Fraunhofer Institute for Algorithms and Scientific Computing SCAIThe use and impact of numerical simulation for virtual product development and understanding product properties are continuously growing. More refined methods and software are required to analyze, evaluate and optimize simulation results. SCAI develops new technologies in numerical analysis and in information technology which help reduce the computational time for numerical simulation without sacrificing the detailed modeling and high resolution of the simulation.
The core aspects of research and development are new methods and tools that enable more efficient use of industrial software. This includes the development of highly efficient numerical methods for the optimal and scalable solution of large systems of linear equations.
Recent Publications:
S. Gries: Informed Machine Learning to Maximize Robustness and Computational Performance of Linear Solvers. In: D. Schulz and C. Bauckhage (editors): Informed Machine Learning. Springer Cham, April 2025.
S. Gries, G. Hülsmann: ML-Based Linear Solver Control to Improve the Performance of Groundwarer Simulations, Modflow and More Conference 2024, Princeton University.
S. Gries: Autonomous Solver Control to Improve Performance of Simulations, ECMOR 2022. Vol. 2022. No. 1. European Association of Geoscientists & Engineers, 2022. Link
S. Gries: Algebraic Wavefront Parallelization for ILU(0) Smoothing in Reservoir Simulation, ECMOR XVII. Vol. 2020. No. 1. European Association of Geoscientists & Engineers 2020. Link
B. Metsch, F. Nick, J. Kuhnert: Algebraic multigrid for the finite pointset method. Comput. Visual Sci. 23 (3), 2020.