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| Certification Vendor: | NVIDIA |
|---|---|
| Exam Name: | NVIDIA-Certified Professional AI Infrastructure Exam |
| Exam Number: | NCP-AII |
| 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) |
| Exam Format: | Scenario-based items, Multiple-choice questions |
| Exam Price: | $400 USD |
| Real Exam Qty: | 60-70 |
| Available Languages: | English |
| Exam Duration: | 120 minutes |
| Certificate Validity Period: | 2 years |
| Passing Score: | Pass/Fail only, no numerical score |
| 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 2โ3 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 # 133
You are deploying a BlueField-2 DPU-based server in a VMware vSphere environment. Which network virtualization technology is most commonly used in conjunction with the DPU to provide accelerated networking and security features within the virtualized environment?
Answer: B
Explanation:
VXLAN is a widely adopted network virtualization technology that is frequently used with BlueField DPUs in vSphere environments. DPUs can offload VXLAN encapsulation and decapsulation, improving performance and reducing the CPU load on the host. SR-IOV provides direct access to the NIC for VMs, but it's not a network virtualization technology in the same sense as VXLAN. GRE and IPsec are tunneling protocols but less common in vSphere for this specific use case. LACP is for link aggregation, not virtualization.
NEW QUESTION # 134
You have an Intel Xeon Gold server with 2 NVIDIA Tesla VI 00 GPUs. After deploying your A1 application, you observe that one GPU is consistently running at a significantly higher temperature than the other What could be a plausible reason for this behavior?
Answer: B,E
Explanation:
Uneven heat distribution often points to airflow problems or unbalanced workloads. Inadequate airflow can cause localized hotspots. Uneven workload distribution will naturally cause one GPU to work harder and generate more heat. While a defective GPU or driver issues are possibilities, they are less likely than airflow and workload imbalances in this scenario. High ambient temperature is also a contributing factor but less direct.
NEW QUESTION # 135
When configuring an out-of-core HPL burn-in for a 40B matrix on 8x H100 nodes, which environment variable prevents GPU out-of-memory errors while reserving space for drivers?
Answer: A
Explanation:
The correct option is export HPL_OOC_SAFE_SIZE=4.0. NVIDIA HPL out-of-core mode allows matrix data that exceeds GPU memory capacity to be placed in host memory, but the GPU still needs reserved memory for drivers and runtime overhead. NVIDIA documents HPL_OOC_SAFE_SIZE as the amount of GPU memory, in GiB, reserved for the driver and not used by HPL out-of-core mode; increasing it is recommended when GPU out-of-memory errors occur. HPL_OOC_MODE=0 disables out-of-core mode, which would not help run a larger 40B matrix. HPL_OOC_NUM_STREAMS=8 changes the number of CUDA streams used for out-of-core operations, but it does not reserve driver memory.
HPL_OOC_MAX_GPU_MEM=90 limits total GPU memory use, but the specific variable intended to leave safe driver space is HPL_OOC_SAFE_SIZE. During cluster burn-in, this setting helps preserve test validity while avoiding false failures caused by memory reservation issues rather than actual hardware instability.
NEW QUESTION # 136
You're setting up a BlueField-3 DPIJ to offload storage virtualization tasks. Specifically, you want to use SPDK (Storage Performance Development Kit) on the DPIJ. What are the MINIMUM required steps to enable SPDK on the BlueField-3 after the DPIJ has been flashed with the appropriate OS image? (Select TWO)
Answer: A,E
Explanation:
The minimum steps involve installing the SPDK packages using the DPU's package manager, assuming prebuilt packages are available, and configuring Huge Pages. SPDK relies heavily on Huge Pages for memory management. While configuring network interfaces and starting services are important, installing SPDK and configuring Huge Pages are required first steps. Downloading and compiling from source might be necessary in some cases but not minimally required if packages are available.
NEW QUESTION # 137
You're profiling the performance of a PyTorch model running on an AMD server with multiple NVIDIA GPUs. You notice significant overhead in the data loading pipeline. Which of the following strategies can help optimize data loading and improve GPU utilization?
Select all that apply.
Answer: A,D,E
Explanation:
Using multiple worker processes in 'DataLoader' enables parallel data loading. Asynchronous prefetching allows data to be loaded while the GPU is processing the current batch. A faster storage system reduces the 1/0 bottleneck. Loading the entire dataset into RAM might not be feasible for large datasets. Reducing batch size reduces the amount of data loaded but could decrease overall GPU utilizatiom
NEW QUESTION # 138
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