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Compression and Heuristic Caching for GPU Particle Tracing in Turbulent Vector Fields

  • Conference paper
Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 598))

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Abstract

Particle tracing in fully resolved turbulent vector fields is challenging due to their extreme resolution. Since particles can move along arbitrary paths through large parts of the domain, particle integration requires access to the entire field in an unpredictable order. Thus, techniques for particle tracing in such fields require a careful design to reduce performance constraints caused by memory and communication bandwidth. One possibility to achieve this is data compression, but so far it has been considered rather hesitantly due to supposed accuracy issues. We shed light on the use of data compression for turbulent vector fields, motivated by the observation that particle traces are always afflicted with inaccuracy. We quantitatively analyze the additional inaccuracies caused by lossy compression. We propose an adaptive data compression scheme using the discrete wavelet transform and integrate it into a block-based particle tracing approach. Furthermore, we present a priority-based GPU caching scheme to reduce memory access operations. In some experiments we confirm that the compression has only minor impact on the accuracy of the trajectories, and that on a desktop system our technique can achieve comparable performance to previous approaches on supercomputers.

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References

  1. Treib, M., Bürger, K., Reichl, F., Meneveau, C., Szalay, A., Westermann, R.: Turbulence visualization at the terascale on desktop PCs. IEEE Trans. Vis. Comput. Graphics 18, 2169–2177 (2012)

    Article  Google Scholar 

  2. Li, Y., Perlman, E., Wan, M., Yang, Y., Meneveau, C., Burns, R., Chen, S., Szalay, A., Eyink, G.: A public turbulence database cluster and applications to study Lagrangian evolution of velocity increments in turbulence. J. Turbul. 9, N31 (2008)

    Article  MATH  Google Scholar 

  3. Post, F.H., Vrolijk, B., Hauser, H., Laramee, R.S., Doleisch, H.: The state of the art in flow visualisation: feature extraction and tracking. Comput. Graph. Forum 22, 775–792 (2003)

    Article  Google Scholar 

  4. Laramee, R.S., Hauser, H., Doleisch, H., Vrolijk, B., Post, F.H., Weiskopf, D.: The state of the art in flow visualization: dense and texture-based techniques. Comput. Graph. Forum 23, 203–221 (2004)

    Article  Google Scholar 

  5. McLoughlin, T., Laramee, R.S., Peikert, R., Post, F.H., Chen, M.: Over two decades of integration-based, geometric flow visualization. Comput. Graph. Forum 29, 1807–1829 (2010)

    Article  Google Scholar 

  6. Teitzel, C., Grosso, R., Ertl, T.: Efficient and reliable integration methods for particle tracing in unsteady flows on discrete meshes. In: Lefer, W., Grave, M. (eds.) Visualization in Scientific Computing 1997. Eurographics, pp. 31–41. Springer, Vienna (1997)

    Google Scholar 

  7. Yeung, P.K., Pope, S.B.: An algorithm for tracking fluid particles in numerical simulations of homogeneous turbulence. J. Comput. Phys. 79, 373–416 (1988)

    Article  MATH  Google Scholar 

  8. Balachandar, S., Maxey, M.R.: Methods for evaluating fluid velocities in spectral simulations of turbulence. J. Comput. Phys. 83, 96–125 (1989)

    Article  MATH  Google Scholar 

  9. Rovelstad, A.L., Handler, R.A., Bernard, P.S.: The effect of interpolation errors on the Lagrangian analysis of simulated turbulent channel flow. J. Comput. Phys. 110, 190–195 (1994)

    Article  MATH  Google Scholar 

  10. Schirski, M., Gerndt, A., van Reimersdahl, T., Kuhlen, T., Adomeit, P., Lang, O., Pischinger, S., Bischof, C.H.: ViSTA FlowLib: a framework for interactive visualization and exploration of unsteady flows in virtual environments. In: 9th Eurographics Workshop on Virtual Enviroments, pp. 77–86 (2003)

    Google Scholar 

  11. Krüger, J., Kipfer, P., Kondratieva, P., Westermann, R.: A particle system for interactive visualization of 3D flows. IEEE Trans. Vis. Comput. Graph. 11, 744–756 (2005)

    Article  Google Scholar 

  12. Schirski, M., Bischof, C., Kuhlen, T.: Interactive particle tracing on tetrahedral grids using the GPU. In: Proceedings of Vision, Modeling, and Visualization (VMV), pp. 153–160 (2006)

    Google Scholar 

  13. Bürger, K., Schneider, J., Kondratieva, P., Krüger, J., Westermann, R.: Interactive visual exploration of unsteady 3D flows. In: Eurographics/IEEE VGTC Visualization (EuroVis) (2007)

    Google Scholar 

  14. Murray, L.: GPU acceleration of Runge-Kutta integrators. IEEE Trans. Parallel Distrib. Syst. 23, 94–101 (2011)

    Article  Google Scholar 

  15. Sayood, K.: Introduction to Data Compression, 3rd edn. Morgan Kaufmann Publishers Inc., San Francisco (2005)

    MATH  Google Scholar 

  16. Rodriguez, M.B., Gobbetti, E., Guitián, J.I., Makhinya, M., Marton, F., Pajarola, R., Suter, S.: A survey of compressed GPU-based direct volume rendering. In: Eurographics 2013 - STARs, pp. 117–136 (2013)

    Google Scholar 

  17. Treib, M., Reichl, F., Auer, S., Westermann, R.: Interactive editing of gigasample terrain fields. Comput. Graph. Forum 31, 383–392 (2012)

    Article  Google Scholar 

  18. Lane, D.A.: UFAT–a particle tracer for time-dependent flow fields. In: IEEE Visualization, pp. 257–264 (1994)

    Google Scholar 

  19. Bruckschen, R., Kuester, F., Hamann, B., Joy, K.I.: Real-time out-of-core visualization of particle traces. In: Proceedings of IEEE 2001 Symposium on Parallel and Large-Data Visualization and Graphics, pp. 45–50 (2001)

    Google Scholar 

  20. Ellsworth, D., Green, B., Moran, P.: Interactive terascale particle visualization. In: IEEE Visualization, pp. 353–360 (2004)

    Google Scholar 

  21. Pugmire, D., Childs, H., Garth, C., Ahern, S., Weber, G.H.: Scalable computation of streamlines on very large datasets. In: Proceedings of the Conference on High Performance Computing, Networking, Storage and Analysis, pp. 16: 1–16: 12 (2009)

    Google Scholar 

  22. Camp, D., Garth, C., Childs, H., Pugmire, D., Joy, K.: Streamline integration using MPI-hybrid parallelism on a large multicore architecture. IEEE Trans. Vis. Comput. Graph. 17, 1702–1713 (2011)

    Article  Google Scholar 

  23. Nouanesengsy, B., Lee, T.Y., Shen, H.W.: Load-balanced parallel streamline generation on large scale vector fields. IEEE Trans. Vis. Comput. Graph. 17, 1785–1794 (2011)

    Article  Google Scholar 

  24. Peterka, T., Ross, R., Nouanesengsy, B., Lee, T.Y., Shen, H.W., Kendall, W., Huang, J.: A study of parallel particle tracing for steady-state and time-varying flow fields. In: Parallel Distributed Processing Symposium (IPDPS), pp. 580–591 (2011)

    Google Scholar 

  25. Yu, H., Wang, C., Ma, K.L.: Parallel hierarchical visualization of large time-varying 3D vector fields. In: Proceedings of ACM/IEEE Conference on Supercomputing, pp. 24:1–24:12 (2007)

    Google Scholar 

  26. Isenburg, M., Lindstrom, P., Snoeyink, J.: Lossless compression of predicted floating-point geometry. Comput. Aided Des. 37, 869–877 (2005)

    Article  MATH  Google Scholar 

  27. Lindstrom, P., Isenburg, M.: Fast and efficient compression of floating-point data. IEEE Trans. Vis. Comput. Graph. 12, 1245–1250 (2006)

    Article  Google Scholar 

  28. Fout, N., Ma, K.L.: An adaptive prediction-based approach to lossless compression of floating-point volume data. IEEE Trans. Vis. Comput. Graph. 18, 2295–2304 (2012)

    Article  Google Scholar 

  29. Fout, N., Ma, K.L.: Fuzzy volume rendering. IEEE Trans. Vis. Comput. Graph. 18, 2335–2344 (2013)

    Article  Google Scholar 

  30. Zheng, Z., Xu, W., Mueller, K.: VDVR: Verifiable volume visualization of projection-based data. IEEE Trans. Vis. Comput. Graph. 16, 1515–1524 (2010)

    Article  Google Scholar 

  31. Frigo, M., Johnson, S.G.: The design and implementation of FFTW3. Proc. IEEE 93, 216–231 (2005)

    Article  Google Scholar 

  32. Eiter, T., Mannila, H.: Computing discrete Frèchet distance. Technical report CD-TR 94/64, Technische Universität Wien (1994)

    Google Scholar 

  33. Aurell, E., Boffetta, G., Crisanti, A., Paladin, G., Vulpiani, A.: Predictability in the large: an extension of the concept of Lyapunov exponent. J. Phys. A: Math. Gen. 30, 1–26 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  34. Dormand, J.R., Prince, P.J.: A family of embedded Runge-Kutta formulae. J. Comput. Appl. Math. 6, 19–26 (1980)

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgements

The work was partly funded by the European Union under the ERC Advanced Grant 291372: Safer-Vis - Uncertainty Visualization for Reliable Data Discovery. The authors want to thank Charles Meneveau from Johns Hopkins University and Tobias Pfaffelmoser from TUM for helpful discussions and constructive criticism.

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Authors and Affiliations

  1. Department of Computer Science, Technische Universität München, Munich, Germany

    Marc Treib, Kai Bürger, Jun Wu & Rüdiger Westermann

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  1. Marc Treib
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  2. Kai Bürger
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  3. Jun Wu
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  4. Rüdiger Westermann
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Correspondence to Jun Wu .

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Editors and Affiliations

  1. Escola Superior de Tecnologia do IPS, Setúbal, Portugal

    José Braz

  2. Inria-Rennes/MimeTIC Team, Rennes cedex, France

    Julien Pettré

  3. LISA - ISTIA, University of Angers, Angers, France

    Paul Richard

  4. Linnaeus University, Växjö, Sweden

    Andreas Kerren

  5. Jacobs University, Bremen, Germany

    Lars Linsen

  6. Università di Catania, Catania, Catania, Italy

    Sebastiano Battiato

  7. Research Innovation Center, Canon U.S.A. Inc, San Jose, CA, USA

    Francisco Imai

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Treib, M., Bürger, K., Wu, J., Westermann, R. (2016). Compression and Heuristic Caching for GPU Particle Tracing in Turbulent Vector Fields. In: Braz, J., et al. Computer Vision, Imaging and Computer Graphics Theory and Applications. VISIGRAPP 2015. Communications in Computer and Information Science, vol 598. Springer, Cham. https://doi.org/10.1007/978-3-319-29971-6_8

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  • DOI: https://doi.org/10.1007/978-3-319-29971-6_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-29970-9

  • Online ISBN: 978-3-319-29971-6

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