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STAR Level-3 C. Struck
CHEP 981
Level-3 Trigger Level-3 Trigger for the for the
Experiment at Experiment at RHICRHIC
J. Berger1, M. Demello5 , M.J. LeVine2, V. Lindenstruth3,A. Ljubicic, Jr.2, D. Roehrich1, E. Schaefer6,
J.J. Schambach4, D. Schmischke1, M.W. Schulz2, R. Stock1, C. Struck1,a , P. Yepes5
(1) University of Frankfurt(2) Brookhaven National Lab., Upton, NY(3) University of Heidelberg(4) University of Texas at Austin(5) Rice University, Houston, TX(6) Max-Plank-Institut fuer Physik, Munich(a) Yale University, New Haven, CT
Christof Struck August, 98University of FrankfurtYale University
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Solenoidal Tracker At RHICAu+Au at s = 200 GeV/nucleon pair5000-10000 charged particles/eventpolarized p+p at s = 500GeV baseline detector: large TPC
STAR Experiment
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STAR DAQ• TPC organized in 24 geometrical sectors;
each sector delivers digitized data through 6 readout boards (custom built VME boards); same readout scheme for SVT (4 sectors) and FTPC (6 sectors)
• readout boards equipped with:
– buffer for 12 uncompressed events
– processing power (three i960 per board)
• STAR DAQ hierarchical system of VME systems - interconnected by a low latency and high bandwidth network:
SCI: event building, inter-crate communication/synchronization and for Level-3 data-passing
Global VME Crate
SCI Ring
TPC Sector Crate SVT Sector Crate
24 crates 4 crates
SCSI
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Level-3 Requirements
Au+Au collisions:TPC event rate after Level-0 Trigger: 100 Hz,expected event size: 100 MByte
2.0 GByte/secafter zero suppressionevent size 20 MByte
20 MByte/sec
10 8 bit translationzero suppression
Level-3
Tape / Offline
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Level-3 Trigger
• software trigger:select events according to
– event topology, kinematics
– specific signature
• selecting sub-events:store only raw data of interesting tracks(regions-of-interest, ROI),e.g. tracks of lepton candidates
• data compression
process the raw data:perform pattern recognition in real time at 100 Hz
Reduce data by a factor of 100, therefore use knowledge of physics of these collisions.
Possibilities:
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Software Triggeror
Regions-of-Interest
Estimated rates for J/ e+e–
and e+e– . 100 Au+Au collisions/sec
L3-Trigger sensitivity 1:100 assumed
J/ e+e–
pT(e)>1.5 GeV/c
e+e–
Signal/event 10-5 0.02
S/B 1:58 1:50
Background/event 6 · 10-4 1
Method L3-Trigger ROI
Signal/year with L3 104 2 · 107
Seff/year with L3 102 2 · 105
Seff/year without L3 1 2 · 103
Seff = S / (1+2B / S)
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Online Pattern Recognition
Reconstruction of full eventincluding track merging between different detectors
max. TPC event rate 100 Hz average time for one event 10 msec
DAQ receiver boards provide buffer for 12 uncompressed raw events Level-3 processing time 120 msec
tracking quality not as high as offline analysis, but precise enough to enable fast trigger decision
Input:• raw data of slow detectors:
TPC, SVT, FTPC• raw data of fast detectors:
CTB, MWC, VTC, VPD, ZDC, EMC
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Concept of Level-3
• scalable hierarchical structure of processors
• pattern recognition done sequentially
• DAQ readout boards:cluster findingtransform raw ADC data into space coordinates
• Sector Level-3: track findingperform track finding on sector level
• Global Level-3:collect all information from local nodes, merge tracks and make trigger decision
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Cluster Finder I
• runs on DAQ readout board processors (Intel i960)
• input:beginning and ending time of pixel sequences in each pad prepared in receiver board ASICs
• output:space coordinates and charge of found clusters
• optimized for speed
• includes deconvolution of merged clusters
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Cluster Finder II
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Simulation: Au+Au, Venus + GEANT
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Cluster FinderResults
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Simulation: Au+Au, Venus + GEANTpad row 16 - 20
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Cluster FinderTiming
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Track Finder
• combines a number of space points to form track segments
• track segments are merged to form vertex and non-vertex tracks
• provides: – particle momenta– particle identification via dEdx
• algorithm: (P. Yepes at CHEP ‘97)
– conformal mapping to speed up fitting procedures– optimized data organization and memory management
• results:– efficiency between 80 - 90 % for pT > 0.4 GeV/c and
pseudorapidity < 1.2; comparable to offline track finder
– momentum resolution pT/ pT < 1.5 % forpT > 0.4 GeV/c (vertex constraint)
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Track FinderResults
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Track FinderTiming
task PentiumPro
200 MHz
PentiumII
400 MHz
PowerPC750
266 MHz
Alpha21164
600 MHz
Alpha21264
667 MHzSPEC-95 int 8.7 15.8 12.4 18 44
SPEC-95 fp 6.7 12.4 8.4 27 66
fast tracker 200 msec 110 msec 150 msec 80 msec 30 msec
timing for one TPC sectorsimulated central Au+Au, Venus
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Architecture
• distributed, symmetric, scalable processor system
• OS and Software:WinNT (or Linux/ Solaris) for processing nodes; VxWorks for DAQ nodes; software is written in C/C++
• SCI network connection between local sector units and global system to provide high bandwidth(poster, J. Schambach, CHEP ‘98)
• baseline configuration:12 local processing clusters
• later:24 TPC sectors, 4 SVT sectors and 6 FTPC sectors
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Architecture:Sector Level-3
SB1
SBn
DAQ SCI Ring
SL31/1
Level-3 localSCI Ring 1
SL3 machine1 processor
Alpha 21264
SL31/4 SL3
1/4 SL31/4 SL3
1/4
SL3 SMP machine4 processors
Quad Pentium II
Level-3 localSCI Ring n
GL3
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Architecture:Global Level-3
GL3Broker
SB1
SBn
EVB
DAQ SCI Ring
GL31/4 GL3
1/4 GL31/4 GL3
1/4
Level-3 globalSCI Ring
GL3 SMP machine 14 processors
GL3n/4 GL3
n/4 GL3n/4 GL3
n/4
GL3 SMP machine n4 processors
Token Manager
To Trigger System
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Examples forLevel-3
• Au+Au collisionsSelect events with J/ candidates in e+e–-channel– find electron candidates
– loop over electron pair candidates» calculate mass with vertex constraint
» select events in mass window (e.g. 2.5 - 4 GeV)
• p+p collisions– remove pile-up in TPC:
select trigger event out of 600 - 800 visible events in the TPC
– select events based on threshold for jets,photons and electrons
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Data Compression I
• zero suppression• general data compression methods, loss-
free (e.g. Huffman encoding) or lossy reduce only by a factor of 2 to 5
• later phase of the experimentdata modeling techniques reduce by a factor up to 15,keep only relevant information:– assume data model for cluster and tracks (helix
for STAR)– store only quantized differences to data model
of found tracks– pattern recognition can be redundant– detector performance has to be well understood
!!
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Data Compression II
parameter size
curvature R 4 Byte (float)
begin (X,Y,Z) 12 Byte (float)
dip angle 4 Byte (float)
azimuthal angle 4 Byte (float)
track length 2 Byte (integer)
(average) cluster charge 2 Byte (fixed point)2 2 Byte (fixed point)
number of clusters 1 Byte (integer)
sum 31 Byte
track parameter for a helix model
parameter size
Flag empty cluster 1 Bittime 6 Bitpad 6 Bit
cluster charge 7 Bitshape 4 Bit
sum 24 Bit (3 Byte)
cluster parameter
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Data Compression III
• typical event:8000 tracks with 45 cluster each(Venus simulation, worst case)
track data: 8000 • 32 Byte = 0.24 MByte
cluster data: 8000 • 45 • 3 Byte = 1.03 MByte
total: 1.3 MByte needed (lower limit)
• compare to
- raw data (zero suppressed) : 20 MByte
- cluster data: 2.7 MByte(8 Byte per cluster)
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Summary / Outlook
• Level-3 Trigger is needed for most of the STAR physics programs
• reduction of data rate by a factor of 100 requires pattern recognition in real time at 100 Hz
• processed event rate of about 15 - 20 Hz can be achieved using the shown fast algorithms and either one Alpha 21264 or aQuad Pentium II (sufficient for year one)
• system is scalable by adding more CPUs higher event rates
What needs to be done?
• choose processors and OS– therefore timing results for Alpha 21264 needed
• prototype setup
• full simulation of trigger scenarios using the Level-3 chain (cluster finder + tracking)