High-performance computing (HPC) is now one of the fundamental research methods in many scientific disciplines. High-performance computers have been reaching the exaflop performance class (at least 10¹⁸ operations per second) since this year. For applications to efficiently exploit the power of exascale systems, scalability must be improved on very large and heterogeneous systems. A variety of components are required for modern high-performance computing: from processors to data storage and file systems to software and algorithms. All these components also require new technologies and adaptations to specific applications and interfaces.

The IFCES2 project, led by the Leibniz Institute for Tropospheric Research (TROPOS), will develop new methods to optimize the parallel execution of simulation algorithms from the Earth system model ICON on heterogeneous and modular exascale systems. Code parallelism will be improved and methods will be applied to enable better communication between the individual model components as well as dynamic load distribution. The methods will be validated with use cases from cloud microphysics and ocean biogeochemistry. As a result, the necessary prerequisites will be created for the efficient use of modular exascale systems for complex simulations.

The project contributes to increasing the level of detail of the Earth system model ICON and thus to reducing the uncertainties of future climate simulations. In addition to increasing the efficiency of exascale systems, the project results contribute to improved climate simulation and thus to energy savings. The methods developed in the project can also be transferred to other HPC applications.