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cs.DC2026
ReCoVer: Resilient LLM Pre-Training System via Fault-Tolerant Collective and Versatile Workload
Ziyue Liu, Zhengyang Wang, Ruijie Zhang +7
Pre-training large language models on massive GPU clusters has made hardware faults routine rather than rare, driving the need for resilient training systems. Yet existing framewor…
cs.DC2026
SPARe: Stacked Parallelism with Adaptive Reordering for Fault-Tolerant LLM Pretraining Systems with 100k+ GPUs
Jin Lee, Zhonghao Chen, Xuhang He +6
In large-scale LLM pre-training systems with 100k+ GPUs, failures become the norm rather than the exception, and restart costs can dominate wall-clock training time. However, exist…