Particle-Based Fluid Simulation on the GPU

  • Kyle Hegeman
  • Nathan A. Carr
  • Gavin S. P. Miller
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3994)


Large scale particle-based fluid simulation is important to both the scientific and computer graphics communities. In this paper, we explore the effectiveness of implementing smoothed particle hydrodynamics on the streaming architecture of a GPU. A dynamic quadtree structure is proposed to accelerate the computation of inter-particle forces. Our method readily extends to higher dimensions without undue increase in memory or computation costs. We show that a GPU implementation runs nearly an order of magnitude faster than our CPU version for large problem sizes.


Smooth Particle Hydrodynamic Collision Detection Smooth Particle Hydrodynamic Graphic Hardware Geometry Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Miller, G., Pearce, A.: Globular dynamics: A connected particle system for animating viscous fluids. Computers and Graphics 13(3), 305–309 (1989)CrossRefGoogle Scholar
  2. 2.
    Müller, M., Charypar, D., Gross, M.: Particle-based fluid simulation for interactive applications. In: Proc. of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation, pp. 154–159 (2003)Google Scholar
  3. 3.
    Baraff, D., Witkin, A.: Large steps in cloth simulation. In: Proc. of SIGGRAPH 1998, pp. 43–54 (1998)Google Scholar
  4. 4.
    Premože, S., Tasdizen, T., Bigler, J., Lefohn, A., Whitaker, R.T.: Particle-based simulation of fluids. In: Proc. of Eurographics 2003, vol. 22 (2003)Google Scholar
  5. 5.
    Owens, J.D., Luebke, D., Govindaraju, N., Harris, M., Krüger, J., Lefohn, A.E., Purcell, T.J.: A survey of general-purpose computation on graphics hardware. In: Eurographics 2005, State of the Art Reports, pp. 21–51 (2005)Google Scholar
  6. 6.
    Kolb, A., Latta, L., Rezk-Salama, C.: Hardware-based simulation and collision detection for large particle systems. In: Proc. of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware, pp. 123–131 (2004)Google Scholar
  7. 7.
    Krüger, J., Kipfer, P., Kondratieva, P., Westermann, R.: A particle system for interactive visualization of 3D flows. IEEE Trans. on Visualization and Computer Graphics 11(6) (2005)Google Scholar
  8. 8.
    Chiara, R.D., Erra, U., Scarano, V., Tatafiore, M.: Massive simulation using GPU of a distributed behavioral model of a flock with obstacle avoidance. In: Proc. of the Vision, Modeling, and Visualization Conference 2004, pp. 233–240 (2004)Google Scholar
  9. 9.
    Kolb, A., Cuntz, N.: Dynamic particle coupling for GPU-based fluid simulation. In: Proc. of 18th Symposium on Simulation Technique, pp. 722–727 (2005)Google Scholar
  10. 10.
    Foley, T., Sugerman, J.: KD-tree acceleration structures for a GPU raytracer. In: Proc. of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware, pp. 15–22 (2005)Google Scholar
  11. 11.
    Simonsen, L.O., Thrane, N., Ørbæk, P.: A comparison of acceleration structures for GPU assisted ray-tracing. Masters Thesis (2005)Google Scholar
  12. 12.
    Lefohn, A., Kniss, J.M., Strzodka, R., Sengupta, S., Owens, J.D.: Glift: Generic, efficient, random-access GPU data structures. ACM Transactions on Graphics 25(1) (2006)Google Scholar
  13. 13.
    Lefebvre, S., Hornus, S., Neyret, F.: Octree textures on the GPU. In: Pharr, M. (ed.) GPU Gems 2, pp. 595–613. Addison Wesley, Reading (2005)Google Scholar
  14. 14.
    Govindaraju, N.K., Redon, S., Lin, M.C., Manocha, D.: CULLIDE: Interactive collision detection between complex models in large environments using graphics hardware. In: Proc. of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware, pp. 25–32 (2003)Google Scholar
  15. 15.
    Govindaraju, N.K., Lin, M.C., Manocha, D.: Fast and reliable collision culling using graphics hardware. In: Proc. of the ACM symposium on Virtual reality software and technology, pp. 2–9 (2004)Google Scholar
  16. 16.
    Govindaraju, N.K., Knott, D., Jain, N., Kabul, I., Tamstorf, R., Gayle, R., Lin, M.C., Manocha, D.: Interactive collision detection between deformable models using chromatic decomposition. ACM Transactions on Graphics 24(3), 991–999 (2005)CrossRefGoogle Scholar
  17. 17.
    Gottschalk, S., Lin, M.C., Manocha, D.: OBBTree: a hierarchical structure for rapid interference detection. In: Proc. of SIGGRAPH 1996, pp. 171–180 (1996)Google Scholar
  18. 18.
    Klosowski, J.T., Held, M., Mitchell, J.S.B., Sowizral, H., Zikan, K.: Efficient collision detection using bounding volume hierarchies of k-dops. IEEE Trans. on Visualization and Computer Graphics 4(1), 21–36 (1998)CrossRefGoogle Scholar
  19. 19.
    Beneš, B., Villanueva, N.G.: GI-COLLIDE: collision detection with geometry images. In: Proc. of the 21st spring conference on Computer graphics, pp. 95–102 (2005)Google Scholar
  20. 20.
    Purcell, T.J., Donner, C., Cammarano, M., Jensen, H.W., Hanrahan, P.: Photon mapping on programmable graphics hardware. In: Proc. of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware, pp. 41–50 (2003)Google Scholar
  21. 21.
    Lucy, L.B.: A Numerical Approach to Testing the Fission Hypothesis. The Astronomical Journal 82(12), 1013–1924 (1977)CrossRefGoogle Scholar
  22. 22.
    Gingold, R., Monaghan, J.: Smoothed particle hydrodynamics: Theory and application to non-spherical stars. Monthly Notices of the Royal Astronomical Society 181, 375–389 (1977)zbMATHGoogle Scholar
  23. 23.
    Gu, X., Gortler, S.J., Hoppe, H.: Geometry images. In: Proc. of SIGGRAPH 2002, pp. 355–361 (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Kyle Hegeman
    • 1
  • Nathan A. Carr
    • 2
  • Gavin S. P. Miller
    • 2
  1. 1.Stony Brook University 
  2. 2.Adobe Systems Inc. 

Personalised recommendations