Free NCA-AIIO: NVIDIA-Certified Associate AI Infrastructure and Operations Exam Questions and Answers
49 verified practice questions for NCA-AIIO.
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Last updated: September 19, 2026
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Question #1
Which of the following aspects have led to an increase in the adoption of AI? (Choose two.)
Select 2 answers.
Please select an optionIncorrectCorrect answer: C, D
The AI boom was driven by massively parallel GPUs providing the compute for deep learning and by the explosion of digital data to train on. Rule-based systems are the older approach AI moved away from, and Moore's Law alone did not deliver this speedup.
Was this answer correct?Question #2
Which type of GPU core was specifically designed to realistically simulate the lighting of a scene?
Please select an optionIncorrectCorrect answer: C
RT Cores are dedicated hardware for ray-triangle intersection and BVH traversal, accelerating real-time ray tracing for physically accurate lighting, shadows, and reflections. Tensor Cores accelerate matrix math and CUDA Cores handle general parallel compute.
Was this answer correct?Question #3
In training and inference architecture requirements, what is the main difference between training and inference?
Please select an optionIncorrectCorrect answer: B
Training iterates over huge datasets and is throughput-bound, while inference serves individual requests where low latency and real-time response matter most.
Was this answer correct?Question #4
Which of the following NVIDIA tools is primarily used for monitoring and managing AI infrastructure in the enterprise?
Please select an optionIncorrectCorrect answer: D
NVIDIA Base Command Manager provisions, monitors, and manages entire AI clusters, including nodes, networking, and workloads. DCGM monitors GPUs only, and the other two products do not exist.
Was this answer correct?Question #5
An IT professional is considering whether to implement an on-prem or cloud infrastructure. Which of the following is a key advantage of on-prem infrastructure?
Please select an optionIncorrectCorrect answer: C
On-premises infrastructure keeps data within the organization's own facilities, giving full control over security, compliance, and data sovereignty. Low upfront cost, elastic scalability, and easy remote management are advantages of the cloud.
Was this answer correct?Question #6
What NVIDIA tool should a data center administrator use to monitor NVIDIA GPUs?
Please select an optionIncorrectCorrect answer: C
The Data Center GPU Manager (DCGM) provides health monitoring, diagnostics, and telemetry for NVIDIA data center GPUs. NetQ monitors network fabrics, and NVIDIA System Monitor is not a data center tool.
Was this answer correct?Question #7
Which solution should be recommended to support real-time collaboration and rendering among a team?
Please select an optionIncorrectCorrect answer: C
Real-time collaborative rendering and visualization (for example with Omniverse) requires RTX GPUs with RT Cores and graphics capabilities on NVIDIA-Certified Servers. T4 clusters and DGX SuperPODs are compute-oriented rather than graphics platforms.
Was this answer correct?Question #8
Which NVIDIA software provides the capability to virtualize a GPU?
Please select an optionIncorrectCorrect answer: B
NVIDIA vGPU software lets a single physical GPU be shared among multiple virtual machines. Horizon is VMware's VDI product, and virtGPU is not an NVIDIA product.
Was this answer correct?Question #9
Which phase of deep learning benefits the greatest from a multi-node architecture?
Please select an optionIncorrectCorrect answer: B
Training large models is the most compute-intensive phase and scales across many GPUs and nodes with data or model parallelism, so it gains the most from a multi-node architecture. Inference typically runs on a single GPU or node.
Was this answer correct?Question #10
When deploying high-density workloads in a data center, what are the three main resource constraints that need to be considered?
Please select an optionIncorrectCorrect answer: B
High-density GPU systems draw many kilowatts per rack, so available power, cooling capacity to remove that heat, and rack space are the physical constraints that limit deployment in a data center.
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