GridAssist, making the Grid invisible Ruud Grim Mark ter Linden Ivan Petiteville CEOS March 2005 Argentina.

Slides:



Advertisements
Similar presentations
The Access Grid Ivan R. Judson 5/25/2004.
Advertisements

ESA Data Integration Application Open Grid Services for Earth Observation Luigi Fusco, Pedro Gonçalves.
C. Grimme, A. Papaspyrou Scheduling in C3-Grid AstroGrid-D Workshop Project: C3-Grid Collaborative Climate Community Data and Processing Grid Scheduling.
1 CHEP 2000, Roberto Barbera Roberto Barbera (*) Grid monitoring with NAGIOS WP3-INFN Meeting, Naples, (*) Work in collaboration with.
A Computation Management Agent for Multi-Institutional Grids
May 17, Capabilities Description of a Rapid Prototyping Capability for Earth-Sun System Sciences RPC Project Team Mississippi State University.
USING THE GLOBUS TOOLKIT This summary by: Asad Samar / CALTECH/CMS Ben Segal / CERN-IT FULL INFO AT:
GRID workload management system and CMS fall production Massimo Sgaravatto INFN Padova.
Grid S.G. Ansari 15 June June June 2015 VSWG – Observatoire de Genève Variability detection, period search with GaiaGrid S. Ansari, L. Eyer,
Grid S.G. Ansari 16 June June June 2015 GaiaGrid – A three Year Experience Salim Ansari Toulouse 20 th October, 2005.
Computational Steering on the GRID Using a 3D model to Interact with a Large Scale Distributed Simulation in Real-Time Michael.
Office of Science U.S. Department of Energy Grids and Portals at NERSC Presented by Steve Chan.
Data Grids: Globus vs SRB. Maturity SRB  Older code base  Widely accepted across multiple communities  Core components are tightly integrated Globus.
Web-based Portal for Discovery, Retrieval and Visualization of Earth Science Datasets in Grid Environment Zhenping (Jane) Liu.
Astronomical GRID Applications at ESAC Science Archives and Computer Engineering Unit Science Operations Department ESA/ESAC.
Data Grid Web Services Chip Watson Jie Chen, Ying Chen, Bryan Hess, Walt Akers.
Slide 1 of 9 Presenting 24x7 Scheduler The art of computer automation Press PageDown key or click to advance.
Enabling Grids for E-sciencE Medical image processing web portal : Requirements analysis. An almost end user point of view … H. Benoit-Cattin,
Sergey Belov, Tatiana Goloskokova, Vladimir Korenkov, Nikolay Kutovskiy, Danila Oleynik, Artem Petrosyan, Roman Semenov, Alexander Uzhinskiy LIT JINR The.
EU 2nd Year Review – Jan – WP9 WP9 Earth Observation Applications Demonstration Pedro Goncalves :
The SAM-Grid Fabric Services Gabriele Garzoglio (for the SAM-Grid team) Computing Division Fermilab.
QCDgrid Technology James Perry, George Beckett, Lorna Smith EPCC, The University Of Edinburgh.
GRACE Project IST EGAAP meeting – Den Haag, 25/11/2004 Giuseppe Sisto – Telecom Italia Lab.
Connecting OurGrid & GridSAM A Short Overview. Content Goals OurGrid: architecture overview OurGrid: short overview GridSAM: short overview GridSAM: example.
DISTRIBUTED COMPUTING
Nicholas LoulloudesMarch 3 rd, 2009 g-Eclipse Testing and Benchmarking Grid Infrastructures using the g-Eclipse Framework Nicholas Loulloudes On behalf.
GT Components. Globus Toolkit A “toolkit” of services and packages for creating the basic grid computing infrastructure Higher level tools added to this.
Grids and Portals for VLAB Marlon Pierce Community Grids Lab Indiana University.
Grid Resource Allocation and Management (GRAM) Execution management Execution management –Deployment, scheduling and monitoring Community Scheduler Framework.
Through the development of advanced middleware, Grid computing has evolved to a mature technology in which scientists and researchers can leverage to gain.
COMP3019 Coursework: Introduction to GridSAM Steve Crouch School of Electronics and Computer Science.
Grid Workload Management & Condor Massimo Sgaravatto INFN Padova.
Scalable Systems Software Center Resource Management and Accounting Working Group Face-to-Face Meeting October 10-11, 2002.
Contents 1.Introduction, architecture 2.Live demonstration 3.Extensibility.
Shannon Hastings Multiscale Computing Laboratory Department of Biomedical Informatics.
Resource Brokering in the PROGRESS Project Juliusz Pukacki Grid Resource Management Workshop, October 2003.
Grid Computing at Yahoo! Sameer Paranjpye Mahadev Konar Yahoo!
EGEE-Forum – May 11, 2007 Enabling Grids for E-sciencE EGEE and gLite are registered trademarks A gateway platform for Grid Nicolas.
EGEE-III INFSO-RI Enabling Grids for E-sciencE EGEE and gLite are registered trademarks, An Overview of the GridWay Metascheduler.
Grid Architecture William E. Johnston Lawrence Berkeley National Lab and NASA Ames Research Center (These slides are available at grid.lbl.gov/~wej/Grids)
Ames Research CenterDivision 1 Information Power Grid (IPG) Overview Anthony Lisotta Computer Sciences Corporation NASA Ames May 2,
NA-MIC National Alliance for Medical Image Computing UCSD: Engineering Core 2 Portal and Grid Infrastructure.
Grid Security: Authentication Most Grids rely on a Public Key Infrastructure system for issuing credentials. Users are issued long term public and private.
What is SAM-Grid? Job Handling Data Handling Monitoring and Information.
GRID Overview Internet2 Member Meeting Spring 2003 Sandra Redman Information Technology and Systems Center and Information Technology Research Center National.
Introduction to Grids By: Fetahi Z. Wuhib [CSD2004-Team19]
INFSO-RI User Forum 1-3 March 2006 Enabling Grids for E-sciencE Worldwide ozone distribution by using Grid infrastructure ESA: L.
August 2003 At A Glance The IRC is a platform independent, extensible, and adaptive framework that provides robust, interactive, and distributed control.
Introduction to Grid Computing and its components.
EC Review – 01/03/2002 – WP9 – Earth Observation Applications – n° 1 WP9 Earth Observation Applications 1st Annual Review Report to the EU ESA, KNMI, IPSL,
2. WP9 – Earth Observation Applications ESA DataGrid Review Frascati, 10 June Welcome and introduction (15m) 2.WP9 – Earth Observation Applications.
EGI-InSPIRE RI EGI-InSPIRE EGI-InSPIRE RI How to integrate portals with the EGI monitoring system Dusan Vudragovic.
Open Grid Services for Earth Observation Pedro Gonçalves.
SAN DIEGO SUPERCOMPUTER CENTER Welcome to the 2nd Inca Workshop Sponsored by the NSF September 4 & 5, 2008 Presenters: Shava Smallen
Status of Globus activities Massimo Sgaravatto INFN Padova for the INFN Globus group
Copyright 2007, Information Builders. Slide 1 iWay Web Services and WebFOCUS Consumption Michael Florkowski Information Builders.
© Geodise Project, University of Southampton, Workflow Support for Advanced Grid-Enabled Computing Fenglian Xu *, M.
Simulation Production System Science Advisory Committee Meeting UW-Madison March 1 st -2 nd 2007 Juan Carlos Díaz Vélez.
A System for Monitoring and Management of Computational Grids Warren Smith Computer Sciences Corporation NASA Ames Research Center.
Frascati, 2-3 July 2008 Slide 1 HMA User Management in G-POD HMA-T Phase 2 KO Meeting 2-3 July 2008, Frascati Fabrice Brito, Terradue Srl
Research and Service Support Resources for EO data exploitation RSS Team, ESRIN, 23/01/2013 Requirements for a Federated Infrastructure.
DataGrid France 12 Feb – WP9 – n° 1 WP9 Earth Observation Applications.
WP 9.4 Use Case (ESA-ESRIN, IPSL, KNMI)
Simulation Production System
GLAST Release Manager Automated code compilation via the Release Manager Navid Golpayegani, GSFC/SSAI Overview The Release Manager is a program responsible.
Module 01 ETICS Overview ETICS Online Tutorials
04/02/2019 The Use of Grid Technology in Large Scale Data Processing Collaboration Environments S.G. Ansari S.G. Ansari 04/02/2019.
Large Scale Distributed Computing
Grid Systems: What do we need from web service standards?
Presentation transcript:

GridAssist, making the Grid invisible Ruud Grim Mark ter Linden Ivan Petiteville CEOS March 2005 Argentina

GridAssist, March 2005 CEOS Argentina Contents History Technical Details Operational Experiences Future Plans A user friendly service to support instrument calibration/validation & data (re-) processing.

GridAssist, March 2005 CEOS Argentina History EC FP4 OASE project –Collaboration environments for the simulation and data processing of Earth Observation data –Chains of applications in distributed environment –Used CORBA technology provided only limited functionality and was not properly secure (opening of ports in firewall needed) Atmosphere Model OMI Simulator Ground Data Processor Total Ozone Column UV Prediction Dutch Space Dutch Space DLR-DFDKNMIFMI

GridAssist, March 2005 CEOS Argentina GREASE Project (ESA) Same concept, with new chassis (Grid) and powered by new engine (Globus Toolkit 2.x) The environment should be easy to use and should hide the underlying Grid technology for the scientific user Workflow and service oriented approach – more than simple chains of applications. Service A Service B Service C Service D Service E Service F

GridAssist, March 2005 CEOS Argentina Concept User friendly client tools run locally on the users workstations for constructing workflows and monitoring jobs Centralized controller executes the workflows on the Grid Controller implemented as Web Service for easy and standardized access (even through firewalls) Workstations with client tools Controller Grid resources LAN SOAPGrid

GridAssist, March 2005 CEOS Argentina Use cases within ESA Instrument validation Mission simulation Archive reprocessing Instrument test data generation (via simulation) Production-on-Demand Concurrent design Satisfying different functional needs: Collaboration Computing power Controlled provision & access of services

GridAssist, March 2005 CEOS Argentina Grid Instrument validation (#3) Mission simulation (#2) Archive reprocessing Instrument test data generation (#1) Production-on-Demand Concurrent design Examples (#) 1.OMI test data generation 2.ENVISAT validation 3.GAIA mission analysis & Grid-on-Demand Concurrent Design Facility

GridAssist, March 2005 CEOS Argentina UC#1: OMI (NASA AURA) (launched summer 2004) Main products: Ozone columns, profiles 6-7 GB / day (Level 0 data) Optical Assembly Electronic Assembly

GridAssist, March 2005 CEOS Argentina UC#1: Scanning the Earth daily Continue global total ozone trends Nominal 13 x 24 km spatial resolution or 13 x 13 km for detecting and tracking urban-scale pollution sources

GridAssist, March 2005 CEOS Argentina UC#1: Test data generation Fall 2003: Generation of one month of simulated OMI data for Ground Segment Verification (starting beginning 2004) –230,000 simulation runs of 2 minutes each (total 7666 hours) –Between 50 and 80 CPU’s were used in a 6 week period –32 Gb telemetry data produced and transferred to NASA Existing GOME Data OMI Instr. Simulator Level 2 Algorithm Level 1b Processor Raw Data Generator Level 0 Processor spectrum CCD output telemetry Level 0 Level 1 Grid NASA GS

GridAssist, March 2005 CEOS Argentina UC#2: Instrument Validation What is required? Additional validated data –In-situ measurements Aircraft Balloon Ground (lidar) –Other space instrumentation Quality Assurance Common data sets Algorithms Tools, converters, visualization tools Good communication & collaboration

GridAssist, March 2005 CEOS Argentina UC#2: ECV Prototype (ESA THE VOICE project) Demonstrate possibilities of e-Collaboration for cal / val Authorization & Authentication Communication (agenda, documentation) Access to –Meta data catalogue –Data store –Applications & tools Under configuration control In development Workflow Management (GridAssist) Publish & Subscribe

GridAssist, March 2005 CEOS Argentina UC#2: Validation Workflow Access to data stores –GOME Level 2 –LIDAR (at IPSL or NILU) On-demand processing Publish/Subscribe to notify users

GridAssist, March 2005 CEOS Argentina UC#2 THE VOICE Workflow Environment Data stores Applications Workflow submission Drag-and-Drop Connecting Click-and-Drop Access to Data stores

GridAssist, March 2005 CEOS Argentina UC#2: VOICE collaboration crossing boundaries ESAC VillaFranca ESTEC & Dutch Space KNMI RIVM IPSL Univ Bremen Tor Vergata BIRA/IASB Genève NILU ESRIN NASA

GridAssist, March 2005 CEOS Argentina UC#3: Gaia mission analysis Science objectives Map 10^9 stars in our Galaxy –Astrometry –Photometry –Spectra Studies –Structure & kinematics of Galaxy –Stellar populations –Origin, formation & evolution of Galaxy –Stellar astrophysics –Cosmology –Extra-solar planetary science –Fundamental physics Core Processing (Global Iterative Solution) using subset of 10^8 stars with –Raw data –Calibrated data –Attitude data –Science data 500 TB over 5 yr 10^20 flop CPU

GridAssist, March 2005 CEOS Argentina UC#3: Gaia Processing Foreseen architecture (May 2004)

GridAssist, March 2005 CEOS Argentina UC#3: GAIA collaboration Barcelona Core Tasks Meudon RVS Heidelberg Quick Looks Cambridge Photometry Leiden Photometry Lund Astrometry Trieste RVS Bruxelles ABS Turino Minor Planets RVS Geneve Variable Stars Nice Fundamental Algos CopenhagueESTEC Dutch Space ESRIN ESAC Database CNES? Binary star simulation with the GASS (Gaia Simulator) –5 year period, submitted as 5 jobs covering 1 year each –Executed on 23 CPU’s in 8 institutes of 5 countries –Total of 3.8 million CPU seconds used –16.5 Gb telemetry data produced and transferred to CESCA –>1,100 jobs submitted in 6 months Data extraction from GDAAS database (Oracle) –Very flexible using Java as query language

GridAssist, March 2005 CEOS Argentina Benefits of GridAssist Easy and secure access to applications, data and resources Satisfying both collaboration & HPC needs Unattended execution of large and/or complex jobs using workflows Low failure rate (>95% of jobs are successfully completed) Supports logging at three levels –Application, GridAssist, Globus No or little modifications needed to existing applications; new applications can be added fast The Grid environment can easily be extended with more resources Easiness of installation

GridAssist, March 2005 CEOS Argentina Lessons Learned The GridAssist Workflow Tool proved to be a very user- friendly and intuitive tool; users can use it almost directly It complies to both High Performance Computing and collaboration needs within ESA; users are very enthusiastic Interface problems between applications can be detected early in the development process Approach to use GridAssist to run applications on the Grid is usable for many fields that have similar scientific data processing needs (Earth Observation, Astronomy, …?)

GridAssist, March 2005 CEOS Argentina Future plans Continue development –Improve robustness –Improved workflow features, user management –Improved access to data stores –Interoperability (e.g. gLite) Project operations support –Mission analysis –Instrument calibration / validation –Application development –Level 3 & 4 product processing –Archive re-processing

GridAssist, March 2005 CEOS Argentina More info? Web site: Contact persons: –Ivan Petiteville (ESA ESRIN) telephone: –Ruud Grim (GridAssist Project Manager) telephone: –Mark ter Linden (GridAssist Developer) telephone: Photos: courtesy ESA, NASA, KNMI and Internet

GridAssist, March 2005 CEOS Argentina Questions ? + + Develop locally, compute and collaborate globally on the Grid.

GridAssist, March 2005 CEOS Argentina The Grid Around 1998 the Grid concept was introduced: Sharing resources in Virtual Organizations Demand driven access to computing power Increased utilization of idle capacity Greater sharing of computational results

GridAssist, March 2005 CEOS Argentina Grid Environment Grid environment based on Globus Toolkit 2.x using: Globus Resource Allocation and Management (GRAM) –Remote job submission and control –Interface to local job management systems (PBS, LSF, Condor) GridFTP –High performance, secure, reliable data transfer Grid Security Infrastructure (GSI) –Single sign-on and secure communication –Based on Public Key encryption and X.509 certificates

GridAssist, March 2005 CEOS Argentina Features Workflow Tool –User interface implemented in Java (Windows, Linux, Unix, Mac) –To add / modify / remove applications, resources and properties –To create, start and monitor workflows –Embed additional (new) services, e.g. browsing in database, logging at 3 levels, converters, notification services, visualization Embed batch programs, not (yet) interactive –No requirements on language (Java, Fortran, C, IDL, …). –User can configure runtime parameters Central registry –Storage of information about applications and resources –Configuration control

GridAssist, March 2005 CEOS Argentina Architecture Implementation in Java – cross platform (tested on Windows, Linux and Mac) Apache Jakarta Tomcat Web Server Apache AXIS GridAssist Workflow Engine Java CoG-kit JDBC Connector GridAssist Workflow Tool MySQL Database Globus Toolkit Data Processing Application Apache AXIS User Workstation Controller Grid Resource SOAP Globus specific protocols LAN Grid

GridAssist, March 2005 CEOS Argentina Workflow Tool Maintaining the registry Resources Services Resource or service details

GridAssist, March 2005 CEOS Argentina Workflow Tool Creating the workflow Data stores Applications Workflow submission Drag-and-Drop Connecting Click-and-Drop

GridAssist, March 2005 CEOS Argentina Workflow Tool Status Monitoring Availability & Usage Submitted workflows & status overview

GridAssist, March 2005 CEOS Argentina Hiding Grid technology Intuitive GUI preferred DAG structured Dynamic execution Fault tolerance build-in

GridAssist, March 2005 CEOS Argentina Data Processing Applications Batch programs, not interactive. No requirements on language (Java, Fortran, C, IDL, …). Applications do not have to be modified. Applications can be configured by the user using runtime parameters. A simple wrapper shell script can be written to handle the input, output and the runtime parameters. The application itself can be stored on the Grid resource but also on a storage node (in this case only the wrapper script need to be present on the Grid resource).