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Theory, Grid and VO

Theory, Grid and VO. Matthias Steinmetz (AIP). Data analysis. Data Archive. Data Archive. PC Cluster. PC Cluster. application. Data analysis. Super Computer. Super computer. Telescopes. Characteristics of a Grid: network of IT-Ressourcen. MIDDLEWARE. User.

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Theory, Grid and VO

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  1. Theory, Grid and VO Matthias Steinmetz (AIP)

  2. Data analysis Data Archive Data Archive PC Cluster PC Cluster application Data analysis Super Computer Super computer Telescopes Characteristics of a Grid: network of IT-Ressourcen MIDDLEWARE User Resources are "virtualized", i.e. can not be identified individually

  3. VO and Grid • What is the dividing line between VO and Grid? • Not well defined • Example UK: • AstroGrid covers VO and Grid aspects • Example Germany • GAVO: application layer • AstroGrid-D: middle ware

  4. Theory and Grid • Benefits of the Grid • Logistics (resource monitoring, scheduler/broker, virtual organizations, …) • Virtual Surveys (Millenium simulation) • Enterprise computing (access to supercomputers via grids, e.g. DEISA) • Cloud computing (“task farming”) • Volunteer computing (@home model) • Visualization

  5. StellarIS: resource monitoring Grid-Ressource-Map Basiert auf GoogleMap

  6. Stellaris: Job monitoring Minutes Time table for submitted Jobs hours days Webinterface for simple job monitoring

  7. Analysing Cosmological Simulations in the Virtual Observatory:Designing and Mining the Millennium Simulation Database Gerard Lemson German Astrophysical Virtual Observatory ARI, Heidelberg MPE, Garching bei München

  8. Time evolution: merger trees

  9. Merger trees : select prog.* from galaxies des , galaxies prog where des.galaxyId = 0 and prog.galaxyId between des.galaxyId and des.lastProgenitorId Branching points : select descendantId from galaxies des where descendantId != -1 group by descendantId having count(*) > 1

  10. Usage statistics • Up since August 2006 (astro-ph/...) • ~210 registered users • > 4.4 million queries • ~ 35 billion rows (since March 2007) # secs/day # queries/day # rows/day

  11. Enterprise Computing:Mare Nostrum Simulations at HLRZ WMAP3 parameters, w=0.8 Testrun using the grid: 10243+10243 particles

  12. NBODY6++ UseCase Computer simulation of dense stellar systems Example: globular clusters Gravitational Star-Star interaction Complexity N2 (N: number of stars)

  13. Enterprise Computers Recent Development: GPU – Graphics Cards GeForce 8800 GTX (NVIDIA) Using CUDA Library Special Interfaces and API from GRACE project ported. Berczik et al. 2008 Spurzem et al. 2008

  14. Cloud Computing: UseCase DynamoVisualization of results 2D-Darstellung der Magnetfeldstärke auf der Sternoberfläche Querschnitt durch den Stern Rechner 1 Rechner 2 Rechner 3 Rechner 4

  15. Dynamo JDSL und RSL <jsdl:JobDefinition xmlns="http://www.gacg-grid.de/namespaces/job-mgmt/2006/08/jsdl" xmlns:jsdl="http://schemas.ggf.org/jsdl/2005/11/jsdl" xmlns:jsdl-posix="http://schemas.ggf.org/jsdl/2005/11/jsdl-posix" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"> <jsdl:JobDescription> <jsdl:JobIdentification> <jsdl:JobName> Sample Dynamo run </jsdl:JobName> <jsdl:Description> Use Case Dynamo </jsdl:Description> <jsdl:JobProject> n/a </jsdl:JobProject> </jsdl:JobIdentification> <jsdl:Resources> <jsdl:FileSystem name="HOME"> <jsdl:Description> User's home directory </jsdl:Description> </jsdl:FileSystem> </jsdl:Resources> […] <?xml version="1.0" encoding="UTF-8"?> <job> <executable>test.x</executable> <directory>/${GLOBUS_USER_HOME}/ dynamo</directory> <stdout>test.out</stdout> <maxWallTime>100</maxWallTime> <maxMemory>1</maxMemory> <fileStageIn> […]

  16. Volunteer Computing: GEO600 / LIGO Laser Interferometer Gravitational Wave Observatory

  17. GEO600/LIGO Network von 4 Detectors Hanford (2000m side length) USA Livingston (4000m side length) USA GEO600 ( 600m side length) Germany Virgo (3000m side length) Italy Pathfinder for LISA, Satellite mission with 3 detectors side length: 5*109 m!

  18. Gravitationional waves: Data analysis via the Grid • Data analysis via small data packages, “embarrassingly parallel”. • Einstein@Home is, like SETI@Home, suitable to exploit idle cycles on work stations. • Einstein@Home is an ideal, simple Grid application, supporting many operation system. • Checkpointing and Recovery allows a very accurate control of CPU-Requirements and walltime. • Automatic software deployment job submission and job management, a good scalability of grid application can be obtained • Current workload: 30000 CPU h per week

  19. GEO600 – Resource Integration • user friendly User-Management viaVOMRS • Resource information via MDS und StellarIS • Grid Service Monitoring • automatic job submission on D-Grid resources • Job monitoring und job management using a Laptop • data management on Astrogrid-D Storage Cluster

  20. Visualization of a galaxy merger Submit Execution ... ZIB AIP ARI Video Workflow A ProC Submit Workflow Video Workflow B start GT4 submit exit GT4 submit exit stop • Simulation: two galaxies on collision orbit • Visualization: 2D-projections of 3D snapshots

  21. Grid-Visualization • Submission Host: ZIB • ProC + Master workflow • Submission of video workflows • Display of videos • Execution Hosts: AIP + ZAH • PiCo + Video workflow • Projection to 2D • Color coding • Future: • Graphics rendering at LRZ, graphics output on local host

  22. Theory and Grid • Benefits of the Grid • Logistics (resource monitoring, scheduler/broker, virtual organizations, …) • Virtual Surveys (Millenium simulation) • Enterprise computing (access to supercomputers via grids, e.g. DEISA) • Cloud computing (“task farming”) • Volunteer computing (@home model) • Visualization

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