AI Energy Monitoring
Carbontracker
Open-source tool that tracks and predicts energy use and carbon footprint of model training.
- Pricing
- Free
- Compliance
- Not stated
- Platforms
- On-premise, Cloud
AI Energy Monitoring
NVIDIA's data center GPU management toolkit with a Prometheus exporter for power and energy telemetry.
NVIDIA Data Center GPU Manager (DCGM) provides libraries and tools for observing, managing, validating and integrating NVIDIA data-center accelerators. The companion DCGM Exporter exposes GPU telemetry in Prometheus text format; its documented metrics include DCGM_FI_DEV_POWER_USAGE as a gauge for board power draw and DCGM_FI_DEV_TOTAL_ENERGY_CONSUMPTION as a counter for cumulative GPU energy. The exporter repository ships source, container and package builds, a Helm chart and dashboards, and NVIDIA documents installing it, configuring Prometheus, the command-line reference and the metric list. DCGM also publishes C, C++ and Go interfaces plus command-line tools such as dcgmi and nv-hostengine.
Fits GPU platform teams that already run Prometheus and want board power draw and cumulative energy counters from NVIDIA data-center accelerators, with a Helm chart, dashboards and documented metric names to scrape. The trade-off is scope and attribution: it supplies GPU telemetry from NVIDIA's own stack, so per-process or per-tenant attribution and any carbon conversion sit outside it, and it covers NVIDIA accelerators only. Health checks and diagnostics come through dcgmi. Teams with mixed-vendor fleets or needing emissions reporting should pair it with other instrumentation.
Written by the GreenAIX editors from the recorded fields above. Vendors do not review or approve verdicts.
AI Energy Monitoring
Open-source tool that tracks and predicts energy use and carbon footprint of model training.
AI Energy Monitoring
Open-source Python library that estimates the carbon emissions of compute.
AI Energy Monitoring
Python library for tracking the CO2 emissions of machine learning models.