tags: - green-ai - edge-computing - c++ - spectral-graph-theory - ramanujan-graphs - topological-deep-learning license: other
⚡ Ramanujan Spectral Reservoir (RSR)
"Intelligence is not about weight adjustment, but optimal topology."
This repository hosts the reference implementation and benchmarks for the Ramanujan Spectral Reservoir, a topological AI architecture that replaces Backpropagation with closed-form solutions on spectral expander graphs.
🚀 Key Benchmarks
We achieved hard real-time performance on commodity hardware by eliminating iterative training in hidden layers:
| Device | Metric | Result | Speedup vs MLP |
|---|---|---|---|
| Legacy CPU (i5-4570, 4th Gen) | Inference Time | ~287x Faster | 287x |
| Mobile (Android ARM64) | Latency | < 0.6 ms | >100x |
| Throughput | FPS | 1600+ inf/sec | N/A |
📄 The Paper
Full mathematical derivation, proofs, and the "Poliform Industrial Secret Protocol" details are available on Zenodo: [LINK A TU ZENODO AQUÍ]
🔧 How it Works
- Project: Input data is projected onto a fixed Ramanujan Graph ($d$-regular spectral expander).
- Diffuse: Information propagates via spectral diffusion (mixing time is optimal).
- Solve: The readout layer is computed analytically (Closed-Form) using Ridge Regression.
- Result: Deterministic, Green AI that runs on bare metal C++.
💻 Code Availability
The C++ kernel for Android and the Python reference implementation are available under the Polyform Strict License 1.0.0 (Non-commercial research only).
Developed by Andrés Sebastián Pirolo (Independent Researcher). Contact: apirolo@abc.gob.ar