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NVIDIA NCP-AII Exam Overview:

Certification Vendor:NVIDIA
Exam Name:NVIDIA AI Infrastructure (NCP-AII) Certification Exam
Exam Number:NCP-AII
Certificate Validity Period:2 years
Exam Price:$400
Exam Format:Scenario-based questions, Multiple-choice
Real Exam Qty:70-75
Available Languages:English
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)
Exam Duration:120 minutes
Recommended Training:AI Infrastructure Professional Workshop
AI Infrastructure & Operations Fundamentals (NVIDIA Training)
Exam Registration:Official NVIDIA Certification Portal
NVIDIA AI Infrastructure Certification Page
Sample Questions:NVIDIA NCP-AII Sample Questions
Exam Way:Online proctored exam (remote) or authorized test center depending on region
Pre Condition:Recommended 2–3 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/

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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
  • 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 3
  • 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 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 (Q167-Q172):

NEW QUESTION # 167
A system engineer needs to set the vGPU scheduling behavior for all GPUs to share the scheduling equally with the default time slice length. What command should be used?

Answer: B

Explanation:
When deploying NVIDIA vGPU on VMware ESXi, the NVIDIA driver provides several scheduling policies to determine how GPU physical resources are shared among multiple virtual machines. The default behavior is often the "Best Effort" scheduler, but for environments requiring predictable performance across all users, the "Equal Share" scheduler is preferred. This scheduler gives each vGPU an equal "time slice" of the physical GPU's engines. The configuration is managed via module parameters passed to the nvidia kernel driver during host boot. The specific registry key for this behavior is RmPVMRL. Setting RmPVMRL=0x01 enables the Equal Share scheduler (Option A). Conversely, 0x00 would revert to the default time-sliced behavior. It is critical to use system module parameters set to ensure the setting persists across reboots and is applied globally to the NVIDIA driver stack. This ensures that no single "noisy neighbor" VM can monopolize the GPU cycles, which is a common requirement in shared AI research labs or virtual desktop infrastructures where consistency is more important than raw peak throughput of a single task.


NEW QUESTION # 168
Which of the following are key considerations when choosing between CPU pinning and NUMA (Non-Uniform Memory Access) awareness for a distributed training job on a multi-socket AMD EPYC server with multiple GPUs?

Answer: A,B

Explanation:
CPU pinning and NUMA awareness are both important for optimizing performance on multi-socket systems. CPU pinning reduces context switching overhead, while NIJMA awareness reduces memory access latency. Using them together provides the best performance. They ensure the CPU and memory being used are on the same node, which reduces latency. While GPUs handle intense computation, CPUs prepare and feed data to the GPUs, and are critical for performance.


NEW QUESTION # 169
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?

Answer: C

Explanation:
A QSA adapter is used to connect an SFP/SFP28 transceiver or cable to a QSFP/QSFP28 port when the QSFP port supports the lower-speed mode. This fits the requirement of connecting a 25 GbE SFP-based host adapter to a QSFP port capable of operating at 25 GbE.


NEW QUESTION # 170
After deploying BlueField OS, you notice that the network interfaces are not automatically configured with IP addresses. Which of the following actions would be the MOST appropriate first step to troubleshoot this issue?

Answer: D

Explanation:
In most modern systems, network interfaces are automatically configured using DHCP. Therefore, the first step is to check if the DHCP client is enabled and configured correctly. If DHCP fails, then other troubleshooting steps, such as static IP assignment or driver reinstallation, can be considered.


NEW QUESTION # 171
An engineer needs to verify the current firmware versions of all components (ATF, BSP, NIC, UEFI) on a BlueField-3 DPU's BMC. Which Redfish API command provides this information?

Answer: C

Explanation:
Modern NVIDIA BlueField DPUs include an integrated Baseboard Management Controller (BMC) that supports the industry-standardRedfish APIfor out-of-band management. While CLI tools like mlxconfig (Option A) or mstflint (Option C) can be used from the host OS to check the NIC firmware, they cannot easily query the BMC-specific components like the ARM Trusted Firmware (ATF), the Board Support Package (BSP), or the UEFI bootloader of the DPU. The Redfish standard specifies a common URI for hardware inventory. The FirmwareInventory endpoint (Option D) is the correct RESTful path to retrieve a comprehensive JSON object containing the versioning details for all firmware-controllable components on the DPU. This is the preferred method for automated data center management systems (like NVIDIA Base Command Manager) to verify that DPUs are at the correct "Golden Image" version during the staging phase.
Note that "FirmwareList" (Option B) is not a standard Redfish URI for this specific data.


NEW QUESTION # 172
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