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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…
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…
Characterizing Soft-Error Resiliency in Arm's Ethos-U55 Embedded Machine Learning Accelerator
Abhishek Tyagi, Reiley Jeyapaul, Chuteng Zhu +2
As Neural Processing Units (NPU) or accelerators are increasingly deployed in a variety of applications including safety critical applications such as autonomous vehicle, and medic…