1AHM04

gViz: Visualization and Computational Steering on the Grid

Ken Brodlie, Jason Wood – University of Leeds

David Duce, Musbah Sagar – Oxford Brookes University

2AHM04

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

3AHM04

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 committingto particular system… modules assumed to execute locally

BUT

4AHM04

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

5AHM04

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

<?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>…

6AHM04

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

<?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>…

7AHM04

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

8AHM04

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

9AHM04

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

control visualize

visualization environment

simulation environment

gViz library

gViz library

10AHM04

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

11AHM04

Pollution Simulation Using the gViz Library and IRIS Explorer

DiscoverGrid resources

Launchsimulation

Connectto simulation

Send controlparameters

Get datato visualize

Visualize

12AHM04

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

13AHM04

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

14AHM04

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

15AHM04

gViz Anatomy

DiscoverGrid resources

Launch simulation(register with Directory Service)

Call up Directory Serviceand select simulation

Visualize Visualizemultiplesimulations

Getresults

16AHM04

…Or with Matlab as Visualization Environment

17AHM04

… 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

18AHM04

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

19AHM04

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

20AHM04

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