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cs.DC2026
UBEP: Re-architecting Expert Parallelism Communication Library for Production Superpods
Yipeng Liu, Chang Liu, Si Shen +16
The deployment of Mixture-of-Experts (MoE) models on production high-bandwidth superpods, such as NVIDIA's NVL72/576 and Huawei's CloudMatrix384, introduces critical challenges bey…
cs.DC2025
Opt4GPTQ: Co-Optimizing Memory and Computation for 4-bit GPTQ Quantized LLM Inference on Heterogeneous Platforms
Yaozheng Zhang, Wei Wang, Jie Kong +5
The increasing adoption of large language models (LLMs) on heterogeneous computing platforms poses significant challenges to achieving high inference efficiency. To address these e…
cs.DC2025
HAP: Hybrid Adaptive Parallelism for Efficient Mixture-of-Experts Inference
Haoran Lin, Xianzhi Yu, Kang Zhao +7
Current inference systems for Mixture-of-Experts (MoE) models primarily employ static parallelization strategies. However, these static approaches cannot consistently achieve optim…