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NVIDIA NCP-AII Exam Overview:

Certification Vendor:NVIDIA
Exam Name:NVIDIA-Certified Professional AI Infrastructure Exam
Exam Number:NCP-AII
Exam Duration:120 minutes
Exam Price:$400 USD
Exam Format:Scenario-based items, Multiple-choice questions
Real Exam Qty:60-70
Related Certifications:NVIDIA-Certified Professional AI Networking (NCP-AIN)
NVIDIA-Certified Associate AI Infrastructure and Operations (NCA-AIIO)
NVIDIA-Certified Professional AI Operations (NCP-AIO)
Passing Score:Pass/Fail only, no numerical score
Certificate Validity Period:2 years
Available Languages:English
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 2โ€“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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NVIDIA NCP-AII Exam Syllabus Topics:

TopicDetails
Topic 1
  • System and Server Bring-up: Covers end-to-end physical setup of GPU-based AI infrastructure, including BMC
  • OOB
  • TPM configuration, firmware upgrades, hardware installation, and power and cooling validation to ensure servers are workload-ready.
Topic 2
  • Cluster Test and Verification: Covers full cluster validation through HPL and NCCL benchmarks, NVLink and fabric bandwidth tests, cable and firmware checks, and burn-in testing using HPL, NCCL, and NeMo.
Topic 3
  • Troubleshoot and Optimize: Covers identifying and replacing faulty hardware components such as GPUs, network cards, and power supplies, along with performance optimization for AMD
  • Intel servers and storage.
Topic 4
  • Physical Layer Management: Covers configuring BlueField network platform devices and setting up Multi-Instance GPU (MIG) partitioning for AI and HPC workloads.
Topic 5
  • Control Plane Installation and Configuration: Covers deploying the software stack including Base Command Manager, OS, Slurm
  • Enroot
  • Pyxis, NVIDIA GPU and DOCA drivers, container toolkit, and NGC CLI.

NVIDIA AI Infrastructure Sample Questions (Q158-Q163):

NEW QUESTION # 158
After installing the NGC CLI, you attempt to run 'ngc config set' and encounter the following error: 'Error: API key is invalid or missing'.
What are the most likely causes of this issue and how can you resolve them?

Answer: B,C,D

Explanation:
The most likely cause is an invalid API key (B) or a corrupted configuration file (C), or the host lacks network access (E). Reinstalling the package (A) might not resolve the issue if the problem lies with the API key or config file. While NGC service outages (D) are possible, they are less common.


NEW QUESTION # 159
Given the following 'nvswitch-cli' output, what does the 'Link Speed' indicate, and what potential bottleneck might a low 'Link Speed' suggest?

Answer: D

Explanation:
The 'Link Speed' in 'nvswitch-cli' output refers to the effective bandwidth of the NVLink connection between the GPUs and the switch. A low value compared to the expected speed indicates a potential problem with the NVLink cables, their connections, or misconfiguration that's preventing the link from operating at its full potential. It is not related to memory clock, PCle, or NVLink protocol version but direct NVLink performance.


NEW QUESTION # 160
After a firmware upgrade on a DGX H100, the administrator notices that one GPU is not detected by the system. Which troubleshooting step should be performed first to identify the root cause?

Answer: B

Explanation:
The first step is to review the firmware update logs and run nvsm show health. After a DGX H100 firmware upgrade, a missing GPU can result from incomplete firmware activation, failed component update, PCIe enumeration failure, GPU tray communication issues, BMC inventory mismatch, or an actual hardware fault.
NVSM is the correct DGX platform-level health tool because it checks hardware state across GPUs, NVSwitch components, PCIe devices, storage, power, cooling, and system sensors. Firmware logs are equally important because they show whether each update completed successfully and whether a reboot, cold power cycle, BMC reset, or AC power cycle is still required. Replacing the GPU immediately is premature and may cause unnecessary downtime. Ignoring the issue is unsafe because production AI workloads expect all GPUs to be visible and healthy. Re-running firmware across all components without diagnosis can hide the original failure or introduce more risk. Proper bring-up practice is to collect evidence, verify hardware health, confirm firmware activation state, and then decide whether reseating, power cycling, reapplying firmware, or service escalation is required.


NEW QUESTION # 161
Refer to the exhibit. What is the maximum bandwidth supported by Direct Attach Copper (DAC) LinkX cables?

Answer: D

Explanation:
NVIDIA LinkX Direct Attach Copper cables support high-speed Ethernet and InfiniBand connectivity up to 400 Gbps, making them suitable for dense GPU cluster interconnects and short-reach data center links.


NEW QUESTION # 162
You are tasked with validating the NVLink performance between GPUs in an NVIDIA DGXAI 00 system. Which tool is the most appropriate for measuring the bandwidth and latency of NVLink interconnections under a synthetic workload?

Answer: C

Explanation:
NCCL tests, specifically , are designed for benchmarking the communication performance between GPUs using NVLink. 'nvidia-smr provides GPU monitoring information but not detailed bandwidth/latency tests. 'iostat' is for 1/0 statistics. 'memtest86'' tests system memory. 'dmesg' displays kernel messages.


NEW QUESTION # 163
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