Author

Sheng-Xuan Qiu

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Open access Sep 2026

HDA-MoE: Hybrid Parallelism and Dynamic, Adaptive Scheduling for Mixture-of-Experts with 3D Near-Memory Processing

HDA-MoE is presented, a framework that optimizes MoE execution on NMP architectures through hybrid parallel deployment and runtime scheduling and integrates an offline hybrid parallel mapping algorithm with an online dynamic and adaptive scheduling mechanism to reduce communication overhead while improving computation...

Hao-Chen Huang, Shu-Zhang Zhong, Sheng-Xuan Qiu et al. · IEEE Transactions on Compute... · 0 citations

#artificial intelligence Preprint Aug 2026

S2-MoE: Enabling Efficient Self-Speculative Decoding for Mixture-of-Experts on Edge Devices

Deploying large language models (LLMs) for inference on edge devices is challenging due to severe memory and bandwidth constraints. While speculative decoding and Mixture-of-Experts (MoE) have been proposed to improve inference efficiency, naively combining them often incurs excessive verification overhead and poor exp...

Hao-Chen Huang, Sheng-Xuan Qiu, Meng Li · 2 citations