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Updated NVIDIA NCP-AII Practice Questions in PDF Format

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NVIDIA AI Infrastructure Sample Questions (Q76-Q81):

NEW QUESTION # 76
In a distributed training environment with NVLink switches, you need to optimize the data transfer between GPUs on different servers.
Which strategy is most likely to minimize the impact of inter-server latency on the overall training time?

A. Compressing the data before transferring it over the network.
B. Using asynchronous data transfers with overlapping computation.
C. Using a centralized parameter server architecture.
D. Increasing the batch size to amortize the cost of data transfers.
E. Switching to a synchronous SGD (Stochastic Gradient Descent) algorithm.

Answer: A,B,D

Explanation:
Increasing batch size reduces the frequency of transfers, amortizing latency. Asynchronous transfers allow computation to proceed while data is being transferred. Compression reduces the amount of data to be transferred. A centralized parameter server can exacerbate latency issues. Synchronous SGD is not directly related to minimizing inter-server latency. Asynchronous SGD helps masking out the data transfer overhead during training iteration, but is less reliable for the convergency of traing models.

NEW QUESTION # 77
Which of the following is the MOST critical consideration when planning the cooling strategy for a server rack containing multiple NVIDIA A100 GPUs?

A. Increasing the fan speed of the server chassis fans to maximum.
B. Ensuring the server room temperature is kept below 25 degrees Celsius.
C. Using liquid cooling for the CPUs, but air cooling for the GPUs.
D. Applying thermal paste to the GPU memory chips.
E. Optimizing airflow to ensure hot air is efficiently exhausted from the rack and cool air is drawn in.

Answer: E

Explanation:
While ambient temperature is important, optimized airflow is crucial for removing the heat generated by the GPUs. Focusing solely on CPU cooling neglects the GPU heat. Applying thermal paste to memory chips is generally unnecessary unless specifically recommended by the manufacturer. Maximizing fan speed can help, but efficient airflow design is more effective.

NEW QUESTION # 78
During NVLink Switch configuration, you encounter issues where certain GPUs are not being recognized by the system. Which of the following troubleshooting steps are most likely to resolve this problem?

A. Check the Power supply for enough capacity and stability.
B. Reinstall the operating system.
C. Check the system BIOS settings to ensure that NVLink is enabled and configured correctly.
D. Ensure that the NVLink Switch firmware is compatible with the installed GPUs.
E. Verify that all NVLink cables are securely connected and properly seated.

Answer: C,D,E

Explanation:
Explanation:Physical connection issues (A), BIOS configuration (B), and firmware incompatibility (C) are the most common causes of GPUs not being recognized. Reinstalling the operating system is a drastic measure that is unlikely to solve the problem. Checking the Power supply may also required to ensure the complete system have enough capacity and stability.

NEW QUESTION # 79
You've flashed the BlueField OS to your SmartNlC, but you need to customize the kernel command line arguments (bootargs) to enable a specific feature. Where is the MOST appropriate place to modify these arguments for persistent changes that survive reboots?

A. In the '/proc/cmdline' file. This allows immediate changes.
B. Directly in the kernel image file itself using a hex editor.
C. In the '/etc/default/grub' file on the BlueField OS, followed by updating the GRUB configuration.
D. In the bootloader configuration file (e.g., extlinux.conf or grub.cfg) on the BlueFieId's flash memory.
E. Passing it as an argument to bfboot during deployment.

Answer: D

Explanation:
The bootloader configuration file (extlinux.conf, grub.cfg, uEnv.txt depending on the system) is where boot arguments are persistently stored. Modifying the kernel image directly is highly discouraged and risky. 'letc/default/grub' is a common location on standard Linux systems, but not necessarily on the BlueField OS's boot environment. '/proc/cmdline' shows the currently used arguments, but modifying it doesn't persist changes across reboots. bfboot will only change the image during that flash, changes at the bootloader level persist after subsequent flashes.

NEW QUESTION # 80
After installing NGC CLI using pip, you encounter 'ngc' command not found error even though pip install reported successful. What can be the cause?

A. The host's operating system is not supported by NGC CLI.
B. NGC CLI only works inside Docker containers.
C. The shell needs to be reloaded or a new terminal session initiated for PATH changes to take effect.
D. The NGC CLI installation was corrupted. Run 'pip install -force-reinstall nvidia-cli'
E. The python executable where NGC CLI got installed is not in the system PATH.

Answer: C,E

Explanation:
The most common reason the 'ngc' command isn't found is that the python environment's executable path isn't in the system PATH (A). A quick fix to ensure environment variables are updated in your current shell is to reload the shell or start a new session (C).

NEW QUESTION # 81
......

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Test NCP-AII Sample Questions | Test NCP-AII Cram

Updated NVIDIA NCP-AII Practice Questions in PDF Format

NVIDIA AI Infrastructure Sample Questions (Q76-Q81):

NCP-AII Quiz Torrent: NVIDIA AI Infrastructure - NCP-AII Exam Guide & NCP-AII Test Bootcamp

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