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metadata
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