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---
title: Coherent Compute Engine
emoji: 🌖
colorFrom: pink
colorTo: red
sdk: gradio
sdk_version: 6.2.0
app_file: app.py
pinned: false
license: other
short_description: Live coherence + throughput benchmark (no precomputed result
thumbnail: >-
https://cdn-uploads.huggingface.co/production/uploads/685edcb04796127b024b4805/Sr9bUuYsRuDtVZnb-7kke.png
---
# Coherent Compute Engine
This Space demonstrates a **live, coherent compute engine** running entirely on CPU.
No precomputed benchmarks.
No synthetic scaling.
No hidden accelerators.
Every result shown is produced **at runtime** on the machine hosting this Space.
---
## What Is Being Measured
Each “item” is defined as:
> One coherent update of a state vector `[Ψ, E, L]` for a single oscillator.
The engine evolves millions of oscillators using:
- Numerically stable
- Branchless
- Energy-retentive updates
Metrics reported:
- **Throughput** — coherent updates per second
- **Coherence** — stability between initial and final state
- **Mean Energy** — energy retention across the system
- **Elapsed Time** — real wall-clock time
---
## Why This Matters
Most benchmarks optimize for raw FLOPs.
This engine optimizes for **coherent progression under constraint**.
It shows that:
- High throughput does not require GPUs
- Stability can be preserved at scale
- Energy retention can remain high even under load
This is **architecture**, not a paper claim.
---
## What This Is Not
- Not a neural network
- Not a pre-trained model
- Not a simulation with fixed outputs
- Not a GPU demo
It is a **compute engine**, measured live.
---
## Reproducibility
You can:
- Change oscillator count
- Change step count
- Rerun at any time
Results will change depending on:
- Host CPU
- Available cores
- Runtime conditions
That is the point.
---
## Ethics & Transparency
No data is uploaded.
No background processes.
No hidden scaling.
What you see is what runs.
---
## Author
Built as part of the **Rendered Frame Theory (RFT)** engineering work.
Focus:
- Truthful measurement
- Energy-aware compute
- Coherent system design
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference