1. National Center for Supercomputing Applications University of Illinois at Urbana–Champaign Practical HPC Visualization Mark Van Moer Visualization Programmer Advanced Digital Services NCSA/XSEDE/Blue Waters

2. SciVis – InfoVis Spectrum SciVis InfoVis Specific geometry and topology – meshes, coordinates, … Physical data – temp, pressure, charge, … Natural processes – weather, CFD, MD, … Arbitrary spatial arrangement – modifiable network graphs Cultural data – text, census data, music, … Relationships – statistical, social graphs, …

3. SciVis – InfoVis Spectrum

4. General – Domain Specific Applications General ParaView VisIt Selected Domain Specific VMD (molecular dynamics)VMD NCL/NCARG (climate/weather)NCL/NCARG Ovito (atomistic)Ovito Gephi (network graphs)Gephi Tableau (info vis)Tableau VAPOR (atmos/oceanography)VAPOR yt (astro, but evolving into general)yt

5. ParaView and VisIt Widely supported at HPC centers Open source Built on VTK C++ library Python scriptable Can build Java wrappers; Fortran bindings for in-situ Batch processing Client-Server interactivity In-situ steering/co-processing Scalable

6. ParaView and VisIt Approaches ParaView Bottom-up Load source Apply filter(s) to create vis pipeline Pick visual representation VisIt Top-down Load source Chose plotting style Refine plot through plot attributes or operators/operator attributes

7. ParaView Wiki Client GUI section

8. Sample data In /scratch/staff/mvanmoer/public/ Regular orthogonal mesh (vtkImageData) Pressure, temperature, wind vector 110x110x35

9. Scalars – Color Mapping

10. Scalars – 2D Contouring

11. Scalars – 3D Contouring, Isosurfaces

12. Scalars – Layering Isosurfaces

13. Scalars – Volume Rendering

14. Vectors - Glyphs

15. Vectors - Warping

16. Vectors – Streamlines/Path Lines/Particles

17. Combining Techniques

18. Pain Points for HPC Vis Anything requiring unknown amount of communication Streamlines/Path Lines Ray tracing Alpha blending Image compositing Gather step for vis I/O Non-linear finite elements Will load, but few VTK algorithms work correctly Animation Entire pipeline has to be recreated each step Pipelines with history (path lines) have to cache steps

19. Blue Waters Architecture from a Vis Perspective Do not use X11 forwarding, extremely slow and clunky! Interactive jobs on Mom nodes, must use aprun Run ParaView or VisIt directly only on compute nodes, via ccm VisIt client can launch remote jobs via host-profiles ParaView is clunkier, working on host-profile equivalent Workstation Login node Mom node XE node(s) firewall

20. Remote Vis

21. In-situ vis Connect to running simulations instead of loading data Steering Data too large to store Don’t want to store data, I/O too slow or unnecessary VisIt libsim2 ParaView Catalyst

22. General Vis Workflow Suggestions Unless allocation is vis-specific, don’t waste SUs on mundane tasks, work locally: Extract region of interest or sub-sample Export scene/session from VisIt or ParaView, batch render Export polygonal data from end of vis pipeline Save camera settings often Save scene settings often Look at provenance plugins, like VisTrails Reset the default colormap and background color Render at 4X and down sample for anti-aliasing Use python tracing to export script of actions, batch render

23. References Ware, C. (2004). Information Visualization. Amsterdam: Elsevier Schroeder, W. et al (2006). The Visualization Toolkit, An Object-Oriented Approach to 3D Graphics. Kitware Childs, H. et al (2012). VisIt: An End-User Tool For Visualizing and Analyzing Very Large Data. Pg 357-372, High Performance Visualization-Enabling Extreme-Scale Scientific Insight Ahrens, James, Geveci, Berk, Law, Charles, ParaView: An End-User Tool for Large Data Visualization, Visualization Handbook, Elsevier, (2005), ISBN-13: 978- 0123875822 Ayachit, Utkarsh, The ParaView Guide: A Parallel Visualization Application, Kitware, (2015), ISBN 978-1930934306 Boland, D., Taylor, R. M., Rainbow Color Map (Still) Considered Harmful, (2007), Computer Graphics and Applications, IEEE DOI:10.1109/MCG.2007.323435 Diverging Color Maps for Scientific Visualization