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GPU Unbound
GPU Unbound is a real-time GPU health monitoring and automated remediation system that transforms AMD ROCm telemetry into audible intelligence. Traditional dashboards bury critical warnings under utilization graphs that show what is happening without explaining why. A memory bottleneck can stall a training job for hours while the utilization graph looks normal, costing AI teams significant infrastructure spend. GPU Unbound solves this by reading rocm-smi for system vitals and rocprof for kernel-level tracing to distinguish compute-bound, memory-bound, and communications-bound states. The system sonifies these states: a healthy run hums steadily, a memory bottleneck makes the tone rise and jitter, a communication stall produces arrhythmic clicks, and a power throttle distorts the tone. An AI agent classifies telemetry in real time using a lightweight scikit-learn/ONNX model trained on performance-counter patterns, then selects a fix from a pre-validated menu: adjust batch size, enable gradient accumulation, tune NCCL flags, or reduce checkpoint frequency. The action is applied and the full detect-diagnose-act-verify sequence is logged to an auditable timeline with timestamps. The backend is Python 3.10+ with subprocess wrappers for rocm-smi and rocprof, and WebSockets stream telemetry and audio parameters to a Next.js 14 frontend that renders a live dashboard, audio controls, and a searchable audit log; the browser synthesizes the final audio via Web Audio API for minimal latency. Safety is paramount: the AI never writes code; it only invokes reversible, known-safe configuration changes, and every action is logged for review. Built by Team Magnum Opus for the AMD Developer Hackathon, GPU Unbound turns silent failures into audible, actionable alerts, reducing downtime and infrastructure waste while keeping human engineers fully in the loop with complete transparency.
13 Jul 2026
