software and simulation status
DESCRIPTION
Software and Simulation Status. Volker Friese. CBM Collaboration Meeting, GSI, 13 March 2009. Status detector simulations. Transport. Transport. CbmMCPoint. CbmMCPoint. Digitiser. HitProducer. CbmDigi. HitFinder. CbmHit. CbmHit. Track Finder. Track Finder. Detector response model - PowerPoint PPT PresentationTRANSCRIPT
Software and Simulation Status
CBM Collaboration Meeting, GSI, 13 March 2009
Volker Friese
CBM Collaboration Meeting, Darmstadt, 13 March 2009 Volker Friese2
Status detector simulations
Transport
CbmMCPoint
HitProducer
CbmHit
Track Finder
Transport
CbmMCPoint
Digitiser
CbmDigi
Track Finder
HitFinder
CbmHit
Position smearing,
independent points
Detector response model
Interaction of points
simulation
reconstruction
CBM Collaboration Meeting, Darmstadt, 13 March 2009 Volker Friese3
Status detector simulations: MVD
No Electric Field:
Electrons are diffusing
θ
sensitive volume
C. Dritsa
Model for charge production and diffusion in sensor2D cluster of fired pixelsCross-check with prototype measurementsCluster finder
CBM Collaboration Meeting, Darmstadt, 13 March 2009 Volker Friese4
Status detector simulations: STS
Model for charge production and diffusion in sensor1D cluster of fired stripsCluster finding (centre of gravity)Hit finding (crossing of front/back cluster centres)
A. Kotynia
CBM Collaboration Meeting, Darmstadt, 13 March 2009 Volker Friese5
Status detector simulations: ECAL
Very detailed studies on photon reconstruction
Shower library developed
Problem of merging clusters
M. Prokudin
CBM Collaboration Meeting, Darmstadt, 13 March 2009 Volker Friese6
Status detector simulations
• With MVD and TRD, detector response models are now implemented for all subsystems
• Tuning to prototype data to come once available
• Study and tuning of detailed detector and FEE properties now accessible
• Latest developments (MVD, STS, TRD) not yet taken into account in tracking / physics simulations
CBM Collaboration Meeting, Darmstadt, 13 March 2009 Volker Friese7
Observables: open charm
Extensive studies by I. Vassiliev in many channels
Signals observed over background in all cases
Requires 1st MVD @ 5 cm
To be checked:
influence of clustering in MVD, STS
delta electrons
pile up (up to 10 tolerable?)
I. Vassiliev
CBM Collaboration Meeting, Darmstadt, 13 March 2009 Volker Friese8
Observables: neutral particles in ECAL
Reconstruction of vertex γ, π0, η studied Reasonable reconstruction efficiency obtained π0 signal clearly visible above background η requires more simulation statistics (O(106)
events) Low-mass background studied (A. Stavinskiy)
S. Kiselev
CBM Collaboration Meeting, Darmstadt, 13 March 2009 Volker Friese9
Observables: Flow (event plane angle resolution)
Event plane reconstruction (and centrality selection) using PSD information
First results promising (resolution 40o – 50o) Needs to be checked for non-zero event plane
angles Possibly requires selection of neutrons in PSD Similar studies by S. Seddiki, A. Maevskaya
V. Pozdniakov
CBM Collaboration Meeting, Darmstadt, 13 March 2009 Volker Friese10
Algorithms and methods: wavelets
Promising method for detection of noisy signals
New application examples shown Possible application: Extracting signal yields
for small S/B ratios (no BG subtraction needed)
G. Ososkov
CBM Collaboration Meeting, Darmstadt, 13 March 2009 Volker Friese11
Algorithms and methods: particle ID in TRD and TOF
• Application of statistical criteria (likelihood, mena value, ωkn) in TRD was studied
and compared to ANN.
• Performance of ANN was found superior.
• However, cross-check with independent method is desirable.
• Online implementation to be investigated (J/ψ trigger)
• Difference of dE/dx GEANT/prototype deteriorate the electron ID performance.
• First application of ωkn method to TOF hadron ID (requires two independent TOF
measurement). Preliminary results require further investigations.
O. Denisova
T. Akishina
V. Ivanov
CBM Collaboration Meeting, Darmstadt, 13 March 2009 Volker Friese12
Trigger studies: open charm
L1CATrackFinder
L1KFTrackFitter
Charm Track Candidates Selection χ2prim > 3
Charm Pairs χ22geo
< 3.0, zv <1 cm χ2
topo < 3.0, minv > 1.3 GeV
Charm Triplets χ23geo+topo < 3.0 ☺D+c Ds
☺D0☻☻
I. Vassiliev
Trigger algorithm developed Requires 1st MVD @ 5cm Rejection factors O(100) achievable
w/o loss of signal (w.r.t. offline analysis)
Requires (full) STS reconstruction, but only reduced combinatorics due to selection on single-track level
CBM Collaboration Meeting, Darmstadt, 13 March 2009 Volker Friese13
Trigger studies: charmonium (e+e-)
Simple trigger logic: Require >2 tracks/event with pt > 1 GeV, identified as electrons in TRD
A. Maevskaya
MC PIDMC PID Like>0.4Like>0.4 Ann>0.5Ann>0.5
Target 250Target 250μμ 1428514285 559559 119119
Target 25Target 25μμ 2000020000 813813 172172
No loss of signal w.r.t. offline analysis Requires:
(full) STS reconstruction partial TRD reconstruction electron ID in TRD (ANN / statistical)
CBM Collaboration Meeting, Darmstadt, 13 March 2009 Volker Friese14
Trigger studies: charmonium (μ+μ-)
x=0,y=0x=0,y=0
∆x,∆y∆x,∆y Trigger strategy:
Have two tracks after last absorber Fit triplet and extrapolate back to target Cut on distance to target
Requires: information only from last three detector stations
Can be improved by using TOF (2nd level?)
segmentation
trigger without χ2 xz=0 yz=0
εJ/ψmBias, % 23.4 20.3 15.5 15.2
background
suppression factor (bsf)
for mbias events
1 1 318 606
A. Kiseleva
CBM Collaboration Meeting, Darmstadt, 13 March 2009 Volker Friese15
Reconstruction: Hough Transform
Z
X
Y
P y/P z
P x/P z
1 /P z
Algorithm is being implemented on CellBE (Sony Playstation III) as prototyping system of FPGA array
Hough transform is calculated offline through LUT: details of field and geometry are uncritical
C. Steinle
CBM Collaboration Meeting, Darmstadt, 13 March 2009 Volker Friese16
Reconstruction: L1
Real-time performance on the quad-core Xeon 5345 Real-time performance on the quad-core Xeon 5345 (Clovertown) at 2.4 GHz – speed-up 30 with 16 threads(Clovertown) at 2.4 GHz – speed-up 30 with 16 threads
CPU/GPUCPU/GPU AMD: AMD: FusionFusion
CPU/GPUCPU/GPU AMD: AMD: FusionFusion
OpenCL?OpenCL?OpenCL?OpenCL?
GamingGaming STI: STI: CellCell
GamingGaming STI: STI: CellCell
GP CPUGP CPU Intel: Intel: LarrabeeLarrabee
GP CPUGP CPU Intel: Intel: LarrabeeLarrabee
GP GPUGP GPU Nvidia: Nvidia: TeslaTesla
GP GPUGP GPU Nvidia: Nvidia: TeslaTesla
CPUCPU Intel: Intel: XXX-coresXXX-cores
CPUCPU Intel: Intel: XXX-coresXXX-cores
FPGAFPGA XilinxXilinx
FPGAFPGA XilinxXilinx
I. Kisel
Impressive gain by vectorisation and multi-core architecturs
Future paths not clear, but computing paradigm will surely be parallelisation
Impact on our computing / software model? Migration from C++ to ???
CBM Collaboration Meeting, Darmstadt, 13 March 2009 Volker Friese17
Analysis: computing model
• It is yet unclear whether the physics analysis of CBM data will be done
– on a world-wide grid (LHC-like)
– on a small number of supercomputing centres (Frankfurt, ...)
• For the medium-term simulations, we will use CBM-GRID where necessary
• Set-up done by F. Uhlig (currently GSI only); first SIM+RECO run done successfully (Jan. 2009)
• Next step: JINR-LIT; ressources deployed
CBM-GRID user tutorialthis afternoon
You are welcome!
CBM Collaboration Meeting, Darmstadt, 13 March 2009 Volker Friese18
Reconstruction: computing model
• Raw date size: 5 PB / CBM run year
• Conventional approach: Several reconstruction runs with improved detector understanding / alignment / calibration befor physics analysis
• 2009 core time per min. bias Au+Au event: ≈ 10 s
• Core time per reconstruction run: 6 · 106 d
• Number of cores required (target: 100d / run): 6 · 104
• Will most probably executed on the same farm as online event selection
• Can, be proper means, the complete reconstruction be made fast enough to be performed on-line?
CBM request for POF II:2 · 104 core days (2009)+ 100% annual growth20 TB storage (2009) + 100% annual growthTarget (2014): 10% of full ressources
CBM Collaboration Meeting, Darmstadt, 13 March 2009 Volker Friese19
Next steps?
• Physics performance:– Go beyond simple S/B as quality check
– Simulate spectra to assess the performance for a given physics goal
– Determine number of needed events for this goal
– Arrive at a runtime scenario for each physics observable
– CBM Physics Performance Report: 2012/2013
• Short-term priority: Simulations for CBM@SIS100– A+A, 2-10 AGeV
– p+p, p+A, 2-30 GeV
• Demonstrate feasibility of event reconstruction from free-streaming raw data