Data transfer in partitioned multi-physics simulations : interpolation & communication

Abstract

Partitioned multi-physics simulations allow to reuse existing solvers and to combine them to multi-physics scenarios. This provides not only greater flexibility and improved time-to-solution, but also helps to manage the increasing complexity of modern scientific software. This thesis sees itself as a continuation of the works of B. Gatzhammer and B. Uekermann who developed a comprehensive tool to couple independent simulation codes. I focus on the two important aspects of interpolation between non-matching grids as well as communication between several parallel codes and conclude with aspects of software development of the coupling library preCICE. The interpolation part puts special emphasis on radial-basis function interpolation. It starts with a thorough review of existing interpolation methods with special consideration of the black-box approach to multi-physics simulations and explores promising enhancements to RBF interpolation. Numerical experiments provide a rigorous testing for accuracy, stability and scaling behavior of different variants of RBF implementations. Following the insights gained from the numerical experiments, a highly-optimized parallel implementation for preCICE is developed, containing various measures to improve accuracy and stability of the interpolation. The communication part first defines the requirements for partitioned simulations in terms of communication. A new technique for peer-to-peer communication networks between distinct MPI domains is developed and evaluated against existing approaches. Furthermore, a fast method to establish connections via the file system is presented. Both measures optimize the initialization phase and achieve a considerable speedup. Finally, a strategy to fully decouple algorithmically independent participants on the communication protocol level is implemented and tested. In the last part, the software-related challenges in developing a parallel scientific application involving multiple independent solvers are outlined. I show how the preCICE project handles testing, profiling and integration of a large parallel scientific software with multiple participants. A profiling library for distributed applications has been developed and is extensively used in preCICE and potentially other projects.