Q: 13
[AI Network Architecture]
You are designing a new AI data center for a research institution that requires high-performance
computing for large-scale deep learning models. The institution wants to leverage NVIDIA's reference
architectures for optimal performance.
Which NVIDIA reference architecture would be most suitable for this high-performance AI research
environment?
Options
Discussion
Yeah, D makes sense here. DGX SuperPOD is the actual reference architecture for massive AI/HPC clusters on-prem, while LaunchPad (C) is just for quick hands-on labs. Pretty sure SuperPOD is what NVIDIA recommends for these research setups. Anyone see a reason to consider B instead?
C/D? LaunchPad is more for hands-on demos, not for production-grade HPC. Pretty sure D is right since SuperPOD is the go-to blueprint for big AI datacenters, but C might trap some folks since it's also widely used. Thoughts?
Is there a budget constraint? If price is a factor, that would make B a more likely choice.
D
C/D? LaunchPad looks tempting but DGX SuperPOD fits reference architecture for HPC AI data centers. C only if they're after small-scale demos.
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