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| Certification Vendor: | NVIDIA |
|---|---|
| Exam Name: | NVIDIA-Certified Professional AI Infrastructure Exam |
| Exam Number: | NCP-AII |
| Related Certifications: | NVIDIA-Certified Professional AI Operations (NCP-AIO) NVIDIA-Certified Associate AI Infrastructure and Operations (NCA-AIIO) NVIDIA-Certified Professional AI Networking (NCP-AIN) |
| Available Languages: | English |
| Real Exam Qty: | 60-70 |
| Exam Duration: | 120 minutes |
| Passing Score: | Pass/Fail only, no numerical score |
| Exam Format: | Scenario-based items, Multiple-choice questions |
| Certificate Validity Period: | 2 years |
| Exam Price: | $400 USD |
| Recommended Training: | NVIDIA AI Infrastructure Training |
| Exam Registration: | NVIDIA Certification Portal |
| Sample Questions: | NVIDIA NCP-AII Sample Questions |
| Exam Way: | Online remote proctored or onsite at authorized test centers |
| Pre Condition: | No mandatory prerequisites; recommended 2–3 years of experience in data center infrastructure, Linux administration, and NVIDIA hardware/software environments |
| Official Syllabus URL: | https://www.nvidia.com/en-us/learn/certification/ai-infrastructure-professional/ |
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NEW QUESTION # 165
An infrastructure engineer in an AI factory has successfully replaced a power supply unit on an NVIDIA DGX H100. After installation, both the IN and OUT LEDs on the new power supply illuminate solid green.
Which NVSM CLI command should the engineer use to quickly verify the overall system status and ensure it is operating as expected?
Answer: D
Explanation:
The NVIDIA System Management (NVSM) tool is the definitive CLI utility for monitoring the health of DGX platforms. While replacing a PSU (Power Supply Unit) is a common maintenance task, verifying that the new component is correctly integrated into the system's health model is mandatory. While nvsm show power would provide specific data regarding wattage and voltage for the PSU, the most comprehensive way to ensure the replacement hasn ' t caused secondary issues or that the system hasn ' t remained in a " Degraded
" state is to run nvsm show health. This command performs a global check across all subsystems: GPUs, NVLink switches, storage, fans, and power. If the PSU replacement was successful and the system is back to full redundancy, nvsm show health will return a " Healthy " status. In an AI factory setting, where DGX H100 nodes pull significant power, ensuring that all 6 PSUs (in an N+N or N+1 configuration) are not only physically green but logically acknowledged by the Baseboard Management Controller (BMC) is critical for preventing unexpected shutdowns during high-load training iterations.
NEW QUESTION # 166
Your deep learning training job that utilizes NCCL (NVIDIA Collective Communications Library) for multi-GPU communication is failing with "NCCL internal error, unhandled system error" after a recent CUDA update. The error occurs during the 'all reduce' operation.
What is the most likely root cause and how would you address it?
Answer: E
Explanation:
NCCL relies on specific CUDA versions. An incompatibility after a CUDA update is the most probable cause. Insufficient shared memory is less likely to cause a system error within NCCL. Firewall rules usually manifest as connection refused errors. Faulty network cables affect inter-node communication, not intra-node. While RDMA issues can cause problems, they typically don't present as 'unhandled system error' immediately after a CUDA update, and are more likely if RDMA was working previously.
NEW QUESTION # 167
A system administrator needs to change the RAID level of DGX station and use the script included in the DGX software with no data on the array. What are the options the administrator can choose?
Answer: A
Explanation:
The DGX Station RAID configuration script supports configuring the data array as RAID 0 or RAID 5. RAID 0 provides maximum performance and capacity, while RAID 5 provides fault tolerance with usable capacity tradeoff.
NEW QUESTION # 168
A user reports that their CUDA application is running slower than expected after an NVIDIA driver update. You suspect a driver compatibility issue. How can you revert to a previous NVIDIA driver version on an Ubuntu system, assuming you have the older driver package 'nvidia-driver-470 470.82.00-0ubuntu1_amd64.deb'?
Answer: A
Explanation:
The safest and most reliable approach is to first remove the current NVIDIA driver using 'sudo apt purge nvidia- to avoid conflicts. Then, install the .deb' package using 'sudo dpkg -i' and resolve any potential dependency issues with 'sudo apt -fix-broken install'. 'nvidia-smi' cannot downgrade drivers. Editing "/etc/apt/sources.list' can be risky and lead to system instability. Directly installing with 'dpkg -i' without purging the old driver can cause conflicts. If you installed with .run' before, then you must uninstall using that method first.
NEW QUESTION # 169
The system administrator plans to use Multi-Instance GPU profiles. What command should be used to verify that the GPU has this mode enabled?
Answer: D
Explanation:
The correct command is nvidia-smi. Multi-Instance GPU, or MIG, is managed and verified through NVIDIA System Management Interface utilities. On supported GPUs such as NVIDIA A100 and H100, nvidia-smi can be used to check whether MIG mode is enabled, list available GPU instances, and confirm how the GPU is partitioned. For example, administrators commonly use commands such as nvidia-smi, nvidia-smi -L, or nvidia-smi -i < GPU_ID > -q to inspect GPU state and MIG information. The options nvidia-mode, nvidia- mig, and nvidia-enable are not standard NVIDIA commands for verifying MIG mode. This is an important server bring-up step because MIG profiles must be confirmed before workloads are scheduled through Kubernetes, Slurm, NVIDIA GPU Operator, or other cluster management tools. If MIG is not enabled or profiles are not created correctly, users may not see the expected GPU slices, and AI inference or multi-tenant workloads can fail placement or run with incorrect resource isolation.
NEW QUESTION # 170
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