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LHCb-INFN Computing for the years 2003-2005

LHCb-INFN Computing for the years 2003-2005. CSN1, Perugia, November 11, 2002 Domenico Galli, Bologna. Outline. LHCb Constraints : Experiment milestones in 2003-2005 which require computing power. Software : SICbMC/Geant-3, Gaudi, Gauss/Geant-4, Giga, Brunel, DaVinci. Grid integration :

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LHCb-INFN Computing for the years 2003-2005

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  1. LHCb-INFN Computing for the years 2003-2005 CSN1, Perugia, November 11, 2002 Domenico Galli, Bologna

  2. Outline • LHCb Constraints: • Experiment milestones in 2003-2005 which require computing power. • Software: • SICbMC/Geant-3, Gaudi, Gauss/Geant-4, Giga, Brunel, DaVinci. • Grid integration: • Ganga. • Computing Model: • Tier-1, (Tier-2), Tier-3, Tier-4 functionalities. • Last Bologna/CNAF Farm improvement: • Analysis facility. Status of LHCb-INFN Computing, 2 Domenico Galli

  3. LHCb Constraints Status of LHCb-INFN Computing, 3 Domenico Galli

  4. LHCb Constraints • LHCb TDR: September 2003. • L0/L1 trigger TDR: September 2003. • L23 trigger TDR: Q4/2003. • Statistics increase of a factor of 2. • Computing TDR: Q4/2004. • Gauss/Geant-4 large scale testing and tuning: • After LHCb design and TDR delivery. Status of LHCb-INFN Computing, 4 Domenico Galli

  5. MC Production Plan (2002-2003) • Nov 22: End software improvement. • Nov 22 – Dec 16: Brunel final commissioning. • Dec 16 – Jan 13: Pre-production (~3 Mevents). • Jan 8 – Jan 27: Data quality tests. • Jan 22 – Feb 4: Prepare production version. • Feb 4 – May 4: Final MC production (~15 Mevents). • Summer: Possible reprocessing. • Sep 9: TDR submission (LHCb, Trigger). Status of LHCb-INFN Computing, 5 Domenico Galli

  6. Software Status of LHCb-INFN Computing, 6 Domenico Galli

  7. Software Status • Present LHCb production software: • Monte Carlo: SICbMC: Geant-3/FORTRAN • Reconstruction: Brunel: OO/Gaudi/C++ • Analysis: DaVinci: OO/Gaudi/C++ • Present LHCb development software: • Monte Carlo: Gauss: OO/Geant-4/Gaudi/C++ • A first version of the whole simulation chain using Gauss/Geant-4 is now working. • Starting to study the response of the detectors in detail. Status of LHCb-INFN Computing, 7 Domenico Galli

  8. GAUDI: the Framework • LHCb Collaboration is convinced of the importance of the architecture since long time. • Sep 1998 – project started, GAUDI team assembled. • Brunel (reconstruction) & DaVinci (analysis) use GAUDI. • “framework is an artefact that guarantees the architecture is respected” • to be used in all the LHCb event data processing applications including: high level trigger, simulation, reconstruction, analysis. • Build high quality components and maximize reuse. • The proposed LCG architectureis not very different from the GAUDI architecture (see RTAG architectural “blueprint”). • the component model, role of interfaces, plug-in, basic framework services, interactive services, etc. are very similar. Status of LHCb-INFN Computing, 8 Domenico Galli

  9. Converter Converter Application Manager Converter Event Selector Transient Event Store Data Files Message Service Persistency Service Event Data Service JobOptions Service Algorithm Algorithm Algorithm Data Files Transient Detector Store Particle Prop. Service Persistency Service Detec. Data Service Other Services Data Files Transient Histogram Store Persistency Service Histogram Service The GAUDI Framework Status of LHCb-INFN Computing, 9 Domenico Galli

  10. GAUDI Architecture: Design Criteria • Framework contains real code. • Implementations of class methods, not only interfaces. • Clear separation between data-type and actor-type (algorithms) objects. • Three basic types of data: event, detector, statistics. • Clear separation between persistent and transient data. • Computation-centric architectural style. • focus is on the transformation of objects that are interesting to the system. • User code encapsulated in few specific places: algorithms and converters. • All components with well defined interfaces and as generic as possible. Status of LHCb-INFN Computing, 10 Domenico Galli

  11. GAUDI: Collaboration with Other Experiments • ATLAS also contributing to the development of GAUDI • Open-Source style, experiment independent web and release area. • Other experiments are also using GAUDI: • HARP, GLAST, OPERA • Encouragement to put more quality into the product. • Better testing in different environments (platforms, domains,…). • Shared long-term maintenance. Status of LHCb-INFN Computing, 11 Domenico Galli

  12. GAUDI: Changes to Comply with LCG • The proposed LCG architecture is not very different from the GAUDI architecture. • No big problem in adopting the concrete LCG software when available • Unavoidable code changes will be required but the end-user code is well isolated. • The “end-user” physicist should not see any difference. • The Algorithm code stays unchanged. • Most probable changes in the component configuration (JobOptions). Status of LHCb-INFN Computing, 12 Domenico Galli

  13. GAUDI: Changes to Comply with LCG (III) LCG CTS LCG Pool LCG CTS LCG CTS LCG DDDD HepPDT Other LCG services AIDA LCG Pool Status of LHCb-INFN Computing, 13 Domenico Galli

  14. Gauss: Transition to Geant 4 • Geometry Input: XML database. A version available for all the detectors in LHCb. • All detectors are in the new framework (GAUSS: Geant-4 simulation). • Gaudi-Geant4 interface (GiGa: GEANT4 Interface for Gaudi Applications). • Input events: From Pythia or other similar programs through the HEPMC interface into GEANT4. • Starting to study the response of the detectors in detail. • Need large scale testing and tuning (after LHCb design and TDR delivery). • MC transition to Geant4/C++ in production foreseen for 2004. Status of LHCb-INFN Computing, 14 Domenico Galli

  15. Grid Integration Status of LHCb-INFN Computing, 15 Domenico Galli

  16. Ganga: Gaudi/Athena and Grid Alliance • ATLAS and LHCb develop applications within a common framework: Gaudi/Athena. • Both collaborations aim to exploit potential of Grid for large-scale, data-intensive distributed computing. • Simplify management of analysis and production jobs for end-user physicists by developing tool for accessing Grid services with built-in knowledge of how Gaudi/Athena works. Status of LHCb-INFN Computing, 16 Domenico Galli

  17. GANGA GUI Collective & Resource Grid Services Histograms Monitoring Results JobOptions Algorithms GAUDI Program Ganga: Gaudi/Athena and Grid Alliance Status of LHCb-INFN Computing, 17 Domenico Galli

  18. General requirements for GANGA • The user will interact with a single application integrating all stages of job life-time. • He will be able to restore his or her workspace (list of files, tools state, jobs in preparation) at the beginning of each session. • The GUI will be similar to work with, for both the Grid and a local network. • It will be similar to the mailing system (e.g. Outlook Express), with jobs taking role the mails. The goal is to perform configuring/running Gaudi job as easy as sending a mail. • Interface access not only from the computer with the Grid UI program running, but also from a remote “thin” client. • The aim is to have a first release of Ganga for the end of the year. Status of LHCb-INFN Computing, 18 Domenico Galli

  19. Ganga Prototyping Tree of user jobs Job options for selected job Embedded Python interpreter Status of LHCb-INFN Computing, 19 Domenico Galli

  20. Computing Model Status of LHCb-INFN Computing, 20 Domenico Galli

  21. Tier-2 Computer Centers • Network bandwidth increase and grid software integration make the resources location transparent for the end-users (the physicists performing analysis jobs). • LHCb-Italy plans to store computing resources in the places in which is available manpower for system design, management and administration (not for physical analysis). • Need of Tier-2 Computer Centers not foreseen for LHCb-Italy (at least at present). Status of LHCb-INFN Computing, 21 Domenico Galli

  22. Tier-3 Computer Centers • Not thought for Monte Carlo production but can be used as a booster for peak needs. • 2 Functionalities: • As buffer-cache for the analysis data between Tier-1 (AOD storage) and Tier-4 (user desktop/interactive analysis). • As parallel interactive analysis facility (using JAS/RMI or ROOT/PROOF, like PIAF facility at CERN since 1993). • The size in CPU-power and disk storage need to be determined on the basis of the simulation of the data flow between Tier-1 and Tier-4. • Preliminary test on Firenze Farm. • On-the-field test in high level trigger studies foreseen. Status of LHCb-INFN Computing, 22 Domenico Galli

  23. Tier-3 as Buffer-Cache Request load AOD retrieve Tier-4 Tier-3 Tier-1 Look-up register Data not present on local storage Catalog Data present on local storage AOD AOD Status of LHCb-INFN Computing, 23 Domenico Galli

  24. proof master proof slave proof slave proof slave proof slave ROOT/PROOF (Parallel Root Facility) • Traditional Master/Slave approach root node1 node2 • Cint ROOT C++ command line interface is usable by C++ gurus, but not by most of physics. node3 node4 Status of LHCb-INFN Computing, 24 Domenico Galli

  25. JAS/RMI (Remote Method Invocation) • Server calls registry to associate a name with a remote object. • Client looks up the remote object by its name in the server’s registry and then invokes a method on it. registry RMI RMI server client RMI RMI RMI URL Web server registry URL server RMI Status of LHCb-INFN Computing, 25 Domenico Galli

  26. Possible JavaSpaces implementation • Based on Lindacoordination language (Yale University). • Programming = Computation + Coordination • Uncoupling senders and receivers. • Intrinsic adaptive load balancing (on heterogeneous resources too). • Intrinsic robustness. Status of LHCb-INFN Computing, 26 Domenico Galli

  27. Last Bologna/CNAF Farm improvement Status of LHCb-INFN Computing, 27 Domenico Galli

  28. NAS NAS 1 TB RAID5 1 TB RAID5 Gateway Analysis Station 1 PVFS Striped Disk Array (1 TB) Analysis Station 12 Public Private VLAN VLAN Analysis Station 13 Fast Ethernet Uplink Switch Analysis Station 14 Analysis Station 15 Manager Node MC Prod. node 1 MC Prod. node 40 Bologna/CNAF LHCb Farm Architecture Status of LHCb-INFN Computing, 28 Domenico Galli

  29. Ntuple ION 1 DaVinci 1 ION 2 Ntuple DaVinci 2 I/O servers Network ION 12 Ntuple DaVinci 80 MGR Meta data server High Performance I/O System • I/O parallelization system successfully tested and put in production • PVFS (Parallel Virtual File System). • Striping of data files among local disks of several I/O servers (ION). • Scalable System (maximum throughput ~ 100 Mbit/s x number of IONs) Status of LHCb-INFN Computing, 29 Domenico Galli

  30. Benchmark Results on B Analysis • 80 DaVinci processes reading from PVFS (2000 events per job) • 2288 files (500 OODST events each) x 120 MB • 75 MB out of 120 MB are actually retrieved by the algorithm • 167 GB read from the network and processed in 4600 s Status of LHCb-INFN Computing, 30 Domenico Galli

  31. Farm Monitor Tool • Interactive. • Based on java applet (presentation logic)/java servlet (data selection logic) technology and Jakarta Tomcat. • Transfers data (not graphics). • Completely configurable using XML. • Developed together with CNAF. Status of LHCb-INFN Computing, 31 Domenico Galli

  32. Extra slides Status of LHCb-INFN Computing, 32 Domenico Galli

  33. Applications Reconstruction Framework Visualization Framework Simulation Framework OtherFrameworks . . . Basic Framework Foundation Libraries Optional Libraries Software Structure Applications built on top of frameworks and implementing the required physics algorithms. Various specialized frameworks: visualization, persistency, interactivity, simulation, etc. Main framework A series of basic libraries widely used: STL, CLHEP, etc. Status of LHCb-INFN Computing, 33 Domenico Galli

  34. GAUDI: Changes to Comply with LCG (II) • LHCb model of describing the Event Model with GOD (Gaudi Object Description) XML files will continue to work. • We can generate the code to populate the LCG Object dictionary, which then will be used by POOL to provide object persistency (based on ROOT I/O). • The “end-user” physicist should not see any difference. • The Algorithm code stays unchanged. • Most probable changes in the component configuration (JobOptions). Status of LHCb-INFN Computing, 34 Domenico Galli

  35. Gauss application JobOpts JobOpts JobOpts Int.face GiGa Digi Alg Geant4 (GiGa) Pythia etc Geant4 MCParticle MCVertex MCHit Digit MCDigit HepMC Cnv Cnv Cnv Geometry Generator Detector Simulation Status of LHCb-INFN Computing, 35 Domenico Galli

  36. GiGa structure Data Files Persistency Service Application Manager GiGaKine Conversion Service G4 Kine Transient Event Store Event Service Geant4 GiGaHits Conversion Service G4 Hits Converter Algorithm Cnv GiGa Service Algorithm Algorithm Cnv Transient Detector Store GiGaGeom Conversion Service G4 Geom Action Detec. Service Action Other Services Data Files Persistency Service Status of LHCb-INFN Computing, 36 Domenico Galli

  37. Production Editor Work flow Editor Production DB Production data Scripts Edit Instantiate Workflow Production Server • Job request • Status updates Prod.Mgr Production Center Bookkeeping info BookkeepingUpdates Production Components Status of LHCb-INFN Computing, 37 Domenico Galli

  38. Bookkeeping info Production center Local Prod. manager Submit job Central Prod. manager Job n Transfer data Job scripts Production Worker scripts BK files Log files bbftp Data files Histo files Castor Storage Batch farm Current Production Scheme Status of LHCb-INFN Computing, 38 Domenico Galli

  39. Job status update Job request Job status update Production center Production Agent Submit job Job Bookkeeping info n Check data Transfer data Production Worker scripts BK files Log files bbftp Castor Data files Histo files Batch farm Storage Production Agent Status of LHCb-INFN Computing, 39 Domenico Galli

  40. Agent Advantages • Actively asks for the work to be done: • no idle “forgotten” resources; • Runs locally at a production center: • no problems with write access to local file system; • Automates most of the routine production tasks: • software updates; • submit jobs; • transfer data; • update bookkeeping; Status of LHCb-INFN Computing, 40 Domenico Galli

  41. Required Functionality (I) • Job preparation and configuration • Resource booking • Job submission • User can choose between Grid and local resource management system • Job monitoring and control • GUI for the resource browsing • Virtual Organisation active services • Computing Elements • Storage Elements • Query existing files in the Grid • GUI for data management tools • e.g., Dataset registration to the Grid (used by Production Manager) • Copy file from a Computing Element to a Storage Element • Replication of files Status of LHCb-INFN Computing, 41 Domenico Galli

  42. Required Functionality (II) • Job preparation and configuration: • Determine job requirements in terms of software products needed: executables, libraries, databases, etc. • Get access to the Job Configurations DB: • Common configurations could be stored in a database and retrieved using high-level commands • User would have possibility of modifying settings and storing personalised configurations in his/her own area • Perform job configuration: • select algorithms to run and set properties • specify input event data, requested output, etc • Provide graphical tools for editing default Job Options files. • Contact the Gaudi Bookkeeping Database and the Grid Replica Catalogue to obtain the list of Logical File Names (LFNs) from high-level physics selection criteria. • Automated generation of JDL scripts for job submission. Status of LHCb-INFN Computing, 42 Domenico Galli

  43. Design of GANGA • Two ways of implementation have been discussed: • Based on one of the general-purpose grid portals (not tied to a single application/framework): • Alice Environment(AliEn). • Grid Enabled Web eNvironment for Site-Independent User Job Submission(GENIUS) • Grid access portal for physics applications (Grappa). • Simulation for LHCb and its Integrated Control Environment(SLICE). • Based on the concept of Python bus (P. Mato): • use different modules whichever are required to provide full functionality of the interface • use Python to glue this modules, i.e., allow interaction and communication between them • A new development using Python software bus is better suited to the aims of ATLAS and LHCb. Status of LHCb-INFN Computing, 43 Domenico Galli

  44. Ganga Prototyping (Current State) • GUI is created using wxPython extension module. • Access to the Gaudi Job Configuration DB is implemented with the xmlrpclib module. • User can browse and create Job Options files using this DB. • Serialization of objects (user jobs) is implemented with the Python pickle module. • Python interpreter is embedded into the GUI and allows user to configure interface from the command line • GRID stuff is under development at the moment and is oriented on EDG testbed 1.2. Status of LHCb-INFN Computing, 44 Domenico Galli

  45. General Requirements for the Architecture • Simplicity of implementation • Portability (platform independence) • Rich functionality • Modularity, which allows for Extensibility • Should provide interactivity Status of LHCb-INFN Computing, 45 Domenico Galli

  46. GUI PYTHON SW BUS GaudiPython PythonROOT LRMS Athena\GAUDI XML RPCserver PYTHON SW BUS Server Production DB Bookkeeping DB Local Job DB OS Module EDG UI XML RPC module GANGA Core Module Remote user (client) Job Configuration DB Python Bus Design LAN/WAN GRID Status of LHCb-INFN Computing, 46 Domenico Galli

  47. Ganga Prototyping: Towards the First Release • The aim is to have a first release of Ganga for the end of the year. • GANGA will be able to handle the configuration, submission (to LSF) and monitoring of a single Gaudi/Athena application. • The GUI will be similar to the mailing system (e.g. Outlook Express), with jobs taking role the mails. The goal is to perform configuring/running Gaudi job as easy as sending a mail. • The first release will work (at least) with Atlfast and DaVinci. Status of LHCb-INFN Computing, 47 Domenico Galli

  48. Data Organization (GAUDI) Event versions Event Event Phy Rec Phy Raw MyTrk Tracks Hits Cand Velo Calo Private RAW ESD AOD Status of LHCb-INFN Computing, 48 Domenico Galli

  49. Files Dataset RAW2 - 1/1/2008 Dataset File Event 1 RAW3 - 22/9/2007 Event 1 Event 2 Event 1 RAW4 - 2/2/2008 Event 2 … Event 2 … … … Event 3 Event 3 Event N Dataset Dataset Collection Set Event tag collctn Event 1 Event 1 B - > ππ Candidates ( Phy ) Event 2 Tag 1 5 0.3 Event 2 + - B - > J/ Ψ ( μ μ ) Candidates … Tag 2 2 1.2 … … … Event 3 Event 3 Tag M 8 3.1 Gaudi Model to Access Event Data DataSet (file) DataSets table Bookkeeping DB Gaudi EventTagColl table EventTag collection Status of LHCb-INFN Computing, 49 Domenico Galli

  50. Architectural Styles • General categorization of systems [1]: user-centric focus on the direct visualization and manipulation of the objects that define a certain domain data-centric focus upon preserving the integrity of the persistent objects in a system computation-centric focus is on the transformation of objects that are interesting to the system [1] G. Booch, “Object Solutions”, Addison-Wesley 1996 Status of LHCb-INFN Computing, 50 Domenico Galli

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