5 citations · 7 across the 10 of their papers we have counts for
Showing 2026Show all
2 papers · 1 filter
cs.DC2026
Charon: A Unified and Fine-Grained Simulator for Large-Scale LLM Training and Inference
Mengtian Yang, Zhekun Zhang, Mingheng Wu +3
Deploying large-scale LLM training and inference with optimal performance is exceptionally challenging due to a complex design space of parallelism strategies, system optimizations…
cs.DC2026
UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training
Size Zheng, Xuegui Zheng, Li-wen Chang +1
The exponential growth in Large Language Model (LLM) parameters has transformed model training into an increasingly resource-intensive endeavor. With the stagnation of Moore's Law…