NCA-AIIO Practice Questions: Hardware and System Architecture Domain

Published: June 12, 2025 | 5 min read

Test your NCA-AIIO knowledge with 5 practice questions from the Hardware and System Architecture domain. Includes detailed explanations and answers.

NCA-AIIO Practice Questions

Master the Hardware and System Architecture Domain

Part of Complete NCA-AIIO Study Series: This practice set covers the Hardware and System Architecture domain (~40% of exam). For comprehensive preparation, review our Complete NCA-AIIO Study Guide first, then progress through all domains systematically.

Master the Hardware and System Architecture domain with these practice questions covering GPU architecture, data center operations, networking, and virtualization technologies essential for NCA-AIIO certification success.

Domain Prerequisites

Before diving into hardware architecture, ensure you understand the fundamentals covered in our AI Infrastructure Fundamentals practice questions. This foundation will help you better understand GPU architectures and system design concepts.

Question 1: GPU Architecture Fundamentals

Which NVIDIA GPU architecture feature allows for partitioning a single GPU into multiple smaller, isolated instances for improved resource utilization in multi-tenant environments?

A) CUDA Cores

B) Multi-Instance GPU (MIG)

C) Tensor Cores

D) NVLink

Show Answer & Explanation

Correct Answer: B

Explanation: Multi-Instance GPU (MIG) technology allows you to partition supported NVIDIA GPUs into multiple GPU instances, each with dedicated memory and compute resources. This is crucial for understanding resource allocation concepts that connect to performance optimization strategies.

Question 2: Data Center Infrastructure

In a high-performance AI data center, what is the primary advantage of using InfiniBand over traditional Ethernet for inter-node communication?

A) Lower cost per port

B) Higher bandwidth and lower latency

C) Better compatibility with existing networks

D) Easier configuration and management

Show Answer & Explanation

Correct Answer: B

Explanation: InfiniBand provides significantly higher bandwidth (up to 400 Gbps) and ultra-low latency compared to traditional Ethernet, making it ideal for AI workloads that require fast inter-node communication. This network performance directly impacts the deployment strategies covered in our Deployment and Operations practice questions.

Question 3: Storage Architecture

When designing storage architecture for AI training workloads, which storage configuration provides the best balance of performance and capacity for large datasets?

A) Single large SSD

B) RAID 0 array of NVMe SSDs

C) Network-attached storage (NAS)

D) Traditional hard disk drives

Show Answer & Explanation

Correct Answer: B

Explanation: RAID 0 arrays of NVMe SSDs provide the highest sequential read/write performance essential for AI training data loading, while offering scalable capacity. This storage design principle connects directly to the concepts covered in our Data Management and Storage practice questions.

Question 4: Power and Cooling

What is the recommended power delivery configuration for a high-density GPU server rack to ensure stable power supply and minimize voltage fluctuations?

A) Single 240V power supply

B) Redundant power supplies with different phases

C) Standard UPS backup only

D) Battery-powered systems

Show Answer & Explanation

Correct Answer: B

Explanation: Redundant power supplies connected to different electrical phases provide both failover protection and load balancing, crucial for maintaining system stability under high GPU workloads. Power management is essential for the troubleshooting scenarios covered in our Troubleshooting and Maintenance practice questions.

Question 5: Virtualization Technology

In a virtualized environment, which NVIDIA technology enables multiple virtual machines to share GPU resources while maintaining isolation and security?

A) CUDA Streams

B) vGPU (Virtual GPU)

C) GPU Direct

D) TensorRT

Show Answer & Explanation

Correct Answer: B

Explanation: NVIDIA vGPU technology allows multiple virtual machines to share GPU resources with hardware-level isolation and security. Understanding vGPU is fundamental for implementing the security practices detailed in our Security and Compliance practice questions.

Continue Your Hardware Architecture Mastery

Now that you understand hardware fundamentals, advance to related operational domains:

• Next: Performance Optimization and Monitoring Practice Questions (builds on GPU architecture knowledge)

• Related: Data Management and Storage Practice Questions (complements storage architecture)

• Foundation: AI Infrastructure Fundamentals Practice Questions (review if needed)

• Overview: Return to Complete Study Guide

Master All NCA-AIIO Domains with FlashGenius

Get unlimited access to practice questions across all exam domains with detailed explanations and performance tracking.