3 papers
cs.DC2025
OptPipe: Memory- and Scheduling-Optimized Pipeline Parallelism for LLM Training
Hongpei Li, Han Zhang, Huikang Liu +2
Pipeline parallelism (PP) has become a standard technique for scaling large language model (LLM) training across multiple devices. However, despite recent progress in reducing memo…
math.OC2025
PDHCG: A Scalable First-Order Method for Large-Scale Competitive Market Equilibrium Computation
Huikang Liu, Yicheng Huang, Hongpei Li +2
Large-scale competitive market equilibrium problems arise in a wide range of important applications, including economic decision-making and intelligent manufacturing. Traditional s…
cs.AI2025
Solver-Informed RL: Grounding Large Language Models for Authentic Optimization Modeling
Yitian Chen, Jingfan Xia, Siyu Shao +2
Optimization modeling is fundamental to decision-making across diverse domains. Despite progress in automating optimization formulation from natural language descriptions, Large La…