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NVIDIA NCP-AIO Exam - Topic 1 Question 17 Discussion

You have successfully pulled a TensorFlow container from NGC and now need to run it on your stand-alone GPU-enabled server.Which command should you use to ensure that the container has access to all available GPUs?
D) docker run --gpus all nvcr.io/nvidia/tensorflow:<tag>
A) kubectl create pod --gpu=all nvcr.io/nvidia/tensorflow:<tag>
B) docker run nvcr.io/nvidia/tensorflow:<tag>
C) docker start nvcr.io/nvidia/tensorflow:<tag>

NVIDIA NCP-AIO Exam - Topic 1 Question 17 Discussion

Actual exam question for NVIDIA's NCP-AIO exam
Question #: 17
Topic #: 1
[All NCP-AIO Questions]

You have successfully pulled a TensorFlow container from NGC and now need to run it on your stand-alone GPU-enabled server.

Which command should you use to ensure that the container has access to all available GPUs?

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Suggested Answer: D

Comprehensive and Detailed Explanation From Exact Extract:

When running a GPU-enabled container directly on a server with Docker, the flag --gpus all is required to allow the container access to all GPUs on the host system. This ensures that the TensorFlow container can utilize GPU resources fully. The other options either do not specify GPU access correctly or are Kubernetes-specific commands.


by Jacquelyne at Jun 28, 2026, 10:31 PM

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Katina
16 hours ago
I feel like I might confuse the `docker run` and `docker start` commands. I hope I remember which one is for running a new container.
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Jeanice
6 days ago
I remember practicing a similar question, and I think the correct option is the one that specifies `--gpus all`.
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Kenia
11 days ago
I think the command should allow access to all GPUs, but I'm not entirely sure if it's the one with the `--gpus` flag.
upvoted 0 times
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