env 200616.1 envisioning information lecture 16 – distributed and collaborative visualization ken...
TRANSCRIPT
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ENV 2006 16.1
Envisioning Information
Lecture 16 – Distributed and Collaborative Visualization
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ENV 2006 16.2
Outline of Lecture
• From Visualization to Computational Steering
• Distributed visualization– Extending dataflow across the network– Grid-based visualization and computational steering
• Collaborative visualization– Sharing the display screen– Sharing the visualization
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ENV 2006 16.3
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
http://www.nag.co.uk
data visualize render
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ENV 2006 16.4
• IRIS Explorer is one of a family of similar visualization systems
• First product was AVS– Still major player but no longer visual programming– http://www.avs.com
• Amira, IBM Open Visualization Data Explorer (DX), IRIS Explorer– visual programming based : plug, play, throw away– application decomposed as set of modules, configured at run-time (blur
between building and running an application)– open : user can write modules– low-cost
Visualization Software Environments
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ENV 2006 16.5
IBM Open Visualization Data Explorer – now OpenDX
• Released around 1991 by IBM
• Made open source in 1999– www.opendx.org
• A major use of it has been for weather visualization
http://www.research.ibm.com/weather/
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ENV 2006 16.6
Amira
• More recent product
• Increasing use for medical applications..
• .. But also engineering including CFD
• Marketed by TGS
• www.tgs.com
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ENV 2006 16.7
vtk - Visualization Toolkit
• vtk is a programming - based toolkit
• Open source C++ library
• www.kitware.com
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ENV 2006 16.8
.. And there are many others
http://www.kdnuggets.com/software/visualization.html
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ENV 2006 16.9
IRIS Explorer - Creating Your Own Modules
• It is possible to create your own modules • The mbuilder tool creates a wrapper around your own code• See:
http://www.nag.co.uk/visual/ie/iecbb/doc/html/unix-iemwg5-0.htm
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ENV 2006 16.10
• IRIS Explorer can be driven either by GUI or by command line interface
• Commands can be grouped as a ‘script’ that IRIS Explorer runs– explorer -script <file>
• This allows Explorer to be run in batch mode, or to be driven by another application
• The scripting language is called Skm (pronounced as ‘scheme’)• Can be used interactively…• … in linux
– explorer -script %
• … in Windows, – use Skm editor (view menu)
Scripting - skm
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ENV 2006 16.11
• To launch a module:(start “ReadImg”)
(start “DisplayImg”)
• To connect ports:(connect “ReadImg” “Output” “DisplayImg” “Input”)
• To start a map:(start-map “cfd”)
• See chapter 6 of User Manual on Web
http://www.nag.co.uk/visual/ie/iecbb/doc/html/unix-ug-chap06.htm
Creating a Simple Script
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ENV 2006 16.12
Visualization and Simulation
• Visualization is a key tool in understanding the results of numerical simulations of complex physical phenomena
• Different modes of combining simulation and visualization:
– Post-processing
– Tracking
– Steering
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ENV 2006 16.13
Linking Visualization and Simulation – Post Processing
• Post-processing
– Do the simulation and store results (step 1)
– Look at the results in a separate process (step 2)
– Revise the simulation (back to step 1)
simulation
data visualize render
Step 1
Step 2
PRO: study at your own pace
CON: must finish simulation first
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ENV 2006 16.14
Linking Simulation and Visualization - Tracking
• Tracking
– Exploit extensibility of the dataflow visualization environment by including the simulation in the pipeline
– Track the behaviour of simulation as it runs
simulate visualize render
PRO: can abort fruitless simulations
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ENV 2006 16.15
Linking Simulation and Visualization - Steering
• Computational steering:– By including a control module in the pipeline, we can direct the simulation in
response to the visualization
simulate visualize rendercontrol
PRO: not only can we track, we can alterthe actual course of the simulation
‘Human-in-the-loop’‘Human-in-the-loop’
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ENV 2006 16.16
Computational Steering Environments
• Early visualization systems all have this extensibility feature and so can be used for steering
– IRIS Explorer for example
• New systems have emerged specifically to support steering
– SCIRun from Utah
Pressure profile for EHL contact
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ENV 2006 16.17
Imagine this ….
• An explosion!
• A dangerous chemical escapes!
• Where is the fugitive pollutant headed?
• Who needs to be evacuated?
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ENV 2006 16.18
Understanding What Will Happen
• Model the dispersion by solving system of PDEs
• Understand solution by visualization
• What if scenarios … need to be able to steer the simulation
• For example, what if the wind changes direction?
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ENV 2006 16.19
Tracking the Pollution
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ENV 2006 16.20
What can be Steered?
• Steering requires the writer of the simulation code to expose parameters that can be legitimately modified in the course of a run
– frequency of output of results– values of external influences that may vary over a simulation
• Not all parameters can be changed– time step used by numerical codes to achieve stability and/or accuracy
• Notion of backtracking is important in some simulations– Often you first observe, then wish to rewind a few timesteps, then replay with
different parameter settings
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ENV 2006 16.21
Our Scenario
• We shall use this scenario to illustrate:
– Distributed visualization : we need to understand where the pollutant is headed in faster than real-time … therefore we need to run the simulation on a powerful compute resource
– Collaborative visualization : there is no time to collocate the scientist, the meteorologist, the politician or whoever needs to be involved … so we need to link people in over the network to allow them to visualize collaboratively
… while still using IRIS Explorer!
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ENV 2006 16.22
Harnessing Remote Compute Resources – Grid Computing
Explorer on single host
Explorer on multiple hosts
Select remote host
Automatic authentication using: •Globus certificate
•SSH Key pair
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ENV 2006 16.23
Simulation Runs Remotely
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ENV 2006 16.24
A Tale
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ENV 2006 16.25
The Monkey Gets the Nuts – Two Heads ARE Better than One
Thanks to Accra Academy, Ghana
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ENV 2006 16.26
Collaborative Working
• Radical collocation has proved highly successful in a number of areas
– Space missions
– Safety critical software development
• Productivity doubled– Teasley et al, Univ of Michigan
• But this requires:– Social disruption
– Advance planning
– … and can end in tears
• Can we gain at least part of this success using electronic collaboration?
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ENV 2006 16.27
Visualizing Collaboratively
• We need to move away from seeing collaborative visualization as a group around a display screen..
• .. Towards collaboration over a network
Collaborative visualization
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ENV 2006 16.28
Collaborating in the Pollution Demonstrator
• Who needs to collaborate and in what way?
• Scientists and numerical modellers– Discuss amongst each other possible scenarios– Discuss need to pull in further Grid resources perhaps
• Meteorologist– Will play an active part in controlling the simulation
• Environmental agency decision makers– Need to analyse ‘what-if’ scenarios and construct presentations for
politicians
• Politicians, local authorities– Want to see clear presentation of consequences– Probably not interested in steering
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ENV 2006 16.29
Sharing the Display Screen
• A very simple model is to broadcast the display screen of an application to a set of (passive) users
– Operating system level
– Screen image is broadcast using intelligent compression
– Only active user can enter input
data visualize render
internet
User A executes application
User B receives copy of user A desktop- does not execute application
data visualize render
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ENV 2006 16.30
Sharing the Display Screen
• There are a number of available technologies for screen sharing
• VNC – Virtual Network Computing– Family of open source products evolved from original VNC development
by AT&T– RealVNC : www.realvnc.com (original development team)– tightVNC : www.tightvnc.com (new compression algorithms)– Heterogeneous
• Microsoft NetMeeting (and now MSN Messenger)
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ENV 2006 16.31
Sharing Display Screen
• Advantages– Very simple concept – works for any application– Good for training– Good for presentation to a group
• Disadvantages– No independent working– Performance issues when rapid screen changes
• Variations– (1) Only one master – only one can control by mouse and keyboard input– (2) Any participant can input
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ENV 2006 16.32
Sharing the Visualization
• This is a more flexible approach – and specific to dataflow visualization
• Each collaborator is an active participant in the visualization process
• Multiple, interlinked applications, where each collaborator runs their own application but data and parameter settings are programmed to be shared between the different applications
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ENV 2006 16.33
internet
data visualize render
Sharing the Visualization
• Extends the dataflow model to interlink pipelines across the Internet
• Collaborative server provides the link
• So one user – for example - can send geometry to another person for viewing
collaborative server
share
share
render
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ENV 2006 16.34
Programming the Collaboration
• It is useful to be able to program the collaboration
– To adapt to how people want to collaborate
– To adapt to network bandwidths
• Here raw data is exchanged so a different visualization can be created
internet
collaborative server
data visualize render
share
share
visualise render
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ENV 2006 16.35
COVISA in action
sharing isosurface level
sharing data
Collaborator A Collaborator B
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ENV 2006 16.36
Multiple, Interlinked Applications
• COVISA part of IRIS Explorer
• Advantages– Great flexibility– Independent working
• Disadvantages– Difficult to understand what the other user is doing
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ENV 2006 16.37
Bring in the Meteorologist Remotely
Scientistin lab
Initiatecollaborativesession
Link inmeteorologistremotely
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ENV 2006 16.38
Conclusions
• We have studied many aspects of scientific visualization:
– Applications and history– Different techniques for scalar
and vector data– Distributed and collaborative
visualization
• The practical work is giving experience in
– Exploratory visualization (what is going on?)
– Presentational visualization (here’s what is going on!)
• Finally, this afternoon, two case studies
– Exploration using parallel coordinates
– Focus and context for volume visualization