EGEE-II INFSO-RI Enabling Grids for E-sciencE EGEE and gLite are registered trademarks The EGEE Infrastructure and Remote Instruments Erwin Laure EGEE-II Technical Director

Enabling Grids for E-sciencE EGEE-II INFSO-RI EGEE Main Objectives Operate a large-scale, production quality grid infrastructure for e-Science Attract new resources and users from industry as well as sciences Flagship grid infrastructure project co-funded by the European Commission Now in 2 nd phase with 91 partners in 32 countries RISGE - OGF22

Enabling Grids for E-sciencE EGEE-II INFSO-RI EGEE – What do we deliver? Infrastructure operation –Sites distributed across many countries  Large quantity of CPUs and storage  Continuous monitoring of grid services & automated site configuration/management  Support multiple Virtual Organisations from diverse research disciplines Middleware –Production quality middleware distributed under open source licence  Implements a service-oriented architecture that virtualises resources  Adheres to recommendations on web service inter-operability and evolving towards emerging standards User Support Managed process from first contact through to production usage –Training –Expertise in grid-enabling applications –Online helpdesk –Networking events (User Forum, Conferences etc.) RISGE - OGF22 Workload ManagementData Management Security Information & Monitoring Access API Computing Element Workload Management Metadata Catalog Storage Element Data Movement File & Replica Catalog Authorization Authentication Information & Monitoring Application Monitoring Auditing Job Provenance Package Manager CLI Accounting

Enabling Grids for E-sciencE EGEE-II INFSO-RI RISGE - OGF sites 48 countries 50,000 CPUs 13 PetaBytes >5000 users >200 VOs >140,000 jobs/day Archeology Astronomy Astrophysics Civil Protection Comp. Chemistry Earth Sciences Finance Fusion Geophysics High Energy Physics Life Sciences Multimedia Material Sciences … 32%

Enabling Grids for E-sciencE EGEE-II INFSO-RI Application Examples EGEE is used to analyze data coming from remote instruments LHC Medical Imaging Earth Observation and many others 5 RISGE - OGF22

Enabling Grids for E-sciencE EGEE-II INFSO-RI RISGE - OGF22 6 Accelerating and colliding particles Large Hadron Collider Mont Blanc (4810 m) Downtown Geneva 27 km circumference tunnel Due to start up in Million Particle collisions per second –Online filter reduces to a few 100 “good” events per second recorded on disk and magnetic tape at ,000 MegaBytes/sec –~15 PetaBytes per year for all four experiments Data analyzed by 100s of research groups world wide

Enabling Grids for E-sciencE EGEE-II INFSO-RI RISGE - OGF22 The Data Acquisition 7

Enabling Grids for E-sciencE EGEE-II INFSO-RI RISGE - OGF22 Acquisition, First pass reconstruction, Storage Distribution 8

Enabling Grids for E-sciencE EGEE-II INFSO-RI RISGE - OGF22 Data Distribution on the Grid 9

Enabling Grids for E-sciencE EGEE-II INFSO-RI Medical Data Manager Objectives –Expose an standard grid interface (SRM) for medical image servers (DICOM)‏ –Fulfil application security requirements without interfering with clinical practice DICOM server DICOM Interface SRM User Interface Worker Node DICOM clients 10 RISGE - OGF22

Enabling Grids for E-sciencE EGEE-II INFSO-RI Medical Data Registration DICOM server LFCAMGA Metadata Hydra Key store gfal 1. Image is acquired 2. Image is stored in DICOM server 3. lcg-put 3a. Image is registered (a GUID is associated)‏ 3b. Image key is produced and registered 4. image metadata are registered 11 RISGE - OGF22

Enabling Grids for E-sciencE EGEE-II INFSO-RI Earth Science Applications in EGEE ESA, UTV(IT), KNMI(NL), IPSL(FR)- Production and validation of 7 years of Ozone profiles from GOME Rapid Earthquake analysis (mechanism and epicenter) CPUs IPGP(FR) Modelling seawater intrusion in costal aquifer (SWIMED) CRS4(IT),INAT(TU), Univ.Neuchâtel(CH)- Geocluster for Academy and industry CGG(FR)- Flood of a Danube river- Cascade of models (meteorology,hydraulic,hydrodynamic….) UISAV(SK)- Specfem3D: Seismic application. Benchmark for MPI (2 to 2000 CPUs) (IPGP,FR) DKRZ(DE)- Data access studies, climate impacts on agriculture Data mining Meteorology & Space Weather (GCRAS, RU) Air Pollution model- BAS(BG) Mars atmosphere CETP( FR): 12 RISGE - OGF22

Enabling Grids for E-sciencE EGEE-II INFSO-RI GOME ESA(IT) – KNMI(NL) Processing of raw GOME data to ozone profiles. 2 alternative algorithms ~28000 profiles/day IPSL(FR) Validate some of the GOME ozone profiles (~10 6 /y) Coincident in space and time with Ground-Based measurements Visualization & Analyze EGEE environment Level 2 (example of 1 day total O 3 ) Level 1 Raw satellite data from the GOME instrument (~75 GB - ~5000 orbits/y) Meta Database server PosgreSQL geospatial search 13 RISGE - OGF22

Enabling Grids for E-sciencE EGEE-II INFSO-RI Summary EGEE provides a unique environment for storing, managing, and analyzing data from remote instruments Data production, collection, and initial processing is typically out of band –Instruments are not (and will not) be integrated in EGEE –Data is initially stored at domain specific data stores not connected to the Grid Sensor Grids are being established –E.g. LOFAR –Potential to be more directly integrated EGEE provides mechanisms to connect data collections to the infrastructure such that they can be used on the infrastructure 14 RISGE - OGF22