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C. Prasanna

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Review Aug 2026

When Does Distributed AI Inference Need More Wide-Area Bandwidth? A Co-Design Evaluation of Optical, Packet, and Software Levers

A workload model predicting when moving inference state across sites beats recomputing it is derived, and five sensitivity axes are quantify: context length, attention architecture, queueing, agentic compounding, and loss/jitter-induced bandwidth collapse are quantified.

C. Prasanna · 0 citations