NCP-AII Pruefungssimulationen, NCP-AII Zertifikatsdemo

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NVIDIA NCP-AII Prüfungsplan:

ThemaEinzelheiten
Thema 1
  • Physical Layer Management: Covers configuring BlueField network platform devices and setting up Multi-Instance GPU (MIG) partitioning for AI and HPC workloads.
Thema 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.
Thema 3
  • 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.
Thema 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.
Thema 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.

>> NCP-AII Pruefungssimulationen <<

NCP-AII Übungstest: NVIDIA AI Infrastructure & NCP-AII Braindumps Prüfung

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NVIDIA AI Infrastructure NCP-AII Prüfungsfragen mit Lösungen (Q190-Q195):

190. Frage
You are tasked with installing the latest NVIDIA driver on a server running Ubuntu 22.04 for A1 workloads. You have downloaded the driver package 'NVIDIA-Linux-x86 64-535.104.05.run'. Before installation, what is the most critical step to ensure a smooth process, assuming secure boot is enabled?

Antwort: C,E

Begründung:
Secure Boot requires kernel modules to be signed. Directly running the .run' file or disabling Secure Boot are generally not recommended. DKMS and MOK signing allows the driver to be validated by the system. Blacklisting nouveau ensures that it won't conflict with the NVIDIA driver. Installing via apt doesn't guarantee Secure Boot compatibility without further steps, so the best approach involves DKMS/MOK and blacklisting.


191. Frage
During the physical installation of an NVIDIA GPU, you accidentally touch the gold connector pins on the card. What is the recommended course of action BEFORE inserting the GPU into the PCle slot?

Antwort: B

Begründung:
Touching the pins can transfer oils or static electricity that can interfere with the electrical connection. Cleaning with isopropyl alcohol and a lint-free swab removes these contaminants and ensures a proper connection. Blowing, wiping with a dry cloth, or using compressed air may not be sufficient and could even introduce more contaminants.


192. Frage
During server maintenance, a system administrator wants to ensure that the NVIDIA DGX server has sufficient disk space for operational activities. The administrator is scripting an alert system that will notify the team if disk space falls below a threshold. Which command could be included in the maintenance script to check the available disk space on the server?

Antwort: B

Begründung:
The correct command is df -h | grep ' /var ' because df reports filesystem capacity, used space, available space, and mount utilization. In DGX systems, monitoring disk space is important because system logs, container runtime data, package caches, telemetry, temporary files, and service data can consume space under operational filesystems such as /var. If /var fills up, services such as Docker, containerd, logging, monitoring agents, NVIDIA management tools, or package management can fail or behave unpredictably. nvidia-smi -- query-disk-space is incorrect because nvidia-smi reports GPU telemetry, not filesystem capacity. du -sh /home
/* summarizes directory usage under /home, but it does not directly show remaining filesystem space or a threshold-ready view of the mounted filesystem. lsof +L1 is useful for finding deleted files still held open by processes, but it is not the primary command for checking available disk capacity. In NVIDIA AI infrastructure, routine OS-level checks like filesystem capacity are part of reliable server operations and help prevent avoidable workload failures.


193. Frage
A system administrator receives an alert about a potential hardware fault on an NVIDIA DGX A100. The GPU performance seems degraded, and the system fans are operating loudly. What step should be recommended to identify and troubleshoot the hardware fault?

Antwort: D

Begründung:
When a DGX system exhibits high fan speeds and performance degradation, it is typically engaging in Thermal Throttling. High-performance GPUs like the A100 or H100 will automatically reduce their clock speeds (and thus performance) if they exceed safe temperature thresholds. The first and most critical diagnostic step is to run nvidia-smi. This utility provides immediate, real-time telemetry on GPU temperatures, power draw, and "Clocks Throttle Reasons." By reviewing the output, an administrator can see if "Thermal" is listed as the reason for reduced clocks. This identifies whether the issue is environmental (blocked airflow/hot aisle temperature) or hardware-specific (a failed GPU thermal interface or a dead internal fan). Running more workloads (Option A) would exacerbate the heat, while a power drain (Option C) is a
"last resort" that doesn't provide diagnostic data. nvidia-smi provides the evidentiary data needed to determine if an RMA (Return Merchandise Authorization) is required for the GPU tray.


194. Frage
A system administrator wants to configure MIG for seven slices on an H100 GPU in an NVIDIA HGX system. Which command should be used?

Antwort: A

Begründung:
The correct answer is mig-parted. NVIDIA MIG Partition Editor, commonly called mig-parted, is designed to automate and manage Multi-Instance GPU partitioning profiles, especially in environments where repeatable MIG layouts are required. An H100 GPU can be divided into multiple isolated GPU instances, and a seven- slice configuration is a common profile pattern for maximizing the number of smaller MIG instances on a single GPU. While nvidia-smi can enable MIG mode and manually create or destroy GPU instances, mig- parted is better suited when an administrator needs to apply defined MIG profiles consistently across HGX systems or multiple nodes. nvcc is the CUDA compiler and has no role in configuring MIG partitions. nvlink- config is not the correct utility for MIG profile configuration. In NVIDIA AI infrastructure, MIG configuration must be controlled carefully because Kubernetes device plugins, GPU Operator, Slurm GRES configuration, and tenant scheduling depend on consistent GPU instance layouts. Using mig-parted helps reduce manual errors and supports repeatable server bring-up for shared inference or multi-tenant AI environments.


195. Frage
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