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Grid Production Experience in the ATLAS Experiment

Grid Production Experience in the ATLAS Experiment. Kaushik De University of Texas at Arlington BNL Technology Meeting March 29, 2004. ATLAS Data Challenges. Original Goals (Nov 15, 2001)

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Grid Production Experience in the ATLAS Experiment

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  1. Grid Production Experience in the ATLAS Experiment Kaushik De University of Texas at Arlington BNL Technology Meeting March 29, 2004

  2. ATLAS Data Challenges • Original Goals (Nov 15, 2001) • Test computing model, its software, its data model, and to ensure the correctness of the technical choices to be made • Data Challenges should be executed at the prototype Tier centres • Data challenges will be used as input for a Computing Technical Design Report due by the end of 2003 (?) and for preparing a MoU • Current Status • Goals are evolving as we gain experience • Computing TDR ~end of 2004 • DC’s are ~yearly sequence of increasing scale & complexity • DC0 and DC1 (completed) • DC2 (2004), DC3, and DC4 planned • Grid deployment and testing is major part of DC’s Kaushik De, BNL Technology Meeting

  3. ATLAS DC1: July 2002-April 2003Goals : Produce the data needed for the HLT TDR Get as many ATLAS institutes involved as possibleWorldwide collaborative activityParticipation : 56 Institutes • Australia • Austria • Canada • CERN • China • Czech Republic • Denmark * • France • Germany • Greece • Israel • Italy • Japan • Norway * • Poland • Russia • Spain • Sweden * • Taiwan • UK • USA * • * using Grid Kaushik De, BNL Technology Meeting

  4. Process No. of events CPU Time CPU-days (400 SI2k) Volume of data kSI2k.months TB Simulation Physics evt. 107 415 30000 23 Simulation Single part. 3x107 125 9600 2 Lumi02 Pile-up 4x106 22 1650 14 Lumi10 Pile-up 2.8x106 78 6000 21 Reconstruction 4x106 50 3750 Reconstruction + Lvl1/2 2.5x106 (84) (6300) Total 690 (+84) 51000 (+6300) 60 DC1 Statistics (G. Poulard, July 2003) Kaushik De, BNL Technology Meeting

  5. U.S. ATLAS DC1 Data Production • Year long process, Summer 2002-2003 • Played 2nd largest role in ATLAS DC1 • Exercised both farm and grid based production • 10 U.S. sites participating • Tier 1: BNL, Tier 2 prototypes: BU, IU/UC, Grid Testbed sites: ANL, LBNL, UM, OU, SMU, UTA (UNM & UTPA will join for DC2) • Generated ~2 million fully simulated, piled-up and reconstructed events • U.S. was largest grid-based DC1 data producer in ATLAS • Data used for HLT TDR, Athens physics workshop, reconstruction software tests... Kaushik De, BNL Technology Meeting

  6. BNL - U.S. Tier 1, 2000 nodes, 5% for ATLAS, 10 TB, HPSS through Magda LBNL - pdsf cluster, 400 nodes, 5% for ATLAS (more if idle ~10-15% used), 1TB Boston U. - prototype Tier 2, 64 nodes Indiana U. - prototype Tier 2, 64 nodes UT Arlington - new 200 cpu’s, 50 TB Oklahoma U. - OSCER facility U. Michigan - test nodes ANL - test nodes, JAZZ cluster SMU - 6 production nodes UNM - Los Lobos cluster U. Chicago - test nodes U.S. ATLAS Grid Testbed Kaushik De, BNL Technology Meeting

  7. U.S. Production Summary • Exercised both farm and grid based production • Valuable large scale grid based production experience * Total ~30 CPU YEARS delivered to DC1 from U.S. * Total produced file size ~20TB on HPSS tape system, ~10TB on disk. * Black - majority grid produced, Blue - majority farm produced Kaushik De, BNL Technology Meeting

  8. Figure : Pie chart showing the number of pile-up jobs successfully completed at various U.S. grid sites for dataset 2001 (25 GeV dijets). A total of 6000 partitions were generated. Figure : Pie chart showing the sites where DC1 single particle simulation jobs were processed. Only three grid testbed sites were used for this production in August 2002. Grid Production Statistics These are examples of some datasets produced on the Grid. Many other large samples were produced, especially at BNL using batch. Kaushik De, BNL Technology Meeting

  9. DC1 Production Systems • Local batch systems - bulk of production • GRAT - grid scripts, generated ~50k files produced in U.S. • NorduGrid - grid system, ~10k files in Nordic countries • AtCom - GUI, ~10k files at CERN (mostly batch) • GCE - Chimera based, ~1k files produced • GRAPPA - interactive GUI for individual user • EDG/LCG - test files only • + systems I forgot… • More systems coming for DC2 • Windmill • GANGA • DIAL Kaushik De, BNL Technology Meeting

  10. GRAT Software • GRid Applications Toolkit • developed by KD, Horst Severini, Mark Sosebee, and students • Based on Globus, Magda & MySQL • Shell & Python scripts, modular design • Rapid development platform • Quickly develop packages as needed by DC • Physics simulation (GEANT/ATLSIM) • Pileup production & data management • Reconstruction • Test grid middleware, test grid performance • Modules can be easily enhanced or replaced, e.g. EDG resource broker, Chimera, replica catalogue… (in progress) Kaushik De, BNL Technology Meeting

  11. Prod. (UTA) MAGDA (BNL) Replica (local) 9 8 scratch 2 4 7 1,4,5,10 DC1 Remote Gatekeeper 5 Batch Execution 6 3 Param (CERN) GRAT Execution Model 1. Resource Discovery 2. Partition Selection 3. Job Creation 4. Pre-staging 5. Batch Submission 6. Job Parameterization 7. Simulation 8. Post-staging 9. Cataloging 10. Monitoring Kaushik De, BNL Technology Meeting

  12. Databases used in GRAT • Production database • define logical job parameters & filenames • track job status, updated periodically by scripts • Data management (Magda) • file registration/catalogue • grid based file transfers • Virtual Data Catalogue • simulation job definition • job parameters, random numbers • Metadata catalogue (AMI) • post-production summary information • data provenance Kaushik De, BNL Technology Meeting

  13. U.S. Middleware Evolution Globus Used for 95% of DC1 production Condor-G Used successfully for simulation Used successfully for simulation (complex pile-up workflow not yet) DAGMan Tested for simulation, used for all grid-based reconstruction Chimera LCG Kaushik De, BNL Technology Meeting

  14. DC1 Production Experience • Grid paradigm works, using Globus • Opportunistic use of existing resources, run anywhere, from anywhere, by anyone... • Successfully exercised grid middleware with increasingly complex tasks • Simulation: create physics data from pre-defined parameters and input files, CPU intensive • Pile-up: mix ~2500 min-bias data files into physics simulation files, data intensive • Reconstruction: data intensive, multiple passes • Data tracking: multiple steps, one -> many -> many more mappings Kaushik De, BNL Technology Meeting

  15. Grid Quality of Service • Anything that can go wrong, WILL go wrong • During a 18 day run, every system died at least once • Local experts were not always be accessible • Examples: scheduling machines died 5 times (thrice power failure, twice system hung), Network outages multiple times, Gatekeeper died at every site at least 2-3 times • All three databases died at least once! • Scheduled maintenance - HPSS, Magda server, LBNL hardware... • Poor cleanup, lack of fault tolerance in Globus • These outages should be expected on the grid - software design must be robust • We managed > 100 files/day (~80% efficiency) in spite of these problems! Kaushik De, BNL Technology Meeting

  16. Software Issues • ATLAS software distribution worked well for DC1 farm production, but not well suited for grid production • No integration of databases - caused many problems • Magda & AMI very useful - but we are missing data management tool for truly distributed production • Required a lot of people to run production in the U.S., especially with so many sites on both grid and farm • Startup of grid production slow - but learned useful lessons • Software releases were often late - leading to chaotic last minute rush to finish production Kaushik De, BNL Technology Meeting

  17. New Production System for DC2 • Goals • Automated data production system for all ATLAS facilities • Common database for all production - Oracle currently • Common supervisor run by all facilities/managers - Windmill • Common data management system - Don Quichote • Executors developed by middleware experts (Capone, LCG, NorduGrid, batch systems, CanadaGrid...) • Final verification of data done by supervisor Kaushik De, BNL Technology Meeting

  18. Windmill - Supervisor • Supervisor development/U.S. DC production team • UTA: Kaushik De, Mark Sosebee, Nurcan Ozturk + students • BNL: Wensheng Deng, Rich Baker • OU: Horst Severini • ANL: Ed May • Windmill web page • http://www-hep.uta.edu/windmill • Windmill status • version 0.5 released February 23 • includes complete library of xml messages between agents • includes sample executors for local, pbs and web services • can run on any Linux machine with Python 2.2 • development continuing - Oracle production DB, DMS, new schema Kaushik De, BNL Technology Meeting

  19. XML switch (Jabber Server) XMPP (XML) XMPP (XML) Web server SOAP supervisor agent executor agent Windmill Messaging • All messaging is XML based • Agents communicate using Jabber (open chat) protocol • Agents have same command line interface - GUI in future • Agents & web server can run at same or different locations • Executor accesses grid directly and/or thru web services Kaushik De, BNL Technology Meeting

  20. Jabber Clients Jabber Clients Jabber Server XMPP Intelligent Agents • Supervisor/executor are intelligent communication agents • uses Jabber open source instant messaging framework • Jabber server routes XMPP messages - acts as XML data switch • reliable p2p asynchronous message delivery through firewalls • built in support for dynamic ‘directory’, ‘discovery’, ‘presence’ • extensible - we can add monitoring, debugging agents easily • provides ‘chat’ capability for free - collaboration among operators • Jabber grid proxy under development (LBNL - Agarwal) Kaushik De, BNL Technology Meeting

  21. Core XML Messages • numJobsWanted • supervisor-executor negotiation of number of jobs to process • executeJobs • supervisor sends XML based job definitions • getExecutorData • job acceptance, handle exchange (supports stateless executors) • getStatus • polling of job status • fixJobs • post-reprocessing and cleanup • killJob • forced job abort Kaushik De, BNL Technology Meeting

  22. Core Windmill Libraries • interact.py - command line interface library • agents.py - common intelligent agent library • xmlkit.py - xml creation (generic) and parsing library • messages.py - xml message creation (specific) • proddb.py - production database methods for oracle, mysql, local, dummy, and possibly other options • supervise.py - supervisor methods to drive production • execute.py - executor methods to run facilities Kaushik De, BNL Technology Meeting

  23. Capone Executor • Various executors are being developed • Capone - U.S. VDT executor by U. of Chicago and Argonne • Lexor - LCG executor mostly by Italian groups • NorduGrid, batch (Munich), Canadian, Australian(?) • Capone is based on GCE (Grid Computing Environment) • (VDT Client/Server, Chimera, Pegasus, Condor, Globus) • Status: • Python module • Process “thread” for each job • Archive of managed jobs • Job management • Grid monitoring • Aware of key parameters (e.g. available CPUs, jobs running) Kaushik De, BNL Technology Meeting

  24. Message protocols Web Service Jabber Translation Windmill ADA CPE Grid Stub DonQuixote Capone Architecture • Message interface • Web Service • Jabber • Translation level • Windmill • CPE (Capone Process Engine) • Processes • Grid • Stub • DonQuixote from Marco Mambelli Kaushik De, BNL Technology Meeting

  25. DAXgen RLSreg translate running/checking genmydax registerToRLS gceTrans check recovery recovery recovery recovery Capone Processing executeJob received • Supervisor requests • Jobs • Different job statuses: • 'received','translate','DAXgen','RLSreg','scheduling','cDAGgen','submission','running', 'checking','stageOut','cleaning','end','killing’ • completed/failed (each step) • Completion/failure (job) recovery … stageOut stageOut recovery end fixJob Kaushik De, BNL Technology Meeting

  26. Windmill Screenshots Kaushik De, BNL Technology Meeting

  27. Kaushik De, BNL Technology Meeting

  28. Web Services Example Kaushik De, BNL Technology Meeting

  29. Conclusion • Data Challenges are important for ATLAS software and computing infrastructure readiness • Grids will be the default testbed for DC2 • U.S. playing a major role in DC2 planning & production • 12 U.S. sites ready to participate in DC2 • Major U.S. role in production software development • Test of new grid production system imminent • Physics analysis will be emphasis of DC2 - new experience • Stay tuned Kaushik De, BNL Technology Meeting

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