1. TPC reconstruction in the HLT
S. Gorbunov1 and I. Kisel2,3
( for the ALICE Collaboration )
1 Kirchhoff Institute for Physics, University of Heidelberg, Germany
2 Gesellschaft für Schwerionenforschung mbH, Darmstadt, Germany
3 Laboratory of Information Technologies, JINR, Dubna, Russia
ALICE offline week
CERN, October 23, 2008

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

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

4. 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:
local search for each TPC cluster
cluster-wise parallelism
less combinatorics left for the further processing
row 1 x y z
row 0
23 October 2008, CERN
Sergey Gorbunov, KIP

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

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

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

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

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

10. 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 …… ms
Creation of segments ms
Fit of segments ……… 0.1 ms
Merging of segments ms
Reconstruction performance:
All Set
(Hits >10, P > .05)
Reference Set
(All Set + P>1.)
Extra Set
(All Set + P<1.)
Eff
Clone
Eff
Clone
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

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

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

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