Extreme-scale block-structured adaptive mesh refinement. (English) Zbl 06890193


65Y05 Parallel numerical computation
65Y20 Complexity and performance of numerical algorithms
76P05 Rarefied gas flows, Boltzmann equation in fluid mechanics
Full Text: DOI arXiv


[1] M. Adams, P. Colella, D. T. Graves, J. N. Johnson, H. S. Johansen, N. D. Keen, T. J. Ligocki, D. F. Martin, P. W. McCorquodale, D. Modiano, P. O. Schwartz, T. D. Sternberg, and B. V. Straalen, Chombo Software Package for AMR Applications – Design Document, Tech. Report, Lawrence Berkeley National Laboratory, 2015.
[2] C. K. Aidun and J. R. Clausen, Lattice-Boltzmann method for complex flows, in Annual Review of Fluid Mechanics, Annu. Rev. Fluid Mech. 42, Annual Reviews, 2010, pp. 439–472, . · Zbl 1345.76087
[3] D. Bartuschat and U. Rüde, Parallel multiphysics simulations of charged particles in microfluidic flows, J. Comput. Sci., 8 (2015), pp. 1–19, .
[4] S. Becker, S. Kniesburges, S. Müller, A. Delgado, G. Link, M. Kaltenbacher, and M. Döllinger, Flow-structure-acoustic interaction in a human voice model, J. Acoust. Soc. Amer., 125 (2009), pp. 1351–1361, .
[5] J. E. Boillat, Load balancing and Poisson equation in a graph, Concurr. Comp.-Pract. E., 2 (1990), pp. 289–313, .
[6] E. G. Boman, U. V. Catalyurek, C. Chevalier, and K. D. Devine, The Zoltan and Isorropia parallel toolkits for combinatorial scientific computing: Partitioning, ordering, and coloring, Sci. Program., 20 (2012), pp. 129–150, .
[7] Boost \CPP libraries, (accessed 2018-04-15).
[8] J. Bordner and M. L. Norman, Enzo-P / Cello: Scalable adaptive mesh refinement for astrophysics and cosmology, in Proceedings of the Extreme Scaling Workshop, BW-XSEDE ’12, University of Illinois at Urbana-Champaign, 2012, pp. 4:1–4:11.
[9] BoxLib, (accessed 2017-08-31).
[10] G. L. Bryan, M. L. Norman, B. W. O’Shea, T. Abel, J. H. Wise, M. J. Turk, D. R. Reynolds, D. C. Collins, P. Wang, S. W. Skillman, B. Smith, R. P. Harkness, J. Bordner, J. Kim, M. Kuhlen, H. Xu, N. Goldbaum, C. Hummels, A. G. Kritsuk, E. Tasker, S. Skory, C. M. Simpson, O. Hahn, J. S. Oishi, G. C. So, F. Zhao, R. Cen, and Y. Li, ENZO: An adaptive mesh refinement code for astrophysics, Astrophys. J. Suppl. S., 211 (2014), 19, .
[11] H.-J. Bungartz, M. Mehl, T. Neckel, and T. Weinzierl, The PDE framework Peano applied to fluid dynamics: An efficient implementation of a parallel multiscale fluid dynamics solver on octree-like adaptive Cartesian grids, Comput. Mech., 46 (2010), pp. 103–114, . · Zbl 1301.76056
[12] C. Burstedde, D. Calhoun, K. Mandli, and A. R. Terrel, ForestClaw: Hybrid forest-of-octrees AMR for hyperbolic conservation laws, Adv. Parallel Comput., 25 (2014), pp. 253–262, .
[13] 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 (2011), pp. 1103–1133, . · Zbl 1230.65106
[14] Cactus, (accessed 2018-04-15). · Zbl 1051.83539
[15] P. M. Campbell, K. D. Devine, J. E. Flaherty, L. G. Gervasio, and J. D. Teresco, Dynamic Octree Load Balancing Using Space-Filling Curves, Tech. Report CS-03-01, Williams College Department of Computer Science, 2003.
[16] Carpet, (accessed 2018-04-15). · Zbl 1010.60075
[17] H. Chen, O. Filippova, J. Hoch, K. Molvig, R. Shock, C. Teixeira, and R. Zhang, Grid refinement in lattice Boltzmann methods based on volumetric formulation, Phys. A, 362 (2006), pp. 158–167, .
[18] S. Chen and G. D. Doolen, Lattice Boltzmann method for fluid flows, in Annual Review of Fluid Mechanics, Annu. Rev. Fluid Mech. 30, Annual Reviews, 1998, pp. 329–364, .
[19] C. Chevalier and F. Pellegrini, PT-Scotch: A tool for efficient parallel graph ordering, Parallel Comput., 34 (2008), pp. 318–331, .
[20] G. Cybenko, Dynamic load balancing for distributed memory multiprocessors, J. Parallel Distrib. Comput., 7 (1989), pp. 279–301, .
[21] J.-C. Desplat, I. Pagonabarraga, and P. Bladon, LUDWIG: A parallel Lattice-Boltzmann code for complex fluids, Comput. Phys. Commun., 134 (2001), pp. 273–290, . · Zbl 1032.76055
[22] A. Dubey, A. Almgren, J. Bell, M. Berzins, S. Brandt, G. Bryan, P. Colella, D. Graves, M. Lijewski, F. Löffler, B. O’Shea, E. Schnetter, B. V. Straalen, and K. Weide, A survey of high level frameworks in block-structured adaptive mesh refinement packages, J. Parallel Distrib. Comput., 74 (2014), pp. 3217–3227, .
[23] A. Dubey, K. Antypas, M. K. Ganapathy, L. B. Reid, K. Riley, D. Sheeler, A. Siegel, and K. Weide, Extensible component-based architecture for FLASH, a massively parallel, multiphysics simulation code, Parallel Comput., 35 (2009), pp. 512–522, .
[24] Enzo-P/Cello, (accessed 2018-04-15).
[25] A. Fakhari, M. Geier, and T. Lee, A mass-conserving lattice Boltzmann method with dynamic grid refinement for immiscible two-phase flows, J. Comput. Phys., 315 (2016), pp. 434–457, . · Zbl 1349.76678
[26] A. Fakhari and T. Lee, Finite-difference lattice Boltzmann method with a block-structured adaptive-mesh-refinement technique, Phys. Rev. E (3), 89 (2014), 033310, .
[27] J. Fietz, M. J. Krause, C. Schulz, P. Sanders, and V. Heuveline, Optimized hybrid parallel lattice Boltzmann fluid flow simulations on complex geometries, in Euro-Par 2012 Parallel Processing, Springer, 2012, pp. 818–829, .
[28] FLASH, (accessed 2018-04-15). · Zbl 1321.94065
[29] S. Freudiger, J. Hegewald, and M. Krafczyk, A parallelisation concept for a multi-physics lattice Boltzmann prototype based on hierarchical grids, Progr. Comput. Fluid Dynam., 8 (2008), pp. 168–178, . · Zbl 1388.76289
[30] C. Godenschwager, F. Schornbaum, M. Bauer, H. Köstler, and U. Rüde, A framework for hybrid parallel flow simulations with a trillion cells in complex geometries, in Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, SC ’13, ACM, 2013, pp. 35:1–35:12, .
[31] T. Goodale, G. Allen, G. Lanfermann, J. Massó, T. Radke, E. Seidel, and J. Shalf, The Cactus framework and toolkit: Design and applications, in Vector and Parallel Processing – VECPAR’2002, 5th International Conference, Lecture Notes in Comput. Sci. 2565, Springer, 2003, . · Zbl 1027.65524
[32] J. Götz, K. Iglberger, M. Stürmer, and U. Rüde, Direct numerical simulation of particulate flows on 294912 processor cores, in Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, IEEE Computer Society, 2010, pp. 1–11, .
[33] D. Groen, O. Henrich, F. Janoschek, P. Coveney, and J. Harting, Lattice-Boltzmann methods in fluid dynamics: Turbulence and complex colloidal fluids, in Juelich Blue Gene/P Extreme Scaling Workshop 2011, Juelich Supercomputing Centre, 2011.
[34] D. Groen, J. Hetherington, H. B. Carver, R. W. Nash, M. O. Bernabeu, and P. V. Coveney, Analysing and modelling the performance of the HemeLB lattice-Boltzmann simulation environment, J. Comput. Sci., 4 (2013), pp. 412–422, .
[35] M. Hasert, K. Masilamani, S. Zimny, H. Klimach, J. Qi, J. Bernsdorf, and S. Roller, Complex fluid simulations with the parallel tree-based Lattice Boltzmann solver Musubi, J. Comput. Sci., 5 (2014), pp. 784–794, .
[36] V. Heuveline and J. Latt, The OpenLB project: An open source and object oriented implementation of lattice Boltzmann methods, Int. J. Mod. Phys. C, 18 (2007), pp. 627–634, . · Zbl 1388.76293
[37] D. Hilbert, Ueber die stetige Abbildung einer Linie auf ein Flächenstück, Math. Ann., 38 (1891), pp. 459–460. · JFM 23.0422.01
[38] L. V. Kale and G. Zheng, Charm++ and AMPI: Adaptive runtime strategies via migratable objects, in Advanced Computational Infrastructures for Parallel and Distributed Adaptive Applications, John Wiley & Sons, 2009, pp. 265–282, .
[39] D. Lagrava, O. Malaspinas, J. Latt, and B. Chopard, Advances in multi-domain lattice Boltzmann grid refinement, J. Comput. Phys., 231 (2012), pp. 4808–4822, . · Zbl 1246.76131
[40] M. Lahnert, C. Burstedde, C. Holm, M. Mehl, G. Rempfer, and F. Weik, Towards lattice-Boltzmann on dynamically adaptive grids – minimally-invasive grid exchange in ESPResSo, in Proceedings of the ECCOMAS Congress 2016, VII European Congress on Computational Methods in Applied Sciences and Engineering, 2016, pp. 1–25.
[41] LB3D, (accessed 2018-04-15).
[42] P. MacNeice, K. M. Olson, C. Mobarry, R. de Fainchtein, and C. Packer, PARAMESH: A parallel adaptive mesh refinement community toolkit, Comput. Phys. Commun., 126 (2000), pp. 330–354, . · Zbl 0953.65088
[43] R. C. Martin, The open-closed principle, C++ Report, 1996.
[44] M. Mehl, T. Neckel, and P. Neumann, Navier-Stokes and Lattice-Boltzmann on octree-like grids in the Peano framework, Internat. J. Numer. Methods Fluids, 65 (2011), pp. 67–86, . · Zbl 1427.76188
[45] B. Meyer, Object-Oriented Software Construction, Prentice–Hall, 1988.
[46] G. M. Morton, A Computer Oriented Geodetic Data Base; and a New Technique in File Sequencing, Tech. Report, IBM Ltd., 1966.
[47] P. Neumann and T. Neckel, A dynamic mesh refinement technique for Lattice Boltzmann simulations on octree-like grids, Comput. Mech., 51 (2013), pp. 237–253, . · Zbl 1312.76051
[48] OpenLB, (accessed 2018-04-15).
[49] Palabos, (accessed 2018-04-15).
[50] PARAMESH, (accessed 2018-04-15).
[51] S. G. Parker, A component-based architecture for parallel multi-physics PDE simulation, Future Gener. Comput. Syst., 22 (2006), pp. 204–216, .
[52] ParMETIS, (accessed 2018-04-15).
[53] T. Preclik and U. Rüde, Ultrascale simulations of non-smooth granular dynamics, Comput. Particle Mech., 2 (2015), pp. 173–196, .
[54] PT-Scotch, (accessed 2018-04-15).
[55] A. Randles, Modeling Cardiovascular Hemodynamics Using the Lattice Boltzmann Method on Massively Parallel Supercomputers, Ph.D. thesis, Harvard University, 2013.
[56] M. Rohde, D. Kandhai, J. J. Derksen, and H. E. A. van den Akker, A generic, mass conservative local grid refinement technique for lattice-Boltzmann schemes, Internat. J. Numer. Methods Fluids, 51 (2006), pp. 439–468, . · Zbl 1276.76060
[57] K. Schloegel, G. Karypis, and V. Kumar, Parallel static and dynamic multi-constraint graph partitioning, Concurr. Comp.-Pract. E., 14 (2002), pp. 219–240, . · Zbl 1012.68146
[58] E. Schnetter, S. H. Hawley, and I. Hawke, Evolutions in 3D numerical relativity using fixed mesh refinement, Class. Quantum Grav., 21 (2004), pp. 1465–1488, . · Zbl 1047.83002
[59] M. Schönherr, K. Kucher, M. Geier, M. Stiebler, S. Freudiger, and M. Krafczyk, Multi-thread implementations of the lattice Boltzmann method on non-uniform grids for CPUs and GPUs, Comput. Math. Appl., 61 (2011), pp. 3730–3743, .
[60] F. Schornbaum and U. Rüde, Massively parallel algorithms for the lattice Boltzmann method on nonuniform grids, SIAM J. Sci. Comput., 38 (2016), pp. C96–C126, .
[61] The Enzo Project, (accessed 2018-04-15).
[62] J. Tölke, S. Freudiger, and M. Krafczyk, An adaptive scheme using hierarchical grids for lattice Boltzmann multi-phase flow simulations, Comput. & Fluids, 35 (2006), pp. 820–830, . · Zbl 1177.76332
[63] Uintah, (accessed 2018-04-15).
[64] waLBerla, (accessed 2018-04-15).
[65] Z. Yu and L.-S. Fan, An interaction potential based lattice Boltzmann method with adaptive mesh refinement (AMR) for two-phase flow simulation, J. Comput. Phys., 228 (2009), pp. 6456–6478, . · Zbl 1261.76048
[66] Zoltan, (accessed 2018-04-15).
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