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GPU Computing and Applications pp 15–34Cite as

Real-Time Deformation of Constrained Meshes Using GPU

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Abstract

Constrained meshes play an important role in free-form architectural design, as they can represent panel layouts on free-form surfaces. It is challenging to perform real-time manipulation on such meshes, because all constraints need to be respected during the deformation while the shape quality needs to be maintained. This usually leads to nonlinear constrained optimization problems, which are challenging to solve in real time. In this chapter, we present a GPU-based shape manipulation tool for constrained meshes, using the parallelizable algorithm proposed in Deng et al. (Computer-Aided Design, 2014). We discuss the main challenges and solutions for the GPU implementation and provide timing comparison against CPU implementations of the algorithm. Our GPU implementation significantly outperforms the CPU version, allowing real-time handle-based deformation for large constrained meshes.

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References

  1. Eigensatz, M., Kilian, M., Schiftner, A., Mitra, N.J., Pottmann, H., Pauly, M.: Paneling architectural freeform surfaces. ACM Trans. Graph. 29(4), 1–10 (2010)

    Article  Google Scholar 

  2. Yang, Y.L., Yang, Y.J., Pottmann, H., Mitra, N.J.: Shape space exploration of constrained meshes. ACM Trans. Graph. 30(6), 124:1–124:12 (2011)

    Google Scholar 

  3. Bouaziz, S., Deuss, M., Schwartzburg, Y., Weise, T., Pauly, M.: Shape-up: shaping discrete geometry with projections. Comput. Graph. Forum 31(5), 1657–1667 (2012)

    Article  Google Scholar 

  4. Vaxman, A.: Modeling polyhedral meshes with affine maps. In: Symposium on Geometry Processing (2011)

    Google Scholar 

  5. Zhao, X., Tang, C.C., Yang, Y.L., Pottmann, H., Mitra, N.J.: Intuitive design exploration of constrained meshes. In: Advances in Architectural Geometry (2012).

    Google Scholar 

  6. Poranne, R., Ovreiu, E., Gotsman, C.: Interactive planarization and optimization of 3D meshes. Comput. Graph. Forum 32(1), 152–163 (2013)

    Article  Google Scholar 

  7. Deng, B., Bouaziz, S., Deuss, M., Zhang, J., Schwartzburg, Y., Pauly, M.: Exploring local modifications for constrained meshes. Comput. Graph. Forum 32(2), 11–20 (2013)

    Article  Google Scholar 

  8. Deng, B., Bouaziz, S., Deuss, M., Kaspar, A., Schwartzburg, Y., Pauly, M.: Interactive design exploration for constrained meshes. Computer-Aided Design (2014)

    Google Scholar 

  9. Song, P. Fu, C.W., Goswami, P. Zheng, J. Mitra, N.J., Cohen-Or, D.: Reciprocal frame structures made easy. ACM Trans. Graph. 32(4), 94:1–94:13 (2013)

    Google Scholar 

  10. Bao, F., Yan, D.M., Mitra, N.J. Wonka, P.: Generating and exploring good building layouts. ACM Trans. Graph. 32(4), 122:1–122:10 (2013)

    Google Scholar 

  11. Umeyama, S.: Least-squares estimation of transformation parameters between two point pat- terns. IEEE Trans. Pattern Anal. Mach. Intell. 13(4), 376–380 (1991)

    Article  Google Scholar 

  12. Bertsekas, D.P.: Constrained Optimization and Lagrange Multiplier Methods. Athena Scientific, Belmont, MA (1996)

    Google Scholar 

  13. Boyd, S., Parikh, N., Chu, E., Peleato, B., Eckstein, J.: Distributed optimization and statistical learning via the alternating direction method of multipliers. Found. Trends Mach. Learn. 3(1), 1–122 (2011)

    Article  Google Scholar 

  14. NVIDIA: NVIDIA GeForce GTX 580 datasheet (2010)

    Google Scholar 

  15. Glaskowsky, P.N.: NVIDIA’s Fermi: The First Complete GPU Computing Architecture. (2009)

    Google Scholar 

  16. NVIDIA: Fermi Compute Architecture Whitepaper (2009). Version 1.1

    Google Scholar 

  17. Torres, Y., Gonzalez-Escribano, A., Llanos, D.: Understanding the impact of CUDA tuning techniques for Fermi. In: 2011 International Conference on High Performance Computing and Simulation (HPCS), pp. 631–639 (2011)

    Google Scholar 

  18. Glymph, J., Shelden, D., Ceccato, C., Mussel, J., Schober, H.: A parametric strategy for free- form glass structures using quadrilateral planar facets. Automation in Construction 13(2): 187–202 (2004), Conference of the Association for Computer Aided Design in Architecture

    Google Scholar 

  19. Deng, B., Pottmann, H., Wallner, J.: Functional webs for freeform architecture. Comput. Graph. Forum 30(5), 1369–1378 (2011)

    Article  Google Scholar 

  20. NVIDIA: CUDA C Programming Guide

    Google Scholar 

  21. Press, W.H., Teukolsky, S.A., Vetterling, W.T., Flannery, B.P.: Numerical Recipes: The Art of Scientific Computing, 3rd edn. Cambridge University Press, New york (2007)

    Google Scholar 

  22. McAdams, A., Selle, A., Tamstorf, R., Teran, J., Sifakis, E.: Computing the singular value decomposition of 3 × 3 matrices with minimal branching and elementary floating point operations. Technical Report, University of Wisconsin-Madison (2011)

    Google Scholar 

  23. Bell, N., Garland, M.: Cusp: generic parallel algorithms for sparse matrix and graph computations. http://cusp-library.googlecode.com (2012). Version 0.3.0

  24. Bell, N., Garland, M.: Implementing sparse matrix-vector multiplication on throughput-oriented processors. In: Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis, SC’09, pp. 18:1–18:11 (2009)

    Google Scholar 

  25. Guennebaud, G., Jacob, B., et al.: Eigen v3. http://eigen.tuxfamily.org (2010)

  26. Baskaran, M.M., Bordawekar, R.: Optimizing sparse matrix-vector multiplication on GPUs. Technical Report RC24704, IBM (2008)

    Google Scholar 

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Acknowledgments

The authors thank Asymptote Architecture for providing the figure of Yas Viceroy Hotel. The mesh models are provided by Asymptote Architecture and Waagner Biro (Yas), Zaha Hadid Architects and Amir Vaxman (Lilium1 and Lilium2), and Mario Deuss (Roof1, Roof2, and Snale). This work has been supported by Swiss National Science Foundation (SNSF) grant 200021_137626.

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Authors and Affiliations

  1. Computer Graphics and Geometry Laboratory, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Alexandre Kaspar & Bailin Deng

Authors
  1. Alexandre Kaspar
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  2. Bailin Deng
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Corresponding author

Correspondence to Alexandre Kaspar .

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Editors and Affiliations

  1. Nanyang Technological University, Singapore, Singapore

    Yiyu Cai

  2. Nvidia, Singapore, Singapore

    Simon See

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Kaspar, A., Deng, B. (2015). Real-Time Deformation of Constrained Meshes Using GPU. In: Cai, Y., See, S. (eds) GPU Computing and Applications. Springer, Singapore. https://doi.org/10.1007/978-981-287-134-3_2

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  • DOI: https://doi.org/10.1007/978-981-287-134-3_2

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-287-133-6

  • Online ISBN: 978-981-287-134-3

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