D-Grid Grid and e-science in Germany

Transcription

1 D-Grid Grid and e-science in Germany Michael Ernst

2 Orientation Drivers of e-science development are advanced user groups Program primarily oriented towards science, with active participation of commercial sector Fundamental goals are Development of e-science services for the research sector Open to any approach Perspective for future usage Criteria of success Scientific power of Communities Ability to add new Communities Robustness and flexibility of technical approach

3 Phase 1 ( /7) Process Establishment of Community-Grids and integrated Middleware-Platform Call 1 picks up work from D-Grid initiative and marks start of this program Therefore bidding process with special emphasis More calls planned to further support this development Phase 2 (2006/7 2009) Development of science-oriented services and self sufficient infrastructure with production quality

4 Supported will be 3-5 Community specific Grids (CG) Primarily applications that include substantial Grid- and e-science specific R&D tasks Development of application and community specific Middleware and network based services wrt a system solution Application independent solutions Application as proof-of-concept no support for development of applications Duration 3 years, starting on 1 January 2005

5 Supported will be Grid-Middleware-Integration-Platform (GMIP) Platform based on existing components and a base architecture Extension by integration of Middleware components developed by CGs Some development in tight collaboration with CGs Version control, quality assurance, documentation, operations models Only one IP

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7 LoI 27 total (23 * CGs, 1 * GMIP, 3 *?) Total cost ~ Euro 90 Mio. Request for funding ~ Euro 50 Mio. Communities Astro- and particle physics: 3 Computational Science and Engineering: 6 Medical and Bioinformatics: 3 Climate and earth science: 2 HPC: 1 Information management: 4

8 Schedule Community Grids and Grid Middleware Integration Platform Applications until 22 October 2004 First response expected by mid November Review Contribution to generic solution Importance of application domain Contribution to grid-based infrastructure Previous work, matching funds, potential for future usage Planned start of all projects: 1 January 2005

9 HEP CP LoI Theme: Community-Grid für die Simulation und verteilte Datenanalyse in der Teilchenphysik Particle, Nuclear, Astro, Theory Huge amount of data growing exponentially requires new Computing Models and new methods to realize a suitable infrastructure Initial Grid experience with simulation Important to work on improvements wrt Resource Scheduling and Monitoring for collaborative data analysis Data Management based on Metadata Catalogs Integration of collaborating instituts Request for funding: Euro 3 Mio. (~ 46 FTE-years) Duration: 3 years

10 HEP CP Partners DESY, FHG-IPSI, FZK, GSI, Hochschule Niederrhein, HUB, LMU Muenchen, NIC, Uni- Dortmund (CEI, Physik), Uni-Freiburg, Uni- Mainz, Uni-Wuppertal, TU Dresden, ZAM/FZ Juelich, ZIB Konsortialfuehrer: Matthias Kasemann, DESY

11 Grid-specific Tasks Data Management: Development of a generic, scalable Storage Element based on standard interfaces Optimized Job Scheduling in data intensive applications: Coscheduling of compute and storage resources Datamining: semantic catalogs (e.g. XML based) as web services Integration of all German Resources of collaboration Experiments in one or more production grids based on the same Middleware Installation and Management: improve usability for institutes (reduce effort) User Support, Monitoring, Bookkeeping: based on efficient job monitoring automatic user support (failure analysis, resubmission strategies, user friendly information systems) Data Analysis in a Distributed Environment: application specific scheduling based on service requirements and availability of data and computing resources, data access and data transfer

12 Grid-specific Tasks Data Management: Development of a generic, scalable Storage Element based on standard interfaces Optimized Job Scheduling in data intensive applications: Coscheduling of compute and storage resources Datamining: semantic catalogs (e.g. XML based) as web services Integration of all German Resources of collaboration Experiments in one or more production grids based on the same Middleware Installation and Management: improve usability for institutes (reduce effort) User Support, Monitoring, Bookkeeping: based on efficient job monitoring automatic user support (failure analysis, resubmission strategies, user friendly information systems) Data Analysis in a Distributed Environment: application specific scheduling based on service requirements and availability of data and computing resources, data access and data transfer

13 organized in 3 Work Packages WP1: Data Management WP2: User Support WP3: Data Analysis