Unverified50% confidenceFactExact time
All of MoE's expert weights must reside in VRAM even if a given token does not use them; it has high demands on memory bandwidth and expert-parallel communication, and cross-device routing brings additional scheduling overhead.
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50%
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Long-term
Relevance
10/12/2026
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UnverifiedMoE专家并行架构中不同专家分布在不同GPU上，路由决策需要跨设备的All-to-All通信，该通信开销在高并发时成为系统瓶颈79% similarUnverifiedMoE架构中每个Token需通过All-to-All通讯路由到对应专家GPU，随集群规模增大通讯开销呈近似平方级增长73% similarVerifiedThe MoE architecture uses multiple expert networks and a routing mechanism to selectively activate only a subset of experts during each forward pass, reducing computational overhead while maintaining large model capacity.70% similarUnverified专家并行会带来跨设备的All-to-All通信开销，在高并发时往往成为系统瓶颈66% similarUnverifiedThe MoE architecture typically introduces auxiliary loss functions to force the gating network to distribute requests evenly, preventing routing to only a small number of popular experts.64% similar
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