Dynamic HPC software frameworks: Seamless integration of existing simulation frameworks and code generation techniques

• Applicants: Professor Dr.-Ing. Harald Köstler; Professor Dr. Ulrich Rüde
• Subject Area: Data Management, Data-Intensive Systems, Computer Science Methods in Business Informatics ; Software Engineering and Programming Languages
• Term: from 2020 to 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 433735254

Complex phenomena in the natural and the engineering sciences are increasingly being studied with the help of simulation techniques. This is facilitated by a dramatic increase of the available computational power, and Computational Science and Engineering (CSE) is emerging as a third fundamental pillar of science. CSE aims at designing,analyzing, and implementing new simulation methods on high-performance computing(HPC) systems such that they can be employed in a robust, user-friendly, and reliable fashion to a wide variety of scientific and engineering problems. Considering the high cost of supercomputing, reaching the best possible computational efficiency becomes a primary criterion and is central to the research agenda of CSE. Furthermore, HPC software must support a range of increasingly complex applications on modern heterogeneous and volatile hardware platforms, where often many different algorithms are combined to model interacting physical processes. For that HPC software has often to be modified extensively to make full use of the additional performance of newly released architectures. Our main goal is to provide a new class of dynamic software frameworks to the HPC users that combine existing and established HPC frameworks with current code generation technology to increase the productivity when introducing new applications or porting to new platforms. We will show the benefits of this approach for three real-world multi-physics applications, optimization of wind turbines and wind farms, formation and dynamics of dunes that occur in many environmental systems such as riverbeds, and simulation of charged particles in microfluidic flows.

• DFG Programme: Research Grants