We develop languages for the description of simulation models, e.g., in cell biology or demography. To speed up the execution of simulation models, improved execution algorithms are developed, implemented, and evaluated.

So-called General Purpose Computing on Graphics Processing Units (GPGPU) requires specific programming paradigms to achieve an efficient execution. Specialized GPGPU-subprograms are used to massively speed up algorithms.

Many approaches in modeling and simulation are firmly grounded on mathematical foundations. Such mathematical foundations, e.g., in stochastics/statistics, allow investigating the correctness of simulation algorithms and, based on that, correct extensions and improvements of algorithms.

Modeling and simulation is often applied outside of computer science. For example, we are currently cooperating with scientists from cell biology and demography. These cooperations yield exciting interdisciplinary question, which are addressed jointly with our partners.

In practice, simulation experiments are often only one step in a longer process, which, for example, also includes modeling and pre- and post-processing of data. To support users in this process, smart user interfaces and automation methods are developed.