gViz: Visualization and Computational Steering on the Grid

1. gViz: Visualization and Computational Steering on the Grid Ken Brodlie, Jason Wood – University of Leeds David Duce, Musbah Sagar – Oxford Brookes University

2. gViz is an e-Science Core Programme project – just finished… … has made a start at understanding: How to evolve existing visualization systems to the Grid How to link visualization and simulation environments gViz partners: Academic: Leeds, Oxford, Oxford Brookes, CLRC/RAL Industrial: NAG, IBM UK and Streamline Computing International: Caltech, MIT Leeds contribution through the White Rose Grid e-Science Centre of Excellence e-Science Centre of Excellence gViz – Visualization Middleware for e-Science

3. Visualization represented as pipeline: Read in data Construct a visualization in terms of geometry Render geometry as image Realised as modular visualization environment IRIS Explorer is one example Visual programming paradigm Extensible – add your own modules Others include IBM Open Visualization Data Explorer visualize data render … pipeline design done after committing to particular system … modules assumed to execute locally BUT Starting Point: Dataflow Visualization Systems

4. Revisit the visualization pipeline Start with the traditional reference model Progressively bind in software and hardware resources Three-layer reference model Conceptual: intent of the visualization Show me isosurface of constant temperature Logical: bind in the software system Use IRIS Explorer (or vtk, or whatever) Physical: bind in the resources to be used Run the isosurface extraction on particular Grid resource visualize data render Extending the Reference Model to Grid Environments

5. First – the conceptual layer Dataflow consists fundamentally of: a map containing links between ports on modules which have parameters This leads us to a simple XML application for visualization: called skML Here a data reader is linked to an isosurfacer <?xml version="1.0"?> <skml> <map> <link> <module name="ReadLat” out-port="Output"> <param name="Filename"> testVol.lat </param> </module> <module id=“iso” name="IsosurfaceLat" in-port="Input"> <param name="Threshold" min="0" max="27"> 1.8</param> </module> </link> … Developing an XML Language for Conceptual Layer: skML

6. skML gives us an XML application for visualization at the conceptual layer In addition to language representation, a diagrammatic representation has been created in SVG – so we can do dataflow programming in a web browser Transforming to the logical layer binds in the software resource A new IRIS Explorer module can read skML and generate corresponding map skML can also be turned into an IBM Open Visualization Data Explorer network Diagrammatic Representation using SVG <?xml version="1.0"?> <skml> <map> <link> <module name="ReadLat” out-port="Output"> <param name="Filename"> testVol.lat </param> </module> <module id=“iso” name="IsosurfaceLat" in-port="Input"> <param name="Threshold" min="0" max="27"> 1.8</param> </module> </link> …

7. Moving to the physical layer, we need to be able to execute modules on remote Grid resources IRIS Explorer has been extended to allow a user to place modules on specific compute resources – dataflow pipeline thus spans the Grid Compute-intensive modules can be placed remotely - design the dataflow for the Grid Select remote host Physical Layer – Secure Distributed IRIS Explorer IRIS Explorer on multiple hosts • Automatic authentication using: • Globus certificate • SSH Key pair

8. Some tangible benefits… … Next release of IRIS Explorer will include the distributed execution facility… … but much remains to be done Conceptual level Visualization ontology needed to define and organize set of canonical processes Useful to include resource constraints (initial steps made with RDF) Logical level Visualization data exchange between systems needs to be studied Initial steps made by Julian Gallop (this conference) Physical level User allocation of modules to resources needs to be replaced by a brokering service Next Steps

9. gViz library gViz library Computational Steering visualization environment • Computational steering requires a link between a visualization environment and a simulation environment… • … gViz library provides this glue • Design aims: • Use with different simulation environments and different visualization environments • Allow connect and disconnect • Lack of intrusion and minimize performance loss • Robustly handle different producer-consumer rates • Support multiple simulations • Support collaboration • Support historical audit trail control visualize simulation environment

10. Environmental Application • Demonstrator created for an environmental crisis scenario • Dangerous chemical escapes! • Model dispersion using system of PDEs and solve numerically over mesh • Visualize mesh elements where concentration exceeds threshold • What happens when the wind changes? • ‘faster-than-real-time’ • Simulation environment • Finite volume code written in C

11. Get data to visualize Send control parameters Discover Grid resources Launch simulation Connect to simulation Visualize Pollution Simulation Using the gViz Library and IRIS Explorer

12. IRIS Explorer as Visualization Environment • Distributed module execution: • Allows visualization modules to be collocated with simulation to minimize data traffic to desktop • Collaborative visualization: • Allows the COVISA multi-user visualization facility to be exploited

13. Pollution example with other visualization environments • Different visualization environments can be connected through gViz library to the underlying simulation • Note that multiple users – with multiple visualization environments – can connect… allowing collaboration amongst a team SCIRun vtk Matlab

14. Computational Biology • In another application the gViz library provides monitoring and control of heart modelling experiments – Arun Holden & Richard Clayton • Multiple simulations of electrical activity of the heart

15. Get results Call up Directory Service and select simulation Visualize Visualize multiple simulations Discover Grid resources Launch simulation (register with Directory Service) gViz Anatomy

16. …Or with Matlab as Visualization Environment

17. … Or with Grid/Web Services approach • Grid service interface to gViz library • Heart Modelling Grid Service uses: • Web interface where user specifies user name and passphrase, and location of gViz directory service • Grid service connects to simulations to allow steering parameters to be sent, and results to be retrieved, via the gViz library • A second grid service builds images from simulation data • Returned as a Web page

18. gViz meets Integrative Biology • The application to heart modelling continues in the Integrative Biology project with David Gavaghan • Here Matlab is the simulation environment … • .. linked by gViz library to IRIS Explorer as the visualization environment… • … or indeed Matlab can act as the visualization environment • Reality Grid steering also being used in IB project, so hope is to gain convergence between the two approaches

19. Conclusions • The gViz project has begun to explore the issues in evolving visualization systems to Grid environments • Tangible benefits: • Secure distributed IRIS Explorer in next release from NAG • gViz library code will be made available as open source (LGPL) • Raising issues: • Ontology • Visualization data exchange • Visualization brokering service • Continuing development of gViz library within Integrative Biology – with potential convergence with RealityGrid steering library • Demonstration: WRG Stand, Friday 10.30 – 14.30

20. Acknowledgements The gViz project team has involved many people: • Leeds University: Ken Brodlie, Jason Wood, Chris Goodyer, Martin Thompson, Mark Walkley, Haoxiang Wang, Ying Li, James Handley, Arun Holden, Richard Clayton (now Sheffield) • Oxford Brookes University: David Duce, Musbah Sagar • Oxford University: Mike Giles, David Gavaghan • CLRC/RAL: Julian Gallop • NAG: Steve Hague, Jeremy Walton • Streamline Computing: Mike Rudgyard • IBM UK: Brian Collins, Alan Knox, John Illingworth • CACR, Caltech: Jim Pool, Santiago de Lombeyda, John McCorquadale • MIT: Bob Haimes Development environment at Leeds: White Rose Grid – e-Science Centre of Excellence