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readme.md

Outline

DOI

This repository contains the source files, manuscript, and supplemental materials for:

A Bipartite Tensor Instruction Set Architecture (ISA) for Deterministic Consensus and Thermal Efficiency in High-Performance Computing

This repository contains the reference implementation of the Linear Conglomerate Calculus (LCC), a bipartite tensor instruction set architecture (ISA) designed for deterministic consensus and thermal efficiency.

Prerequisites

  • Rust Toolchain: Install rustc and cargo via rustup.rs.
  • Dependencies: The engine utilizes num-integer for GCD calculations and uuid for node identification.

Build Instructions

To compile the engine with maximum optimizations (recommended for benchmarking):

cargo build --release

Running Benchmarks

The engine includes three primary validation tests: ComparativeTest1 (Standard LinAlg vs LCC), ComparativeTest2 (TAD-Bridge Performance), and the MaximumRecoveryTest.

cargo run --release

Project Structure

  • BipartiteTensor: Implements hardware-level gate partitioning[cite: 188].
  • GeodesicSolver: Executes the Axiomatic Truth Transform via the Path of Least Action.
  • TAD: Implements Topologically Associating Domains for resonance recovery.

Rosetta Stone

Rust Variable / Struct LCC Academic Mapping Hardware/Logical Function
anchor: u32 Prime Anchor (n) Settled integer identity stored in the vaulted B0-31 segment.
delta: f32 Residual Phase Variance Fractional jitter processed in the voltage-gated B32-63 segment.
mass() Identity Density Metric calculating the stability of a node; 1.0 represents absolute truth.
action: f32 dS (Accumulated Energy) The computational expenditure required to traverse the field.
suction_break() Quantized State Finalization The deterministic trigger for snapping jitter into a crystalline anchor.
GeodesicSolver Axiomatic Truth Transform The engine that calculates the path of least action through the 156-Metric.
TAD Topologically Associating Domain A localized resonance scaffold used to recover high-latency data.

Citation

If using this engine for research, please cite the associated PeerJ manuscript: Crago, N. (2026). A Bipartite Tensor Instruction Set Architecture (ISA) for Deterministic Consensus and Thermal Efficiency in High-Performance Computing. DOI: 10.5281/zenodo.20186701

You can however cite all versions by using the DOI: 10.5281/zenodo.19728655 as this will always resolve to the latest one.

License

MIT

Additional Helpful Documentation

-Deterministic Resolution of the Quantum State via a Discrete Prime‑Indexed Manifold

-Linear Comglomerate Calculus - Specification

-The Bipartite Tensor Architecture and LCC Repository

-SpaceTCO Architecture - Repository

-The Generator Field

-SpaceTCO - Unified Field Architecture (v3)


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