Research project
Learning From The Past: Making Software Greener and Faster By Mining Past Performance Data
Exploring the application of data-driven AI optimizations, this work leverages past software performance to reduce the carbon footprint and energy consumption of powerful computing applications.
- Duration
- 2026
- Contact
- Ben van Werkhoven
- Funding
- NWO XS
This project aims to make powerful computing applications, like those used in Artificial Intelligence (AI), climate modeling, astronomy, and self-driving cars, run faster and greener. By mining extensive data sets on the specific interactions between software and hardware, the project develops intelligent tools using explainable AI and transfer learning that learn from past software optimizations to improve future software optimization sessions and automatically adjust software to run more efficiently. The result: better performance, lower energy use, and reduced carbon emissions from the world’s fastest computers.