Comet: Fine-grained Computation-communication Overlapping for Mixture-of-Experts

• URL: http://arxiv.org/abs/2502.19811v3
• Date: Tue, 04 Mar 2025 09:54:37 GMT
• Title: Comet: Fine-grained Computation-communication Overlapping for Mixture-of-Experts
• Authors: Shulai Zhang, Ningxin Zheng, Haibin Lin, Ziheng Jiang, Wenlei Bao, Chengquan Jiang, Qi Hou, Weihao Cui, Size Zheng, Li-Wen Chang, Quan Chen, Xin Liu,
• Abstract summary: Mixture-of-experts (MoE) has been extensively employed to scale large language models to trillion-plus parameters.<n>Existing methods suggest the communication in a MoE layer to be pipelined with the computation for overlapping.<n>We present COMET, an optimized MoE system with fine-grained communication-computation overlapping.
• Score: 8.80408909878008
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Mixture-of-experts (MoE) has been extensively employed to scale large language models to trillion-plus parameters while maintaining a fixed computational cost. The development of large MoE models in the distributed scenario encounters the problem of large communication overhead. The inter-device communication of a MoE layer can occupy 47% time of the entire model execution with popular models and frameworks. Therefore, existing methods suggest the communication in a MoE layer to be pipelined with the computation for overlapping. However, these coarse grained overlapping schemes introduce a notable impairment of computational efficiency and the latency concealing is sub-optimal. To this end, we present COMET, an optimized MoE system with fine-grained communication-computation overlapping. Leveraging data dependency analysis and task rescheduling, COMET achieves precise fine-grained overlapping of communication and computation. Through adaptive workload assignment, COMET effectively eliminates fine-grained communication bottlenecks and enhances its adaptability across various scenarios. Our evaluation shows that COMET accelerates the execution of a single MoE layer by $1.96\times$ and for end-to-end execution, COMET delivers a $1.71\times$ speedup on average. COMET has been adopted in the production environment of clusters with ten-thousand-scale of GPUs, achieving savings of millions of GPU hours.

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