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Australian Virtual Observatory A distributed volume rendering grid service

Australian Virtual Observatory A distributed volume rendering grid service. Gridbus 2003 June 7 Melbourne University David Barnes School of Physics, The University of Melbourne. Overview. what is a virtual observatory? astronomy data cubes 101 volume rendering

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Australian Virtual Observatory A distributed volume rendering grid service

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  1. Australian Virtual ObservatoryA distributed volume rendering grid service Gridbus 2003 June 7 Melbourne University David Barnes School of Physics, The University of Melbourne

  2. Overview • what is a virtual observatory? • astronomy data cubes 101 • volume rendering • distributed data volume rendering • turning it into a grid service • future projects

  3. Virtual observatories • bring legacy astronomy archives on-line and ensure future project compliance • describe data fully, and support a finite, well-chosen set of interoperability protocols • develop toolsand interfaces to find, acquire, process and visualise data • build national and international grids and embed the data, tools and interfaces in those grids

  4. Astronomy data cubes 101 • you may have only seen 2d astronomy images • an increasing number of telescopes and simulations produce multi-dimensional data • astronomy data cubes are 3d arrays of pixels (voxels) • typically the axes might be latitude and longitude on the sky, and frequency of radiation • lots of information! Radio frequency Declination Right ascension

  5. Volume rendering • 3d data can be viewed in slices, or we can render lines of sight through the entire volume - this is volume rendering and may offer new insights to complex data collections

  6. Distributed data volume rendering • split large volume into smaller pieces • share the pieces out to nodes of a Beowulf cluster • on demand the nodes render their piece of data • other nodes glue the pieces together to form the final image • provides increased speed and ability to handle larger-than-memory volumes • See Beeson, Barnes & Bourke, 2003. PASA, submitted

  7. Distributed data volume rendering • Rendering controlled by a remote client connected on a socket • Joint project with AstroGrid (UK) to recast the software as a grid service for demonstration in July at a major astronomy conference in Sydney.

  8. Making a grid service • Collaborating groups now include • Melbourne (Physics & Computer Science / SE) • AstroGrid (Cambridge, Leicester) • VPAC, APAC, CSIRO CMIS, …, as data centres and rendering clusters • Lead is being set by Guy Rixon (Cambridge) who has designed the system and is managing the project plan day-to-day • Why? • Saves you from fetching large data files • Enables use of distributed computing resources • Demonstrator of grid technologies for VOs

  9. Structure • Portal provide an interface for the user to find and select data and to select a rendering cluster (80% complete) • Data centre service provides a registry of its data holdings and some tools to eg. extract sub-images (60%) • Data centre runs a gsiftp server to provide authenticated access to the data (~100%) • Cluster centre service fetches the data, starts up a rendering tree, loads the data and opens up a port (90%) • Portal provides an applet to connect to that port and control and display the rendering (25%)

  10. Development environment • Globus 2.4 for gsiftp servers • Tomcat 4.1.24 for portals and service wrappers • Globus 3.0 alpha 4 for grid services deployed within Tomcat • Sun J2SDK 1.4.1_03 • Netscape 7.02 (Gecko/20030208) • All data and rendering centres are Linux • Tested clients include Linux, Windows and Mac OS X

  11. “Release 0” - June 6 2003 • One hard-coded compressed FITS image in place of final data selection result • One hard-coded rendering cluster in place of final cluster selection result • Rendering cluster retrieves image from data centre via HTTP, decompresses it, converts it to volume rendering input format and stores it locally • Applet served from portal server, running in client’s browser, successfully connects to rendering cluster and requests an image.

  12. The future • Jia’s GridFTP client code to be incorporated next week - render cluster service complete! • Data registry and data centre grid service including selection to be ready in ~two weeks • Display and control applet to be largely completed over next four weeks.

  13. Beyond the demo… • Review demonstration in August • CSIRO ATNF group developing Java interface to legacy astronomy software • suitable long-term location of this project? • Conversion of Beowulf-class rendering tree to genuine distributed grid service for the piecewise rendering? • Integration with massive on-line parameterised databases?

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