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| Certification Vendor: | NVIDIA |
|---|---|
| Exam Name: | NVIDIA AI Infrastructure (NCP-AII) Certification Exam |
| Exam Number: | NCP-AII |
| Exam Duration: | 120 minutes |
| Available Languages: | English |
| Certificate Validity Period: | 2 years |
| Exam Price: | $400 |
| Real Exam Qty: | 70-75 |
| Exam Format: | Multiple-choice, Scenario-based questions |
| Related Certifications: | NVIDIA-Certified Associate AI Infrastructure and Operations (NCA-AIIO) NVIDIA-Certified Professional AI Operations (NCP-AIO) NVIDIA-Certified Professional AI Networking (NCP-AIN) |
| Recommended Training: | AI Infrastructure Professional Workshop AI Infrastructure & Operations Fundamentals (NVIDIA Training) |
| Exam Registration: | NVIDIA AI Infrastructure Certification Page Official NVIDIA Certification Portal |
| Sample Questions: | NVIDIA NCP-AII Sample Questions |
| Exam Way: | Online proctored exam (remote) or authorized test center depending on region |
| Pre Condition: | Recommended 2โ3 years of experience working in data center environments with NVIDIA hardware solutions (GPU servers, networking, storage). |
| Official Syllabus URL: | https://www.nvidia.com/en-eu/learn/certification/ai-infrastructure-professional/ |
>> NCP-AII Certification Sample Questions <<
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NEW QUESTION # 26
After running a 24-hour stress test on a DGX node, the administrator should verify which two key metrics to ensure system stability?
Answer: A
Explanation:
A 24-hour stress test (using tools like HPL or NCCL) is designed to push the thermal and electrical limits of a DGX system. To verify a " Pass, " the administrator must ensure that the hardware maintained its performance targets without degradation. Consistent GPU utilization > 95% confirms that the workload successfully saturated the compute cores for the entire duration. Crucially, the absence of thermal throttling events (verified via nvidia-smi -q -d PERFORMANCE) ensures that the system ' s cooling solution (fans and heatsinks) is adequate for the environment; if throttling occurred, the GPUs would have slowed down to protect themselves, indicating a potential cooling failure or environmental heat issue. While power consumption (Option D) and CPU usage (Option A) are interesting, they are not the primary indicators of " Stability " under extreme AI training loads. System stability is defined by the ability to run at peak speeds indefinitely without hardware-level interventions or slowdowns.
NEW QUESTION # 27
A critical AI model training job consistently fails on a specific GPU server in your cluster after running for approximately 24 hours.
Monitoring data shows a sudden drop in GPU power consumption followed by a system reboot. All other GPUs on the server appear normal. The server has redundant PSUs. What is the MOST likely cause?
Answer: D
Explanation:
Thermal runaway (B) is the most probable cause. The 24-hour delay suggests a gradual heat buildup. A failing TIM would cause the GPU to overheat until it triggers a thermal shutdown, resulting in the power drop and reboot. While a PSU issue (C) is possible, redundant PSUs should prevent a complete failure unless one PSU is completely dead and the second PSU is overloaded by the entire load for a short period. The other options are less likely to cause this specific failure pattern.
NEW QUESTION # 28
An AI infrastructure utilizes NVIDIA ConnectX-7 NICs for inter-node communication. The requirement is to achieve a bandwidth of 400GbE with low latency over a distance of 100 meters. Which transceiver and cable type combination is MOST suitable for this scenario?
Answer: D
Explanation:
QSFP-DD SR4 with OM4 provides 400GbE over short distances (up to 100m) using multi-mode fiber. DR4 and FR4 require single- mode fiber and are typically used for longer distances. LR8 typically requires single mode fibre for specified distances. Using SR8 with OM3 is unlikely to achieve 400GbE as SR8 works best with OM4/OM5.
NEW QUESTION # 29
You are setting up a BlueField-2 SmartNIC and want to offload network functions. Which of the following are valid methods for enabling hardware offload capabilities?
Answer: A,C
Explanation:
The 'ethtoor command is used to configure various network interface settings, including enabling/disabling hardware offload features. Installing the correct Mellanox OFED drivers is crucial, as they provide the necessary modules and tools to utilize the hardware offload capabilities. While device tree modification can influence hardware behavior, it's less common and typically handled by driver configuration. A custom script directly programming the hardware is unlikely and driver recompilation may be required, but often isn't necessary with default settings.
NEW QUESTION # 30
A systems administrator needs to provide an AI workload environment for a developer. Which profile type should the Administrator choose for vGPU?
Answer: A
Explanation:
C-series vGPU profiles are intended for compute workloads such as AI, deep learning, data science, and high-performance computing. They provide a vGPU profile type optimized for GPU- accelerated workload environments rather than graphics-focused use cases.
NEW QUESTION # 31
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