NVIDIA NCA-AIIO Online Practice Questions and Exam Preparation

NVIDIA NCA-AIIO Online Questions & Answers

• Question 61:

  What NVIDIA tool should a data center administrator use to monitor NVIDIA GPUs?

  A. NVIDIA System Monitor
  B. NetQ
  C. DCGM
  C. DCGM

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  Explanation

  The NVIDIA Data Center GPU Manager (DCGM) is the recommended tool for data center administrators to monitor NVIDIA GPUs. It provides real-time health monitoring, telemetry (e.g., utilization, temperature), and diagnostics, tailored for large-scale deployments. NetQ focuses on network monitoring, and there’s no “NVIDIA System Monitor” in this context, making DCGM the correct choice.(Note: The document incorrectly lists D; C is intended.) (

  NVIDIA DCGM Documentation, Overview Section)

• Question 62:

  Which NVIDIA software provides the capability to virtualize a GPU?

  A. Horizon
  B. vGPU
  C. virtGPU
  B. vGPU

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  Explanation

  NVIDIA vGPU (Virtual GPU) software enables GPU virtualization by partitioning a physical GPU into multiple virtual instances, assignable to virtual machines or containers for accelerated workloads. Horizon is a VMware product, and

  “virtGPU” isn’t an NVIDIA offering, confirming vGPU as the correct solution.

  (

  NVIDIA vGPU Documentation, Overview Section)

• Question 63:

  What is an advantage of InfiniBand over Ethernet?

  A. InfiniBand always provides higher bandwidth than Ethernet.
  B. InfiniBand supports RDMA while Ethernet does not.
  C. InfiniBand offers lower latency than Ethernet.
  C. InfiniBand offers lower latency than Ethernet.

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  Explanation

  InfiniBand’s advantage over Ethernet lies in its lower latency, achieved through a streamlined protocol and hardware offloads, delivering microsecond-scale communication critical for AI clusters. While InfiniBand often offers high bandwidth,

  Ethernet can match or exceed it (e.g., 400 GbE), and Ethernet supports RDMA via RoCE, making latency the standout differentiator.

  (

  NVIDIA Networking Documentation, Section on InfiniBand vs. Ethernet)

• Question 64:

  What enables moving data between GPU memory and local or remote storage without using the CPU?

  A. NVLink
  B. GPUDirect P2P
  C. InfiniBand
  D. GPUDirect Storage
  D. GPUDirect Storage

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  Explanation

  NVIDIA GPUDirect Storage enables direct data paths between GPU memory and local or remote storage (e. g., NVMe over fabrics), bypassing the CPU and host memory. This maximizes throughput and minimizes latency in AI data

  pipelines. NVLink connects GPUs, GPUDirect P2P facilitates GPU-to-GPU transfers, and InfiniBand is a network fabric, but only GPUDirect Storage targets storage access.

  (

  NVIDIA GPUDirect Storage Documentation, Overview Section)

• Question 65:

  How many distinct network fabrics are in an AI cluster?

  A. 3
  B. 2
  C. 4
  D. 5
  A. 3

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  Explanation

  An AI cluster typically employs three distinct network fabrics: one for management and client traffic (e.g., Ethernet), one for storage I/O (e.g., accessing datasets), and one for low-latency RDMA interconnects (e.g., InfiniBand or RoCE)

  between compute nodes for tasks like gradient synchronization. This separation optimizes performance, scalability, and reliability, distinguishing AI clusters from simpler setups.

  (

  NVIDIA AI Infrastructure and Operations Study Guide, Section on Network Fabrics in AI Clusters)