Author

Philipp Wiesner

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Preprint Oct 2026

Revisiting Cauchy-Schwarz Norm Bounds for SDC Detection in LLM Inference

Large Language Models (LLMs) execute billions of floating-point operations per output token across many hardware accelerators. At this scale, hardware-induced faults can bypass system-level detection mechanisms and cause Silent Data Corruption (SDC). Algorithm-Based Fault Tolerance (ABFT) is the state-of-the-art techni...

A. Altenbernd, Dylan Everingham, Philipp Wiesner et al. · 0 citations

Preprint Aug 2026

Evaluating MFU as a Proxy for GPU Power for Energy-Aware Simulation of LLM Training

This work evaluates whether Model FLOPs Utilization (MFU) can serve as a portable, software-defined predictor of GPU power for LLMs, finding that a linear MFU-based power model fits every tested GPU as long as the workload is compute-bound, as in production LLM training.

Niklas Enskat, Philipp Wiesner · 1 citation · ⚡1