Multidisciplinary research led by the HLRS Department of Philosophy of Computational Sciences is developing perspectives for assessing the trustworthiness of computational science and limiting the spread of misinformation.
By combining machine learning, sensor technology, network analysis and virtual reality in digital twins, HLRS is developing planning and decision support tools for conflict analysis and reduction between cyclists and pedestrians.
SERRANO aims to introduce a novel ecosystem of cloud-based technologies, from specialized hardware resources to software toolsets, to enable application-specific service instantiation and optimal customization.
aqua3S is developing a new system for detecting threats in drinking water safety and security, combining data from state-of-the-art sensors and other detection mechanisms.
This interdisciplinary Excellence Cluster at the University of Stuttgart is developing simulation technologies to enable integrative systems science.
This consortium of academic institutes, HPC centers, and industrial partners in Europe and Brazil is developing novel algorithms and state-of-the-art codes to support the development of more efficient technologies for wind power.
The Science Data Center for Literature is an interdisciplinary research project to sustainably organize the data life cycle in digital literature.
The project aims to provide an optimized, resilient, heterogeneous execution environment that enables operational transparency between cloud and HPC infrastructures.
CYBELE is integrating tools from high-performance computing, high-performance data analytics, and cloud computing to support the development of more productive, data driven methods for increasing agricultural productivity and reducing food scarcity.
This project coordinates strategic collaboration and outreach among EU-funded Centres of Excellence to more efficiently exploit the benefits of extreme scale applications for addressing scientific, industrial, or societal challenges.
This Center of Excellence in Computing Applications provides performance optimization and productivity services for academic and industrial users of high-performance computing.
ChEESE developed European flagship codes for upcoming pre-exascale and exascale supercomputing systems, focusing on Earth science fields such as computational seismology, magnetohydrodynamics, physical volcanology, tsunamis, and earthquake monitoring.
