2 papers
cs.DC2026
COPUS: Co-adaptive Parallelism and Batch Size Selection in Large Language Model Training
Akhmed Sakip, Erland Hilman Fuadi, Omar Sayedelahl +6
Training large language models requires jointly configuring two interdependent aspects of the system: the global batch size, which governs statistical efficiency, and the 3D parall…
cs.DC2025
Learning In Chaos: Efficient Autoscaling and Self-Healing for Multi-Party Distributed Training
Wenjiao Feng, Rongxing Xiao, Zonghang Li +6
Node and link churn in multi-party, cross-region clusters over wide-area networks (WANs) often disrupts distributed training. However, checkpoint-based recovery and cloud-centric a…