3 papers
cs.DC2026
TTrace: Lightweight Error Checking and Diagnosis for Distributed Training
Haitian Jiang, Shaowei Zhu, Zhen Zhang +5
Distributed training is essential for scaling the training of large neural network models, such as large language models (LLMs), across thousands of GPUs. However, the complexity o…
cs.LG2025
PolyG: Adaptive Graph Traversal for Diverse GraphRAG Questions
Renjie Liu, Haitian Jiang, Xiao Yan +2
GraphRAG enhances large language models (LLMs) to generate quality answers for user questions by retrieving related facts from external knowledge graphs. However, current GraphRAG…
cs.LG2025
DiskGNN: Bridging I/O Efficiency and Model Accuracy for Out-of-Core GNN Training
Renjie Liu, Yichuan Wang, Xiao Yan +5
Graph neural networks (GNNs) are machine learning models specialized for graph data and widely used in many applications. To train GNNs on large graphs that exceed CPU memory, seve…