Data Physics & Cyber-Physical Systems - Part VI: Thermo-Algorithmic Determinism and Logical Cavitation: A New Data Physics Paradigm for Frontier AI Clusters
Abstract. As artificial intelligence clusters reach gigawatt-scale, conventional facility engineering encounters hard physical barriers. The IT industry, which traditionally treats software as abstract logic, must confront the reality that code is energy shaped into information. This publication defines the framework of Data Physics, explaining the geostrategic necessity of relocating AI infrastructure to stable continental cratons (e.g., Greenland), and formalizes the phenomenon of "Logical Cavitation"- the digital equivalent of hydraulic instability that drastically degrades algorithmic performance at NCCL synchronization barriers.
Authors
- Rajmund Olszewski
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-10-08
- DOI
- https://doi.org/10.5281/zenodo.23248005
- Primary Topic
- Energy Efficiency in Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00