5 citations · 8 across the 11 of their papers we have counts for
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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
Understanding Stragglers in Large Model Training Using What-if Analysis
Jinkun Lin, Ziheng Jiang, Zuquan Song +13
Large language model (LLM) training is one of the most demanding distributed computations today, often requiring thousands of GPUs with frequent synchronization across machines. Su…
cs.DC2024★ 1 cited
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…