2 papers
cs.AR2026
The Anatomy of Silent Data Corruption: GPU Error Pattern Study and Modeling Guidance
Chung-Hsuan Tung, Yanxiang Huang, Nirmal Saxena +5
Silent data corruption (SDC) threatens the reliability of large-scale GPU clusters used for training large language models, yet its rarity and lack of explicit error signals make a…
cs.AR2026
LLM-PRISM: Characterizing Silent Data Corruption from Permanent GPU Faults in LLM Training
Abhishek Tyagi, Saurabh Hukerikar, Nirmal Saxena +4
Large-scale LLM training is increasingly susceptible to hardware defects stemming from manufacturing escapes and silicon aging. These defects manifest as Silent Data Corruption (SD…