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AFORE: Attention-FFN Disaggregation with Overlapped Reconfiguration of Experts
Efficient serving of Mixture-of-Experts (MoE) models is challenging due to large expert parameters, input-dependent expert activation, and dynamic workloads. Expert parallelism distributes expert computation across GPUs, while attention-FFN disaggregation (AFD) separates attention and feed-forward c
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