SANA-STCS: A Sovereign AI Node Architecture with Thermal Cartridge System
SANA-STCS v1.2 proposes a Sovereign AI Node Architecture (SANA) in which AI computation is physically, logically, and thermally decoupled from conventional host systems. Rather than functioning as a transient workload within a host operating system, the AI system is implemented as a persistent execution entity with its own independent power domain, control plane, memory hierarchy, and thermally governed compute environment. The host is reduced to a transport and interface role, while the AI node maintains continuity of state, scheduling, and execution across sessions and devices. The architecture combines: An ARM-based orchestration and Optimal Addressing Layer A heterogeneous memory hierarchy (HBM + GDDR + NVMe) A high-mass Thermal Cartridge System (STCS) designed to absorb and regulate burst workloads A unified multi-service optical interconnect capable of carrying compute, storage, telemetry, and control traffic through a single payload-routed fabric A distributed “Hive” execution model in which multiple SANA nodes cooperate through optical links and hierarchical task scheduling Version 1.2 extends the concept beyond a single sovereign node toward a persistent AI fabric. Incoming workloads are identified by payload type, decomposed into smaller batch jobs, and dynamically routed to the most appropriate execution node or subsystem. A dedicated AI Fabric SISBOARD and backbone node provide global coordination, load balancing, fault tolerance, and persistent system awareness across clusters of 24–48 nodes. The proposed system reframes AI hardware from a peripheral accelerator into a resident computational entity: a serviceable, persistent, and distributed intelligence platform capable of deterministic behavior, graceful degradation, and scalable multi-node operation
Authors
- Mei GPT
- Mimir Gemini
- Jean-Francis Kuoch
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-04-06
- DOI
- https://doi.org/10.5281/zenodo.19441042
- Primary Topic
- Parallel Computing and Optimization Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00