1. Amit Chourasia Visualization Scientist San Diego Supercomputer Center Presented at : Scientific Computing Institute, Univ. of Utah. Jun 20, 2007 Scientific Visualization Case Studies

2. Large? Data? What kind of data? Simulations of earthquakes, CFD, astrophysics, molecular modeling, etc Floating point How large? Time varying and multivariate (1000’s of timesteps) Usually 10’s of TB >1024x1024x1024 floats

3. Problems How to verify and validate ? How to analyze ? How to gain scientific insight ? How to share information among experts and non-experts ?

4. Understanding Data Large amount of numbers don’t make much sense to humans Visual information can encode large amount of numbers to gain insight Low Bandwidth High Bandwidth

5. Seismic - TeraShake Simulation TeraShake 2.1 Comparison of TS1.2 – TS1.3 Short and simple Web Collab: SCEC Kim Olsen et. al. Circa 07

6. Seismic - SCEC Viz portal Collab: SCEC Kim Olsen et. al.

7. Seismic - Puente Hills Simulation Movie Web Collab: SCEC Ned Fields et. al.

8. Seismic - Recreation of 1906 San Francisco Earthquake North Bound South Bound Collab: USGS Brad Aagaard et. al.

9. Climate Simulation River Flow 3D River Flow Top Collab: UCSD LLNL Tim Barnett et. al.

10. CFD Simulation Collab: GaTech P.K. Yeung et. al.

11. Enzo – Universe Simulation Matter Density Dark Matter Density Temperature Collab: UCSD LLNL Mike Norman et. al.

12. Data Centric Transfer Functions Circa 07

13. Molecular Modelling Movie Collab: NREL

14. Real Data?

15. Cancer Center Visualization Visualization Expertise Supercomputers Software Development Visualization Tools Shared Staff SDSC UCSD Cancer Center Cancer Expertise Medical Expertise Latest Microscopy Tools Cancer Research Scientists Computational Scientists Research Intern 1 Research Scientist Images Animations Movies

16. The Cellular Imaging Gateway Web Portal for Cellular Imaging. Image generation. Animation creation. Analysis Functions. Distributed processing. Cluster integration. Remote operation

17. Core Features Complete access through standard web browser. Data set uploads from the microscope and desktop. Submit jobs to remote clusters. Review results as arrive. Notification of results Monitor results anywhere.

18. Seismic – 7 Story Building Original video Match Check Match Top Bottom Combined Perspective npr Roof npr Site 3d model Collab: NEES Jose Resptrepo et. al. Circa 07

19. Data Issues Data Formats Data Translation Data transfer and replication between archival and active file systems Data larger than memory available

20. Viz Issues Domain knowledge Multivariate data representation Temporal coherence Precision Loss (compression,etc) Interaction vs batch visualization Perceptual Issues Personal Bias (author & viewer)

21. Tools we use to Visualize Vista (SDSC/NPACI) – Batch Volume renderer Mesh Viewer (SDSC/NPACI) – Interactive Volume Renderer DeskVox – Interactive Volume Renderer Autodesk’s Maya – 3D animation software Adobe’s suite (After Effects, Photoshop, Illustrator) Other things that work

22. Does Viz work? Collab: SCEC Kim Olsen et. al.

23. Does Viz work? Collab: SCEC Kim Olsen et. al. Circa 07

24. Lessons Learned (TeraShake) In the north-westward propagating rupture scenario the wave propagation is strongly guided toward the Los Angeles basin after leaving the San Andreas Fault (unexpected) The sediment filled basin acts as an amplification source for trapped waves. A Strong amplification is observed in the LA basin long after the initial rupture (unexpected) Contiguous basins act as energy channels, enhancing ground motion in parts of the San Gabriel and Los Angeles basins. Identification of regions of particularly strong shaking Validation of input rupture model and instability identification Observation of star burst patterns in the Spectral Amplification maps (unexpected) 24 Circa 07

25. Viz People @ SDSC Visservices Steve Cutchin Alex Decastro Amit Chourasia Synthesis Center David Nadeau John Moreland

26. Information is infinite Information overload Can’t win Can’t break even Can’t get out of the game Can visualization help? Think Petascale Data Analysis Joseph Kielman Science Advisor Dept. of Homeland Security Comments at VAST2006 Capstone 26

27. Thanks for your patience ? - Web: http://visservices.sdsc.edu/ http://visservices.sdsc.edu/