3 papers
cs.DC2026
MemFine: Memory-Aware Fine-Grained Scheduling for MoE Training
Lu Zhao, Rong Shi, Shaoqing Zhang +21
The training of large-scale Mixture of Experts (MoE) models faces a critical memory bottleneck due to severe load imbalance caused by dynamic token routing. This imbalance leads to…
cs.DC2025
MoFa: A Unified Performance Modeling Framework for LLM Pretraining
Lu Zhao, Rong Shi, Shaoqing Zhang +14
The exponential growth in LLM scales, with parameters soaring from billions to trillions, has necessitated distributed pretraining across large clusters comprising thousands to ten…
cs.DC2025
Disaggregated Prefill and Decoding Inference System for Large Language Model Serving on Multi-Vendor GPUs
Xing Chen, Rong Shi, Lu Zhao +4
LLM-based applications have been widely used in various industries, but with the increasing of models size, an efficient large language model (LLM) inference system is an urgent pr…