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NVIDIA NCP-AII PDF Format
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NVIDIA AI Infrastructure Sample Questions (Q284-Q289):
NEW QUESTION # 284
You have a large dataset stored on a BeeGFS file system. The training job is single node and uses data augmentation to generate more data on the fly. The data augmentation process is CPU-bound, but you notice that the GPU is underutilized due to the training data not being fed to the GPU fast enough. How can you reduce the load on the CPU and improve the overall training throughput?
- A. Enable data compression on the BeeGFS file system to reduce the amount of data being transferred over the network.
- B. Increase the number of BeeGFS metadata servers (MDSs) to improve metadata performance.
- C. Decrease the batch size of the training job to reduce the amount of data being processed at each iteration.
- D. Implement asynchronous 1/0 in the data loading pipeline using a library like NVIDIA DALI to offload data processing tasks from the CPU to the GPU.
- E. Move the training data to a local NVMe drive on the training node.
Answer: D
Explanation:
Using NVIDIA DALI (option C) allows you to offload data augmentation and preprocessing tasks from the CPU to the GPU, freeing up CPU resources for other tasks and enabling faster data loading. Moving to a local NVMe drive (A) bypasses BeeGFS but doesn't address the CPU bottleneck. Increasing MDSs (B) improves metadata performance but doesn't directly help with the CPU-bound data augmentation. Decreasing the batch size (D) reduces the workload but doesn't solve the underlying CPU bottleneck. Data compression (E) can increase CPU load due to the decompression process.
NEW QUESTION # 285
After upgrading the network card drivers on your A1 inference server, you experience intermittent network connectivity issues, including packet loss and high latency. You've verified that the physical connections are secure. Which of the following steps would be most effective in troubleshooting this issue?
- A. Check the system logs for error messages related to the network card or driver.
- B. Roll back the network card drivers to the previous version.
- C. Run network diagnostic tools like 'ping', 'traceroute', and 'iperf3' to assess the network performance.
- D. Reinstall the operating system.
- E. Update the server's BIOS.
Answer: A,B,C
Explanation:
Rolling back drivers is a quick way to revert to a known working state. Checking system logs will provide valuable information about driver errors or network issues. Network diagnostic tools will quantify the network performance and help isolate the problem. Reinstalling the OS is drastic and should be a last resort. Updating the BIOS is unlikely to resolve driver-related network issues unless specifically recommended for the network card.
NEW QUESTION # 286
You need to verify the integrity of the BlueField OS image before flashing it to the SmartNIC. Which method would provide the strongest guarantee that the image has not been tampered with?
- A. Comparing the image size with the expected size from the download source.
- B. Verifying the SHA256 checksum of the image against the published SHA256 checksum.
- C. Checking the MD5 checksum of the image against the published MD5 checksum.
- D. Utilizing gpg to verify the image.
- E. Downloading the image from a trusted source.
Answer: B,D
Explanation:
SHA256 provides a stronger collision resistance than MD5, making it a more reliable method for verifying image integrity. Comparing the image size is not a reliable method, as a small change can be made without significantly altering the size. Downloading from a trusted source is important, but doesn't guarantee the image hasn't been tampered with after it was published. GPG provides cryptographic assurance that the file originated from and was signed by an identified party.
NEW QUESTION # 287
You suspect a faulty NVIDIA ConnectX-6 network adapter in a server used for RDMA-based distributed training. Which commands or tools can you use to diagnose potential issues with the adapter's hardware and connectivity?
- A. Ispci -v to verify the adapter is detected and its resources are allocated correctly.
- B. ibstat to check the adapter's status, link speed, and active ports.
- C. ping to test basic network connectivity.
- D. ethtool to examine the adapter's Ethernet settings and statistics.
- E. nvsmimonitord to monitor GPU metrics and detect anomalies.
Answer: A,B,C,D
Explanation:
All options except E are relevant for diagnosing network adapter issues. 'Ispci -v' (A) verifies hardware detection. 'ibstat' (B) checks InfiniBand-specific details. 'ethtoor (C) examines Ethernet settings. 'ping' (D) tests basic connectivity. 'nvsmimonitord' (E) focuses on GPU monitoring, not network adapters.
NEW QUESTION # 288
You encounter an error during MIG instance creation using 'nvidia-smi' stating 'Insufficient GPU resources'. Which of the following could be the cause? (Select all that apply)
- A. There is no error; MIG always creates instances regardless of resources.
- B. The GPU is already fully utilized by other MIG instances or processes.
- C. The NVIDIA driver version is outdated and does not support the requested MIG configuration.
- D. The requested MIG configuration exceeds the GPU's available resources (e.g., compute or memory).
- E. The GPIJ is in a bad state and needs to be reset.
Answer: B,C,D
Explanation:
The 'Insufficient GPIJ resources' error indicates that the requested MIG instance creation cannot be fulfilled due to limitations in available resources (A) such as compute or memory. Outdated drivers (B) may not support the requested MIG configurations and hence can lead to resource management problems. When other instances or processes already consume all available resources (C), the operation can't continue. A GPU in a bad state might cause issues, but the specific error message points to resource exhaustion more directly. MIG does not bypass resource checks (E).
NEW QUESTION # 289
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