Skip to main content
Springer Nature Link
Log in

GPU-accelerated SPH fluids surface reconstruction using two-level spatial uniform grids

  • Original Article
  • Published:
The Visual Computer Aims and scope Submit manuscript

Abstract

An efficient two-level spatial uniform grid structure-based high-quality surface reconstruction method with Marching Cubes (MC) for smoothed particle hydrodynamics (SPH) fluids was presented in this paper. Compared with the traditional way that dividing the simulation domain with uniform grid directly, an enhanced narrow-band approach using the parallel cuckoo hashing method was taken to index the coarse-level surface vertices, hence decrease the memory consumption. Moreover, a two-level spatial uniform grid structure was employed with a scheme of arranging the fine surface vertices, which could preserve the spatial locality property to facilitate the coalesced memory access on the GPU. Our algorithm was designed for parallel architectures, based on which a parallel version of the optimized surface reconstruction was performed on the CUDA platform. In the experiment of comparison to traditional approaches, the results indicated that our surface reconstruction method was more efficient at the same level of quality of the reconstructed surfaces.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Müller, M., Charypar, D., Gross, M.: Particle-based fluid simulation for interactive applications. In: Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation, pp. 154–159. Eurographics Association, UK (2003)

  2. Zhu, Y., Bridson, R.: Animating sand as a fluid. ACM Trans. Graphics 24(3), 965–972 (2005)

    Article  Google Scholar 

  3. Adams, B., Pauly, M., Keiser, R., et al.: Adaptively sampled particle fluids. In: ACM Transactions on Graphics (TOG), vol. 26, no. 3, pp. 48. ACM, New York (2007)

  4. Solenthaler, B., Schläfli, J., Pajarola, R.: A unified particle model for fluid-solid interactions. Comput. Anim. Virtual Worlds 18(1), 69–82 (2007)

    Article  Google Scholar 

  5. Akinci, G., Ihmsen, M., Akinci, N., et al.: Parallel surface reconstruction for particle-based fluids. In: Computer Graphics Forum, vol. 31, no. 6, pp. 1797–1809. Blackwell Publishing Ltd, Hoboken (2012)

  6. Akinci, G., Akinci, N., Ihmsen, M.,Teschner, M.: An efficient surface reconstruction pipeline for particle-based fluids, pp. 61–68. In: Proc. VRIPHYS. Darmstadt, Germany (2012)

  7. Onderik, J., Chládek, M., Durikovic, R.: SPH with small scale details and improved surface reconstruction. In: Proceedings of the 27th Spring Conference on Computer Graphics, SCCG ’11, pp. 29–36(2013)

  8. Yu, J., Turk, G.: Reconstructing surfaces of particle-based fluids using anisotropic kernels. ACM Trans. Graphics 32(1), 5 (2013)

    Article  MATH  Google Scholar 

  9. Lorensen, W.E., Cline, H.E.: Marching cubes: A high resolution 3D surface construction algorithm. In: ACM siggraph computer graphics, vol. 21, no. 4, pp. 163–169. ACM, New York (1987)

  10. Velasco, F., Torres, J.C.: Cell Octrees: A new data structure for volume modeling and visualization. In: Ertl, T., Girod, B., Niemann, H., Seidel, H.P. (eds.) Proceedings of the Vision Modeling and Visualization Conference 2001 (VMV’01), pp. 151–158. Aka GmbH, Germany (2001)

  11. Lee, H., Yang, H.S.: Real-time Marching-cube-based LOD Surface Modeling of 3D Objects. ICAT (2004)

  12. Ju, T., Udeshi, T.: Intersection-free contouring on an octree grid. In: Proceedings of 14th Pacific Conference. Computer Graphics and Applications (PG ’06). IEEE Computer Society Press, Los Alamitos (2006)

  13. Manson, J., Schaefer, S.: Isosurfaces over simplicial partitions of multiresolution grids. Comput. Graphics Forum 29(2), 377–385 (2010)

    Article  Google Scholar 

  14. Alcantara, D.A., Sharf, A., Abbasinejad, F., et al.: Real-time parallel hashing on the GPU. ACM Trans. Graphics 28(5), 154 (2009)

    Article  Google Scholar 

  15. Blinn, J.F.: A generalization of algebraic surface drawing. ACM Trans. Graphics 1(3), 235–256 (1982)

    Article  Google Scholar 

  16. Zhou, K., Gong, M., Huang, X., Guo, B.: Data-parallel octrees for surface reconstruction. IEEE Trans. Visual Comput. Graphics 17(5), 669–681 (2011)

    Article  Google Scholar 

  17. Akinci, G., Akinci, N., Oswald, E., Teschner, M.: Adaptive surface reconstruction for SPH using 3-Level Uniform Grids. In: WSCG proceedings, pp. 195–204. Union Agency (2013)

  18. Du, S., Kanai, T.: GPU-based Adaptive Surface Reconstruction for Real-time SPH Fluids. In: WSCG proceedings, pp. 141–150 (2014)

  19. Bridson, R.E.: Computational aspects of dynamic surfaces. Stanford University, Stanford (2003)

  20. Houston, B., Wiebe, M., Batty, C.C.: RLE sparse level sets. In: Proceedings of the SIGGRAPH 2004 conference on sketches & applications. New York (2004)

  21. Nielsen, M.B., Museth, K.: Dynamic tubular grid: an efficient data structure and algorithms for high resolution level sets. J. Sci. Comput. 26(3), 261–299 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  22. Nielsen, M. B., Nilsson, O., Söderström, A., Museth, K.: Out-of-core and compressed level set methods. ACM Trans. Graphics 26(4), 16 (2007)

  23. Ihmsen, M., Akinci, N., Becker, M., et al.: A Parallel SPH Implementation on Multi -Core CPUs. In: Computer Graphics Forum, vol. 30, no. 1, pp. 99–112. Blackwell Publishing Ltd, Hoboken (2011)

  24. Goswami, P., Schlegel, P., Solenthaler, B., et al.: Interactive SPH simulation and rendering on the GPU. In: Proceedings of the 2010 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, pp. 55–64. Eurographics Association, UK (2010)

  25. Premoze, S., Tasdizen, T., Bigler, J., Lefohn, A., Whitaker, R.: Particle-based simulation of fluids. In: Computer Graphics Forum (Proceedings of Eurographics), vol. 22, pp. 401–410 (2003)

  26. Yu, J., Wojtan, C., Turk, G., Yap, C.: Explicit mesh surfaces for particle based fluids. Eurographics 2012(30), 41–48 (2012)

    Google Scholar 

  27. Gribble, C.P., Ize, T., Kensler, A., Wald, I., Parker, S.G.: A coherent grid traversal approach to visualizing particle-based simulation data. IEEE Trans. Visual Comput. Graphics 13(4), 758–768 (2007)

  28. Kanamori, Y., Szego, Z., Nishita, T.: GPU-based fast ray casting for a large number of metaballs. Comput. Graphics Forum 27(2), 351–360 (2008)

    Article  Google Scholar 

  29. Zhang, Y., Solenthaler, B., Pajarola, R.: Adaptive sampling and rendering of fluids on the GPU. In: Proceedings Symposium on Point-Based Graphics, pp. 137–146 (2008)

  30. Müller, M., Heidelberger, B., Hennix, M., Ratcliff, J.: Position based dynamics. J. Vis. Commun. 18(2), 109–118 (2007)

    Google Scholar 

  31. Bagar, F., Scherzer, D., Wimmer, M.: A layered particle-based fluid model for real-time rendering of water. In: Computer Graphics Forum (Proceedings EGSR 2010), vol. 29, no. 4, pp. 1383–1389 (2010)

  32. Orthmann, J., Keller, M., Kolb, A.: Topologycaching for dynamic particle, volume raycasting. In: Proceedings Vision, Modeling and Visualization (VMV), pp. 147–154 (2010)

  33. Jang, Y., Fuchs, R., Schindler, B., Peikert, R.: Volumetric evaluation of meshless data from smoothed particle hydrodynamics simulations. In: Proceedings of the 8th IEEE EG International Conference on volume graphics, VG’10, pp. 45–52. Eurographics Association, UK (2010)

  34. Ihmsen, M., Akinci, N., Akinci, G., Teschner, M.: Unified spray, foam and bubbles for particle-based fluids. Vis. Comput. 30(1), 99–112 (2012)

    Google Scholar 

  35. Nvidia: CUDA C Programming Guide. http://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#hardware-implementation (2015). Accessed 10 Nov 2015

  36. Solenthaler, B., Pajarola, R.: Predictive-corrective incompressible SPH. In: ACM transactions on graphics (TOG), vol. 28, no. 3, p. 40. ACM, New York (2009)

Download references

Acknowledgments

This work was jointly supported by the National Natural Science Foundation of China (Grant No. 41275013) and the National High-Tech Research and Development Program (863) (Grant No. 2013AA09A506-4).

Author information

Authors and Affiliations

  1. College of Information Science and Engineering, Ocean University of China, Qingdao, 266100, China

    Wei Wu & Hongping Li

  2. The First Institute of Oceanography, SOA, Qingdao, 266061, China

    Tianyun Su & Haixing Liu

  3. Shenzhen Research Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China

    Zhihan Lv

Authors
  1. Wei Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hongping Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tianyun Su
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Haixing Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Zhihan Lv
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hongping Li.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, W., Li, H., Su, T. et al. GPU-accelerated SPH fluids surface reconstruction using two-level spatial uniform grids. Vis Comput 33, 1429–1442 (2017). https://doi.org/10.1007/s00371-016-1289-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00371-016-1289-x

Keywords

Search

Navigation