adaptive visualization of dynamic unstructured meshesstevec/slides/proposal/proposal.pdfthe proposal...

Adaptive Visualization of Dynamic Unstructured

Meshes

Steven P. Callahan

Advisor: Dr. Cláudio T. Silva

Scientific Computing and Imaging Institute,University of Utah

The Problem

‣ Large-scale simulations produce a lot of data

‣ Interactive visualization techniques not keeping up

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The Problem

Earthquake Simulation14 Million Tetrahedra

CORIE EOFS6 Million Tetrahedra

96 Scalar Time Steps

Heart Simulation48 Higher Order Cells920 Vertex Time Steps

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The Vision

‣ Data exploration

‣ Fast interaction

‣ Multiple configurations

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The Vision

‣ Data exploration

‣ Fast interaction

‣ Multiple configurations

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The Vision

‣ Data exploration

‣ Fast interaction

‣ Multiple configurations

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The Proposal

‣ Adaptive Visualization of Dynamic Unstructured Meshes

‣ Adaptive Volume Rendering

‣ Dynamic Scalars

‣ Dynamic Geometry

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Adaptive Volume Rendering

‣ Hardware-Assisted Visibility Sorting (HAVS)

‣ Sort in Object Space (CPU)

‣ Sort in Image Space (GPU)

‣ http://havs.sf.net

‣ 130 downloads (~15/mo.)

‣ VTK/ParaView

‣ Hardware Proposal

Unstructured Volume Rendering

Algorithms vs. Hardware

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10

100

1000

10000

100000

1000000

10000000

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Year

Te

tra

he

dra

/Se

co

nd

Algorithms

Hardware

Projected

Tetrahedra

Incremental

Slicing

GATOR

HW Ray

Casting

HAVS

Log Scale

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Adaptive Volume Rendering

‣ Dynamic Level-of-Detail

‣ Domain- vs. Sample-based simplification

‣ Importance sampling

‣ Dynamically adjusts the number of triangles rendered at each frame

‣ 10-15 million tets/sec

r r r

t

g1(t) g

2(t)g(t)

tt

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Adaptive Volume Rendering

‣ Point-Based Volume Rendering

‣ Points are more flexible

‣ Large datasets have subpixel-size geometry

‣ Minimize error by approximating cells

‣ LOD improved with point resizing

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Progressive Volume Rendering

3%0.01 sec

33%7 sec

66%18 sec

100%34 sec

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Progressive Rendering

‣ Progressive Rendering‣ Show intermediate results‣ Reuse intermediate results‣ Allow user interrupt‣ Only render pertinent data

‣ Client-Server Architecture‣ Support a thin client with limited memory‣ Standard server used as a data repository‣ Facilitate remote visualization

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Progressive Rendering

‣ The Server

‣ Preprocess

‣ Geometry Server

‣ Octree Traversal

‣ Object-Space Sort

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Progressive Rendering

‣ The Client

‣ Preprocess

‣ Interactive Mode

‣ Boundaries only

‣ Progressive Mode

‣ Complete, Active, and Progressive buffers

‣ Completed Mode

‣ Final image displayed and stored

ProgressiveComplete Active

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Progressive Rendering

‣ Facilitates fine-scale exploration

‣ Allows remote and out-of-core rendering for large datasets

‣ A variety of configurations are possible

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Time-Varying Scalar Fields

‣ Volume Rendering

‣ Dynamic Level-of-Detail

‣ Compression & Data Transfer

‣ Parallel Processing16

Time-Varying Scalar Fields

‣ Volume Rendering

‣ Dynamic Level-of-Detail

‣ Compression & Data Transfer

‣ Parallel Processing17

Time-Varying Scalar Fields

‣ Volume Rendering

‣ Dynamic Level-of-Detail

‣ Compression & Data Transfer

‣ Parallel Processing18

Time-Varying Scalar Fields

‣ Importance sampling for time varying scalar fields

‣ Local sampling

‣ Global sampling

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Time-Varying Scalar Fields

‣ Volume Rendering

‣ Dynamic Level-of-Detail

‣ Compression & Data Transfer

‣ Parallel Processing20

Time-Varying Scalar Fields

Uncompressed Compressed21

Time-Varying Scalar Fields

‣ Volume Rendering

‣ Dynamic Level-of-Detail

‣ Compression & Data Transfer

‣ Parallel Processing22

Time-Varying Scalar Fields

‣ Achieves about 3 Million tetrahedra/second

‣ Only a 5% increase over static rendering

‣ Adaptive for large datasets

‣ Efficient use of resources

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Time-Varying Geometry

‣ Future Work

‣ Focus on compression/decompression

‣ Data transfer may need to be revisited

‣ Point-based or triangle based rendering?

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‣ Dynamic Topology

‣ Higher Order Elements

‣ Future Hardware

Out of Scope

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The Progress

Adaptive Volume Rendering

Time-Varying Scalars

Time-Varying Geometry

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The Progress

‣Hardware-Assisted Visibility Sorting for Unstructured Volume Rendering, S. Callahan, M. Ikits, J. Comba, and C. Silva, IEEE Transactions on Visualization and Computer Graphics, 11(3):285–295, 2005.‣Interactive Rendering of Large Unstructured Grids Using Dynamic Level-Of-Detail, S. Callahan, J. Comba, P. Shirley, and C. Silva. IEEE Visualization, pp. 199–206, 2005. ‣Progressive Volume Rendering of Large Unstructured Grids, S. Callahan, L. Bavoil, V. Pascucci, C. Silva, IEEE Transactions on Visualization and Computer Graphics (Proceedings of Visualization 2006), 12(5), pp. 1307-1314, 2006. ‣Interactive Volume Rendering of Unstructured Grids with Time-Varying Scalar Fields, F. Bernardon, S. Callahan, J. Comba, and C. Silva. Eurographics Symposium on Parallel Graphics and Visualization, pp. 51–58, 2006.. ‣An Adaptive Framework for Visualizing Unstructured Grids with Time-Varying Scalar Fields, F. Bernardon, S. Callahan, J. Comba, C. Silva. Parallel Computing, 2006, submitted.‣Multi-Fragment Effects on the GPU using the k-Buffer, L. Bavoil, S. Callahan, A. Lefohn, J. Comba, C. Silva, ACM Symp. on Interactive 3D Graphics and Games (i3D). 2007, to appear‣Hardware-Assisted Point-Based Volume Rendering, E. Anderson, S. Callahan, C. Scheidegger, J. Schreiner, C. Silva. 2006, submitted.‣iRun: Interactive Rendering of Large Unstructured Grids, H. Vo, S. Callahan, N. Smith, C. Silva, W. Martin, D. Owen, D. Weinstein. 2006, submitted.‣Interactive Transfer Function Specification for Direct Volume Rendering of Disparate Volumes, F. Bernardon, L. Ha, S. Callahan, J. Comba, C. Silva. 2006, submitted.

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Dissertation Outline

1 Introduction2 Related Work3 Background

3.1 HAVS3.2 Dynamic LOD

4 Adaptive Volume Rendering4.1 Point-based Volume Rendering4.2 Progressive Volume Rendering

5 Time-Varying Scalar Fields6 Time-Varying Geometry7 Discussion8 Conclusion

Target Graduation: Spring 2008Target Employment: Academia/Research Institution

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Acknowledgments

‣ Advisor‣ Cláudio T. Silva

‣ Collaborators‣ Erik W. Anderson‣ Louis Bavoil‣ Fábio F. Bernardon‣ João L. D. Comba‣ Milan Ikits‣ Linh H. Ka‣ Aaron Lefohn‣ Valerio Pascucci‣ John Schreiner ‣ Peter Shirley‣ Huy T. Vo

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