Skip to main content

Zipped Data Structure for Adaptive Mesh Refinement

  • Conference paper
  • First Online:
  • 887 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12942))

Abstract

Adaptive mesh refinement (AMR) is a dynamic approach to non-uniform grids which is commonly used to cut the simulation costs of multiscale problems in mathematical modeling of physical phenomena.

In this work, we propose a new dynamic data structure for AMR implementations which is based on a Z-order curve and tiles with variable size. It is a generalization of classical octree and various tile-based octrees, which can be seen as special cases of it. The tree height is dynamically decreased wherever possible by adjusting the number of children of nodes, increasing the size of tiles. Thus, the events of access to neighboring tiles become less frequent, and the complexity of access becomes less. Trivial data serialization presents another advantage of the data structure. In a specific case where the refinement level is constant over some region, the sub-tree height is equal to one, thus the neighbor access is just as simple as in a uniform multidimensional mesh. The structure inherits the locality properties of the Z-order space-filling curve.

In the text, the detailed description of the structure, algorithms for traversal, random access, neighbor search, and mesh adaptation are described.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Adams, M., et al.: Chombo software package for AMR applications design document. Lawrence Berkeley National Laboratory Technical Report LBNL-6616E (2015)

    Google Scholar 

  2. Berger, M.J., Colella, P.: Local adaptive mesh refinement for shock hydrodynamics. J. Comput. Phys. 82(1), 64–84 (1989)

    Article  Google Scholar 

  3. Bryan, G.L., et al.: Enzo: an adaptive mesh refinement code for astrophysics. Astrophys. J. Suppl. Ser. 211(2), 19 (2014)

    Article  MathSciNet  Google Scholar 

  4. Burstedde, C., Wilcox, L.C., Ghattas, O.: p4est: scalable algorithms for parallel adaptive mesh refinement on forests of octrees. SIAM J. Sci. Comput. 33(3), 1103–1133 (2011)

    Article  MathSciNet  Google Scholar 

  5. Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C.: Introduction to algorithms second edition. The Knuth-Morris-Pratt Algorithm (2001)

    Google Scholar 

  6. Dubey, A., et al.: A survey of high level frameworks in block-structured adaptive mesh refinement packages. J. Parallel Distrib. Comput. 74(12), 3217–3227 (2014)

    Article  Google Scholar 

  7. Ivanov, A.V., Khilkov, S.A.: Aiwlib library as the instrument for creating numerical modeling applications. Sci. Vis. 10(1), 110–127 (2018). https://doi.org/10.26583/sv.10.1.09

    Article  Google Scholar 

  8. Khokhlov, A.M.: Fully threaded tree algorithms for adaptive refinement fluid dynamics simulations. J. Comput. Phys. 143(2), 519–543 (1998)

    Article  MathSciNet  Google Scholar 

  9. Kirk, B.S., Peterson, J.W., Stogner, R.H., Carey, G.F.: libmesh: a c++ library for parallel adaptive mesh refinement/coarsening simulations. Eng. Comput. 22(3–4), 237–254 (2006). https://doi.org/10.1007/s00366-006-0049-3

    Article  Google Scholar 

  10. Ivanov, A., Levchenko, V., Korneev, B., Perepelkina, A.: Management of computations with LRnLA algorithms in adaptive mesh refinement codes. In: Voevodin, V., Sobolev, S. (eds.) RuSCDays 2020. CCIS, vol. 1331, pp. 25–36. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-64616-5_3

    Chapter  Google Scholar 

  11. Ivanov, A., Perepelkina, A., Levchenko, V., Pershin, I.: Memory-optimized tile based data structure for adaptive mesh refinement. In: Voevodin, V., Sobolev, S. (eds.) RuSCDays 2019. CCIS, vol. 1129, pp. 64–74. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-36592-9_6

    Chapter  Google Scholar 

  12. Lutsky, A.E., Severin, A.V.: Numerical study of flow x–43 hypersonic aircraft using adaptive grids. Keldysh Institute Preprints (102) (2016)

    Google Scholar 

  13. MacNeice, P., Olson, K.M., Mobarry, C., De Fainchtein, R., Packer, C.: PARAMESH: a parallel adaptive mesh refinement community toolkit. Comput. Phys. Commun. 126(3), 330–354 (2000)

    Article  Google Scholar 

  14. Menshov, I., Sheverdin, V.: A parallel locally-adaptive 3D model on cartesian nested-type grids. In: Malyshkin, V. (ed.) PaCT 2017. LNCS, vol. 10421, pp. 136–142. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-62932-2_12

    Chapter  Google Scholar 

  15. Morton, G.M.: A computer oriented geodetic data base and a new technique in file sequencing (1966)

    Google Scholar 

  16. Museth, K.: VDB: high-resolution sparse volumes with dynamic topology. ACM Trans. Graph. (TOG) 32(3), 1–22 (2013)

    Article  Google Scholar 

  17. Pavlukhin, P., Menshov, I.: Parallel implicit matrix-free CFD solver using AMR grids. In: Journal of Physics: Conference Series, vol. 1141, p. 012035. IOP Publishing (2018)

    Google Scholar 

  18. Popinet, S.: Gerris: a tree-based adaptive solver for the incompressible Euler equations in complex geometries. J. Comput. Phys. 190(2), 572–600 (2003)

    Article  MathSciNet  Google Scholar 

  19. Samet, H.: The quadtree and related hierarchical data structures. ACM Comput. Surv. (CSUR) 16(2), 187–260 (1984)

    Article  MathSciNet  Google Scholar 

  20. Schive, H.Y., ZuHone, J.A., Goldbaum, N.J., Turk, M.J., Gaspari, M., Cheng, C.Y.: GAMER-2: a GPU-accelerated adaptive mesh refinement code - accuracy, performance, and scalability. Mon. Notices Royal Astron. Soc. 481(4), 4815–4840 (2018). https://doi.org/10.1093/mnras/sty2586

    Article  Google Scholar 

  21. Stout, Q.F., De Zeeuw, D.L., Gombosi, T.I., Groth, C.P.T., Marshall, H.G., Powell, K.G.: Adaptive blocks: a high performance data structure. In: Proceedings of the 1997 ACM/IEEE Conference on Supercomputing. SC 1997, pp. 1–10. ACM, New York (1997). https://doi.org/10.1145/509593.509650

  22. Wahib, M., Maruyama, N., Aoki, T.: Daino: a high-level framework for parallel and efficient AMR on GPUs. In: SC 2016: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, pp. 621–632 (2016). https://doi.org/10.1109/SC.2016.52

  23. Weinzierl, T.: The Peano software–parallel, automaton-based, dynamically adaptive grid traversals. ACM Trans. Math. Softw. (TOMS) 45(2), 1–41 (2019)

    Article  MathSciNet  Google Scholar 

  24. Williams, S., Waterman, A., Patterson, D.: Roofline: an insightful visual performance model for multicore architectures. Commun. ACM 52(4), 65–76 (2009)

    Article  Google Scholar 

  25. Zhang, W., et al.: AMReX: a framework for block-structured adaptive mesh refinement. J. Open Source Softw. 4(37), 1370–1370 (2019)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Anastasia Perepelkina .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Ivanov, A., Perepelkina, A. (2021). Zipped Data Structure for Adaptive Mesh Refinement. In: Malyshkin, V. (eds) Parallel Computing Technologies. PaCT 2021. Lecture Notes in Computer Science(), vol 12942. Springer, Cham. https://doi.org/10.1007/978-3-030-86359-3_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-86359-3_19

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-86358-6

  • Online ISBN: 978-3-030-86359-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics