2 papers
cs.DC2026
TensorHub: Scalable and Elastic Weight Transfer for LLM RL Training
Chenhao Ye, Huaizheng Zhang, Mingcong Han +11
Modern LLM reinforcement learning (RL) workloads require a highly efficient weight transfer system to scale training across heterogeneous computational resources. However, existing…
cs.DC2025
Enhancing Large-Scale AI Training Efficiency: The C4 Solution for Real-Time Anomaly Detection and Communication Optimization
Jianbo Dong, Bin Luo, Jun Zhang +22
The emergence of Large Language Models (LLMs) has necessitated the adoption of distributed training techniques, involving the deployment of thousands of GPUs to train a single mode…