A newer version of the Gradio SDK is available:
6.2.0
license: other
title: RFT Adaptive Computing Kernel
sdk: gradio
emoji: 🚀
colorFrom: blue
colorTo: green
short_description: Adaptive RFT kernel computing stability and coherence metric
sdk_version: 6.0.0
thumbnail: >-
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🚀 RFT Adaptive Computing Kernel (v1.0)
The Rendered Frame Theory (RFT) Adaptive Computing Kernel demonstrates real-time compute stability and harmonic coherence across CPU, GPU, and TPU workloads.
It applies RFT’s motion-based harmonic model to show how computation can self-balance under noise, load, or timing variance.
🔧 Overview
This kernel simulates adaptive performance regulation through harmonic metrics:
| Metric | Description |
|---|---|
| QΩ | Harmonic stability (amplitude equilibrium). |
| ζ_sync | Synchronisation coherence (phase alignment). |
| items/sec | Throughput estimate after adaptive correction. |
| status | System state — nominal / perturbed / critical. |
🧩 Profiles
- CPU — Linear compute flow tests.
- GPU — Parallel matrix or transformer operations.
- TPU — Tensor inference and batch stability.
- Mixed / I/O — Combined memory and data-path stress tests.
⚙️ How to Use
- Choose a Profile and Workload.
- Adjust Noise σ (0 – 0.30) to simulate load variation.
- Run the kernel.
- Review the JSON output showing QΩ, ζ_sync, items/sec, and stability status.
- Optionally download the run log for SHA-512 verification.
Repeated runs at fixed σ demonstrate adaptive recovery and equilibrium maintenance.
🎯 Purpose
The Adaptive Computing Kernel bridges theoretical physics and computer engineering by proving that RFT’s harmonic feedback can stabilise computation itself—creating a self-governing, energy-efficient framework for AI, aerospace, and energy systems.
⚖️ Rights & Contact
All Rights Reserved — RFT-IPURL v1.0 (UK / Berne Convention)
Research validation use only; no reverse-engineering or redistribution without written consent.
Author: Liam Grinstead
Affiliation: Rendered Frame Theory Systems (RFTSystems)
DOI: https://doi.org/10.5281/zenodo.17466722