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Only need to practice for 20 to 30 hours

You will get to know the valuable exam tips and the latest question types in our NCP-AII certification training files, and there are special explanations for some difficult questions, which can help you to have a better understanding of the difficult questions. All of the questions we listed in our NCP-AII practice exam materials are the key points for the IT exam, and there is no doubt that you can practice all of NCP-AII best questions within 20 to 30 hours, even though the time you spend on it is very short, however the contents you have practiced are the quintessence for the IT exam. And of course, if you still have any misgivings, you can practice our NCP-AII certification training files again and again, which may help you to get the highest score in the IT exam.

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Simulate the real exam

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NVIDIA AI Infrastructure Sample Questions:

1. A user reports that their deep learning training job is crashing with a 'CUDA out of memory' error, even though 'nvidia-smi' shows plenty of free memory on the GPU. The job uses TensorFlow. What are the TWO most likely causes?

A) The CUDA VISIBLE DEVICES environment variable is not set correctly.
B) The TensorFlow version is incompatible with the installed NVIDIA driver.
C) The system's swap space is full, preventing memory from being allocated.
D) TensorFlow is allocating memory on the CPU instead of the GPU.
E) TensorFlow is fragmenting GPU memory, making it difficult to allocate contiguous blocks.

2. A server with 8 NVIDIAAIOO GPUs is experiencing an unexpected shutdown under heavy load. The IPMI logs show a 'Power Supply Deasserted' event immediately preceding the shutdown. After replacing the PSU, the issue persists. What is the MOST likely cause of the continued shutdowns?

A) Network congestion causing system instability.
B) Overcurrent protection (OCP) tripping due to excessive inrush current during GPU startup.
C) Insufficient system memory (RAM).
D) A faulty CMOS battery.
E) Incompatible GPU driver version.

3. You are tasked with configuring an NVIDIA NVLink Switch system. After physically connecting the GPUs and the switch, what is the typical first step in the software configuration process?

A) Updating the firmware of the NVLink Switch.
B) Installing the latest NVIDIA drivers on all connected GPUs.
C) Installing the NVLink Switch management software.
D) Configuring the system BIOS to enable NVLink support.
E) Running a memory bandwidth test between all connected GPUs.

4. You are using Docker Compose to define a multi-container application that includes a GPU-accelerated service. How would you configure the service in the 'docker-compose.ymr file to leverage the NVIDIA runtime?

A) Set the environment variable 'NVIDIA VISIBLE in the service definition.
B) Add 'nvidia: all' to the service definition.
C) Add 'deploy: resources: reservations: devices: - driver: nvidia count: all capabilities: [gpu]' to the service definition.
D) Add 'command: -gpus all' to the service definition.
E) Add 'runtime: nvidia' to the service definition.

5. Consider a scenario where you want to reset your NVIDIAA100 GPU back to a non-MIG mode state after having previously configured MIG. Which of the following steps are required?

A) Run 'nvidia-smi -set-mig-mode=disable -i O' and then reboot the system.
B) Run 'nvidia-smi -set-mig-mode=disable -i O', then run 'nvidia-smi -i 0 -migrr 0' , and finally reboot.
C) Run 'nvidia-smi -destroy-mig-config -i 0' , then run 'nvidia-smi -set-mig-mode=disable -i 0', and finally reboot.
D) Run 'nvidia-smi -set-mig-mode=disable -i O' followed by 'nvidia-smi -reset-default-mig-mode -i
E) Run 'nvidia-smi -set-mig-mode=disable -i , then power off the system and physically remove and re-install the GPU.

Solutions: