Apeiron v1: A Predictive Microfluidic Cooled 3D Fractal Star Network-on-Chip Architecture for Next-Generation AI Workloads
Year: 2026
Type: preprint
Abstract: This paper presents a conceptual design and theoretical framework for a revolutionary processing architecture optimized for dense matrix computations in artificial intelligence workloads, designated as Apeiron v1. The architecture introduces a novel engineering pathway integrating microfluidic jet impingement cooling with a symmetric 3D Fractal Star Network-on-Chip (NoC) topology to overcome the dynamic thermal wall limitations of conventional silicon layouts. The hosted documentation includes the mathematically constrained steady-state thermal model, a synthesizable Hardware Description Language controller (Verilog FSM) managing four synchronized functions (Predictive Cooling, Thermal Monitoring, Power Gating, and Emergency Shutdown), and a deterministic logic verification environment (Verilog Testbench). Additionally, it establishes a rigorous peer-review and epistemological boundary to isolate verified logical configurations from future empirical, hydraulic, and commercial constraints.
Author: Al-Zaman, Apeiron
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7204862205
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