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NVIDIA NCP-AII Exam Questions

Exam Name: NVIDIA AI Infrastructure Exam
Exam Code: NCP-AII
Related Certification(s): NVIDIA-Certified Professional Certification
Certification Provider: NVIDIA
Actual Exam Duration: 120 Minutes
Number of NCP-AII practice questions in our database: 71 (updated: Jun. 18, 2026)
Expected NCP-AII Exam Topics, as suggested by NVIDIA :
  • 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: Physical Layer Management: Covers configuring BlueField network platform devices and setting up Multi-Instance GPU (MIG) partitioning for AI and HPC workloads.
  • Topic 3: 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.
  • Topic 4: 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 5: 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.
Disscuss NVIDIA NCP-AII Topics, Questions or Ask Anything Related
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Angela Cooper

17 days ago
A teammate who passed told me the physical layer section leaned heavily on diagnosing link training failures using QSFP diagnostics and lane status counters. Expect questions that present transceiver mismatch or degraded lanes and practice optics vs passive cable behavior, pinouts, and how to read SERDES and link negotiation logs.
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Matthew Flores

22 days ago
I passed the NVIDIA NCP AII exam by spending most of my time on hands on system and server bring up, especially BIOS settings, firmware alignment, and driver versions, since the questions assume you can spot bad defaults quickly. Building a small checklist for GPU visibility, PCIe lane health, and power limits saved me on test day.
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Joshua Wright

1 month ago
I passed the NVIDIA AI Infrastructure exam after wrestling with system and server bring-up questions that focused on firmware order and interpreting POST and BMC logs. The test often gives a failed GPU initialization scenario and asks which firmware, BIOS setting, or power sequencing step to verify, so study firmware versions, BMC/IPMI output, physical seating, and power sequencing procedures.
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Jeffrey Wright

2 months ago
The BIOS and firmware version mismatches during system bring-up were the trickiest part for me on the exam. Keeping a simple matrix of firmware combos and exact BIOS settings saved a lot of time.
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Jason Flores

2 months ago
Honestly, I found certificate renewal questions in control plane configuration much more time consuming than firmware checks.
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Sandra Rodriguez

1 month ago
When I hit hardware bring-up issues the exam expected specific BIOS toggles for SR-IOV that weren't obvious from the prompt.
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Rebecca Evans

1 month ago
Also pay attention to cluster test patterns where they ask you to interpret subtle log snippets during verification.
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Sharon Perez

1 month ago
Curiously, a few troubleshooting items pushed me to verify driver and CUDA compatibility matrices rather than just restarting services.
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Elza

3 months ago
Network topology and interconnect technologies like NVLink and InfiniBand are essential. You'll need to know bandwidth specifications, latency characteristics, and when to use each technology for multi-GPU systems.
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Mariann

3 months ago
Just crushed the NVIDIA AI Infrastructure exam! Pass4Success practice exams were game-changers for me—they helped me identify weak spots early. Pro tip: start your prep by taking a full practice test untimed to see where you actually stand, then focus your study sessions on those problem areas.
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Harrison

3 months ago
Container orchestration with Kubernetes for AI workloads came up multiple times. Understand how to deploy GPU-accelerated containers, resource requests/limits, and scheduling policies. Pass4Success materials really helped me master this topic quickly!
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Murray

3 months ago
The exam heavily tested CUDA architecture knowledge. You'll encounter questions about warp scheduling, thread blocks, and memory hierarchy. Study the differences between global, shared, and local memory thoroughly - it's crucial for the certification.
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Cordelia

3 months ago
Just passed the NVIDIA Certified: AI Infrastructure exam! The GPU memory management questions were tricky - make sure you understand VRAM allocation, memory pooling, and how to optimize memory usage across multiple GPUs. Thanks Pass4Success for the comprehensive practice materials!
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Michael

4 months ago
I just cleared the exam with a solid score, and Pass4Success practice questions were a helpful nudge through tricky items, especially when I was unsure about a particular control plane installation nuance; that confidence boost carried me through. For example, one question asked about sequencing of high-availability control plane components during cluster bring-up, emphasizing etcd, kube-apiserver, and controller-manager startup order, and I remember wrestling with whether etcd must be fully initialized before the API server starts. I ultimately passed, but the hesitation was real.
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Free NVIDIA NCP-AII Exam Actual Questions

Note: Premium Questions for NCP-AII were last updated On Jun. 18, 2026 (see below)

Question #1

After configuring HA, the administrator runs cmsh status and notices the secondary head node reports mysql [FAIL]. What is the most likely cause?

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Correct Answer: B

In a Bright Cluster Manager HA setup, the database (MySQL/MariaDB) must remain perfectly synchronized between the active and standby head nodes to allow for a seamless transition. This synchronization typically occurs over a dedicated management or heartbeat network. If cmsh status shows the database service as [FAIL] on the secondary node, it almost always points to a communication breakdown. Without a stable network path, the secondary node cannot receive the binary logs from the primary node to keep its local copy up to date. While licensing (Option A) is important, a license failure usually disables management capabilities entirely rather than just the MySQL sync. Furthermore, head nodes are management servers and do not require GPU drivers (Option C) for their primary function. Ensuring low-latency, reliable connectivity between the two head nodes is the primary troubleshooting step for resolving 'MySQL FAIL' states in BCM.


Question #2

A company has a registered NGC account and their server has NGC CLI installed. What step should be taken first to gain access to NGC?

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Correct Answer: C

The NVIDIA GPU Cloud (NGC) is the central repository for AI-optimized containers, pre-trained models, and specialized SDKs. To interact with the NGC registry via the command line, the ngc CLI must be authenticated to the user's account. The command ngc config set is the verified first step to configure these credentials. When this command is executed, the user is prompted to provide their API Key, which is generated from the NGC web portal. This configuration process creates a local config file (typically in ~/.ngc/config) that stores the authentication token, the preferred organization, and the team settings. Without running ngc config set, the CLI cannot authenticate requests to pull private containers or upload models. ngc init (Option B) is not a standard configuration command for the current NGC CLI architecture, and ngc config get (Option A) is only useful for viewing an existing configuration that has already been established.


Question #3

A cluster administrator needs to validate transceiver firmware versions across 200 ports using UFM. Which GUI-based method provides a consolidated view?

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Correct Answer: A

Managing a large-scale AI fabric requires centralized visibility into the physical layer. The NVIDIA Unified Fabric Manager (UFM) provides a comprehensive Dashboard for InfiniBand networks. To check transceiver firmware---which is critical for ensuring feature parity and stability across the fabric---the administrator can use the UFM Enterprise GUI. By navigating to the 'Devices' section and selecting a specific switch, the 'Cables' tab will aggregate telemetry for every occupied port. This view displays the manufacturer, part number, and the specific firmware version of the transceivers (LinkX) or Active Optical Cables (AOC). This consolidated view is far more efficient than manual CLI queries (Option C) for 200+ ports. Maintaining uniform firmware across transceivers ensures that optimizations like Adaptive Routing and Congestion Control perform consistently across the entire 400G or 200G fabric.


Question #4

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?

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Correct Answer: C

The QSA (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.


Question #5

A team is validating a DGX BasePOD deployment. Using cmsh, they run a command to check GPU health across all nodes. What indicates that the system is ready for AI workloads?

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Correct Answer: C

In an NVIDIA DGX BasePOD or SuperPOD environment, 'Cluster Health' is a binary state: either the entire fabric and all compute resources are ready, or the cluster is considered degraded. Using the Bright Cluster Manager (BCM) shell (cmsh), administrators can aggregate telemetry from every node in the cluster. For a system to be considered 'Production Ready,' every single GPU across the multi-node deployment must report a status of Health = OK. This verification ensures that the hardware is communicating correctly over the PCIe bus, the NVLink fabric is initialized, and no ECC (Error Correction Code) memory errors are present. If even a single GPU in a 32-node cluster is unhealthy, collective communication libraries like NCCL may hang or experience significant performance penalties during 'All-Reduce' operations, as the entire job typically scales to the speed of the slowest/unhealthiest component. Therefore, seeing Status_Health = OK for every device is the mandatory exit criterion for the bring-up phase.



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