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| Certification Vendor: | NVIDIA |
|---|---|
| Exam Name: | NVIDIA-Certified Professional AI Infrastructure Exam |
| Exam Number: | NCP-AII |
| Real Exam Qty: | 60-70 |
| Passing Score: | Pass/Fail only, no numerical score |
| Exam Format: | Multiple-choice questions, Scenario-based items |
| 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) |
| Exam Duration: | 120 minutes |
| Available Languages: | English |
| 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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질문 # 187
You're optimizing an Intel Xeon server with 4 NVIDIAAIOO GPUs for a computer vision application that uses CODA. You notice that the GPU utilization is fluctuating significantly, and performance is inconsistent. Using 'nvprof, you identify that there are frequent stalls in the CUDA kernels due to thread divergence. What are possible causes and solutions?
정답：C,D
설명：
Thread divergence occurs when threads within the same warp take different execution paths due to conditional branches, leading to serialization. Re-writing code to minimize branching is critical. Memory alignment ensures that threads access memory efficiently and doesn't cause thread divergence stalls, which is often misaligned. Thermal throttling is a possible cause of fluctuating utilization but doesn't directly explain the stalls identified in the profiler. Compiler flags and driver version issues can cause performance problems but are less likely to cause frequent thread divergence stalls.
질문 # 188
You are deploying an NVIDIA-Certified A1 server. The documentation specifies a minimum airflow requirement for the GPUs. How would you BEST monitor the GPU temperatures and ensure the airflow is adequate during a stress test?
정답：A
설명：
IPMI provides remote monitoring of hardware sensors, including GPU temperature and fan speeds, allowing you to ensure the cooling system is working correctly during a stress test. 'nvidia-smi' gives the GPU temp but not the fan speed. Ambient temperature isn't an accurate reflection of the GPU's actual temperature.
질문 # 189
What is the purpose of using NCCL in verifying East-West fabric in an NVIDIA AI Factory?
Pick the 2 correct responses below.
정답：C,D
설명：
NCCL is used to validate GPU communication behavior across the East-West fabric, so the correct answers are measuring latency between GPUs and measuring bandwidth between GPUs. NVIDIA describes NCCL as a topology-aware library of multi-GPU collective communication primitives, and NVIDIA GPU debug guidance specifically identifies NCCL performance tests, such as all_reduce_perf, as useful for establishing network performance between groups of nodes. In an AI Factory, East-West traffic is the server-to-server traffic used during distributed training. When models scale across many GPUs and nodes, operations such as all-reduce, broadcast, all-gather, and reduce-scatter depend on low latency and high bandwidth. NCCL testing helps confirm that GPU-to-GPU paths, GPUDirect RDMA, InfiniBand or Spectrum-X fabric behavior, routing, and collective communication performance are healthy before production workloads start. NCCL is not intended to measure storage performance; that requires storage benchmarks or GPUDirect Storage validation. It also does not measure GPU power consumption; that is handled by tools such as nvidia-smi, DCGM, or platform telemetry.
질문 # 190
Which function is used to collect the cluster counters information?
정답：B
설명：
GM is the function used to collect cluster counters information, aggregating fabric-level counter data for cluster monitoring and analysis.
질문 # 191
If two ports must be connected, but one is SFP and one is QSFP, for example, to connect a 25 GbE HOST CHANNEL ADAPTER to a QSFP port capable of both 100 GbE and 25 GbE, which of the following solutions would best meet this requirement?
정답：A
설명：
TheQSA (QSFP to SFP Adapter)is a mechanical and electrical bridge that allows a single-lane SFP/SFP28 transceiver (typically 10G or 25G) to be plugged into a four-lane QSFP/QSFP28 switch port. In AI infrastructure, this is commonly used to connect low-speed management servers or legacy nodes to a high- speed backbone switch without wasting entire 100G/200G ports or requiring specialized breakout cables. The QSA adapter maps the single lane of the SFP module to the first lane of the QSFP port. This is a "pass- through" solution that maintains the signal integrity and latency characteristics of the link. It is the verified hardware solution for port-density mismatch in NVIDIA networking environments.
질문 # 192
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