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Software and Simulation Status

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

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Software and Simulation Status

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  1. Software and Simulation Status Volker Friese CBM Collaboration Meeting, GSI, 13 March 2009

  2. Status detector simulations Transport Transport CbmMCPoint CbmMCPoint Digitiser HitProducer CbmDigi HitFinder CbmHit CbmHit Track Finder Track Finder Detector response model Interaction of points Position smearing, independent points simulation reconstruction Volker Friese

  3. Status detector simulations: MVD No Electric Field: θ Electrons are diffusing sensitive volume Model for charge production and diffusion in sensor 2D cluster of fired pixels Cross-check with prototype measurements Cluster finder C. Dritsa Volker Friese

  4. Status detector simulations: STS Model for charge production and diffusion in sensor 1D cluster of fired strips Cluster finding (centre of gravity) Hit finding (crossing of front/back cluster centres) A. Kotynia Volker Friese

  5. Status detector simulations: ECAL • Very detailed studies on photon reconstruction • Shower library developed • Problem of merging clusters M. Prokudin Volker Friese

  6. 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 Volker Friese

  7. 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 Volker Friese

  8. Observables: neutral particles in ECAL S. Kiselev • 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) Volker Friese

  9. Observables: Flow (event plane angle resolution) V. Pozdniakov • 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 Volker Friese

  10. Algorithms and methods: wavelets G. Ososkov • 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) Volker Friese

  11. Algorithms and methods: particle ID in TRD and TOF O. Denisova • 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 methodto TOF hadron ID (requires two independent TOF measurement). Preliminary results require further investigations. T. Akishina V. Ivanov Volker Friese

  12. Trigger studies: open charm L1CATrackFinder L1KFTrackFitter Charm Track Candidates Selection χ2prim > 3 ☻ Charm Pairsχ22geo< 3.0, zv <1 cm χ2topo < 3.0, minv > 1.3 GeV ☺D0 ☻ ☺D+c Ds Charm Tripletsχ23geo+topo < 3.0 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 Volker Friese

  13. Trigger studies: charmonium (e+e-) Simple trigger logic: Require >2 tracks/event with pt > 1 GeV, identified as electrons in TRD A. Maevskaya • No loss of signal w.r.t. offline analysis • Requires: • (full) STS reconstruction • partial TRD reconstruction • electron ID in TRD (ANN / statistical) Volker Friese

  14. Trigger studies: charmonium (μ+μ-) ∆x,∆y x=0,y=0 A. Kiseleva • 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?) Volker Friese

  15. Reconstruction: Hough Transform 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 Volker Friese

  16. Reconstruction: L1 CPU Intel: XXX-cores Gaming STI: Cell OpenCL? GP GPU Nvidia: Tesla GP CPU Intel: Larrabee CPU/GPU AMD: Fusion FPGA Xilinx I. Kisel Real-time performance on the quad-core Xeon 5345 (Clovertown) at 2.4 GHz – speed-up 30 with 16 threads • 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 ??? Volker Friese

  17. 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 tutorial this afternoon You are welcome! Volker Friese

  18. 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 growth 20 TB storage (2009) + 100% annual growth Target (2014): 10% of full ressources Volker Friese

  19. 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 Volker Friese

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