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OO Software and Data Handling in AMS

OO Software and Data Handling in AMS. Computing in High Energy and Nuclear Physics Beijing , September 3-7 , 2001. Vitali Choutko, Alexei Klimentov MIT, ETHZ. Outline. AMS – particle physics experiment on the international space station : Data flow and AMS ground centers

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OO Software and Data Handling in AMS

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  1. OO Software and Data Handling in AMS Computing in High Energy and Nuclear Physics Beijing , September 3-7 , 2001 Vitali Choutko, Alexei Klimentov MIT, ETHZ

  2. Outline • AMS – particle physics experiment on the international space station : • Data flow and AMS ground centers • Software development • Conditions and Tag Database • Data Processing • AMS Detector • STS91 precursor flight • AMS ISS mission AMS software and data handling CHEP01

  3. AMS : a particle physics experiment in space PHYSICS GOALS : Accurate, high statistics measurements of charged, cosmic ray spectra in space > 0.1GV • The study of dark matter (90% ?) + Nuclei and e- spectra measurement • Determination of the existence or absence of antimatter in the Universe Look for negative nuclei • The study of the origin and composition of cosmic rays Measure isotopes D, He, Li, Be… AMS software and data handling CHEP01

  4. AMS software and data handling CHEP01

  5. Precursor flight : 8 10 events recorded Trigger rates 0.1-1kHz DAQ lifetime 90% Results : _ • Anti-matter search : He / He = 1.1x 10 • Charged Cosmic Ray spectra Pr, D, e- , He, N • Geomagnetic effects on CR under/over geomagnetic cutoff components -6 + Magnet :Nd2Fe14B TOF : trigger, velocity and Z Si Tracker : charge sign, rigidity, Z Aerogel Threshold Cerenkov : velocity Anticounters : reject multi particle events AMS software and data handling CHEP01

  6. AMS software and data handling CHEP01

  7. AMS on ISS , 3 years in space _ + Separate e- from p,p up to 300 GeV 3 4 He, He, B, C… + e-, up to 1000 GeV AMS software and data handling CHEP01

  8. AMS software and data handling CHEP01

  9. ISS to Remote AMS Centers Data Flow White Sand, NM facility AMS Real-time & “Dump” data Payload Operations Control Center Real-time, “Dump”, & White Sand’s LOR playback MSFC, Al Monitoring & science data Real-time & “dump” Payload Data Service system H&S Monitoring Science Flight ancillary data Real-time Data H&S ACOP External Communications Short Term GSE Stored data Long Term NearReal-time Science Operations Center File transfer High Rate Frame MUX playback NASA Ground Infrastructure Telescience centers Remote AMS Sites ISS

  10. RT data Commanding Monitoring NRT Analysis POIC@MSFC AL POCC POCC HOSC Web Server and xterm XTerm commands Monitoring, H&S data Flight Ancillary data AMS science data (selected) cmds archive TReK WS “voice”loop Science Operations Center Science Operations Center TReK WS Video distribution External Communications PC Farm GSE GSE NRT Data Processing Primary storage Archiving Distribution Science Analysis AMS Data, NASA data, metadata Buffer data Retransmit To SOC GSE Production Farm MC production D S A e T r A v e r AMS Remote center Analysis Facilities Data Server MC production Data mirror archiving Analysis Facilities AMS Station AMS Station AMS Station AMS Ground Centers CHEP01

  11. AMS SW development Been started mid 1996 : basic decisions : • new code C++ only (though we had a large part of legacy SW written on Fortran) • Existing libraries (CERNLIB, Geant, etc) incorporated via C/Fortran interface (R.Burow) • transient and persistent classes are separated with implementing of copy member functions • Decide to use Root and HBOOK for histogramming and data visualization AMS software and data handling CHEP01

  12. AMS SW development (cont’d) • Use different persistency solutions for various type of data : • Flat files for the raw data • Ntuples and Root files for ESD • Relational Database (Oracle) tables for file catalogues • Relational Database (Oracle) [Objectivity up to Sep 1998] • Event Tags • Calibration data • Slow control data • NASA ancillary data • Various catalogues (processing history, etc) AMS software and data handling CHEP01

  13. Tag Storage with Oracle RDBMS • Tag is an unsigned 32 bit integer containing 16, 1 to 5 bit long parameters such as charge, momentum sign, ß,… • Model : • Query : retrieve tags with 3 parameters satisfied to the given limits (query taken from the “real analysis chain”) • Data stored on Raid array connected to AS4100(quad-CPU rated at 600MHz, 2GB RAM) • Flat files – 2400 files, one file per DAQ run, tags are stored as an array of unsigned int. • RootN - 10 files, each file with ~240 trees, one tree per DAQ run with single branch (tag) per tree • RootS - 10 files, each file with ~240 trees, one tree per DAQ run , having 16 branches, • every parameter stored in a dedicated branch • OracleN - table with 10 partitions and 1 column, mapping tag to a column • OracleI - table with 10 partitions and 1 column with 16 bitmap indices, mapping tag to a column • OracleS – table with 10 partitions and 16 columns, every parameter mapping to a column AMS software and data handling CHEP01

  14. Oracle RDBMS to store AMS tags 1) 1) 500 sec to build indices for 100M tags AMS software and data handling CHEP01

  15. Design of the Conditions Database • Collection of Time Dependent Values (TDVs) • Primary access keys : name, id, validity interval • Secondary key : insert time • Major Components : table of names and ids, default TDVs, TDVs • Applications : Loading data into database Fetching conditions during event reconstruction Management utilities (TDV browser) • Name, id • Validity begin, validity end time • Insert time • Array of unsigned integers (size 100 byte – 8 Mbyte) AMS software and data handling CHEP01

  16. AMS Conditions Database • Initially Objectivity, then flat files, now Oracle • Performance test for • TOF temperature (many short records) • Tracker pedestals (small amount of large records) (a) BLOB array is stored inside the table, (b) - outside AMS software and data handling CHEP01

  17. Oracle RDBMS to store Tags and TDVs • Currently 8 Gbyte is stored in the Conditions DB (115 different TDV types) • 100 million event tags are stored in Tag DB • Oracle RDBMS performance and functionality satisfy AMS requirements. Using of bitmap indices for tags improves query time dramatically. • The current implementation works with distributed CORBA technology. It allowes to reduce the number of database clients and machine loading. AMS software and data handling CHEP01

  18. Nominal Tables Hosts, Interfaces Producers, Servers… {II} {I} {VI} • {I} submit 1st server • {II} “cold” start • {III} read “active” tables (available hosts, number of servers, producers, jobs/host) • {IV} submit servers • {V} get “run”info (runs to be processed, ESD output path) • {VI} submit producers (LILO, LIRO,RIRO…) • Notify servers server server producers {III} ESD Active Tables : Hosts, Interfaces, Producers, Servers {IV} ESD Raw data server server {V} {VI} Conditions DB server server server Tag DB server server producers ESD Catalogues ESD ESD Oracle RDBMS Raw data AMS Production AMS software and data handling CHEP01

  19. AMS Production Highlights • Stable running for more than 1 month • Average efficiency 95% (98% without Oracle) • Processes communication and control via Corba • LSF for process submission • Run Oracle server on AS4100 Alpha and Oracle clients on Linux. • Oracle RDBMS • Tag DB with 100M entries • Conditions DB with 100K entries • Bookkeeping • Production status • Runs history • File catalogues AMS software and data handling CHEP01

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