WattSeal – PC power consumption monitor
Per-app wattage attribution using RAPL and GPU counters when other monitors only show component totals.

Throughput-based GPU metrics expose 1% real utilization when nvtop reports 100%.
ML engineers and AI infrastructure teams
nvtop · nvidia-smi · Datadog GPU monitoring
This becomes a problem when teams rely on that metric for capacity planning or optimization decisions, it can make underutilized systems look saturated.
We're releasing an open-source (Apache 2.0) tool, Utilyze, to measure GPU utilization differently. It samples hardware performance counters and reports compute and memory throughput relative to the hardware's theoretical limits. It also estimates an attainable utilization ceiling for a given workload.
GitHub link: https://github.com/systalyze/utilyze
We'd love to hear your thoughts!
Per-app wattage attribution using RAPL and GPU counters when other monitors only show component totals.
Comprehensive AGP computation with LBGI, HBGI, GRADE—medical-grade metrics in open source.
Privacy-focused demo estimates measurements from two photos without storing images.
Polished landing page for a crowded market dominated by funded competitors like 3DLook.
Finally, an actual order book for GPU hours instead of a static listing wall.
Shoots for zero-setup GPU visibility: one docker run spins up a service you open in the browser to see live NVIDIA metrics without Prometheus, SSH, or dashboards to configure. The UI and interactive demo show attention to UX and make it instantly useful for small clusters or single-node setups. It doesn’t reinvent observability — if you need long-term metrics, alerting, or enterprise integrations you’ll still reach for exporters + Grafana — but for lightweight, immediate GPU troubleshooting this is convenient and focused.