Advertisement

Exploring Parallel Algorithms for Volumetric Mass-Spring-Damper Models in CUDA

  • Allan Rasmusson
  • Jesper Mosegaard
  • Thomas Sangild S∅rensen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5104)

Abstract

Since the advent of programmable graphics processors (GPUs) their computational powers have been utilized for general purpose computation. Initially by “exploiting” graphics APIs and recently through dedicated parallel computation frameworks such as the Compute Unified Device Architecture (CUDA) from Nvidia. This paper investigates multiple implementations of volumetric Mass-Spring-Damper systems in CUDA. The obtained performance is compared to previous implementations utilizing the GPU through the OpenGL graphics API. We find that both performance and optimization strategies differ widely between the OpenGL and CUDA implementations. Specifically, the previous recommendation of using implicitly connected particles is replaced by a recommendation that supports unstructured meshes and run-time topological changes with an insignificant performance reduction.

Keywords

Mass-Spring-Damper Models GPGPU and Deformable Models 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Liu, A., Tendick, F., Cleary, K., Kaufmann, C.: A survey of surgical simulation: applications, technology, and education. Presence: Teleoper. Virtual Environ. 12(6), 599–614 (2003)CrossRefGoogle Scholar
  2. 2.
    Miller, K., Joldes, G., Lance, D., Wittek, A.: Total lagrangian explicit dynamics finite element algorithm for computing soft tissue deformation. Communications in Numerical Methods in Engineering 23, 121–134 (2007)CrossRefMathSciNetzbMATHGoogle Scholar
  3. 3.
    Irving, G., Teran, J., Fedkiw, R.: Invertible finite elements for robust simulation of large deformation. In: Eurographics/ACM SIGGRAPH Symposium on Computer Animation, pp. 131–140 (2004)Google Scholar
  4. 4.
    Bro-Nielsen, M., Cotin, S.: Real-time volumetric deformable models for surgery simulation using finite elements and condensation  15, 57–66 (1996)Google Scholar
  5. 5.
    Delingette, H., Cotin, S., Ayache, N.: A hybrid elastic model allowing real-time cutting deformations and force feedback for surgery training and simulation. In: Proceedings of the Computer Animation, May 1999, pp. 70–81 (1999)Google Scholar
  6. 6.
    Sørensen, T.S., Mosegaard, J.: An introduction to gpu accelerated surgical simulation. In: Harders, M., Székely, G. (eds.) ISBMS 2006. LNCS, vol. 4072, pp. 93–104. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  7. 7.
    Mosegaard, J., Sørensen, T.S.: Gpu accelerated surgical simulators for complex morphology. Proceedings of Virtual Reality 323, 147–154 (2005)Google Scholar
  8. 8.
    Taylor, Z., Cheng, M., Ourselin, S.: High-speed nonlinerar finite element analysis for surgical simulation using graphics processing units. IEEE Transactions on Medical Imaging (in Press, 2008)Google Scholar
  9. 9.
    NVIDIA: CUDA Programming Guide v. 1.1Google Scholar
  10. 10.
    Jakobsen, T.: Advanced character physics. In: Game Developers Conference (2001)Google Scholar
  11. 11.
    Sørensen, T., Stawiakski, J., Mosegaard, J.: Virtual open heart surgery: Obtaining models suitable for surgical simulation. Stud Health Technol. Inform. 125, 445–447 (2007)Google Scholar
  12. 12.
    Mosegaard, J., Sørensen, T.S.: Real-time deformation of detailed geometry based on mappings to a less detailed physical simulation on the gpu. In: Proceedings of Eurographics Workshop on Virtual Environments, vol. 11, pp. 105–111. Eurographics Association (2005)Google Scholar
  13. 13.
    Sørensen, T.S., Mosegaard, J.: Haptic feedback for the GPU-based surgical simulator. Proceedings of Medicine Meets Virtual Reality 14. Studies in Health Technology and Informatics 119, 523–528 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Allan Rasmusson
    • 1
    • 2
  • Jesper Mosegaard
    • 3
  • Thomas Sangild S∅rensen
    • 1
    • 4
  1. 1.Department of Computer ScienceUniversity of AarhusDenmark
  2. 2.Center for HistoinformaticsUniversity of AarhusDenmark
  3. 3.Alexandra InstituteDenmark
  4. 4.Institute of Clinical MedicineUniversity of Aarhus 

Personalised recommendations