Advances in Interactive Visualization

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Advances in Interactive Visualization

• Robert van Liere
• Centrum voor Wiskunde en Informatica
• Amsterdam

Problem Solving Environments San Feliu
Guixols 12-17 June 1999
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Outline

• Motivation
• Computational Steering
• Hierarchical Visualization
• Advanced Display Technology
• Future Trends

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Motivation Visualization Pipeline
P parameters M model D data I image
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Visualization Techniques Roadmap

• packages exploration, analysis, communication
• rule based visualization

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Motivation Observations

• Post processing
• Independent activities
• Long turn around times
• What is the impact of HPC technology ?
• On simulations ?
• On size and complexity of data sets?
• On presentation ?

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Motivation impact on simulations

• Integration
• faster turn around times
• interactive methods
• multi-level methods
• Computational Steering
• interactive parameters
• interactive solvers
• Need methods and tools for steering

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Motivation impact on large data sets

• Simulation output
• size factor 100 / 10 years
• inherent complexity
• Hierarchical visualization
• avoid cluttering
• raw data vs features
• Need advanced visualization techniques

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Motivation impact on presentation

• 3D / 4D output
• 3D spatial relationships
• 3D interaction
• 3D displays
• stereo
• motion parallax
• spatial input
• Need high res interactive displays

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Steering advantages

• efficiency
• erroneous input
• instabilities
• insight
• parameter space navigation
• sensitivity analysis
• cause/effect analysis

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Smog steering model

• Europe
• 4 layers
• 15 pollutants
• 17 reactions
• Parameters
• meteorological
• geographical
• emission

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Smog steering simulation

• PDEs
• base grid 55x53
• adaptive grids
• Parameters
• grid levels
• tolerance

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Smog steering
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Smog steering goals

• Simulation
• control all model and numerical parameters
• smooth animation ( gt 15 fps)
• Visualization
• pollutant selection
• toggle display of numerical properties
• Record and playback

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Smog steering performance
SGI Power Challenge, O2, ATM OC-3
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Smog steering performance

• Interactive computation / display
• hw tradeoffs
• compute server
• graphics engine
• network
• design tradeoff
• data streaming
• interaction
• shared data spaces

compute
draw
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CSE distributed architecture

• concept
• properties
• distributed coherent shared variable space
• publish/subscribe events
• various visualization modules
• lesson scalable shared data places

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Steering history

• . If the scientist cannot produce unambiguous
  and exhaustive formulations, and wishes instead
  to exercise his intuitive judgements as the
  calculation develops, he can arrange for that
  too. He can instruct the machine to present to
  him the relevant characteristics of the
  simulation, continuously or in discrete
  succession, as the calculation progresses, by
  oscilloscopic graphing. He can then intervene
  whenever he sees fit.
• John von Neumann - 1946

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Steering related work

• Systems
• model exploration
• algorithm exploration
• performance optimization
• Software environments
• VASE92, SCIrun95, CSE97, Covise97
• Magellan97, CUMULVIS97, VIPER97

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Big Data

• Very large and complex data sets
• Properties
• typical flow simulation gt terabyte
• unknown phenomena hidden in data
• levels of scale (spatial/temporal)
• Visualization techniques
• intelligent selection (feature detection)
• out-of-core algorithms
• multi-resolution display algorithms

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Hierarchical Visualization

• Turbulent Flow
• DNS
• Re 22,000
• Structures
• spatial
• temporal
• 740x680x64x120000 4.3 Tbytes
• Re 200,000 ?

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Visualization multi-level spot noise
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Visualization spot noise
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Visualization spot noise

• Technique
• spot
• intensity function
• Texture
• many spots
• Visualization
• adapt spot shape

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Interactive spot noise

• Fast texture synthesis
• using graphics hardware
• Parallel implementation
• multiple processors
• multiple graphics pipes
• Speed / Quality trade off

processors
pipes
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Implementation - 16 CPU, 4 iR pipes

• read
• advect
• texture
• display
• lesson scalable graphics techniques

R
R
A
A
A
T
T
T
D
D
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Visualization multi-level topology
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Visualization multi-level topology
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Visualization multi-level topology
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Advanced Display Technology

• Problem
• qualitative information
• no detailed models
• ambiguous reconstruction
• VR added value
• spatial 3D interrelations
• complex user interactions
• VR interfaces are more natural

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Displays

• Properties
• high resolutions
• stereo
• head tracking
• 3D spatial input
• Examples

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3D graphics vs immersion

• viewing
• user outside
• interaction
• remote manipulation
• 3D to 2D mapping
• no multiple simultaneous
• user is aware

• viewing
• user inside
• interaction
• direct manipulation
• 3D to 3D mapping
• multiple simultaneous
• transparent

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Example VR for Cell Biology
Mitosis
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Example VR for Cell Biology
Lamine
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Summary

• Computational steering
• adds insight to simulation
• Hierarchical Visualization
• abstractions of large complex data sets
• Advanced display technology
• spatial relationships, 3D interaction

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Future Trends

• quantitative qualitative computing
• collaborative analysis
• desktop VR
• component based visualization environments

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Acknowledgements

• People
• Jan Harkes, Mariska Hoogenboom,
• Joris Kniesmeijer, Suzanne Kriegler,
• Wim de Leeuw, Jurriaan Mulder,
• Kamran Sharoudi, Jack van Wijk
• SION, ICES-HPCN, ECRIM, NCF/ALW