GPUnx — Snapfront φ³ Grid Engine

Distributed Compute Framework with Coherence Monitoring

GPUnx is a lightweight, plug-and-play master/worker engine for experimenting with distributed computation, coherence metrics, and adaptive workloads. Built on Snapfront’s φ³ Physics framework, it’s designed to be simple enough for hobbyists yet powerful enough for researchers.

What it does

• Master/Worker Grid: Run one master node and as many worker nodes as you like (local or across LAN).
• Adaptive Tile Engine: Tasks are split into tiles that auto-adjust in size based on worker speed.
• Coherence Tracking (WCT_φ): Every update is measured against Snapfront’s golden-ratio-aligned coherence function. Watch order emerge from chaos in real time.
• Live Dashboard: Rich console view shows tile completion, cycle counts, average timings, and coherence levels.
• CSV Logging: Every cycle is logged for later analysis.

Why it’s valuable

• Perfect for learning distributed systems without the heavy overhead of Kubernetes/Hadoop.
• Explore phi-based coherence metrics in action.
• Visual, instant feedback — you’ll see the system adapt right on screen.
• Simple Python install, no external services required.

What’s included

• master.py — the Snapfront φ³ Master Node
• worker.py — the Worker Node (run as many as you like)
• requirements.txt — one-line install of dependencies
• README.md — quickstart instructions
• Demo screenshot of the live dashboard

Requirements

• Python 3.9+
• Packages: numpy, pyzmq, psutil, rich
• Runs on Windows, macOS, or Linux

License

Personal and educational use included. One-time purchase, no subscriptions, no upsells.