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First-grade Latest NCP-AIO Test Questions–Find Shortcut to Pass NCP-AIO Exam
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Free PDF 2025 Perfect NVIDIA NCP-AIO: Latest NVIDIA AI Operations Test Questions
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NVIDIA AI Operations Sample Questions (Q53-Q58):
NEW QUESTION # 53
Given an NVIDIAAIOO GPU with MIG enabled, you want to create a monitoring dashboard that displays the GPU utilization (GPU core %, memory utilization) for each MIG instance in real-time. Which tools and metrics should you prioritize to effectively build this dashboard?
- A. Use standard system monitoring tools like 'top' and 'vmstat' and display their combined output.
- B. Use NVIDIA Nsight Systems to profile application performance and extract GPU metrics. Use Prometheus as visualization tool.
- C. Parse the output of '/proc/meminfo' for GPU memory utilization data.
- D. Use DCGM (Data Center GPU Manager) to collect metrics like 'gpu_utilization' and 'memory_utilization' , and then use a visualization tool like Grafana to display the data.
- E. Utilize 'nvidia-smi' and parse its output to extract metrics. Then use 'PS to collect CPU utilization metrics and display them in a table.
Answer: D
Explanation:
DCGM is the most appropriate tool because it's designed for monitoring NVIDIA GPUs in data centers and provides the necessary granular metrics (GPU utilization, memory utilization) for individual MIG instances. Grafana is a popular visualization tool that can integrate with DCGM. Nsight Systems focuses on profiling application performance rather than real-time monitoring. Other options are either too limited or not specifically designed for GPU monitoring.
NEW QUESTION # 54
You've deployed a container from NGC containing a computationally intensive AI model training script. You notice that the container is consistently being killed by the Kubernetes OOMKiller, even though the node has sufficient memory available. What are the possible causes and solutions?
- A. The node is running out of swap space, causing the OOMKiller to terminate processes aggressively.
- B. Profile the application's memory usage to identify and fix memory leaks.
- C. The container's memory limit is set too low, causing it to exceed its allocated memory.
- D. Increase the container's memory limit in the Kubernetes deployment manifest.
- E. The application within the container has a memory leak, leading to excessive memory consumption.
Answer: B,C,D,E
Explanation:
An insufficient memory limit triggers the OOMKiller. Memory leaks cause excessive consumption. Increasing the limit and fixing leaks are solutions. C, while a potential issue in some environments, is less likely than the container-specific reasons in a Kubernetes environment.
NEW QUESTION # 55
You've configured a complex NVLink topology with multiple NVSwitches. You need to simulate a link failure to test the resilience of your system and the failover capabilities of 'nvsm'. How could you MOST effectively simulate a link failure for testing purposes?
- A. Physically disconnect an NVLink cable.
- B. Use a network traffic shaping tool to severely limit bandwidth on a specific NVLink connection.
- C. Unload and reload the NVIDIA drivers.
- D. Use 'nvsm' commands (if available) to administratively disable a specific NVLink port or link.
- E. Power off an NVSwitch.
Answer: D
Explanation:
The ideal way to simulate a link failure is to use 'nvsm' commands (if they exist) to administratively disable a specific port or link. This is the least disruptive and most controlled method. Physically disconnecting cables or powering off switches is disruptive and can have unintended consequences. Bandwidth limiting is not the same as a link failure. Driver reloading can also have broader effects than intended.
NEW QUESTION # 56
Your cluster users are complaining about long wait times for interactive jobs. You suspect the default backfill scheduler is not effectively utilizing available resources for these smaller, shorter jobs. What can you do to improve the scheduling of interactive jobs, considering backfill limitations?
- A. Decrease the value of
- B. Set 'Scheduler Type=sched/priority' to prioritize based on job age instead of size.
- C. Disable the backfill scheduler entirely.
- D. Increase the 'bf_intervar parameter to check for backfill opportunities more frequently.
- E. Implement a separate partition specifically for interactive jobs with a higher priority and shorter time limit.
Answer: E
Explanation:
Creating a separate partition with a higher priority and shorter time limit for interactive jobs is the most effective solution. This allows the scheduler to quickly allocate resources to these jobs without significantly impacting larger, longer-running batch jobs.
NEW QUESTION # 57
Your BCM pipeline includes a stage that performs data augmentation. You suspect this stage is a bottleneck. How can you profile and optimize this stage?
- A. Use NVIDIA Nsight Systems to profile the execution of the data augmentation stage.
- B. Implement data augmentation on the GPU using libraries like DALI or cuClM.
- C. Adjust the data augmentation parameters (e.g., number of augmentations) to reduce the computational load.
- D. All of the above.
- E. Cache the augmented data to avoid redundant computations.
Answer: D
Explanation:
Nsight Systems helps identify performance bottlenecks. GPU acceleration speeds up computations. Adjusting parameters reduces load. Caching avoids redundant work. All are valid optimization strategies.
NEW QUESTION # 58
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