The Compute ICE-AGE: Invariant Compute Envelope under Addressable Graph Evolution
R. Jay Martin II

TL;DR
This paper introduces a deterministic semantic graph engine that maintains semantic continuity through local mutations, demonstrating scalable, low-latency performance on Apple Silicon hardware with stable integrity under adverse conditions.
Contribution
It presents a production-grade C++ implementation of a persistent semantic graph system that preserves continuity structurally, contrasting with inference-based recomputation methods.
Findings
Traversal latency remained within microsecond ranges at large scales.
CPU utilization was stable at approximately 17.2% during sustained workloads.
The system maintained integrity under hostile ingress conditions, with degradation localized.
Abstract
This paper presents empirical results from a production-grade C++ implementation of a deterministic semantic state substrate operating under bounded local state evolution. The system was realized as a CPU-resident persistent semantic graph engine designed to preserve semantic continuity structurally rather than repeatedly reconstructing it through probabilistic inference. Contemporary inference-driven AI systems repeatedly recompute semantic state through context replay and probabilistic recomposition. In contrast, the substrate described here evolves semantic continuity incrementally through locality-preserving traversal and bounded local mutation over persistent graph topology. Empirical measurements on Apple Silicon M2-class hardware demonstrated locality-constrained traversal behavior across scaling regimes ranging from 1 million to 25 million persistent semantic nodes.…
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