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LLM-PRISM: Characterizing Silent Data Corruption from Permanent GPU Faults in LLM Training
Large-scale LLM training is increasingly susceptible to hardware defects stemming from manufacturing escapes and silicon aging. These defects manifest as Silent Data Corruption (SDC) that perturb gradients and parameters throughout the training process. We present LLM-PRISM, a methodology to charact
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