1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.DC2026
HiNa-MoE: High-Performance, Non-Intrusive MoE Inference on CPUs with Matrix Engines
Weiling Yang, Junwen Zhang, Dezun Dong +4
Mixture-of-Experts (MoE) inference is increasingly deployed in local and on-premise environments, where expert parameters often exceed GPU memory capacity. In latency-sensitive, lo…
cs.DC2025
Demystifying ARM SME to Optimize General Matrix Multiplications
Chencheng Deng, Weiling Yang, Jianbin Fang +1
General Matrix Multiplication (GEMM) is a critical kernel in high-performance computing and deep learning. While modern architectures like ARM's Scalable Matrix Extension (SME) int…
cs.LG2025★ 1 cited
LayerScope: Predictive Cross-Layer Scheduling for Efficient Multi-Batch MoE Inference on Legacy Servers
Enda Yu, Dezun Dong, Zhaoning Zhang +6
Mixture-of-Experts (MoE) models face memory and PCIe latency bottlenecks when deployed on commodity hardware. Offloading expert weights to CPU memory results in PCIe transfer laten…