AHM04 1 gViz: Visualization and Computational Steering on the Grid Ken Brodlie, Jason Wood – University of Leeds David Duce, Musbah Sagar – Oxford Brookes University

AHM04 2 gViz – Visualization Middleware for e-Science 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

AHM04 3 Starting Point: Dataflow Visualization Systems 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 data visualize render … pipeline design done after committing to particular system … modules assumed to execute locally BUT

AHM04 4 Extending the Reference Model to Grid Environments 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 data visualize render

AHM04 5 Developing an XML Language for Conceptual Layer: skML 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 <module name="ReadLat” out-port="Output"> testVol.lat <module id=“iso” name="IsosurfaceLat" in-port="Input"> <param name="Threshold" min="0" max="27"> 1.8 …

AHM04 6 Diagrammatic Representation using SVG 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 <module name="ReadLat” out-port="Output"> testVol.lat <module id=“iso” name="IsosurfaceLat" in-port="Input"> <param name="Threshold" min="0" max="27"> 1.8 …

AHM04 7 Physical Layer – Secure Distributed IRIS Explorer IRIS Explorer on multiple hosts Select remote host Automatic authentication using: Globus certificate SSH Key pair 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

AHM04 8 Next Steps 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

AHM04 9 Computational Steering 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 controlvisualize visualization environment simulation environment gViz library

AHM04 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

AHM04 11 Pollution Simulation Using the gViz Library and IRIS Explorer Discover Grid resources Launch simulation Connect to simulation Send control parameters Get data to visualize Visualize

AHM04 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

AHM04 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 Matlab vtk

AHM04 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

AHM04 15 gViz Anatomy Discover Grid resources Launch simulation (register with Directory Service) Call up Directory Service and select simulation Visualize multiple simulations Get results

AHM04 16 …Or with Matlab as Visualization Environment

AHM04 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

AHM04 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

AHM04 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 – 14.30

AHM04 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