TACE-Alg: Thermo-Algorithmic Control & Execution Algorithm for Hyperscale mCDU Systems
Rajmund Olszewski · Zenodo (CERN European Organization for Nuclear Research) · 2026
Published September 27, 2026 | Version v1 | Open Access DOI: https://doi.org/10.5281/zenodo.22997888 Thermo-Algorithmic Determinism in Hyperscale AI Architectures: The mCDU Data Physics Framework 1. Abstract & The "Straggler Effect" As semiconductor fabrication advances toward sub-3nm nodes, thermal management in hyperscale AI accelerator clusters has evolved from a facility issue into a critical computational bottleneck. In distributed high-performance computing (HPC), model synchronization relies on deterministic communication barriers, such as the NCCL Ring-AllReduce protocol. However, traditional systems engineering artificially separates mechanical infrastructure from silicon-level algorithmic execution. This paper introduces the Thermo-Algorithmic Control & Execution (TACE-Alg) framework, establishing that hydrodynamic stability is a fundamental unit test for the modern AI software stack. We demonstrate how localized hydraulic anomalies—such as micro-cavitation or gas phase entrainment—provoke hardware-level clock throttling (DVFS), directly transforming physical fluid instabilities into cluster-wide logical delays known as the "Straggler Effect." 2. The 100 Hz Telemetry Solution & Operational Scope To bridge this gap, TACE-Alg utilizes 100 Hz piezoelectric telemetry within the Coolant Distribution Unit (mCDU). This specific frequency window bypasses high-pitched ultrasonic noise, acting as an ultra-fast dynamic barometer to capture macro-scale bulk modulus degradation and gas void fractions before they induce a surge in silicon junction temperatures. System Scope & Boundary Conditions: Crucially, the TACE-Alg framework is engineered to model non-linear dynamic coupling during transient states, operational anomalies, and hydraulic loops with compromised deaeration. It specifically addresses Henry's Law gas desorption, static pressure drops, and micro-cavitation. By explicitly targeting these real-world, turbulent vulnerabilities rather than idealized, steady-state laboratory conditions, this framework definitively neutralizes the "steady-state fallacy" of conventional passive cooling models, providing a robust engineering solution for dynamic power density environments exceeding 100 kW per rack. 3. Proactive Hydraulic Control & Execution Determinism Standard reactive cooling algorithms typically increase pump RPM when temperatures rise, an action that inadvertently lowers suction pressure and exacerbates micro-cavitation in the microchannels. TACE-Alg executes a counter-intuitive, proactive response: it reduces pump RPM or opens bypass circuits to increase static suction pressure. This restores the Net Positive Suction Head (NPSHa) and condenses vapor pockets back into the liquid phase. By mapping this physical intervention to the algorithmic execution time path integral, we prove that preventing localized phase transitions in a single microchannel prevents multi-thousand-node GPU clusters from stalling at collective communication barriers. 4. Industrial Implementation & Licensing The framework translates theoretical physics into pragmatic industrial application. TACE-Alg is designed for seamless integration into standard commodity Programmable Logic Controllers (e.g., Siemens S7, Beckhoff) utilizing a 10 ms cyclic interrupt for continuous moving variance calculations, entirely bypassing the need for expensive DSP processors. The system is validated by object-oriented Python digital twins that confirm pre-emptive anomaly detection with a 300–800 ms lead time. Operating within a hybrid intellectual property framework, TACE-Alg is anchored by Open Science prior art (DOI: 10.5281/zenodo.22997888) and patent-pending control logic. It utilizes a Dual-Licensing Model, offering GNU GPLv3 for academic research alongside Commercial Enterprise Licensing for B2B hyperscale deployment.