DynaNDE: Dynamic Near-Data Expert Scheduling for Batched MoE Inference
DynaNDE is presented, a dynamic near-data expert scheduling framework that exploits NPU-NDP collaboration to accelerate batched MoE inference and introduces an analytical performance model that captures hardware heterogeneity, data-movement costs, and communication-computation overlap in cooperative NPU-NDP execution.