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--- |
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license: other |
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title: RFT Adaptive Computing Kernel |
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sdk: gradio |
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emoji: 🚀 |
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colorFrom: yellow |
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colorTo: pink |
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short_description: Adaptive RFT kernel computing stability and coherence metric |
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sdk_version: 5.49.1 |
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--- |
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# 🧠 RFT Adaptive Computing Kernel (v1.0) |
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The **Rendered Frame Theory (RFT) Adaptive Computing Kernel** simulates harmonic stability and coherence across CPU, GPU, and TPU environments. |
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It benchmarks computational self-stabilisation under varying workloads and randomised system noise, providing a verified proof log for every run. |
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--- |
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## ⚙️ How It Works |
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Each simulation dynamically generates: |
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- **QΩ (Stability Metric):** Reflects harmonic equilibrium of compute operations. |
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- **ζ_sync (Coherence Metric):** Measures synchronization under fluctuating workloads. |
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- **rate_items_per_sec:** Estimated throughput (adaptive, noise-adjusted). |
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- **SHA-512 Sealed Log:** Each run produces a cryptographically signed verification record. |
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--- |
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## 🧩 Parameters |
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| Parameter | Description | |
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|------------|--------------| |
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| **Compute Profile** | CPU, GPU, or TPU mode | |
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| **Workload Type** | Matrix, Transformer, or Mixed | |
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| **Cycles** | Number of operational iterations | |
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| **Seed** | Random seed for reproducibility | |
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--- |
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## 📊 Output Example |
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```json |
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{ |
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"profile": "GPU", |
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"workload": "transformer", |
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"cycles": 5, |
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"rate_items_per_sec": 8.12e+08, |
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"QΩ": 0.841, |
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"ζ_sync": 0.792, |
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"status": "nominal", |
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"timestamp_utc": "2025-10-29T15:02:14Z", |
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"sha512": "..." |
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} |
