3 papers
cs.DC2026
TAOT: Topology-Aware Optimal Transport for Dynamic Expert Replica Placement in MoE Training
Lingyun Zhang, Henghua Zhang, Shilei Gu +5
Mixture-of-Experts (MoE) has become a key architecture for scaling large language models (LLMs), yet its dynamic routing causes severe load imbalance in expert-parallel training. E…
cs.DC2025
Staggered Batch Scheduling: Co-optimizing Time-to-First-Token and Throughput for High-Efficiency LLM Inference
Jian Tian, Shuailong Li, Yang Cao +8
The evolution of Large Language Model (LLM) serving towards complex, distributed architectures--specifically the P/D-separated, large-scale DP+EP paradigm--introduces distinct sche…
cs.DC2025
Astra: Efficient and Money-saving Automatic Parallel Strategies Search on Heterogeneous GPUs
Peiran Wang, Haibing Li, Fu Haohan +3
In this paper, we introduce an efficient and money-saving automatic parallel strategies search framework on heterogeneous GPUs: Astra. First, Astra searches for the efficiency-opti…