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The Application-Infrastructure Gap

A. B. 1. 1. 9. 9. Shared Distributed Infrastructure. The Application-Infrastructure Gap. Dynamic and/or Distributed Applications. Bridging the Gap: Grid Technology. Users. Service-oriented applications Wrap applications as services Compose applications into workflows

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The Application-Infrastructure Gap

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  1. A B 1 1 9 9 Shared Distributed Infrastructure The Application-Infrastructure Gap Dynamicand/orDistributedApplications

  2. Bridging the Gap:Grid Technology Users • Service-oriented applications • Wrap applications asservices • Compose applicationsinto workflows • Service-orientedinfrastructure • Provision physicalresources to support application workloads Composition Workflows Invocation ApplnService ApplnService Provisioning

  3. Tool Tool Reliable File Transfer Uniform interfaces, security mechanisms, Web service transport, monitoring MDS-Index MyProxy DAIS GRAM User Svc User Svc GridFTP Host Env Host Env Grid Technology:Service-Oriented Infrastructure User Application User Application User Application Database Specialized resource Computers Storage

  4. Globus Open Source Grid Software G T 4 Delegation Service Community Scheduler Framework [contribution] Python WS Core [contribution] C WS Core G T 3 CommunityAuthorization Service OGSA-DAI [Tech Preview] WS Authentication Authorization Reliable File Transfer Java WS Core Grid Resource Allocation Mgmt (WS GRAM) Monitoring & Discovery System (MDS4) G T 2 Pre-WS Authentication Authorization GridFTP Grid Resource Allocation Mgmt (Pre-WS GRAM) Monitoring & Discovery System (MDS2) C Common Libraries G T 3 Replica Location Service XIO G T 4 Credential Management Web ServicesComponents Non-WS Components Security Data Management Execution Management Information Services CommonRuntime

  5. GT4 Components Your Python Client Your C Client Your Java Client Your Python Client Your Python Client Your C Client Your C Client CLIENT Your Java Client Your Java Client Your Python Client Your C Client Your Java Client Interoperable WS-I-compliant SOAP messaging X.509 credentials = common authentication Trigger Archiver Your C Service GRAM RFT Delegation Index CAS OGSA-DAI GTCP Your Python Service Your Java Service Your Java Service RLS GridFTP SimpleCA MyProxy Pre-WS MDS Pre-WS GRAM C WS Core pyGlobus WS Core Java Services in Apache Axis Plus GT Libraries and Handlers Python hosting, GT Libraries C Services using GT Libraries and Handlers SERVER

  6. User Applications Custom WSRF Web Services Custom Web Services GT4WSRF Web Services Registry Administration GT4 Container WS-Addressing, WSRF, WS-Notification WSDL, SOAP, WS-Security Web Services:Standards, Tools, Interoperability

  7. NEES: Network for Earthquake Engineering Simulation Links instruments, data, computers, people

  8. Genome sequence analysis Scaling:Grid2003Workflows Sloan digital sky survey Physics data analysis

  9. STAR: 5 TB transfer (SRM, GridFTP) Earth System Grid: O(100TB) online data NASA/NVO: Mosaics from multiple sources Application Examples Fusion Grid: 1000s of jobs

  10. LIGO Scientific Collaboration • Continuous gravitational waves are expected to be produced by a variety of celestial objects • Only a small fraction of potential sources are known • Need to perform blind searches, scanning the regions of the sky where we have no a priori information of the presence of a source • Wide area, wide frequency searches • Search is performed for potential sources of continuous periodic waves near the Galactic Center and the galactic core • Search for binary inspirals collapsing into black holes. • The search is very compute and data intensive P. Brady, S. Koranda, D. Brown, S. Fairhurst UWMilwaukee, USA, S. Anderson, K. Blackburn, A. Lazzarini,H. Pulapaka, T. Creighton Caltech, USA, G. Gonzalez, Louisiana State University, Many Others involved in the Testbed

  11. Montage • Montage (NASA and NVO) • Deliver science-grade custom mosaics on demand • Produce mosaics from a wide range of data sources (possibly in different spectra) • User-specified parameters of projection, coordinates, size, rotation and spatial sampling. B. Berriman, J. Good, A. Laity, Caltech/IPAC J. C. Jacob, D. S. Katz, JPL http://montage.ipac. caltech.edu/ Mosaic created by Pegasus based Montage from a run of the M101 galaxy images on the Teragrid.

  12. Small Montage Workflow ~1200 nodes

  13. Other ApplicationsSouthern California Earthquake Center • Southern California Earthquake Center (SCEC), in collaboration with the USC Information Sciences Institute, San Diego Supercomputer Center, the Incorporated Research Institutions for Seismology, and the U.S. Geological Survey, is developing theSouthern California Earthquake Center Community Modeling Environment (SCEC/CME). • Create fully three-dimensional (3D) simulations of fault-system dynamics. • Physics-based simulations can potentially provide enormous practical benefits for assessing and mitigating earthquake risks through Seismic Hazard Analysis (SHA). • The SCEC/CME system is an integrated geophysical simulation modeling framework that automates the process of selecting, configuring, and executing models of earthquake systems. Acknowledgments : Philip Maechling and Vipin Gupta University Of Southern California

  14. Biology Applications Tomography (NIH-funded project) • Derivation of 3D structure from a series of 2D electron microscopic projection images, • Reconstruction and detailed structural analysis • complex structures like synapses • large structures like dendritic spines. • Acquisition and generation of huge amounts of data • Large amount of state-of-the-art image processing required to segment structures from extraneous background. Dendrite structure to be rendered by Tomography Work performed by Mei-Hui Su with Mark Ellisman, Steve Peltier, Abel Lin, Thomas Molina (SDSC)

  15. BLAST: set of sequence comparison algorithms that are used to search sequence databases for optimal local alignments to a query • 2 major runs were performed using Chimera and Pegasus: • 60 genomes (4,000 sequences each), • In 24 hours processed Genomes selected from DOE-sponsored sequencing projects • 67 CPU-days of processing time delivered • ~ 10,000 Grid jobs • >200,000 BLAST executions • 50 GB of data generated • 2) 450 genomes processed • Speedup of 5-20 times were achieved because the compute nodes we used efficiently by keeping the submission of the jobs to the compute cluster constant. Lead by Veronika Nefedova (ANL) as part of the Paci Data Quest Expedition program

  16. Functional MRI Analysis

  17. GlobalCommunity

  18. Domain-dependent Domain-independent Scaling Up:Service-Oriented Science Simulation code Expt design Simulation code Content Expt output Certificate authority Electronic notebook Telepresence monitor Simulation server Services Portal server Data archive Metadata catalog Resources Servers, storage, networks Experimental apparatus

  19. For More Information • Globus Alliance • www.globus.org • Globus Consortium • www.globusconsortium.com • Global Grid Forum • www.ggf.org • Open Science Grid • www.opensciencegrid.org 2nd Edition www.mkp.com/grid2

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