Workload composition in AI data centers decouples aggregate power variability from short-horizon ramping through asymmetric queueing where batch jobs fill inference-induced idle capacity.
In: Proceedings of the 29th ACM International Conference on Architectural Sup- port for Programming Languages and Operating Systems, Volume 3
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Workload composition smooths aggregate power demand while sustaining short-horizon ramps in AI data centers
Workload composition in AI data centers decouples aggregate power variability from short-horizon ramping through asymmetric queueing where batch jobs fill inference-induced idle capacity.