TPC reconstruction in the HLT S Gorbunov 1

TPC reconstruction in the HLT S. Gorbunov 1 and I. Kisel 2, 3 ( for the ALICE Collaboration ) 1 Kirchhoff Institute for Physics, University of Heidelberg, Germany 2 Gesellschaft für Schwerionenforschung mb. H, Darmstadt, Germany 3 Laboratory of Information Technologies, JINR, Dubna, Russia 23 October 2008, CERN Sergey Gorbunov, KIP ALICE offline week /12 CERN, October 23, 2008

TPC reconstruction scheme TPC slice 0 TPC slice 1 TPC slice 35 Cluster finder clusters Slice tracker slice tracks … clusters Slice tracker slice tracks TPC Global merger TPC tracks 23 October 2008, CERN Sergey Gorbunov, KIP 2

Tracking with the Cellular Automaton method: principles “Game of life” - origin of the Cellular Automatons: birth n A dead cell with exactly three live neighbors becomes a live cell (birth) n A live cell with two or three live neighbors stays alive (survival) survival n In all other cases, a cell dies or remains dead (overcrowding or loneliness) n Evolution of all the cells proceeds in parallel, generation by generation death The Cellular Automaton method for tracking, principles: n Construction of global thing (track) using only local operations (hit-to-hit linking) n Try to keep combinatorics at the local level n Try to perform calculations in parallel n Gradual complication of the calculations with complication of processed data 23 October 2008, CERN Sergey Gorbunov, KIP 3

Cellular Automaton - step 1: Search for neighbours For each TPC cluster find two (up&down) neighbours which compose the best line TPC clusters row 2 TPC row Search for neighbours: n local search for each TPC cluster n cluster-wise parallelism x y z row 1 n less combinatorics left for the further processing row 0 23 October 2008, CERN Sergey Gorbunov, KIP 4

Cellular Automaton - step 2: Evolution Keep only one-to-one links row 3 Evolution step: row 2 n no combinatorics n cluster-wise parallelism x y z row 1 row 0 23 October 2008, CERN Sergey Gorbunov, KIP 5

Cellular Automaton - step 3: Creation of track segments Endpoint Clusters => Endpoints Creation of the track segments: n each sequence of the neighboring clusters is composed to the track segment. n track segment-wise parallelism n fitting mathematics n only endpoints are left for the further reconstruction 23 October 2008, CERN Endpoint Belongs to row, array sorted in Y Endpoint object Somewhere in memory n no search, no combinatorics Sergey Gorbunov, KIP Track object Endpoint object 6

Cellular Automaton - step 4: Merging of segments Empty link [dead] One way link [dead] Merge endpoints One-to-one link [alive] Merging segment endpoints - evolution step: n local search for the best neighbor in the closest rows n endpoint-wise parallelism n competition between links ( track length, closeness of the neighbour ) n endpoints are linked one-to-one n fitting mathematics ( 2 check) 23 October 2008, CERN Sergey Gorbunov, KIP 7

Cellular Automaton: example of event reconstruction Step 0: TPC clusters 23 October 2008, CERN Step 1: Search for neighbours Step 2: Creation of track segments Sergey Gorbunov, KIP 8

Cellular Automaton: example of event reconstruction Step 4: Merging of segments 23 October 2008, CERN Result: Reconstructed tracks Sergey Gorbunov, KIP 9

Cellular Automaton: TPC slice tracker performance Soft track with 7 turns Reconstruction time for the whole TPC (36 slices) : Construction of cells … 0. 5 ms Merging of cells ……. . . 0. 3 ms Creation of segments. 0. 3 ms Fit of segments ……… 0. 1 ms Merging of segments. 1. 8 ms Reconstruction performance: All Set (Hits >10, P >. 05) Reference Set (All Set + P>1. ) Extra Set (All Set + P<1. ) Eff Clone Ghost Time [ms] 94. 7 29. 6 97. 9 5. 9 94. 5 30. 6 2. 9 3. 3 23 October 2008, CERN Sergey Gorbunov, KIP 10

Full HLT TPC tracker performance (Slice tracker + Global merger) Reconstruction performance for the full HLT TPC tracker called from off-line ( Ali. TPCComparison macro ) [ done by Cvetan Cheshkov ] 23 October 2008, CERN Sergey Gorbunov, KIP 11

Cellular Automaton: use of parallel hardware Hardware possibility for the parallel calculations: n SIMD CPU instructions n multi-threading n multi-core CPU n special hardware (Cell processor) CBM 23 October 2008, CERN Sergey Gorbunov, KIP 12

Summary and plans Summary: n The Cellular Automaton tracker for ALICE HLT has been developed n The tracker shows good performance and speed n It reconstructs all kinds of data: Physics, Cosmics, Calibration events; with and w/o magnetic field. n Running on-line in HLT Current work: n Investigation of parallel hardware n Speed up of the global merger n Tuning for Pb-Pb collisions p-p event Pb-Pb event in work 23 October 2008, CERN Sergey Gorbunov, KIP 13