Afrigraph 2004 Tutorial A: State of the Art in Massive Model Visualization

1. INFORMATIK Afrigraph 2004 Tutorial A:State of the Art inMassive Model Visualization Ingo Wald MPI für Informatik Saarbrücken, Germany Andreas Dietrich Saarland University Saarbrücken, Germany

2. The Speakers • Ingo Wald (http://www.mpi-sb.mpg.de/~wald) • Post-doc MPI für Informatik (MPII) Saarbrücken • Main research topics: • Realtime ray tracing (core technologies) • Parallel/distributed rendering • (Interactive) Global Illumination • Andreas Dietrich (http://graphics.cs.uni-sb.de/~dietrich) • Third-year PhD student, Saarland University • Main research topics: • Out-of-core rendering (in particular high-quality OOC rendering) • Realtime Ray Tracing in practical applications (VR, SceneGraphs) Afrigraph 2004 Tutorial A

3. Agenda • Motivation and Introduction [10-15m, Wald] • Part I – Rasterization Based Approaches [1h, Dietrich] • General techniques and concepts • Discussion and classification • Specific rasterization-based massive model rendering systems • Break [15m] • Part II – Ray Tracing Based Approaches [1h, Wald] • Why ray tracing for massively complex models ? • Offline systems • Interactive systems • Summary and Audience Discussion [open end, audience] Afrigraph 2004 Tutorial A

4. Motivation and Introduction

5. Motivation • Rendering a model  Visible surface determination • Basic problem believed to be be solved • Hidden Surface Removal (HSR) methods of choice: • Z-buffer • Ray casting • Dramatic improvements in CG hardware • Can render many million triangles / second • Widely available even in consumer PCs • Ongoing trend to more and more performance • Even faster than Moore’s law: ~2.x performance increase / year Afrigraph 2004 Tutorial A

6. Motivation • Rendering a model  Visible surface determination • Basic problem believed to be be solved • Hidden Surface Removal (HSR) methods of choice: • Z-buffer • Ray casting • Dramatic improvements in CG hardware • Can render many million triangles / second • Widely available even in consumer PCs • Ongoing trend to more and more performance • Even faster than Moore‘s law: ~2.x performance increase / year However: Scene complexity rises even faster Afrigraph 2004 Tutorial A

7. Motivation • Quickly rising scene complexity: • Many scenes too large to be rendered by “brute force” • Definition of “massively complex model”: A model that can’t be handled by standard techniques Afrigraph 2004 Tutorial A

8. Motivation • Quickly rising scene complexity: • Many scenes too large to be rendered by “brute force” • Definition of “massively complex model”: A model that can’t be handled by standard techniques • Many sources for such models… • “Modelling nature” … Real-world complexity • Acquisition/measuring equipment • Scientific computing / simulation datasets • Large-scale engineering projects Afrigraph 2004 Tutorial A

9. Motivation Example I:Modelling nature • “Real world” is excessively complex • Trees (leaves), grass, hair/fur, (fractal) surface structure (stone, bark,…) • Interactive apps allow zooming in  would like high complexity • Modelling only „some“ of these effects generates many triangles Landscape scene [Wand] (4*10^8 triangles) “Sunflowers” scene (10^9 triangles) Afrigraph 2004 Tutorial A

10. Motivation Example II:Acquisition of Real-world objects • Modelled objects often look “artificial” … • Increasing use of “real” objects  Acquisition • Tremendous improvements in measuring equipment (sub-mm accuracy) • Millions to billions of samples / object “Visible Female” 1700+ images of 2k*2k pixels Eye of “David” (1mm accuracy) Even shows chisel marks “Lucy” – 15M points Afrigraph 2004 Tutorial A

11. Motivation Example III:Scientific / simulation datasets • More and more effects today get simulated • Atom bombs, jet engine combustion, airflow, drugs/molecules, … • Tremendous increase in simulation accuracy • Immensely huge datasets Lawrence-Livermore “Richtmeyer-Meshkov simulation” (single time step only) 270 time steps @ 2048x2048x1970 samples  1.5 TeraByte data (sev. years old…) Afrigraph 2004 Tutorial A

12. Motivation Example III:Scientific / Numerical simulation • More and more effects today get simulated • Atom bombs, jet engine combustion, airflow, drugs/molecules, … • Tremendous increase in simulation accuracy • Immensely huge datasets Lawrence-Livermore “Richtmeyer-Meshkov simulation” (single time step only) 270 time steps @ 2048x2048x1970 samples  1.5 TeraByte data (sev. years old…) Afrigraph 2004 Tutorial A

13. Motivation Example IV:Large-scale engineering projects • Virtual prototyping / CAD ever more important • Applied to ever larger engineering projects • cars, airplanes, power plants, ships, … • Large scale projects too complex for single designer  Collaborative engineering • Coll.eng.:Many designers, each models individual parts • Each individual part modelled at full accuracy • Steering wheel: 1-2M tris, Safety belt: 1-2M, screw: 1-10k… • CAD uses NURBS: Growing accuracy demands  Each individual part is already at the FGX card‘s limit • Combined model (sum of all parts…) far too complex • Golf V: ~2,000 parts, 20M triangles • Boeing 777: ~13,000 parts, 350M triangles (sev. years old) Afrigraph 2004 Tutorial A

14. Motivation Example IV:Large-scale engineering projects “Power Plant” – 12.5M triangles “Boeing 777” – 350M triangles “Double eagle tanker” – 80M triangles Afrigraph 2004 Tutorial A

15. Geometric Complexity:Boeing Example… Afrigraph 2004 Tutorial A

16. Geometric Complexity:Boeing Example… Afrigraph 2004 Tutorial A

17. Geometric Complexity:Boeing Example… Afrigraph 2004 Tutorial A

18. Geometric Complexity:Boeing Example… Same complexity all over the model… Afrigraph 2004 Tutorial A

19. Motivation Wrap-up Motivation wrap-up: Three important conclusions Afrigraph 2004 Tutorial A

20. Motivation Wrap-up Motivation wrap-up: Three important conclusions • Complex models ARE important • Come from many different fields • Acquisition, nature/outdoor, simulation, engineering, … • Important for many real-world applications Afrigraph 2004 Tutorial A

21. Motivation Wrap-up Motivation wrap-up: Three important conclusions • Complex models ARE important • Come from many different fields • Acquisition, nature/outdoor, simulation, engineering, … • Important for many real-world applications • Rendering performance increases rapidly…… but model size grows even faster • There will be “massively complex models” even in 10 years… Afrigraph 2004 Tutorial A

22. Motivation Wrap-up Motivation wrap-up: Three important conclusions • Complex models ARE important • Come from many different fields • Acquisition, nature/outdoor, simulation, engineering, … • Important for many real-world applications • Rendering performance increases rapidly…… but model size grows even faster • There will be “massively complex models” even in 10 years… • It’s important to find techniques for rendering them • Todays “complex” models are tomorrows “standard” models Afrigraph 2004 Tutorial A