unit (PSU) only has three 8-pin PCIe power connectors available. What is the BEST course of action to ensure all GPUs receive adequate power?

A. Replace the existing PSU with a higher wattage PSU that has at least four 8-pin PCIe power connectors.
B. Underclock the GPUs significantly to reduce their power consumption below the available PSU capacity.
C. Connect the GPUs using the motherboard's internal SATA power connectors.
D. Use a PCIe power splitter cable on one of the 8-pin connectors to power two GPUs.
E. Install only three GPUs and leave the fourth unpowered.

정답：A

설명：
Using a splitter can overload the original connector and cause instability or damage. Leaving a GPU unpowered defeats the purpose. SATA connectors are not designed for the high power requirements of GPUs. Underclocking might work, but is not a reliable long-term solution. Replacing the PSU is the safest and most reliable solution.

질문 # 123
......

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NCP-AII시험덤프데모 덤프문제 NVIDIA AI Infrastructure 기출자료

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