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

Understand

Deep learning (DL) can achieve impressive results across a wide variety of tasks, but this often comes at the cost of training models for extensive periods on specialized hardware accelerators.

• This energy-intensive workload has seen immense growth in recent years.
• Machine learning (ML) may become a significant contributor to climate change if this exponential trend continues.
• If practitioners are aware of their energy and carbon footprint, then they may actively take steps to reduce it whenever possible.