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NCA-AIIO - AI Infrastructure - Section 2.2

Scale a GPU infrastructure for different use cases.

Describe how GPU infrastructure scales from a single workstation through multi-GPU servers to multi-node clusters, and the role of NVLink, NVSwitch, and high-speed fabrics in enabling that progression. Choose the appropriate scale - single node, DGX BasePOD, or DGX SuperPOD - based on the compute and memory requirements of a given workload.

More in this domain

Identify hardware requirements for specific AI training task use cases.Section 2.1
Identify key concepts and high-level specifications for power and cooling.Section 2.3
Articulate the advantages, challenges, and considerations of on-premise versus cloud infrastructure.Section 2.4
Identify key components and considerations of accelerated infrastructure clusters.Section 2.5
Identify facility requirements for accelerated infrastructure.Section 2.6
Determine networking requirements for AI workloads.Section 2.7
Identify and describe data centre networking protocols and key concepts.Section 2.8
Identify high-speed data centre network options and their use cases.Section 2.9
Explain the purpose and benefits of a DPU in a data centre.Section 2.10

Back to all AI Infrastructure objectives, or the NCA-AIIO cert hub.

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