Learn more about HLRS's current research projects. You can also jump to past projects.
The 3xa project will develop scalable methods for the simulation of three-body interactions in particle systems, applying vectorized kernels, dynamic load balancing approaches and adaptive resolution schemata.
The AI Alliance Baden-Württemberg aims to develop a data platform for AI-relevant data exchange among academic and industrial stakeholders.
This project coordinates support for HPC users in Baden-Württemberg and the implementation of related measures and activities, including data intensive computing and large-scale scientific data management.
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.
CASTIEL 2 facilitates collaboration among the EuroCC 2 National Competence Centers and the EuroHPC Joint Undertaking Centers of Excellence, promoting the development of HPC expertise and the adoption of leading codes across Europe.
The Center of Excellence in Exascale CFD will improve European state-of-the-art computational fluid dynamics algorithms to prepare them for efficient performance on exascale supercomputers.
Focusing on critical applications for the prediction of geohazards, the Centre of Excellence for Exascale in Solid Earth aims to become a hub for HPC software within the solid earth community.
This study will assess potential applications of high-performance computing (HPC) in crisis situations, and what organizational procedures are needed to ensure that HPC resources are immediately available.
DECICE is developing an open and portable cloud management framework that will enable the automatic and adaptive optimization of software applications for heterogeneous computing architectures.
By presenting exciting, immersive experiences of current engineering topics in virtual reality and augmented reality, DimensionLab3 aims to increase young students' interest in and motivation to study technical subjects.
EE-HPC is testing an approach for improving energy efficiency in HPC systems by automatically regulating system parameters and settings based on current job requirements.
Supported by the EuroHPC Joint Undertaking, EuroCC 2 manages a European network of National Competence Centers (NCC) for high-performance computing and related technologies, promoting a common level of expertise across the participating countries.
The EuroHyPerCon project aims to shape the future of HPC in Europe by defining a long-term hyperconnectivity specification and implementation roadmap to meet Europe's future ultra-high-speed network requirements.
EXCELLERAT P2 is developing advanced applications for engineering in the manufacturing, energy, aeronautics, and automotive sectors, focusing on use cases that demonstrate the importance of HPC, HPDA, and AI for European competitiveness.
The goal of Gaia-X4ICM is to implement a scaling production platform based on the Gaia-X ecosystem for the InnovationCampus Mobility of the Future (ICM) to make Gaia-X more usable for production of planning systems, industrial controls, and sensor data, among other applications.
HANAMI fosters collaboration between Europe and Japan to develop applications for future generations of supercomputers across diverse scientific fields, including environmental sciences, biomedicine, and materials science.
The HiDALGO2 project is addressing challenges caused by climate change, focusing on technical issues related to scalability on HPC and AI infrastructures, the use of computational fluid dynamics methods, and uncertainty analysis.
HPC SPECTRA will promote the development of HPC expertise across Europe by building a comprehensive online platform of training opportunities, making it easy for trainees to find courses that fit their interests and needs.
HLRS is the coordinating center for this project to integrate artificial intelligence (AI) topics into curricula at the University of Stuttgart, and to implement AI technologies to improve instruction.
Inno4scale will identify and provide funding to support the development of advanced algorithms and applications for upcoming European exascale systems.
This project is developing tools for meeting and collaborating from remote locations in three-dimensional virtual reality environments.
This project’s goal is to increase the accuracy and reduce the uncertainty of performance and load assessment tools and associated procedures that are commonly used in the industrial design and certification of modern wind energy systems.
As a participant in the German National Research Data Infrastructure initiative, this consortium is creating a national platform for data integration in catalysis and chemical engineering research.
ORCHESTRA is developing a networked platform for sharing data and for creating a new large-scale, pan-European cohort for research on the SARS-CoV-2 pandemic, providing a model for addressing future public health threats.
S+T+ARTS AIR is making supercomputing technologies and expertise available to enable innovative collaborations involving the arts, science, and technology.
This enrichment program offers school-age students opportunities to develop and execute simulation projects in collaboration with HLRS scientists.
SiVeGCS coordinates and ensures the availability of HPC resources of the Gauss Centre for Supercomputing, addressing issues related to funding, operation, training, and user support across Germany's national HPC infrastructure.
SNuBIC is improving methods for multiphysics simulations of coupled systems, with a focus on improving computational efficiency when simulating interfaces between physical systems.
SRI DiTEnS is developing methods for discursive transformation in local energy systems, using urban digital twins involving virtual reality to support decision making among stakeholders.
targetDART is developing a task-based approach for highly scalable simulation software that mitigates load-imbalance on heterogenous systems through dynamic, adaptive and reactive distribution of computational load across compute resources.
Focusing on a large-scale, high-resolution earth system model, TOPIO is investigating read and write rates for large amounts of data on high-performance file systems, as well as approaches that use compression to reduce the amount of data without causing a significant loss of information.
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.
In the first ever project to connect computers in wind parks with an HPC center, WindHPC aims to reduce energy consumption by improving efficiency in simulation codes, HPC workflows, and data management.
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.
BEAM-ME developed strategies based in applied mathematics and computer science to increase computational performance of energy system models on high-performance computing systems.
The project bwHPC-C5 coordinated support on a federated basis for users of high performance computing (HPC) in the state of Baden-Württemberg and implemented related measures and activities.
bwVisu provided powerful visualization resources to scientific institutions in Baden-Württemberg, including working toward the development of a scalable service for remote visualization of scientific data.
CATALYST researches methods for analyzing large datasets produced by modeling and simulation with the goal of implementing a framework that combines HPC and data analytics.
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.
CoeGSS brings together the power of high-performance computing and some of the most promising thinking on global systems in order to improve decision-making in business, politics and civil society.
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.
DASH aims to ease the efficient programming of future supercomputing systems for data-intensive applications. These systems will be characterized by their extreme scale and a multi-level hierarchical organization.
DEGREE is investigating a method for increasing energy efficiency in data centers by dynamically controlling cooling circuit temperatures, and is developing guidelines for implementing the resulting concepts.
This federally funded project is researching possibilities of efficient data management with regard to high amounts of scientific data emerging from the programs of engineering science at the University of Stuttgart.
The ENRICH project will analyze current developments in IT and the operation of high-performance computing (HPC) centers regarding their resource efficiency and sustainability potential.
EOPEN aims to tackle the technical barriers arising from the massive streams of Earth observation data to ensure scalability of the data harmonization, standardization, fusion, and exchange methods.
Eurolab4HPC2 worked to promote the consolidation of European research excellence in exascale HPC systems.
EUXDAT is a Horizon 2020 project building an e-infrastructure addressing agriculture, land monitoring, and energy efficiency for sustainable development.
The main goal of ExaFLOW is to address key algorithmic challenges in CFD (Computational Fluid Dynamics) to enable simulation at exascale, guided by a number of use cases of industrial relevance, and to provide open-source pilot implementations.
exaFOAM is working to reduce bottlenecks in performance scaling for computational fluid dynamics (CFD) applications on massively parallel high-performance computing (HPC) systems.
Today, exascale computers are characterized by billion-way parallelism. Computing on such extreme scale requires methods that scale perfectly and have optimal complexity. This project brings together several crucial aspects of extreme scale solving.
The objective of this European training network for mechanical and computer science engineers is to develop advanced tools for analyzing fluid dynamics in large-scale models of turbine components and to eventually enable the virtual testing of an entire machine.
FF4EuroHPC conducts outreach and provides support to Europe's small and medium-sized enterprises (SMEs) to enable them to profit from the advantages for innovation offered by high-performance computing technologies and services.
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.
The importance of advanced simulation to the competitiveness of both large and small companies is well established. The principal objective of Fortissimo is to enable European manufacturing, particularly small to medium enterprises (SMEs), to benefit from the efficiency and competitive advantage inherent in the use of simulation.
The FORTISSIMO 2 project targets the adoption of advanced simulation in small and medium-sized companies, realizing a “one-stop-shop” to enable state-of-the-art hardware access, expertise, applications, visualization and tools in an efficient fashion.
HPC Europa 3 fosters transnational cooperation among EU scientists (especially junior researchers) who work on HPC-related topics such as applications, tools, and middleware.
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.
This project aims to develop and operationalize new prediction products for the integration of photovoltaics (PV) into the energy market and smart grids by delivering simulations of PV power output at high resolution.
InHPC-DE furthers the federation of the three national HPC centres in Germany, addresses new requirements such as security, and evaluates the Gaia-X ecosystem in the context of high-performance computing.
The MoeWe project developed the Supercomputing-Akademie, a training program in high-performance computing that is conceived to address the unique needs of researchers and IT professionals in industry.
The Mont-Blanc project aims to design a new type of computer architecture capable of setting future HPC standards, built from energy-efficient solutions used in embedded and mobile devices.
HLRS is developing approaches for combining freely available data and supercomputing resources to create a new generation of searchable data products for European citizens, public authorities, economic operators, and decision makers.
This project is testing a novel, simulation-based approach to develop new systems for protecting vehicle occupants in accidents.
The project aims to address the challenges of energy-efficient parallel infrastructure development based on acceleratable heterogeneous hardware such as GPU, CPU, and FPGA in domains like cyber-physical systems, Internet of Things, or high-performance computing.
This Centre of Excellence in Computing Applications offers the service of precisely assessing the performance of computing applications, identifying issues that affect code performance and the best way to alleviate them.
This Center of Excellence in Computing Applications provides performance optimization and productivity services for academic and industrial users of high-performance computing.
The Partnership for Advanced Computing in Europe supports high-impact scientific discovery and engineering R&D to enhance European competitiveness for the benefit of society.
The project Reallabor Stadtquartiere 4.0 explored new methods and technologies to support participatory planning for sustainable development.
The Science Data Center for Literature is an interdisciplinary research project to sustainably organize the data life cycle in digital literature.
The SEQUOIA End-to-End project aims to develop transparent, automated, and controllable end-to-end solutions for the industrial use of hybrid quantum applications and algorithms through holistic quantum software engineering.
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.
This interdisciplinary Excellence Cluster at the University of Stuttgart is developing simulation technologies to enable integrative systems science.
The project aims to provide an optimized, resilient, heterogeneous execution environment that enables operational transparency between cloud and HPC infrastructures.
Motivated by the sustainability strategy, green IT strategy, and HPC strategy of the state of Baden-Württemberg, this project investigated how principles of sustainability could be applied to the High-Performance Computing Center Stuttgart (HLRS).
The project TaLPas (Task-basierte Lastverteilung und Auto-Tuning in der Partikelsimulation) targets an auto-tuning, task-based approach to high-performance particle simulations.
