Hostname: page-component-8448b6f56d-tj2md Total loading time: 0 Render date: 2024-04-24T08:19:46.667Z Has data issue: false hasContentIssue false
  • English
  • Français

A Distributed GPU-Based Framework for Real-Time 3D Volume Rendering of Large Astronomical Data Cubes

Published online by Cambridge University Press:  02 January 2013

A. H. Hassan ,
C. J. Fluke  and
D. G. Barnes
A. H. Hassan*
Affiliation:
Centre for Astrophysics & Supercomputing, Swinburne University of Technology, Hawthorn, Vic. 3122, Australia
C. J. Fluke
Affiliation:
Centre for Astrophysics & Supercomputing, Swinburne University of Technology, Hawthorn, Vic. 3122, Australia
D. G. Barnes
Affiliation:
Monash e-Research Centre, Monash University, Clayton, Vic. 3800, Australia
*
CCorresponding author. Email: ahassan@swin.edu.au
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

We present a framework to volume-render three-dimensional data cubes interactively using distributed ray-casting and volume-bricking over a cluster of workstations powered by one or more graphics processing units (GPUs) and a multi-core central processing unit (CPU). The main design target for this framework is to provide an in-core visualization solution able to provide three-dimensional interactive views of terabyte-sized data cubes. We tested the presented framework using a computing cluster comprising 64 nodes with a total of 128 GPUs. The framework proved to be scalable to render a 204 GB data cube with an average of 30 frames per second. Our performance analyses also compare the use of NVIDIA Tesla 1060 and 2050 GPU architectures and the effect of increasing the visualization output resolution on the rendering performance. Although our initial focus, as shown in the examples presented in this work, is volume rendering of spectral data cubes from radio astronomy, we contend that our approach has applicability to other disciplines where close to real-time volume rendering of terabyte-order three-dimensional data sets is a requirement.

Keywords

methods: data analysistechniques: miscellaneous
Type
Research Article
Information
Publications of the Astronomical Society of Australia , Volume 29 , Special Issue 3: Source Finding and Visualisation , 2012 , pp. 340 - 351
Copyright
Copyright © Astronomical Society of Australia 2012

References

Becciani, U., Antonuccio-Delogu, V., Gheller, C., Calori, L., Buonomo, F. & Imboden, S., 2000, Arxiv preprint (astro-ph/0006402)Google Scholar
Becciani, U., Antonuccio-Delogu, V., Buonomo, F. & Gheller, C., 2001, Arxiv preprint (astroph/0101447)Google Scholar
Becciani, U., Gheller, C., Antonuccio, V., Ferro, D. & Melotti, M., 2003, MmSAIS, 1, 80Google Scholar
Beeson, B., Barnes, D. & Bourke, P., 2003, PASA, 20, 300Google Scholar
Booth, R., De Blok, W., Jonas, J. & Fanaroff, B., 2009, Arxiv preprint (arXiv:09 10.2935)Google Scholar
Comparato, M., Becciani, U., Costa, A., Larsson, B., Garilli, B., Gheller, C. & Taylor, J., 2007, PASP, 119, 898CrossRefGoogle Scholar
Eilemann, S., Makhinya, M. & Pajarola, R., 2008, in ACM SIGGRAPH ASIA 2008 courses (New York: ACM), 44Google Scholar
Gheller, C., Buonomo, F., Calori, L. & Becciani, U., 2002, in Proceedings of Joint Eurographics-IEEE TCVG Symposium on Visualization (Barcelona: Eurographics Association), 1Google Scholar
Goel, V. & Mukherjee, A., 1996, The Visual Computer, 12, 26Google Scholar
Gooch, R., 1995, in Proceedings of the 6th Conference on Visualization '95 (Washington, DC: IEEE Computer Society), 374CrossRefGoogle Scholar
Hassan, A. H. & Fluke, C., 2010, PASA, 122, 119Google Scholar
Hassan, A., Fluke, C. & Barnes, D., 2011, NewA, 16, 100CrossRefGoogle Scholar
Hockney, R. & Eastwood, J., 1988, Computer Simulation Using Particles (London: Taylor & Francis)CrossRefGoogle Scholar
Humphreys, G., Houston, M., Ng, R., Frank, R., Ahern, S., Kirchner, P. & Klosowski, J., 2008, in ACM SIGGR APH ASIA 2008 courses (New York: ACM), 43Google Scholar
Jin, Z., Krokos, M., Rivi, M., Gheller, C., Dolag, K. & Reinecke, M., 2010, ArXiv 1004.1302Google Scholar
Johnston, S., et al. , 2008, ExA, 22, 151Google Scholar
Kaehler, R., Wise, J., Abel, T. & Hege, H., 2006, in Eurographics/IEEE VGTC Workshop on Volume Graphics, ed. Machiraju, R. & Moller, T. (Boston: Eurographics Association), 103Google Scholar
Kaufman, A., 1998, SIGGRAPH Course notes, Advances in Volume Visualization 24Google Scholar
Lacroute, P. & Levoy, M., 1994, in Proc. 21st Annual Conference on Computer Graphics and Interactive Techniques (New York: ACM), 451Google Scholar
Levoy, M., 1988, ICGA, 8, 29Google Scholar
Levoy, M., 1990, ACM Transactions on Graphics (TOG), 9, 245CrossRefGoogle Scholar
Lombeyda, S., Moll, L., Shand, M., Breen, D. & Heirich, A., 2001, in PVG '01: Proceedings of the IEEE 2001 Symposium on Parallel and Large-Data Visualization and Graphics (Piscataway: IEEE Press), 115Google Scholar
Magnor, M., Hildebrand, K., Lintu, A. & Hanson, A., 2005, in IEEE Visualization 2005, VIS 05 (Washington, DC: IEEE Computer Society), 255CrossRefGoogle Scholar
Marmitt, G., Friedrich, H. & Slusallek, P., 2008, in Computer Graphics Forum, Vol. 27 (New York: John Wiley & Sons), 1687Google Scholar
Maximo, A., Ribeiro, S., Bentes, C., Oliveira, A. & Farias, R., 2008, in IEEE/EG Int. Symp. Volume and Point-Based Graph., ed. Hege, H. C., Laidlaw, D., Pajarola, R. & Staadt, O. (Barcelona: Eurographics Association), 55Google Scholar
McClure-Griffiths, N. M., et al. , 2009, ApJS, 181, 398CrossRefGoogle Scholar
Molnar, S., Cox, M., Ellsworth, D. & Fuchs, H., 2008, in ACM SIGGRAPH ASIA 2008 courses (New York: ACM), 35Google Scholar
Muller, C., Strengert, M. & Ertl, T., 2006, in Proc. EG Symp. Parallel Graphics Vis. (PGV), ed. Heirich, A., Raffin, B. & Santos, L. P. dos (Barcelona: Eurographics Association), 59Google Scholar
Muller, C., Strengert, M. & Ertl, T., 2007, ParC, 33, 406Google Scholar
Nadeau, D., Genetti, J., Napear, S., Pailthorpe, B., Emmart, C., Wesselak, E. & Davidson, D., 2001, Computer Graphics Forum, 20, 27Google Scholar
Oosterloo, T., 1995, PASA, 12, 215Google Scholar
Oosterloo, T., 1996, VA, 40, 571Google Scholar
Payne, H., Jedrzejewski, R. & Hook, R., 2003, ADASS, 12, 449Google Scholar
Röttgering, H., 2003, NewAR, 47, 405Google Scholar
Scharsach, H., 2005, Proceedings of CESCG, 5, 67Google Scholar
Schwarz, N., 2007, Master's Thesis, University of IllinoisGoogle Scholar
Strengert, M., Klein, T., Botchen, R., Stegmaier, S., Chen, M. & Ertl, T., 2006, The Visual Computer, 22, 550CrossRefGoogle Scholar
Stuart, J. A., Chen, C.-K., Ma, K.-L. & Owens, J. D., 2010, in HPDC '10: Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing, ed. Hariri, S. & Keahey, K. (New York: ACM), 841CrossRefGoogle Scholar
Wallis, J., Miller, T., Lerner, C. & Kleerup, E., 1989, IEEE Transactions on Medical Imaging, 8, 297Google Scholar
Westover, L., 1990, ACM SIGGRAPH Computer Graphics, 24, 376Google Scholar