The main objective of this project is to build a model and platform for collecting and estimating information of the climate footprint of the HPI Data Center. This will include operational emissions through energy consumption as well as emissions from transport, construction, production, travel, etc. The input data will be stored in a database and the model needs to be adjustable to include new factors that could influence the footprint (e.g., adding solar panels, reusing server heat, or new evaluation of emissions). The project will be built in several phases, similar to the scopes in the greenhouse gas protocol, we start with the direct energy consumption by the servers. The framework should then produce overviews of the daily, monthly, yearly consumption and climate footprint in a dashboard. Furthermore, we want to create updateable reports for compute jobs in the data center to make users aware about the power consumption and climate footprint. The model and framework will be generic to be reusable for other data centers.
During this project, the participants will collaborate with Martin Hüttersen from Hewlett Packard Enterprise and climate researcher Stefan Krottenthaler from University of Passau.
The participants need to have experience in software engineering and at least one programming language (C++, Java, Python). Basic experience in machine learning is beneficial. Participants should be comfortable with documenting their work and visualizing their results. The initial phase of the project will include literature research to find models and estimations for emission calculation.
Please contact Tilmann Rabl (tilmann.rabl(at)hpi.de) for any questions.
3. In Computer Architecture, We Don't Change the Questions, We Change the Answers, Mark D. Hill, Keynote at Data Management on New Hardware (DaMoN) Workshop @ SIGMOD, June 2022. Slides: pdf