Bachelor Thesis BCLR-2021-63

BibliographyKharitenko, Pavel: Coupling Julia-based simulations via preCICE.
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Bachelor Thesis No. 63 (2021).
73 pages, english.
Abstract

The coupling library preCICE allows to couple single-physics solvers to partitioned multi-physics simulations in a black-box fashion. preCICE is a C++ library, but it offers language bindings to access the preCICE API from solvers written in other languages, such as C, Python, Fortran and MATLAB. The Julia Programming Language designed for numerical computing is a strong candidate to be supported by preCICE. While Julia provides a wide set of tools for interfacing with other languages, including C++, porting a library such as preCICE that is made for High Performance Computing and runs on a huge number of processes, requires little to no compromises. Multiple ways of wrapping a C/C++ library are presented and implemented. In addition come Julia’s own features, for example the Distributed base library, that deviate from classic standards of known scientific languages. To test the bindings, two dummy solvers are coupled and presented in an example setup, with an outlook on further development.

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Department(s)University of Stuttgart, Institute of Parallel and Distributed Systems, Simulation of Large Systems
Superviser(s)Uekermann, Jun.-Prof. Benjamin; Desai, Ishaan
Entry dateDecember 22, 2021
   Publ. Computer Science