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---
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: >-
https://cdn-uploads.huggingface.co/production/uploads/685edcb04796127b024b4805/2T1X6xZm2w-L3hdCwtFbM.png
---
# 🚀 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
1. Choose a **Profile** and **Workload**.
2. Adjust **Noise σ** (0 – 0.30) to simulate load variation.
3. Run the kernel.
4. Review the JSON output showing QΩ, ζ_sync, items/sec, and stability status.
5. 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](https://doi.org/10.5281/zenodo.17466722) |