Algorithm for applying the structural adaptation criterion to solve problems using adaptive mesh refinement
Authors
-
Sergey K. Grigoriev
-
Pavel A. Kuchugov
Keywords:
MPI
distributed computing
AMR
buffer layer
octree-mesh
Abstract
Adaptive mesh refinement (AMR) is widely used in solving modern mathematical modeling problems. The specifics of the implementation of numerical methods for AMR require compliance with certain ratios between the linear sizes of adjacent elements, which are called the structural criterion. Structural criterion allows creation of buffer layer of cells between regions, which cell division level difference is greater than two. In this paper we discuss the algorithm for buffer layer generation for tree-based adaptive mesh refinement on distributed computational system. Estimates of the algorithmic complexity and efficiency of the algorithm on distributed computational system are obtained. Experiments have shown the possibility of algorithm for forming a buffer layer in areas of complex shape, but at the same time its poor scalability with an increasing number of processes.
Section
Methods and algorithms of computational mathematics and their applications
References
- Chombo -- Software for Adaptive Solutions of Partial Differential Equations -- Chombo -- Berkeley Lab Commons.
http://chombo.lbl.gov/. Cited September 23, 2025.
- M. Adams, P. Colella, D. T. Graves, J. N. Johnson, N. D. Keen, T. J. Ligocki, et al., “Chombo Software Package for AMR Applications -- Design Document’’, Lawrence Berkeley National Laboratory Technical Report LBNL-6616E, January 9, 2015.
https://escholarship.org/uc/item/5cs5d1sq . Cited September 23, 2025.
- SAMRAI | Computing.
https://computing.llnl.gov/projects/samrai . Cited September 23, 2025.
- R. D. Hornung and S. R. Kohn, “Managing application complexity in the SAMRAI object-oriented framework,” Concurrency and Computat.: Pract. Exper. 14 (5), 347-368 (2002).
doi 10.1002/cpe.652
- W. Zhang, A. Almgren, V. Beckner, J. Bell, et al., “AMReX: a framework for block-structured adaptive mesh refinement,” Journal of Open Source Software 4 (37), 1370. (2019).
doi 10.21105/joss.01370
- M. J. Berger, P. Colella, “Local adaptive mesh refinement for shock hydrodynamics,” Journal of Computational Physics 82, 64-84 (1989).
doi 10.1016/0021-9991(89)90035-1
- C. Burstedde, L. C. Wilcox, and O. Ghattas, “p4est: Scalable Algorithms for Parallel Adaptive Mesh Refinement on Forests of Octrees,” SIAM J. Sci. Comput. 33 (3), 1103-1133 (2011).
doi 10.1137/100791634
- J. Holke, C. Burstedde, D. Knapp, L. Dreyer, S. Elsweijer, V. Ünlü, J. Markert, I. Lilikakis, N. Böing, P. Ponnusamy, A. Basermann, “t8code v. 1.0 -- Modular Adaptive Mesh Refinement in the Exascale Era,” in SIAM International Meshing Round Table. Amsterdam, Niederlande, March 6-9, 2023.
https://internationalmeshingroundtable.com/assets/research-notes/imr31/2017-comp.pdf . Cited September 23, 2025.
- D. Rettenmaier, D. Deising, Y. Ouedraogo, et al., “Load balanced 2D and 3D adaptive mesh refinement in OpenFOAM,” SoftwareX 10, 100317 (2019).
doi 10.1016/j.softx.2019.100317
- O. G. Olkhovskaya, Grid-projection schemes for approximation of the second orderpartial differential equations on irregular computational meshes, Preprint No. 226 (Keldysh Institute of Applied Mathematics, Moscow, 2018)
doi 10.20948/prepr-2018-226 [in Russian].
- G. Karypis, “METIS and ParMETIS,” In: Encyclopedia of Parallel Computing(ed. D. Padua). (Springer US, Boston, MA), pp. 1117-1124.
doi 10.1007/978-0-387-09766-4_500
- B. Hendrickson, T. G. Kolda, “Graph partitioning models for parallel computing,” Parallel Computing 26 (12), 1519-1534 (2000).
doi 10.1016/S0167-8191(00)00048-X
- Institute of Applied Mathematics - V&V_2022_SVI_test_problem.pdf.(Shock wave-vortex interaction: test task for direct numerical simulation methodes) [in Russian].
https://ceaa.imamod.ru/2022/files/V&V_2022_SVI_test_problem.pdf . Cited September 23, 2025.
- V. F. Tishkin, V. V. Nikishin, I. V. Popov, A. P. Favorski, “Finite difference schemes of three-dimensional gas dynamics for the study of Richtmyer-Meshkov instability,” Mat. Model. 7 (5), 15-25 (1995). [in Russian].
- Z. Shen, W. Yan, G. Yuan, “A robust HLLC-type Riemann solver for strong shock,” J. Comput. Phys. 309, 185-206 (2016).
doi 10.1016/j.jcp.2016.01.001
- Center for Collective Use of the Keldysh Institute of Applied Mathematics of the Russian Academy of Sciences. Hybrid supercomputer K60. [in Russian].
https://ckp.kiam.ru . Cited September 23, 2025.