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cs.DC2026
ResiHP: Taming LLM Training Failures with Dynamic Hybrid Parallelism
Tenghui Ma, Jihu Guo, Wei Gao +4
Hybrid parallelism underpins large-scale LLM training across tens of thousands of GPUs. At such scale, hardware failures on individual devices lead to performance skew across devic…
cs.DC2026
PromptTuner: SLO-Aware Elastic System for LLM Prompt Tuning
Wei Gao, Peng Sun, Dmitrii Ustiugov +2
Prompt tuning has become a prominent strategy for enhancing the performance of Large Language Models (LLMs) on downstream tasks. Many IT enterprises now offer Prompt-Tuning-as-a-Se…