Sample NCP-AII Questions, NCP-AII Real Exam Answers

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NVIDIA NCP-AII Exam Syllabus Topics:

Topic	Details
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	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 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	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 5	Physical Layer Management: Covers configuring BlueField network platform devices and setting up Multi-Instance GPU (MIG) partitioning for AI and HPC workloads.

>> Sample NCP-AII Questions <<

NVIDIA NCP-AII Real Exam Answers & NCP-AII Practice Test Pdf

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NVIDIA AI Infrastructure Sample Questions (Q17-Q22):

NEW QUESTION # 17
The system administrator is tasked with updating GPU drivers and needs to check the driver version that is currently running. Which command should the system administrator use?

A. nvidia-smi get gpu driver version --format=csv
B. nvidia-smi --query gpu driver --format=csv
C. nvidia-smi gpu-driver-version --format=csv
D. nvidia-smi --query-gpu=driver_version --format=csv

Answer: D

Explanation:
nvidia-smi --query-gpu=driver_version --format=csv uses the correct NVIDIA SMI query syntax to report the currently running NVIDIA GPU driver version in CSV format, which is useful before performing a driver update.

NEW QUESTION # 18
An Ai infrastructure relies on a liquid cooling system to dissipate heat from multiple NVIDIA GPUs. After a recent software update, users report intermittent performance degradation and system crashes. You suspect a cooling issue. Which TWO of the following checks are the MOST critical in diagnosing the root cause?

A. Check the CPU temperature using 'sensors' command.
B. Examine the ambient temperature in the data center.
C. Run a memory test on the host system.
D. Analyze the system logs for GPU-related errors, specifically those indicating thermal throttling or power capping.
E. Verify the pump speed and coolant flow rate within the liquid cooling system.

Answer: D,E

Explanation:
Verifying pump speed and flow rate (A) is crucial for liquid cooling systems. Reduced flow can lead to inadequate cooling and thermal issues. Analyzing system logs for GPU-related errors (C) will directly indicate whether thermal throttling or power capping are occurring, which are common symptoms of cooling problems.

NEW QUESTION # 19
A System Administrator needs to change the scheduling behavior of a single GPU to use a fixed share scheduler. What command achieves this?

A. esxcli -i 0 -mig 18
B. mlxconfig -d /dev/mst/mt4123_pciconf0 set LINK_TYPE_P1 =2
C. esxcli system module parameters set -m nvidia -p
D. nvidia-smi -i 0 -mig 1

Answer: D

Explanation:
NVIDIA Multi-Instance GPU (MIG) technology, introduced with the Ampere architecture (A100) and enhanced in Hopper (H100), allows a single physical GPU to be partitioned into multiple isolated instances.
To manage these instances and their scheduling behavior (such as moving from a default time-sliced scheduler to a fixed-share or "MIG" partitioned mode), the nvidia-smi utility is used. The command nvidia- smi -i 0 -mig 1 enables MIG mode on the first GPU (index 0). Once MIG is enabled, the administrator can create specific GPU instances with dedicated compute and memory resources. This "Fixed Share" approach ensures that one tenant's workload does not impact the performance or latency of another, which is critical for deterministic AI inference and multi-tenant cloud environments. Option A and B refer to VMware ESXi specific commands which are not the primary method for raw hardware configuration in standard AI infrastructure, and Option D is for network adapter configuration.

NEW QUESTION # 20
During multi-node HPL burn-in, GPUs show uneven utilization. Which configuration ensures balanced workload distribution?

A. HPL_RUN_GEMM_TESTS to skip validation
B. Set --gpu-affinity and --cpu-affinity to align GPU and NUMA nodes
C. Enable HPL_USE_NVSHMEM=1 for shared memory acceleration
D. HPL_OOC_TILE_M to 8192 for larger blocks

Answer: B

Explanation:
Uneven GPU utilization in a multi-node cluster is a classic symptom ofPCIe/NUMA imbalance. In a DGX H100, each set of GPUs is physically closer to a specific CPU socket and a specific set of high-speed NICs. If the workload (HPL) is launched without strict affinity, an MPI rank running on a CPU core attached to Socket
0 might attempt to control a GPU attached to Socket 1. This forces data to cross the inter-processor links (UPI
/QPI), which have significantly higher latency and lower bandwidth than a direct PCIe path. This
"bottlenecking" causes some GPUs to wait for data longer than others, leading to the uneven utilization observed. The verified solution is to use an orchestration script or flags that enforceAffinity. By setting --gpu- affinity and --cpu-affinity, the administrator ensures that each GPU is managed by a CPU core on its local NUMA node. This alignment minimizes latency and ensures that every GPU in the cluster receives data at the same rate, resulting in the flat, high-utilization profile required for a successful HPL burn-in record.

NEW QUESTION # 21
A system administrator noticed a failure on a DGX H100 server. After a reboot, only the BMC is available. What could be the reason for this behavior?

A. The network card has no link / connection.
B. A boot disk has failed.
C. There are more than two failed power supplies.
D. Multiple GPUs have failed.

Answer: C

Explanation:
If more than two DGX H100 power supplies fail, the system may not have enough power capacity to bring up the host, while the BMC can still remain available on standby management power.
This results in a condition where remote management is reachable but the server itself cannot fully boot.

NEW QUESTION # 22
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