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cs.DC2026
Fine-Tuning a 3B-Parameter LLM on a Smartphone: Characterizing Sustained Training
Andrew Geyko, Marius Mosbach, André Brinkmann
Multi-billion-parameter LLMs now run on phones for inference, and training them on the device would personalize them without user data leaving the phone. Prior work has measured in…
cs.DC2023
A More Scalable Sparse Dynamic Data Exchange
Andrew Geyko, Gerald Collom, Derek Schafer +2
Parallel architectures are continually increasing in performance and scale, while underlying algorithmic infrastructure often fail to take full advantage of available compute power…