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Interactive Videostreaming Visualization on Clusters and Grids

Learn how to visualize and process massive data on grids and clusters with interactive tools and techniques. Integration with existing visualization tools, data transportation, and rendering methods are covered. Explore new ways to handle data efficiently.

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Interactive Videostreaming Visualization on Clusters and Grids

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  1. Interactive Videostreaming Visualization on Clusters and Grids Dieter Kranzlmüller kranzlmueller@gup.jku.at GUP LinzJoh. Kepler University Linz

  2. Computing produces possibly huge amounts of data Further increases: multicore architectures clusters grids Users are interested in understanding the data Motivation: Data CCGSC 2006

  3. Example: Biomedicine • Parallel simulationof blood flowon the Grid • Online visualizationof simulationresults on thedesktop • Interactive steeringof simulation • Grid is „invisible“ CCGSC 2006 Cooperation with University Amsterdam

  4. HowTo: Visualization on the Grid • Specification of graphics generation • Transportation of visualization data • Rendering of visual output Prerequisite:  Interactive access to grid nodesglogin CCGSC 2006

  5. Interactive Bidirectional Connection glogin - Interactive Tunneling Client Gatekeeper WorkerNode Point ofContact glogin WorkerNode WorkerNode glogin’ Traffic Forwarding socket WorkerNode WorkerNode on the Grid CCGSC 2006

  6. glogin Shell – Interactive access to grid nodes • Authentication via grid certificates • Tunneling of arbitrary traffic CCGSC 2006

  7. HowTo: Visualization • Specification of graphics generation • Transportation of visualization data • Rendering of visual output CCGSC 2006

  8. 1. Specification of graphics generation • Users utilize different visualization toolkits during their everyday work (VTK, OpenDX, OpenGL, …) • Users are reluctant to learn new tools due to existing experience and learning curve • Requirement 1: Integrate with existing visualization tools CCGSC 2006

  9. 2. Transportationof visualization data • Data needs to be transported to (possibly multiple) output device over long-distance network connections • Latency: download data today, visualize tomorrow • Requirement 2: Reduce amount of data to be transported CCGSC 2006

  10. 3. Rendering ofvisual output • Rendering of data requires sufficient memory at the output device and powerful graphics engines • Different output devices are used in different environments (PDA, …, VR) • Requirement 3: Enable display output on different devices CCGSC 2006

  11. Requirements • Integrate with existing visualization tools • Reduce amount to be transported • Enable display output on different devices • Grid Visualization Kernel (GVK) for interactive visualization on the grid CCGSC 2006

  12. GVK Integration with existing tools ExampleOpenDXflow graph CCGSC 2006

  13. GVK Integrationwith existing tools ExampleOpenDXflow graph using GVK CCGSC 2006

  14. GVK Reductionof data transport Occlusion culling CCGSC 2006

  15. GVK Displayon different devices • Simulation of floodingon the Grid • Visualizationof results in the CAVE • Grid is„invisible“ CCGSC 2006 Cooperation with Slowak Academy of Sciences

  16. GVK Extension Grid-enabled Video streaming • Generate video stream at data origin using off-screen rendering and video capturing Data remains where it is produced! • Transport video stream to output device • Display video stream on output device • Manage interactive input on output device CCGSC 2006

  17. inter-action videostream videostream videostream interaction interaction GVid Extension to GVK Workernode GridVisualization Kernel Workernode WORKING! Workernode glogin’ Client glogin GVidEncode on the Grid CCGSC 2006

  18. Example: GVid CCGSC 2006

  19. Example: GVid Output Device Sony Playstation Portable (PSP): • CPU: MIPS R-4000 • Memory Stick PRO Duo (32 MB-1 GB) • Wi-Fi (802.11b) • MPEG-4 VideoCodec http://en.wikipedia.org/wiki/PlayStation_Portable CCGSC 2006

  20. GVid Output on PSP CCGSC 2006

  21. GVid Characteristics 1/2 • Scientific data remains at producer – only visual output is transported  reduced start-up latency • Integration in any visualization toolkit due to screen capturing • Hardware acceleration (if available) or the power of the source machine(s) can be used at data origin for off-screen rendering CCGSC 2006

  22. GVid Characteristics 2/2 • Standard MPEG video streaming protocols are used for transportation  display on any device • Video stream can be dynamically adapted to output device and network characteristics • Multicast to different output devices (including stereo video) is possible • Encryption of video stream is possible CCGSC 2006

  23. Team Dieter Kranzlmüller, Martin Polak, Thomas Köckerbauer, Paul Heinzlreiter, Herbert Rosmanith, Hans-Peter Baumgartner, Peter Praxmarer, Andreas Wasserbauer, Gerhard Kurka, Jens Volkert CCGSC 2006

  24. More Information GVK: http://www.gup.jku.at/gvk GVid: http://www.gup.jku.at/gvk glogin: http://www.gup.jku.at/glogin E-Mail: kranzlmueller@gup.jku.at CCGSC 2006

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