Program Organization

Topic 1 creates added value for science, technology and society from big and heterogeneous scientific data, data-driven modeling and complex theories, using research data management, data infrastructures, scalable algorithms towards exascale, machine learning and data analytics, and including new computing technologies such as quantum and neuromorphic computing.

Photo by Jack Moreh from Freerange Stock.

Our focus:

A prime objective of Topic 1 is to achieve profound competence in the management and analytics of very large, often heterogeneous data sets as well as the most complex (data-driven) models and theories through research on and application of state of the art research data management procedures, data analytics workflows, advanced machine learning and AI methods.

Another core objective is to research and develop scalable advanced simulation algorithms and tools for the latest high-end modular supercomputers approaching exascale that allow to integrate emerging disruptive computing technologies (see Topic 2), such as quantum computers and quantum annealers as well as neuromorphic computers.

In order to realize these objectives, it is essential that research is interdisciplinary and that computer science and various different subject areas, each having their own scientific challenges, work together. A further central and binding objective involves research on cross-domain generic activities and mathematics. This ensures synergy and knowledge transfer between the different application areas aiming to use data analytics systems and supercomputers.

Speaker of the topic: Kristel Michielsen (FZJ)

Topic 2 develops, procures, operates, maintains and supports simulation and data analytics infrastructures from the co-design of exascale-enabled technology up to the integration of quantum computing architectures and future neuromorphic systems to realize the vision of future hybrid supercomputing.

Copyright: Sascha Kreklau / Forschungszentrum Jülich

Topic 2 hosts and offers leading HPC systems, which are key instruments to target today’s scientific and societal challenges, to the wider scientific community. It focuses on three main topics. The first one is the provision and operation of a cutting-edge simulation and data analytics infrastructure; the second one is the codesign of exascale-capable modular supercomputing systems, in which neuromorphic and quantum computing devices are integrated; and the third one is the federation of the mentioned infrastructure at national and European level.

The HPC infrastructure relies on the Modular Supercomputing Architecture (MSA) to integrate heterogeneous compute resources in the most efficient manner and match the needs of a very diverse portfolio of scientific applications. High-end processing and memory technologies traditionally used in HPC are combined with disruptive technologies that enable acceleration of specific application parts. For example, quantum computers have the potential to solve in much faster and more energy efficient manner multi-dimensional optimization problems, while neuromorphic devices can quickly train neural networks within deep-learning applications. Integrating these devices in HPC systems facilitates their adoption, and prepares more applications to run on future hybrid systems.

Speaker of the topic: Estela Suarez (FZJ)

Topic 3 focuses on engineering secure systems for critical infrastructures. Its research ranges from methodology, e.g., the quantification of security, to the security of concrete applications.

Photo by Buffik on Pixabay

All innovative scenarios in the societally important fields energy supply, mobility, and production share the following three properties: (i) they are realized through the massive use of IT, driven by software-based functionalities, (ii) they are assumed to work securely and dependably, and (iii) they collect vast amounts of data related to individuals. As a consequence, there is a need for methods to engineer secure software-intensive systems.

Engineering in the context of Topic 3 refers to systematically achieving working solutions that are not only secure (in the view of this Topic security also includes privacy and safety), but also yield guaranteed quality properties (e.g., performance, dependability, usability, and also costs) and achieve the best possible trade-offs between conflicting goals regarding different quality properties as well as societal aspects.

The ambitious key objective of Topic 3 is therefore the quantification of security and its application to engineering secure software-intensive systems, particularly in energy, mobility, and production systems.

Speaker of the topic: Jörn Müller-Quade (KIT)

Topic 4 addresses digitization as a technoscientific and social phenomenon and aims to better understand the interactions between technological and social change in this field in order to create a knowledge base that helps innovation actors to shape the digital transformation.

Photo by S. Hermann / F. Richter on Pixabay

New information technologies open numerous new possibilities in almost every aspect of modern society. However, they have also created new challenges: E.g., the high dependence on digital information and communication technologies in infrastructures, such as the energy supply system, the mobility system, or information processing and storage capacities in many fields may create new threats to security and privacy. Furthermore, the whole transformation processes may have huge implications for employment, inclusion, and distributive justice, which could develop into causes for future social conflicts.

Research in this topic is therefore rooted in the fundamental recognition that technology and society mutually influence each other. It aims to enhance our understanding of this coevolution process, and to contribute to shaping the advance of digitalization and the digital transformation, and making use of its outcomes with respect to social needs, expectations and ethical values.

Speaker of the topic: Armin Grunwald (KIT)

Program Organization