# SUSFECIT: Objectives and Concepts

- Institution: CERN
- Speaker: Dwayne Spiteri
- Year: 2026
- Language: English
- Subjects: Mathematics, Business and management
- Source: [CERN](https://videos.cern.ch/record/3025619)
- Licence: [CERN](https://copyright.web.cern)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

Scientific computing contributes significantly to the CO2 footprint created by research conducted in ErUM (Research of Universe and Matter). In order to advance the environmental sustainability in this area the BMFTR—funded SUSFECIT (Sustainable Federated Compute unfrastructures) research network has been established with the goal to contribute to developing a strategy and interlinked software ecosystems to reduce CO2 footprint and to increase the energy efficiency of distributed computing resources. The basic idea is to exploit the dispatchability of compute jobs in space and time and use the partition of a federated computing infrastructure at a place, which at a certain time, is (dominantly) powered by renewable energies such as wind and solar power plants. To realise this basic concept, three interlinked ecosystems are to be developed and optimised: (i) to forecast the available energy mix, power costs and required compute power; (ii) to orchestrate jobs on federated and locally distributed compute clusters, taking the forecasts into account; and (iii) to account for CPU and GPU resources used, in relation to elapsed time, power consumption and CO₂ footprint. A digital twin for the above set of ecosystems shall also be developed in order to optimise e.g. operation parameters. The presentation will discuss the basic concept, the content of the three ecosystems and exploratory work, which has been conducted by partners in the research network (DESY, KIT, Universities in Aachen, Bonn, Göttingen, Freiburg and Öko-Institute).

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## Lectures

1. [SUSFECIT: Objectives and Concepts](https://invisiblenetwork.ai/learn/cern/3025619/935180134d4c), 26 min (CERN's player)