Project overview

Ongoing Projects

bwHPC-S5: Scientific Simulation and Storage Support Services Phase 3

Contact: Dr. Robert Barthel
Funding: MWK
Runtime: 2023-11-01 - 2026-01-31
Project page: https://www.bwhpc.de

Zusammen mit den gewonnenen Erkenntnissen, Bewertungen und Empfehlungen sollen die aktuellen Herausforderungen und definierten Handlungsfelder des Rahmenkonzepts der Universitäten des Landes Baden-Württemberg für das HPC und DIC im Zeitraum 2025 bis 2032 durch folgende Maßnahmen im Projekt konkretisiert werden: • Weiterentwicklung der Wissenschaftsunterstützung bzgl. Kompetenzen zur Unterstützung neuartiger System- und Methodekonzepte (KI, ML oder Quantencomputing), Vernetzung mit Methodenfor- schung, ganzheitliche Bedarfsanalysen und Unterstützungsstrategien (z.B. Onboarding) • Steigerung der Energieeffizienz durch Sensibilisierung sowie Untersuchung und Einsatz neuer Be- triebsmodelle und Workflows inkl. optimierter Software • Erprobung und flexible Integration neuer Systemkomponenten und -architekturen, Ressourcen (z.B. Cloud) sowie Virtualisierung- und Containerisierungslösungen • Umsetzung neue Software-Strategien (z.B. Nachhaltigkeit und Entwicklungsprozesse) • Ausbau der Funktionalitäten der baden-württembergischen Datenföderation (z.B. Daten-Transfer- Service) • Umsetzung von Konzepten beim Umgang mit sensiblen Daten und zur Ausprägung einer digitalen Souveränität • Vernetzung und Kooperation mit anderen Forschungsinfrastrukturen

Development and validation of a hybrid grid/particle method for turbulent flows supported by high performance computations with OpenFOAM

Contact: Dr. Jordan Denev
Funding: NHR
Runtime: 2022-06-15 - 2025-06-14
Project page: scc.kit.edu/forschung/14972.php

The main goal of the present project is the further development and validation of a new computational fluid dynamics (CFD) method using a combination of grid-free (particles) and grid-based techniques. A fundamental assumption of this novel approach is the decomposition of any physical quantity into the grid based (large scale) and the fine scale parts, whereas large scales are resolved on the grid and fine scales are represented by particles. Dynamics of large and fine scales is calculated from two coupled transport equations one of which is solved on the grid whereas the second one utilizes the Lagrangian grid free Vortex Particle Method (VPM).

InterTwin

Contact: Dr. Marcus Hardt
Funding: EU
Runtime: 2022-06-01 - 2025-06-30
Project page: InterTwin.eu

InterTwin co-designs and implements the prototype of an interdisciplinary Digital Twin Engine (DTE), an open source platform that provides generic and tailored software components for modelling and simulation to integrate application- specific Digital Twins (DTs). Its specifications and implementation are based on a co-designed conceptual model - the DTE blueprint architecture - guided by the principles of open standards and interoperability. The ambition is to develop a common approach to the implementation of DTs that is applicable across the whole spectrum of scientific disciplines and beyond to facilitate developments and collaboration.

Numerical modeling of cardiac electrophysiology at the cellular scale

Contact: Prof. Dr. Hartwig Anzt
Funding: BMBF / EU
Runtime: 2021-04-01 - 2024-10-01
Project page: microcard.eu

Cardiovascular diseases are among the most common causes of death worldwide: Every year, more than 300,000 people die in Germany as a result. Around half of these deaths are caused by cardiac arrhythmias. In the European MICROCARD project, in which the Karlsruhe Institute of Technology (KIT) is involved, researchers are now developing a simulation platform that can digitally map the electrophysical signal transmissions in the heart. The computer simulations are to contribute in particular to improved diagnosis and therapy. KIT will receive about 1.3 million euros for its contributions within the framework of the "European High-Performance Computing Joint Undertaking".

HAICORE

Contact: Dr. Markus Götz
Funding: Helmholtz-Gemeinschaft
Runtime: 2020-02-01 - 2025-01-01
Project page: www.helmholtz.ai/themenmenue/you-helmholtz-ai/computing-resources

The Helmholtz AI COmpute REssources (HAICORE) infrastructure project was launched in early 2020 as part of the Helmholtz Incubator "Information & Data Science" to provide high-performance computing resources for artificial intelligence (AI) researchers in the Helmholtz Association. Technically, the AI hardware is operated as part of the high-performance computing systems JUWELS (Julich Supercomputing Centre) and HoreKa (KIT) at the two centers. The SCC primarily covers prototypical development operations in which new approaches, models and methods can be developed and tested. HAICORE is open to all members of the Helmholtz Association in the field of AI research.

Helmholtz AI

Contact: Dr. Markus Götz
Funding: Helmholtz-Gemeinschaft
Runtime: 2019-04-01 - 1970-01-01
Project page: www.helmholtz.ai

The Helmholtz AI Platform is a research project of the Helmholtz Incubator "Information & Data Science". The overall mission of the platform is the "democratization of AI for a data-driven future" and aims at making AI algorithms and approaches available to a broad user group in an easy-to-use and resource-efficient way. (Translated with DeepL.com)

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Simulated worlds

Contact: Prof. Dr. Martin Frank
Funding: MWK
Runtime: 2018-07-01 - 2024-08-31
Project page: simulierte-welten.de

The Simulated Worlds project aims to provide students in Baden-Württemberg with a deeper critical understanding of the possibilities and limitations of computer simulations. The project is jointly supported by the Scientific Computing Center (SCC), the High Performance Computing Center Stuttgart (HLRS) and the University of Ulm and is already working with several schools in Baden-Württemberg.

Computational and Mathematical Modeling Program

Contact: Prof. Dr. Martin Frank
Funding: MWK
Runtime: 2015-01-01 - 2024-08-31
Project page: forschung/CAMMP

CAMMP stands for Computational and Mathematical Modeling Program. It is an extracurricular offer of KIT for students of different ages. We want to make the public aware of the social importance of mathematics and simulation sciences. For this purpose, students actively engage in problem solving with the help of mathematical modeling and computer use in various event formats together with teachers. In doing so, they explore real problems from everyday life, industry or research.

Finished Projects

A new TEstbed for Exploring Machine LEarning in Atmospheric Prediction

Contact: Dr. Jörg Meyer
Funding: KIT-Exzellenzinitiative
Runtime: 2021-09-01 - 2023-08-30
Project page: www.imk-tro.kit.edu/5877_11188.php

Despite steady improvements in numerical weather prediction models, they still exhibit systematic errors caused by simplified representations of physical processes, assumptions about linear behavior, and the challenges of integrating all available observational data. Weather services around the world now recognize that addressing these shortcomings through the use of artificial intelligence (AI) could revolutionize the discipline in the coming decades. This will require a fundamental shift in thinking that integrates meteorology much more closely with mathematics and computer science. TEEMLEAP will foster this cultural change through a collaboration of scientists from the KIT Climate and Environment and MathSEE centers by establishing an idealized testbed to explore machine learning in weather forecasting. In contrast to weather services, which naturally focus on improvements of numerical forecast models in their full complexity, TEEMLEAP intends to evaluate the application possibilities and benefits of AI in this testbed along the entire process chain of weather forecasting.

bwHPC-S5: Scientific Simulation and Storage Support Services

Contact: Dr. Robert Barthel
Funding: MWK
Runtime: 2021-04-01 - 2023-10-31
Project page: www.bwhpc.de

The primary objective of the project is to establish an integrated nationwide computing and data infrastructure and to increase efficiency and effectiveness by providing first-class support to scientists and users.

Exascale Earth System Modeling

Contact: Dr. Jörg Meyer, Dr. Ole Kirner
Funding: Helmholtz-Gemeinschaft
Runtime: 2019-10-01 - 2021-09-01

The Exascale Earth System Modelling (PL-ExaESM) pilot lab explores specific concepts for applying Earth System models and their workflows to future exascale supercomputers.

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RTG 2450 - Taylored Scale-Bridging Approaches to Computational Nanoscience

Runtime: 2019-04-01 - 2023-09-30
Project page: www.compnano.kit.edu

In the Research Training Group Tailored Scale-Bridging Approaches to Computational Nanoscience we investigate problems, that are not tractable by computational chemistry standard tools. The research is organized in seven projects. Five projects address scientific challenges such as friction, materials aging, material design and biological function. In two further projects, new methods and tools in mathematics and computer science are developed and provided for the special requirements of these applications. The SCC is involved in projects P4. P5 and P6.

Numerische Simulation von Schwerinonenstrahlen mittels Minimum-Entropie-Rekonstruktion

Runtime: 2017-09-01 - 2020-12-31

Ziel des Projekts ist die Entwicklung von neuen Werkzeugen zur Simulation von Schwerionenstrahlen in Targets. Wir möchten die Orts- und Energieverteilung aller Primär- und Sekundärteilchen charakterisieren. Dies ist von Interesse in vielen Feldern: Atomphysik (atomare Wechselwirkung, Ioneneinfang), Kernphysik (Untersuchung der Struktur von Atomkernen), Elektronik (Ablagerung von Elementen), Materialwissenschaften (Analyse von Beschädigungen z.B. eines Tokamaks), Biologie (Untersuchung der Toxikologie von Gewebe durch Ionenanalyse). Die Simulation von schweren Ionen ist schwierig aus zwei Gründen: Zum einen ist die gitterbasierte Simulation von Teilchentransport sehr herausfordernd. Zum anderen basieren die Simulationen auf Messungen der Bremsvermögen der Ionen, und müssen daher als unsicher angesehen werden. Daher entwickeln wir ein neues, Entropie-basiertes Diskretisierungsschema, welches eine Sub-Auflösung unterhalb des numerischen Gitters ermöglicht, und daher geeignet für die Simulation von Strahlen ist. Zusätzlich benutzen wir eine ähnliche Methode zur Behandlung von Unsicherheiten in der Teilchenverteilung, die durch die unsicheren Wirkungsquerschnitte bedingt werden. Unsere Methode ist rechenaufwändig, aber hochgradig parallelisierbar, was sie ideal für moderne Rechnerarchitekturen macht.

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Non-Destructive Analysis of Environmental Samples

Runtime: 2016-11-15 - 2020-12-31
Project page: www.nuclear-training.de/forschungsprojekte-details/zebra.html

Development of an innovative measurement system based on P&DGNAA technology for environmental analysis including new evaluation algorithms.

ADA-FS - Advanced Data Placement via Ad-hoc File Systems at Extreme Scales

Runtime: 2016-04-01 - 2019-03-31

Future exascale HPC systems require efficient data management methods. The locality of data and the efficient access during a simulation are of great importance.

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Smart Data Innovation Lab (SDIL)

Contact: Andreas Petzold
Funding: MWK
Runtime: 2015-09-01 - 2018-08-31
Project page: www.sdil.de

The Scientific Computing Center (SCC) operates the research platform Smart Data Innovation Lab (SDIL) at KIT. SDIL creates the conditions for cutting-edge research in the field of Big Data ...

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