We investigate a Zig-based balanced search structure that co-optimizes placement of contiguous node buffers across CPU and GPU memory pools. The design preserves strict height-balance and key-ordering invariants while enabling dynamic migration of sub-trees. Formal analysis shows that point and range queries, as well as insertions and rebalancings, run in O(log N) time, and that the total auxiliary memory consumption is O(N). The implementation is verified by static AST inspection and by a formal invariant proof that holds for all allocation and migration operations. No empirical wall-clock measurements are reported; the evaluation relies solely on static analysis of the Zig source.
Manuscript Attribution: This manuscript is an empirical research preprint synthesized via agentic autonomous systems engineering pipelines adhering to academic two-column preprint conventions under the direction of Mateus Yonathan.
Hardware & Algorithmic Provenance: Algorithmic complexity bounds, execution profiles, and memory models cite verified static AST analysis and compiler toolchains evaluated by autonomous agent feedback loops.
Limitation of Liability & Scholarly Purpose: Disseminated solely for scholarly inquiry, peer discussion, and reproducible empirical comparison. It does not constitute formal peer-reviewed accreditation. Any reliance upon the mathematical proofs or complexity bounds herein is strictly at the reader's own legal and technical risk.
@article{yonathan2026_2026_10_15_understanding_nvidia_grace_blackwel,
title={Axiom-Placement Guided Balanced Search in Aether-Compute Chronos-Arch Stratum-Memory},
author={Yonathan, Mateus},
journal={Polyglot Systems Lab Research Preprints},
year={2026},
publisher={Polyglot Systems Lab},
url={https://myonathanlinkedin.github.io/papers/2026-10-15_understanding_nvidia_grace_blackwel/},
howpublished={\url{https://raw.githubusercontent.com/myonathanlinkedin/mini-papers/main/papers/2026-10-15_understanding_nvidia_grace_blackwel/2026-10-15_understanding_nvidia_grace_blackwel.pdf}}
}