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[General] Free PDF 2026 NVIDIA Reliable Interactive NCP-AII EBook

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【General】 Free PDF 2026 NVIDIA Reliable Interactive NCP-AII EBook

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NVIDIA AI Infrastructure Sample Questions (Q275-Q280):NEW QUESTION # 275
A server with four installed NVIDIA GPUs is experiencing intermittent crashes during heavy AI training workloads. You suspect a power issue. You have monitored the power consumption and found that the GPUs are briefly exceeding the rated power capacity of the PSU during peak loads. What are TWO effective mitigation strategies you can implement? (Select TWO)
  • A. Replace the PSU with a higher wattage PSU.
  • B. Increase the server room temperature.
  • C. Re-seat the GPUs in their respective slots.
  • D. Disable one of the GPUs to reduce the total power draw.
  • E. Underclock the GPIJs to reduce their power consumption.
Answer: A,E
Explanation:
Underclocking the GPUs reduces their power consumption directly. Replacing the PSU provides more headroom to handle the peak loads. Disabling a GPU reduces performance. Increasing server room temperature exacerbates the problem. Reseating GPUs addresses connection issues, not power limitations.

NEW QUESTION # 276
You are troubleshooting a performance issue on an Intel Xeon server with NVIDIAAI 00 GPUs. Your application involves frequent data transfers between CPU memory and GPU memory. You suspect that the PCle bus is a bottleneck. How can you verify and mitigate this bottleneck?
  • A. Monitor the GPU temperature. If it's high, the PCle bus is likely overheating. Mitigate by improving the server's cooling.
  • B. Check the CPU utilization. If it's low, the PCle bus is likely the bottleneck. Mitigate by increasing the number of CPU cores assigned to the data transfer tasks.
  • C. Use 'nvprof to profile the application and identify the exact lines of code that are causing the high PCle traffic. Optimize those sections of code to reduce data transfers.
  • D. Examine the system logs for PCle errors. If there are many errors, the PCle bus is likely unstable. Mitigate by reseating the GPUs and checking the power supply.
  • E. Use 'nvidia-smi' to monitor the PCle bandwidth utilization of the GPUs. If it's consistently high (near the theoretical limit), the PCle bus is likely a bottleneck. Mitigate by reducing the frequency of CPU-GPU data transfers, using pinned (page-locked) memory, and ensuring that the GPUs are connected to PCle slots with sufficient bandwidth.
Answer: C,E
Explanation:
'nvidia-smi' allows monitoring PCle bandwidth utilization, directly indicating a bottleneck. Pinned memory helps with efficient DMA transfers. Reducing transfer frequency and code optimization using 'nvprof are valid mitigation strategies. Low CPU utilization doesn't necessarily indicate PCle bottleneck. PCle errors indicate instability, not necessarily high utilization. GPU temperature is related to cooling, not directly the PCle bus being a bottleneck.

NEW QUESTION # 277
You are designing a storage solution for a new AI inference cluster that requires extremely low latency for model serving. Which storage technology and configuration would be MOST suitable to meet this stringent latency requirement?
  • A. A traditional Fibre Channel SAN with a dedicated storage array.
  • B. NVMe-oF (NVMe over Fabrics) using RDMA over Converged Ethernet (RoCE) connected to a cluster of NVMe drives.
  • C. Amazon S3 object storage accessed over a high-bandwidth internet connection.
  • D. A distributed file system deployed on spinning HDDs with a large read-ahead cache.
  • E. A software-defined storage (SDS) solution running on commodity hardware with SATA SSDs.
Answer: B
Explanation:
NVMe-oF with RoCE (option B) provides the lowest latency due to the combination of NVMe's low-latency access to flash storage and RDMA's ability to bypass the CPU for data transfer. HDDs (A) are too slow. SATA SSDs (C) are slower than NVMe. Object storage (D) introduces network latency. Fibre Channel (E) is a viable option, but NVMe-oF typically offers lower latency and greater flexibility.

NEW QUESTION # 278
You are tasked with installing the NGC CLI on a host that does not have direct internet access. You have downloaded the NGC CLI package to a local repository. Which of the following steps are required to successfully install and configure the NGC CLI in this offline environment?
  • A. Transfer the NGC CLI package to the host and install it using 'pip install .whl'.
  • B. Only copying the whl file is sufficient, NGC CLI dependencies are always local
  • C. Manually download and install all dependencies of the NGC CLI package using 'pip install --no-index --find-links=/path/to/dependencies .whl'.
  • D. Configure the NGC CLI to point to your local package repository by setting the environment variable.
  • E. Run 'ngc config set' to configure the API key, pointing to a local configuration file.
Answer: A,C,D,E
Explanation:
In an offline environment, you need to install the package locally (A), configure the CLI to know where to find the package (B), manually install dependencies (C), and configure the API key (D). Option E is wrong because dependencies must be handled manually in the offline environment.

NEW QUESTION # 279
You are installing four NVIDIAAIOO GPUs into a server designed for AI training. The server motherboard has multiple PCIe Gen4 x16 slots. However, the server's power supply unit (PSU) only has three 8-pin PCIe power connectors available. What is the BEST course of action to ensure all GPUs receive adequate power?
  • A. Use a PCIe power splitter cable on one of the 8-pin connectors to power two GPUs.
  • B. Connect the GPUs using the motherboard's internal SATA power connectors.
  • C. Install only three GPUs and leave the fourth unpowered.
  • D. Replace the existing PSU with a higher wattage PSU that has at least four 8-pin PCIe power connectors.
  • E. Underclock the GPUs significantly to reduce their power consumption below the available PSU capacity.
Answer: D
Explanation:
Using a splitter can overload the original connector and cause instability or damage. Leaving a GPU unpowered defeats the purpose. SATA connectors are not designed for the high power requirements of GPUs. Underclocking might work, but is not a reliable long-term solution. Replacing the PSU is the safest and most reliable solution.

NEW QUESTION # 280
......
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