This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Query-Driven Visualization of Time-Varying Adaptive Mesh Refinement Data
November/December 2008 (vol. 14 no. 6)
pp. 1715-1722
ASCII Text
x 
 
Luke J. Gosink, John C. Anderson, E. Wes Bethel, Kenneth I. Joy, "Query-Driven Visualization of Time-Varying Adaptive Mesh Refinement Data," IEEE Transactions on Visualization and Computer Graphics, vol. 14, no. 6, pp. 1715-1722, November/December, 2008.
 
 
BibTex
x
 
@article{ 10.1109/TVCG.2008.157,
author = {Luke J. Gosink and John C. Anderson and E. Wes Bethel and Kenneth I. Joy},
title = {Query-Driven Visualization of Time-Varying Adaptive Mesh Refinement Data},
journal ={IEEE Transactions on Visualization and Computer Graphics},
volume = {14},
number = {6},
issn = {1077-2626},
year = {2008},
pages = {1715-1722},
doi = {http://doi.ieeecomputersociety.org/10.1109/TVCG.2008.157},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Visualization and Computer Graphics
TI - Query-Driven Visualization of Time-Varying Adaptive Mesh Refinement Data
IS - 6
SN - 1077-2626
SP1715
EP1722
EPD - 1715-1722
A1 - Luke J. Gosink,
A1 - John C. Anderson,
A1 - E. Wes Bethel,
A1 - Kenneth I. Joy,
PY - 2008
KW - Index Terms—AMR
KW - Query-Driven Visualization
KW - Multitemporal Visualization
VL - 14
JA - IEEE Transactions on Visualization and Computer Graphics
ER -
 
The visualization and analysis of AMR-based simulations is integral to the process of obtaining new insight in scientific research. We present a new method for performing query-driven visualization and analysis on AMR data, with specific emphasis on time-varying AMR data. Our work introduces a new method that directly addresses the dynamic spatial and temporal properties of AMR grids that challenge many existing visualization techniques. Further, we present the first implementation of query-driven visualization on the GPU that uses a GPU-based indexing structure to both answer queries and efficiently utilize GPU memory. We apply our method to two different science domains to demonstrate its broad applicability.

[1] A. Almgren, J. Bell, P. Colella, L. Howell, and M. Welcome, A conservative adaptive projection method for the variable density incompressible Navier-Stokes equations. J. Comput. Phys., 142 (1): 1–46, 1998.
[2] C. L. Bajaj, V. Pascucci, G. Rabbiolo, and D. Schikorc, Hypervolume visualization: a challenge in simplicity. In Proc. of IEEE Symposium on Volume Visualization, pages 95–102, 1998.
[3] J. Becla and D. L. Wang, Lessons learned from managing a petabyte. In Conference on Innovative Data Systems Research, pages 70–83, 2005.
[4] J. Bell, M. S. Day, C. A. Rendleman, S. E. Woosley, and M. A. Zingale, Adaptive low Mach number simulations of nuclear flame microphysics. J. Comput. Phys., 195 (2): 677–694, 2004.
[5] M. Berger and J. Oliger, Adaptive mesh refinement for hyperbolic partial differential equations. J. Comput. Phys., 53 (3): 484–512, Mar. 1984.
[6] M. J. Berger and P. Colella, Local adaptive mesh refinement for shock hydrodynamics. J. Comput. Phys., 82 (1): 64–84, May 1989.
[7] E. W. Bethel, S. Campbell, E. Dart, K. Stockinger, and K. Wu, Accelerating Network Traffic Analysis Using Query-Driven Visualization. In Proc. of IEEE Symposium on Visual Analytics Science and Technology, pages 115–122, Oct. 2006.
[8] P. Bhaniramka, R. Wenger, and R. Crawfis, Isosurfacing in higher dimensions. In Proc. of IEEE Visualization, pages 267–273, 2000.
[9] L. Gosink, J. C. Anderson, E. W. Bethel, and K. I. Joy, Variable interactions in query driven visualization. In IEEE Trans. on Visualization and Computer Graphics, volume 13, pages 1400–1407, Nov. 2007.
[10] L. Gosink, K. Wu, E. W. Bethel, J. Owens, and K. Joy, Bin-Hash Indexing: A Parallel Method for Fast Query Processing. Technical Report LBNL-729E, Lawrence Berkeley National Laboratory, 2008. http://www.vis.lbl.gov/Publications/2008 LBNL-729E.pdf.
[11] J. Gray, D. T. Liu, M. A. Nieto-Santisteban, A. S. Szalay, D. J. DeWitt, and G. Heber, Scientific data management in the coming decade. SIGMOD Record, 34 (4): 34–41, 2005.
[12] A. J. Hanson and R. A. Cross, Interactive visualization methods for four dimensions. In Proc. of IEEE Visualization, pages 196–203, 1993.
[13] A. J. Hanson and P. A. Heng, Illuminating the fourth dimension. IEEE Comput. Graph. Appl., 12 (4): 54–62, 1992.
[14] R. Kähler and H.-C. Hege, Texture-based volume rendering of adaptive mesh refinement data. The Visual Computer, 18 (8): 481–492, 2002.
[15] R. Kähler, S. Prohaska, A. Hutanu, and H.-C. Hege, Visualization of time-dependent remote adaptive mesh refinement data. In IEEE Visualization, page 23, 2005.
[16] R. Kähler, J. Wise, T. Abel, and H.-C. Hege, GPU-assisted raycasting for cosmological adaptive mesh refinement simulations. In Proc. of Volume Graphics: Eurographics Assoc., 2006.
[17] S. Lefebvre and H. Hoppe, Perfect spatial hashing. ACM Trans. on Graphics, 25 (3): 579–588, 2006.
[18] T. J. Ligocki, B. V. Straalen, J. M. Shalf, G. H. Weber, and B. Hamann, A Framework for Visualizing Hierarchical Computations, pages 197–204. Jan. 2003.
[19] K.-L. Ma, Parallel Rendering of 3D AMR Data on the SGI/Cray T3E. In Proc. of the Symposium on the Frontiers of Massively Parallel Computation, pages 138–145, Feb. 1999.
[20] N. L. Max, Sorting for polyhedron compositing. In Focus on Scientific Visualization, pages 259–268, 1993.
[21] M. L. Norman, J. Shalf, S. Levy, and G. Daues, Diving deep: Data-management and visualization strategies for adaptive mesh refinement simulations. Computing in Science and Eng., 1 (4): 36–47, 1999.
[22] NVIDIA Corporation. NVIDIA CUDA compute unified device architecture programming guide. http://developer.nvidia.comcuda, Jan. 2007.
[23] S. Park, C. L. Bajaj, and V. Siddavanahalli, Case study: interactive rendering of adaptive mesh refinement data. In Proc. IEEE Visualization, pages 521–524, 2002.
[24] K. Stockinger, E. W. Bethel, S. Campbell, E. Dart, and K. Wu, Imaging and visual analysis - detecting distributed scans using high-performance query-driven visualization. In Supercomputing, page 82, 2006.
[25] K. Stockinger, J. Shalf, E. W. Bethel, and K. Wu, Dex: Increasing the capability of scientific data analysis pipelines by using efficient bitmap indices to accelerate scientific visualization. In Scientific and Statistical Database Management, pages 35–44, 2005.
[26] K. Stockinger, J. Shalf, K. Wu, and E. W. Bethel, Query-driven visualization of large data sets. In Proc. of IEEE Visualization, pages 167–174, 2005.
[27] G. H. Weber, H. Hagen, B. Hamann, K. I. Joy, T. J. Ligocki, K.-L. Ma, and J. M. Shalf, Visualization of adaptive mesh refinement data. In Proc. of Visual Data Exploration and Analysis VIII, volume 4302, pages 121–132, Jan. 2001.
[28] G. H. Weber, O. Kreylos, T. J. Ligocki, J. M. Shalf, H. Hagen, B. Hamann, and K. I. Joy, Extraction of crack-free isosurfaces from adaptive mesh refinement data. In Proc. of Joint EUROGRAPHICS and IEEE TCVG Symposium on Visualization, pages 25–34, 335, May 2001.
[29] G. H. Weber, O. Kreylos, T. J. Ligocki, J. M. Shalf, H. Hagen, B. Hamann, K. I. Joy, and K.-L. Ma, High-quality volume rendering of adaptive mesh refinement data. In Vision, Modeling, and Visualization 2001, pages 121–128, 522, Nov. 2001.
[30] J. Woodring and H.-W. Shen, Chronovolumes: a direct rendering technique for visualizing time-varying data. In Proc. of Eurographics/IEEE TVCG Workshop on Volume Graphics, pages 27–34, 2003.
[31] J. Woodring, C. Wang, and H.-W. Shen, High dimensional direct rendering of time-varying volumetric data. In Proc. of IEEE Visualization, page 55, 2003.
[32] K. Wu, W. S. Koegler, J. Chen, and A. Shoshani, Using bitmap index for interactive exploration of large datasets. In Scientific and Statistical Database Management, pages 65–74, 2003.
[33] K. Wu, E. J. Otoo, and A. Shoshani, On the performance of bitmap indices for high cardinality attributes. In Proc. of Very Large Data Bases, pages 24–35, 2004.

Index Terms:
Index Terms—AMR, Query-Driven Visualization, Multitemporal Visualization
Citation:
Luke J. Gosink, John C. Anderson, E. Wes Bethel, Kenneth I. Joy, "Query-Driven Visualization of Time-Varying Adaptive Mesh Refinement Data," IEEE Transactions on Visualization and Computer Graphics, vol. 14, no. 6, pp. 1715-1722, Nov.-Dec. 2008, doi:10.1109/TVCG.2008.157
Usage of this product signifies your acceptance of the Terms of Use.