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NCP-AII Latest Examprep - NCP-AII Exam Passing Score

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NVIDIA AI Infrastructure Sample Questions (Q41-Q46):

NEW QUESTION # 41
You have installed NVIDIA drivers using the .run' installer on a system running Ubuntu. However, after each kernel update, the NVIDIA drivers stop working. What is the most effective way to address this issue permanently?

A. Disable automatic kernel updates.
B. Manually compile the NVIDIA kernel modules after each kernel update.
C. Re-run the '.run' installer after each kernel update.
D. Create a script that symlinks the old kernel modules to the new kernel directory.
E. Use DKMS (Dynamic Kernel Module Support) to automatically rebuild the NVIDIA kernel modules after each kernel update.

Answer: E

Explanation:
DKMS (Dynamic Kernel Module Support) is the most effective solution. It automatically rebuilds kernel modules (like NVIDIA's) whenever a new kernel is installed. Re-running the Irun' installer is a manual and error-prone process. Disabling kernel updates is not recommended for security reasons. Manually compiling is complex and time-consuming. Symlinking old modules is unlikely to work due to kernel API changes.

NEW QUESTION # 42
You're deploying a multi-GPU training job on a cluster using Slurm. You need to ensure that the GPUs allocated to the job are healthy and functioning correctly before the training starts. What's the MOST effective approach to pre-validate the GPU hardware?

A. Run a simple CUDA vector addition program on each GPU and check for errors.
B. Monitor the GPU temperature using 'nvidia-smi' during the first few minutes of the training job.
C. Execute the NVIDIA Data Center GPU Manager (DCGM) diagnostic suite on the allocated GPUs.
D. Check the output of 'nvidia-smi' to ensure all GPUs are listed and have the expected memory.
E. Allocate all available GPUs to the job and assume they are healthy.

Answer: C

Explanation:
Using the DCGM diagnostic suite is the most thorough way to pre-validate GPU hardware. DCGM provides comprehensive tests to check GPU health, including memory, compute, and interconnects. A simple CUDA program or checking nvidia-smr provides basic validation, but not as comprehensive as DCGM. Monitoring temperature is reactive, not proactive. Assuming GPUs are healthy without validation is risky.

NEW QUESTION # 43
You've installed a new NVIDIA GPU in your A1 server. After the installation and driver setup, you notice that while 'nvidia-smi' recognizes the GPU, the available memory reported is significantly lower than the GPU's specifications. What are the potential root causes and how would you systematically troubleshoot this?

A. The system BIOS is incorrectly configured, limiting GPU memory allocation.
B. The driver is not correctly installed. Reinstall the latest NVIDIA driver.
C. The integrated graphics is using a significant amount of system memory, reducing what's available to the GPU. Disable the integrated graphics in the BIOS.
D. The reported memory is the currently allocated memory, not the total available. Run a CUDA program to allocate more memory and observe the change.
E. The GPU is faulty and needs to be replaced.

Answer: C

Explanation:
Integrated graphics stealing system memory is a common cause, and disabling it frees up resources for the dedicated GPU. While a faulty GPU, BIOS settings, or driver issues are possibilities, integrated graphics is a more likely and easily verifiable cause. The reported memory is the total usable, not just allocated.

NEW QUESTION # 44
You are implementing a security policy on a BlueField-2 DPU to filter traffic based on specific application signatures. Which technology, supported by BlueField, allows you to achieve deep packet inspection (DPI) and apply security rules based on the detected application?

A. IPsec (Internet Protocol Security) tunnels.
B. Netfilter with connection tracking.
C. eBPF (extended Berkeley Packet Filter) with XDP (eXpress Data Path).
D. OVS (Open vSwitch) with OpenFlow rules.
E. TC (Traffic Control) with 'iptables' rules.

Answer: C

Explanation:
eBPF with XDP is the most suitable technology for deep packet inspection (DPI) on BlueField. It allows you to run custom code at near-line speed to inspect packets and apply security rules based on application signatures. TC and Netfilter are less efficient for DPI, OVS/OpenFlow are more for switching policies, and IPsec focuses on encryption.

NEW QUESTION # 45
An AI server with 8 GPUs is experiencing random system crashes under heavy load. The system logs indicate potential memory errors, but standard memory tests (memtest86+) pass without any failures. The GPUs are passively cooled. What are the THREE most likely root causes of these crashes?

A. GPIJ memory errors that are not detectable by standard CPU-based memory tests.
B. Network congestion causing intermittent data corruption during distributed training.
C. A faulty power supply unit (PSU) that is unable to provide stable power under peak load.
D. Insufficient airflow within the server, leading to overheating of the GPUs and VRMs.
E. Incompatible NVIDIA driver version with the installed Linux kernel.

Answer: A,C,D

Explanation:
GPU memory errors (B) are a strong possibility, as CPU-based tests don't test GPU memory directly. Insufficient airflow (C) is likely due to the passive cooling, leading to thermal instability. A faulty PSU (D) can cause random crashes under load due to power fluctuations. Driver incompatibility (A) is less likely to cause random crashes after initial setup, and network congestion (E) usually results in training slowdowns rather than system crashes.

NEW QUESTION # 46
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