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NVIDIA Exam NCA-GENL Topic 6 Question 2 Discussion

Actual exam question for NVIDIA's NCA-GENL exam
Question #: 2
Topic #: 6
[All NCA-GENL Questions]

[Software Development]

In the context of developing an AI application using NVIDIA's NGC containers, how does the use of containerized environments enhance the reproducibility of LLM training and deployment workflows?

Show Suggested Answer Hide Answer
Suggested Answer: B

NVIDIA's NGC (NVIDIA GPU Cloud) containers provide pre-configured environments for AI workloads, enhancing reproducibility by encapsulating dependencies, libraries, and configurations. According to NVIDIA's NGC documentation, containers ensure that LLM training and deployment workflows run consistently across different systems (e.g., local workstations, cloud, or clusters) by isolating the environment from host system variations. This is critical for maintaining consistent results in research and production. Option A is incorrect, as containers do not optimize hyperparameters. Option C is false, as containers do not compress models. Option D is misleading, as GPU drivers are still required on the host system.


NVIDIA NGC Documentation: https://docs.nvidia.com/ngc/ngc-overview/index.html

Contribute your Thoughts:

Alita
3 days ago
Yeah, it encapsulates dependencies and configurations, making it easier to reproduce workflows.
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Sanda
5 days ago
I think using containerized environments ensures consistent execution.
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Edelmira
7 days ago
B is the correct answer. Containers encapsulate all the dependencies and configurations, ensuring that the training and deployment workflows are reproducible across different systems. This is crucial for LLM development.
upvoted 0 times
Rima
2 days ago
I think B is the correct answer. Containers encapsulate dependencies and configurations for reproducibility.
upvoted 0 times
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