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AI & Machine Learning · Advanced

Rail-Optimized Topology

A GPU cluster network design where each GPU index in every server connects to its own dedicated leaf switch (rail).

Definition

Rail optimization keeps most collective traffic between same-index GPUs one hop away, reducing latency and congestion. It is used in DGX SuperPOD and other large AI fabrics, usually in non-blocking fat-tree designs.

Exam tip

In rail-optimized designs, GPU N in every node connects to the same leaf switch.

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