Yeqi Huang
Yeqi Huang
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Benchmarking
MoE-CAP: Benchmarking Cost, Accuracy and Performance of Sparse Mixture-of-Experts Systems
MoE-CAP introduces a comprehensive benchmark for evaluating sparse Mixture-of-Experts systems across three key dimensions: Cost, Accuracy, and Performance. The benchmark reveals fundamental trade-offs in MoE deployments and proposes sparsity-aware metrics (S-MBU and S-MFU) along with CAP Radar Diagrams to help practitioners make informed deployment decisions for large-scale MoE systems.
Yinsicheng Jiang
,
Yao Fu
,
Yeqi Huang
,
Ping Nie
,
Zhan Lu
,
Leyang Xue
,
Congjie He
,
Man-Kit Sit
,
Jilong Xue
,
Li Dong
,
Ziming Miao
,
Dayou Du
,
Tairan Xu
,
Kai Zou
,
Edoardo Ponti
,
Luo Mai
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