Claudio Grandi INFN-Bologna CHEP 2000Abstract B 029 Object Oriented simulation of the Level 1 Trigger system of a CMS muon chamber Claudio Grandi INFN-Bologna

Claudio Grandi INFN-Bologna CHEP 2000 Abstract B 029 Introduction CMS Level 1 Trigger is implemented using custom designed hardware Why is L1 Trigger simulation important: –test the hardware design –base to develop the High Level Trigger software –define data analysis strategies –(online monitoring of the hardware performances) L1 Trigger simulation code has to be integrated with the CMS simulation and reconstruction programs!

Claudio Grandi INFN-Bologna CHEP 2000 Abstract B 029 CMS detector at LHC

Claudio Grandi INFN-Bologna CHEP 2000 Abstract B 029 ORCA and CARF Object Reconstruction for CMS Analysis »see talk by D. Stickland –detector digitization –detector reconstruction –Level 1 trigger simulation –High Level Triggers software (HLT) –physics object reconstruction –analysis tools CMS Analysis and Reconstruction Framework »see talk by V.Innocente –persistent storage of data –reconstruction and analysis framework

Claudio Grandi INFN-Bologna CHEP 2000 Abstract B 029 Signal Zebra files with HITS HEPEVT ntuples CMSIM (GEANT3) MC Prod. Pile-up ORCA Digitization (merge signal and pile-up) Objectivity Database ORCA Prod. ORCA ooHit Formatter Objectivity Database Catalog import Simulation for HLT studies Level 1 Trigger simulation HLT Algorithms Reconstructed Objects HLT Grp Databases Objectivity Database Catalog import Objectivity Database Objectivity Database ytivitcejbOesabataD Mirrored Db’s (US,Russia,Italy...)

Claudio Grandi INFN-Bologna CHEP 2000 Abstract B 029 L1 Trigger of a muon chamber The TRACO builds tracks in a chamber correlating segments found in the R-  view quadruplets The Trigger Server selects the 2 best segments, suppress ghosts and passes the tracks to the Regional Trigger The BTI finds segments in a quadruplet and assigns the bunch crossing using a mean-timer technique

Claudio Grandi INFN-Bologna CHEP 2000 Abstract B 029 L1  -trigger packages in ORCA Interface to end user System setup Configuration Geometry etc... Trigger components simulation

Claudio Grandi INFN-Bologna CHEP 2000 Abstract B 029 Class diagram Objects seen by the user Activate themselves when the trigger output is asked for Chambers and trigger units are in 1-1 correspondence

Claudio Grandi INFN-Bologna CHEP 2000 Abstract B 029 Action on demand Modules register themselves at creation time and are invoked when required (implicit invocation architecture) Use the Dispatcher-Observer pattern –System setup: L1MuDTTrigSetup is a LazyObserver – Event processing: trigger components are LazyObserver Optimization of program flow. User code very simple!

Claudio Grandi INFN-Bologna CHEP 2000 Abstract B 029 Example of user code // Processing an event... L1MuDTTrigSetup* setup = Singleton ::instance(); L1MuDTTrig* dttrig = setup->DTTrig(); //define chamber (iwh,ist,ise) and BX (is) int iwh=…;int ist=…;int ise=…;int is=…; L1MuDTChambPhSegm* first = dttrig->chPhiSegm1(iwh,ist,ise,is); L1MuDTChambPhSegm* second = dttrig->chPhiSegm2(iwh,ist,ise,is); L1MuDTChambThSegm* theta = dttrig->chThetaSegm(iwh,ist,ise,is);

Claudio Grandi INFN-Bologna CHEP 2000 Abstract B 029 BTI simulation More than BTI chips in CMS, on average 35 are not empty in each event –do not instantiate BTI chips at setup time –instantiate BTI chips event by event if not empty The BTI trigger cards (1 per chamber) keep: –map of active BTI chips ( L1MuDTBtiChip ) –vector of output BTI triggers ( L1MuDTBtiTrig ) Reproduce the BTI behaviour as time flows: –run the BTI algorithm 26 times simulating the chip registers as they would appear before and after the expected triggering time

Claudio Grandi INFN-Bologna CHEP 2000 Abstract B 029 BTI interaction diagram When output is asked for When a new event is read in

Claudio Grandi INFN-Bologna CHEP 2000 Abstract B 029 TRACO simulation More than TRACO chips in CMS, on average 10 are not empty in each event –same situation as for the BTI’s The TRACO trigger cards keep: –map of active TRACO chips ( L1MuDTTracoChip ) –vector of output TRACO triggers ( L1MuDTTracoTrig ) Reproduce the TRACO behaviour as time flows: –run the TRACO algorithm 26 times using as input the BTI triggers found at the corresponding triggering time

Claudio Grandi INFN-Bologna CHEP 2000 Abstract B 029 Trigger Server simulation The Trigger Server chips are instantiated at setup time (250 for R-  view and 250 for R-  ) Reproduce the TS behaviour as time flows: –Algorithm is run 26 times using as input the TRACO triggers found at the corresponding triggering time R-  view algorithm implies a sorting of triggers: –example of use of bit-wise algebra: use ad hoc developed BitArray class for bit manipulation –sorting is done using BitArray::operator< R-  view algorithm is a bit packing of BTI’s output –use again BitArray methods

Claudio Grandi INFN-Bologna CHEP 2000 Abstract B 029 Persistency Persistency for MC information, raw data (including trigger) and reconstructed objects –Most CPU consuming processes are only run once! For the Fortran part of the chain use ZEBRA For the OO part of the chain use Objectivity/DB »see talk by L. Silvestris All Objectivity/DB (and ZEBRA) access is via CARF interfaces Use of Objectivity/DB is transparent to the simulation/reconstruction code and to the user program

Claudio Grandi INFN-Bologna CHEP 2000 Abstract B 029 Persistency Simulation is done in transient mode Transition to persistent mode is done at the end of the event processing Make a copy of the cache of the trigger card objects to its persistent representation When reading from the DB CARF copies the objects to the memory The corresponding C++ pointers are loaded into the cache of the trigger cards Analysis is done in transient mode

Claudio Grandi INFN-Bologna CHEP 2000 Abstract B 029 Summary Object technology is well suited to reproduce the behaviour of the different electronic devices –use custom developed class for bit manipulation OO code for L1 trigger simulation of a CMS muon chamber is fully integrated in ORCA, the CMS reconstruction and analysis program –uses reconstruction on demand –allows persistency in Objectivity/DB databases Code already used in 1999 Monte Carlo production