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[General] New NVIDIA NCP-AII Exam Fee - Pass4sure NCP-AII Pass Guide

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【General】 New NVIDIA NCP-AII Exam Fee - Pass4sure NCP-AII Pass Guide

Posted at yesterday 15:25      View：7 | Replies：1        Print      Only Author   [Copy Link] 1#
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NVIDIA AI Infrastructure Sample Questions (Q113-Q118):NEW QUESTION # 113
During the physical installation of an NVIDIA GPU, you accidentally touch the gold connector pins on the card. What is the recommended course of action BEFORE inserting the GPU into the PCle slot?
  • A. Blow on the pins to remove any dust or debris.
  • B. Use compressed air to clean the pins.
  • C. It is okay to insert it directly as is.
  • D. Wipe the pins with a dry cloth.
  • E. Clean the pins with isopropyl alcohol and a lint-free swab, ensuring they are completely dry before installation.
Answer: E
Explanation:
Touching the pins can transfer oils or static electricity that can interfere with the electrical connection. Cleaning with isopropyl alcohol and a lint-free swab removes these contaminants and ensures a proper connection. Blowing, wiping with a dry cloth, or using compressed air may not be sufficient and could even introduce more contaminants.

NEW QUESTION # 114
Which of the following commands or tools can be used to verify the NVIDIA driver version and the CUDA version installed on a Linux system?
  • A. 'cat /proc/driver/nvidia/version'
  • B. 'modinfo nvidia'
  • C. "Ispci I grep NVIDIA'
  • D. nvcc -version'
  • E. 'nvidia-smr
Answer: A,B,D,E
Explanation:
'nvidia-smi' provides detailed information about the NVIDIA driver version and GPU status. 'nvcc -version' shows the CUDA compiler version. 'cat Iproc/driver/nvidia/version' (if the file exists) displays the driver version. 'modinfo nvidia' will display the version of the loaded kernel module. only shows the presence of NVIDIA hardware, not the driver or CUDA version.

NEW QUESTION # 115
You are tasked with diagnosing performance issues on a GPU server running a large-scale HPC simulation. The simulation utilizes multiple GPUs and InfiniBand for inter-GPU communication. You suspect that RDMA (Remote Direct Memory Access) is not functioning correctly. How would you comprehensively test and verify the proper operation of RDMA between the GPUs?
  • A. Run 'nvidia-smi topo -m' to check the GPU interconnect topology and verify that NVLink or PCle is being used for communication.
  • B. Utilize NCCL's internal diagnostic tools to verify proper inter-GPU communication within the simulation.
  • C. Employ and from the 'perftest' suite to measure RDMA bandwidth and latency between GPUs.
  • D. Monitor CPU utilization during the simulation; high CPU usage suggests that RDMA is not offloading communication effectively.
  • E. Use 'ping' to verify basic network connectivity between the server's InfiniBand interfaces.
Answer: A,B,C
Explanation:
(A) and (B) directly measure RDMA performance. 'nvidia-smi topo -m' (C) verifies the physical interconnect. NCCL diagnostic tools (D) confirm application-level communication. 'ping' (A) only tests basic network connectivity, not RDMA functionality. While high CPU usage (E) can indicate RDMA issues, it's an indirect symptom, not a direct test.

NEW QUESTION # 116
An A1 server is exhibiting unusually high CPU utilization during a GPU-accelerated workload. How can you determine if the CPU is becoming a bottleneck, preventing the GPUs from achieving their full potential?
  • A. Run a CPU-intensive benchmark in parallel with the GPIJ workload to observe performance degradation.
  • B. Use 'nvidia-smi' to check the GPU utilization; low GPIJ utilization combined with high CPU utilization indicates a potential CPU bottleneck.
  • C. Monitor CPU utilization using 'top' or 'htop' while the workload is running; sustained high utilization suggests a bottleneck.
  • D. All of the above
  • E. Profile the application with a CPU profiler (e.g., 'perf) to identify CPU-bound functions.
Answer: D
Explanation:
All the options provide valid methods for identifying a CPU bottleneck. Monitoring CPU and GPU utilization, profiling the application, and running parallel benchmarks all help to determine if the CPU is limiting GPU performance.

NEW QUESTION # 117
You are experiencing link flapping (frequent up/down transitions) on several InfiniBand links in your AI infrastructure. This is causing intermittent connectivity issues and performance degradation. What are the MOST likely causes of this issue, and what steps should you take to troubleshoot and resolve it? (Select TWO)
  • A. Software bugs in the operating system or InfiniBand drivers.
  • B. Faulty or damaged cables, connectors, or transceivers.
  • C. Mismatched link speeds or duplex settings between connected devices.
  • D. Excessive broadcast traffic causing congestion.
  • E. Incorrect MTU (Maximum Transmission Unit) configuration on the affected interfaces.
Answer: B,C
Explanation:
Link flapping is most commonly caused by physical layer issues (faulty cables, connectors, or transceivers) or configuration mismatches (link speeds or duplex settings). Troubleshooting should focus on inspecting the physical connections and verifying that the link speed and duplex settings are correctly configured on both ends of the link. While MTIJ issues and software bugs can cause network problems, they are less likely to directly cause link flapping. Excessive broadcast traffic can cause performance issues but is less likely to result in frequent link up/down transitions.

NEW QUESTION # 118
......
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Posted at 8 min. before        Only Author  2#
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