Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models

The power and energy monitoring in carbontracker is limited to a few main components of computational systems. Additional power consumed by the supporting infrastructure, such as that used for cooling or power delivery, is accounted for by multiplying the measured power by the pue of the data center hosting the compute, as suggested by Strubell2019. Previous research has examined pue and its shortcomings (Yuventi2013). These shortcomings may largely be resolved by data centers reporting an average pue instead of a minimum observed value. In our work, we use a pue of 1.58, the global average for data centers in 2018 as reported by Ascierto2018.222Early