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Article

Efficient and Scalable Initialization of Partitioned Coupled Simulations with preCICE

1
Institute for Parallel and Distributed Systems (IPVS), University of Stuttgart, 70569 Stuttgart, Germany
2
Scientific Computing in Computer Science, Technical University of Munich (TUM), 85748 Garching, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Julian Kunkel
Algorithms 2021, 14(6), 166; https://doi.org/10.3390/a14060166
Received: 30 April 2021 / Revised: 22 May 2021 / Accepted: 25 May 2021 / Published: 27 May 2021
(This article belongs to the Special Issue High-Performance Computing Algorithms and Their Applications 2021)
preCICE is an open-source library, that provides comprehensive functionality to couple independent parallelized solver codes to establish a partitioned multi-physics multi-code simulation environment. For data communication between the respective executables at runtime, it implements a peer-to-peer concept, which renders the computational cost of the coupling per time step negligible compared to the typical run time of the coupled codes. To initialize the peer-to-peer coupling, the mesh partitions of the respective solvers need to be compared to determine the point-to-point communication channels between the processes of both codes. This initialization effort can become a limiting factor, if we either reach memory limits or if we have to re-initialize communication relations in every time step. In this contribution, we remove two remaining bottlenecks: (i) We base the neighborhood search between mesh entities of two solvers on a tree data structure to avoid quadratic complexity, and (ii) we replace the sequential gather-scatter comparison of both mesh partitions by a two-level approach that first compares bounding boxes around mesh partitions in a sequential manner, subsequently establishes pairwise communication between processes of the two solvers, and finally compares mesh partitions between connected processes in parallel. We show, that the two-level initialization method is fives times faster than the old one-level scheme on 24,567 CPU-cores using a mesh with 628,898 vertices. In addition, the two-level scheme is able to handle much larger computational meshes, since the central mesh communication of the one-level scheme is replaced with a fully point-to-point mesh communication scheme. View Full-Text
Keywords: parallel programming; high performance computing; multi-physics simulation parallel programming; high performance computing; multi-physics simulation
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MDPI and ACS Style

Totounferoush, A.; Simonis, F.; Uekermann, B.; Schulte, M. Efficient and Scalable Initialization of Partitioned Coupled Simulations with preCICE. Algorithms 2021, 14, 166. https://doi.org/10.3390/a14060166

AMA Style

Totounferoush A, Simonis F, Uekermann B, Schulte M. Efficient and Scalable Initialization of Partitioned Coupled Simulations with preCICE. Algorithms. 2021; 14(6):166. https://doi.org/10.3390/a14060166

Chicago/Turabian Style

Totounferoush, Amin, Frédéric Simonis, Benjamin Uekermann, and Miriam Schulte. 2021. "Efficient and Scalable Initialization of Partitioned Coupled Simulations with preCICE" Algorithms 14, no. 6: 166. https://doi.org/10.3390/a14060166

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