IZ GreenCompute (GreenCompute)
IZ GreenCompute (GreenCompute)
Institution: Humboldt-Universität zu Berlin
Category: Project
Website: https://www.greencompute.hu-berlin.de/de
Short Description
The Interdisciplinary Center GreenCompute conducts research on energy-efficient methods for large-scale data analysis and high-performance computing (HPC) at Humboldt-Universität zu Berlin. The goal is to reduce energy consumption and CO₂ footprint of computing processes without compromising research quality or service performance. Results are provided in the form of technologies, configuration guidelines, and best practices for practical implementation. Universities benefit from more sustainable use of HPC infrastructures and lower operating costs in the long term.
General Description
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Thematic Classification
Subject Areas
- Computer Science
- Physics
- Natural Sciences
- Humanities
- Data Science
- High Performance Computing (HPC)
- Artificial Intelligence (KI)
- Optimization
- Cluster and Data Management
- Energy-Efficient Systems
- Interdisciplinary Research
Research Fields
- Energy-Efficient Artificial Intelligence
- Energy-Efficient Optimization
- Energy-Efficient Cluster/Data Management
- Energy-Efficient Scheduling
Specializations
- Energy-Efficient Artificial Intelligence
- Energy-Efficient Optimization
- Energy-Efficient Cluster/Data Management
- Energy-Efficient Scheduling
- Monitoring of energy consumption
- Development and dissemination of measures
- Community building and strategic development
Keywords
- GreenCompute
- Energy-efficient high-performance computing
- Energy-efficient data analysis
- Research Track
- Transfer Track
- HPC@HU-Services
- Interdisciplinary research
- Reduce CO2 footprint
- Energy consumption measurement
- Energy-saving system configuration
Funding
Funding Provider: -
Funding Program: INSUFFICIENT
Funding Reference: INSUFFICIENT
Funding Period: -
Project Volume: INSUFFICIENT
Team & Partners
Project Leadership
- Prof. Dr. Ulf Leser (Institute of Computer Science, Humboldt-Universität zu Berlin)
- Prof. Dr. Claudia Draxl (Institute of Physics, Humboldt-Universität zu Berlin)
Involved Persons
- Sebastian Tiesler (Coordination, HPC Team, CMS)
Affiliated Institutions
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External Partners
- Berlin University Alliance (BUA)
Project Contents
Goals
- Research and development of energy-efficient methods for large-scale data analysis and High-Performance Computing
- Implementation and introduction of energy-efficient technologies and infrastructures in the HPC domain
- Reduction of energy consumption and CO2 footprint while maintaining high research quality
- Raising user awareness and reducing redundant computing operations
- Coordinated collaboration within Humboldt-Universität and the Berlin University Alliance (BUA)
Work Packages
- Research Track
- Energy-Efficient Artificial Intelligence
- Energy-Efficient Optimization
- Energy-Efficient Cluster/Data Management
- Energy-Efficient Scheduling
- Transfer Track
- Monitoring of energy consumption
- Development and dissemination of measures
- Community building and strategic development
Methods
- Reduction of idle times
- Raising awareness among users
- Reduction of redundant computational operations
- Development and implementation of energy-efficient analysis methods
- Development and implementation of energy-efficient compute units
- Energy-saving configuration of existing systems
- Proper system sizing
- Informed foresight for new systems
- Monitoring of energy consumption
- Development and dissemination of measures
- Community building and strategic development
- Interdisciplinary collaboration between data analysis/HPC experts and researchers from other disciplines
- Research in the following areas:
- Energy-Efficient Artificial Intelligence
- Energy-Efficient Optimization
- Energy-Efficient Cluster/Data Management
- Energy-Efficient Scheduling
Expected Outcomes
- Development and implementation of energy-efficient analysis methods and compute units
- Reduction of idle times in HPC systems
- Energy-saving configuration of existing computing infrastructures
- Optimization of HPC system sizing
- Informed forecasting of future HPC systems with lower energy consumption
- Raising awareness among users about energy-efficient computing
- Reduction of redundant computing operations
- Implementation of research findings into practical technologies and infrastructures
- Strengthening interdisciplinary collaboration between HPC experts and researchers from other disciplines
- Establishment and maintenance of a broad network with institutions dealing with the energy demands of digital research methods
- Monitoring and analysis of energy consumption in HPC systems
- Development and dissemination of energy-saving measures in the field of large-scale data analysis and HPC
Contact
Contact Person: Prof. Dr. Ulf Leser, Prof. Dr. Claudia Draxl, Sebastian Tiesler
Email: iz-greencompute@hu-berlin.de
Project Website: https://www.greencompute.hu-berlin.de/de
Recorded: 2026-01-11
Source: https://www.greencompute.hu-berlin.de/de