NCP-AII Practice Questions: Systems and Networks Domain
Test your NCP-AII knowledge with 10 practice questions from the Systems and Networks domain. Includes detailed explanations and answers.
NCP-AII Practice Questions
Master the Systems and Networks Domain
Test your knowledge in the Systems and Networks domain with these 10 practice questions. Each question is designed to help you prepare for the NCP-AII certification exam with detailed explanations to reinforce your learning.
Question 1
During a network performance audit, you notice intermittent high latency in an InfiniBand network. What is the most effective troubleshooting step?
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Correct Answer: undefined
Explanation: Verifying the configuration of the InfiniBand switch's routing tables is effective as misconfigurations can lead to suboptimal routing and latency. Replacing cables or upgrading hardware should be considered after confirming configuration issues.
Question 2
During a routine check using nvidia-smi, you observe that one of the GPUs in your server is consistently underutilized. What is the most likely cause?
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Correct Answer: undefined
Explanation: A CPU-bound application will not fully utilize the GPU, as the CPU becomes the bottleneck. Persistence mode and exclusive process mode do not inherently cause underutilization, and while an outdated driver might cause issues, it would typically affect functionality rather than utilization.
Question 3
When configuring the CUDA compiler for an NVIDIA AI application, which optimization flag is most critical for maximizing performance on the target GPU architecture?
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Correct Answer: undefined
Explanation: The -gencode flag allows you to specify the target GPU architecture, ensuring the compiled code is optimized for the specific hardware. -O0 disables optimizations, -G is for debugging, and -Xptxas is used for PTX assembler options.
Question 4
When optimizing a CUDA application for an NVIDIA GPU, which of the following is the most effective strategy for improving execution efficiency?
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Correct Answer: undefined
Explanation: Utilizing memory coalescing is effective for improving execution efficiency as it optimizes memory access patterns, reducing latency and increasing throughput. Increasing threads beyond limits, minimizing shared memory, or reducing kernel launches without strategy can degrade performance.
Question 5
What is the primary reason for implementing cabling standards in an NVIDIA AI infrastructure?
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Correct Answer: undefined
Explanation: Implementing cabling standards ensures consistent performance and reliability by providing structured guidelines for cable management and network setup. While reducing interference, simplifying configuration, and minimizing costs are benefits, they are not the primary reason.
Question 6
In setting up a vGPU environment on NVIDIA hardware, what is a key consideration to ensure optimal performance and resource allocation?
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Correct Answer: undefined
Explanation: Matching vGPU profiles to workload requirements ensures that each virtual GPU has the appropriate resources for its tasks. Option A can lead to resource contention, C is irrelevant to vGPU specifically, and D may degrade performance.
Question 7
A newly deployed NVIDIA vGPU environment is experiencing performance bottlenecks. Which tool or method should you use first to identify the cause?
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Correct Answer: undefined
Explanation: Using nvidia-smi with vGPU-specific queries allows you to gather detailed information about GPU utilization and potential bottlenecks. Reinstalling drivers (B), upgrading the hypervisor (C), and increasing vGPUs (D) should be considered after identifying the issue.
Question 8
In an NVIDIA GPU server, which component is most likely to become a bottleneck if not properly configured during high-intensity AI workloads?
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Correct Answer: undefined
Explanation: The network interface card is critical in high-intensity workloads, especially for data transfer between nodes. While the CPU (A), SSD (B), and RAM (D) are important, the network interface often limits data throughput.
Question 9
During a vGPU deployment, which action should be taken to ensure high availability of GPU resources?
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Correct Answer: undefined
Explanation: Implementing GPU resource pooling across multiple hosts allows for failover and load balancing, ensuring high availability of GPU resources. A single point of failure and assigning all VMs to a single GPU would reduce availability, and round-robin scheduling does not inherently provide high availability.
Question 10
You are tasked with optimizing the performance of an NVIDIA DGX A100 system in a data center. The system is connected to an InfiniBand network. Which of the following actions would most effectively reduce latency in data transfers between nodes?
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Correct Answer: undefined
Explanation: Enabling adaptive routing on the InfiniBand fabric allows the network to dynamically choose the best path for data packets, reducing congestion and latency. Increasing MTU size (A) can help with throughput but not necessarily latency. Reducing the number of subnets (C) does not directly affect latency. Switching to Ethernet (D) would likely increase latency compared to InfiniBand.
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About NCP-AII Certification
The NCP-AII certification validates your expertise in systems and networks and other critical domains. Our comprehensive practice questions are carefully crafted to mirror the actual exam experience and help you identify knowledge gaps before test day.