3 papers
cs.DC2025
Efficient Pre-Training of LLMs via Topology-Aware Communication Alignment on More Than 9600 GPUs
Guoliang He, Youhe Jiang, Wencong Xiao +8
The scaling law for large language models (LLMs) depicts that the path towards machine intelligence necessitates training at large scale. Thus, companies continuously build large-s…
cs.DC2025
Mycroft: Tracing Dependencies in Collective Communication Towards Reliable LLM Training
Yangtao Deng, Lei Zhang, Qinlong Wang +13
Reliability is essential for ensuring efficiency in LLM training. However, many real-world reliability issues remain difficult to resolve, resulting in wasted resources and degrade…
cs.DC2025
Minder: Faulty Machine Detection for Large-scale Distributed Model Training
Yangtao Deng, Xiang Shi, Zhuo Jiang +12
Large-scale distributed model training requires simultaneous training on up to thousands of machines. Faulty machine detection is critical when an unexpected fault occurs in a mach…