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STAR High Level Tracking Trigger Upgrade and Physics Opportunities

STAR High Level Tracking Trigger Upgrade and Physics Opportunities. Outline. Why we do it ? – HLT motivations. How we do it ? – HLT layout. What we have achieved ? – HLT performance and achievements. What is the plan for the future ? – HLT upgrade plan and new physics opportunities.

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STAR High Level Tracking Trigger Upgrade and Physics Opportunities

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  1. STAR High Level Tracking Trigger Upgrade and Physics Opportunities Aihong Tang Pusan Nov. 2012

  2. Outline • Why we do it ? – HLT motivations. • How we do it ? – HLT layout. • What we have achieved ? – HLT performance and achievements. • What is the plan for the future ? – HLT upgrade plan and new physics opportunities. Aihong Tang Pusan Nov. 2012

  3. HLT motivations – the increasing date volume at STAR Aihong Tang Pusan Nov. 2012

  4. HLT motivations – the increasing challenge on computing • The improved data taking capability imposes a challenge for STAR on: • 1) computing resource in terms of CPU time and tape storage. • 2) for analyzers, struggle with large data volume and bear with long analysis cycle. • By implementing a HLT it will be possibly to reduce the amount of data written to tape by selecting desired events while still maintaining a high sampling rate to fully utilize the high DAQ rate for a wide range of triggers. How to digest timely ? Aihong Tang Pusan Nov. 2012

  5. STAR Subsystems MTD Barrel EMC Endcap EMC Barrel TOF FMS TPC DAQ1000 COMPLETE Large & uniform acceptance at mid-rapidity Fast data acquisition Excellent particle identification HLT Ongoing HFT FGT Aihong Tang Pusan Nov. 2012

  6. HLT motivations – optimize the potential of subsystems STAR has excellent PID and tracking capability, can we take advantage of its full potential efficiently ? Aihong Tang Pusan Nov. 2012

  7. HLT motivations – efficiently address interesting physics • Heavy flavor measurement • EM probe • High pt probe • Search for exotics A platform for exploring interesting physics ideas. Aihong Tang Pusan Nov. 2012

  8. HLT layout in 2009 SL3 SL3 SL3 BEMC  Total 24 SL3 machines GL3 GL3  • Sector level-3 tracking (SL3) in DAQ machines (24 in total, each for a TPC sector). • Information from subsystems (SL3 and others) are sent to Global L3 machines (GL3) where an event is assembled and a trigger decision is made. Aihong Tang Pusan Nov. 2012

  9. HLT layout in 2010-2012 SL3 SL3 SL3 BEMC TOF  Total 24 SL3 machines GL3 GL3  • Sector level-3 tracking (SL3) in DAQ machines (24 in total, each for a TPC sector). • Information from subsystems (SL3 and others) are sent to Global L3 machines (GL3) where an event is assembled and a trigger decision is made. Aihong Tang Pusan Nov. 2012

  10. HLT layout in 2013 and beyond HFT MTD BEMC TOF  online GL3 computer farm DAQ event builder GL3 GL3  • Both tracking and trigger decision will be done by a online GL3 computer farm. • The farm can be upgraded with Graphic Processing Unit (GPU) or Many Integrated Cores (MIC). Aihong Tang Pusan Nov. 2012

  11. HLT Division by Tasks Tracking Trigger Decision Making Calibrations Online QA Future R & D Aihong Tang Pusan Nov. 2012

  12. Tracker Conformal Transformation where , and (x0,y0) is the primary vertex Fitting lines instead of fitting curves. Final fit with Helix model in real space. Handle primary and global track non-uniformly. Fast tracker with acceptable accuracy, but not an ideal tracker for parallel computing (will be replaced, see later slides). Aihong Tang Pusan Nov. 2012

  13. Tracker Performance Relative pT difference between HLT and offline STAR Preliminary <ΔpT/pT> w.r.t. offline tracking efficiency w.r.t. offline STAR Preliminary Performance evaluated based on online-offline association Aihong Tang Pusan Nov. 2012

  14. Trigger Efficiency STAR Preliminary > 90% for charge -2 ~ 70% for di-electron STAR Preliminary Estimated with AuAu 39 GeV data Aihong Tang Pusan Nov. 2012

  15. HLT Achievements J/ψ v2 highlighted at QM2011 • AntiHelimum-4 discovery made • into top 100 • stories of 2011 : • #20 in all • disciplines, • #3 in Physics. 473, 353-356 (May 2011) Real time feedback on beam – beam pipe background during RHIC Beam Energy Scan program. STAR Preliminary STAR Preliminary Aihong Tang Pusan Nov. 2012

  16. Future Upgrade Plan • Adopt the Cellular Automaton (CA) tracker. • Expand the GL3s to an online computer farm. • Equip GL3 computers with GPU/MIC. Aihong Tang Pusan Nov. 2012

  17. Physics Opportunities with HLT Upgrade • Push the boundary of Standard Model • Dibaryon, Strangelets. • Look for new physics beyond Standard Model • Rare decay of hadrons, Antimatter. • Atom/parton chemistry test ground • Multi-hyperon systems. Aihong Tang Pusan Nov. 2012

  18. Adopting CA tracker Compare to current STAR HLT tracker : same speed, better efficiency, easy for future parallelization. Aihong Tang Pusan Nov. 2012

  19. Adopting CA tracker TPC clusters pad, row, time bucket TPC clusters pad, row, time bucket ... 24 sectors STAR online hits x, y, z (STAR global coordinates) STAR online hits x, y, z (STAR global coordinates) • Treat the Cellular Automata tracking routine as a black-box. • CA tracker is vectorized, if CPU supports SIMD, i.e. SSE/AVX instructions. • CA tracker can run in multi-thread mode, if Intel Thread Building Blocks is available. (we do not turn it on) • Primary vertex finding based on Kalman Filter, i.e. KF Particle package. Can be vectorized. • KF particle can also be used to reconstruct secondary vertices. CA hits x, y, z (CA local coordinates) CA tracker CA tracks dedx calculation KF Particle Primary Vertex finding Global Tracks (gl3Track) other detectors Primary Tracks (gl3Track) Primary Vertex trigger decision making Aihong Tang Pusan Nov. 2012

  20. Trigger on Secondary vertices : Search for strangelets and other exotics v0 vch v0 v0 v0 vch v0v0Ch_v0vch v0ChCh_v0v0 ChChCh_vch v0 v0 v0 v0 vch vch v0 vch vch v0v0v0Ch_v0v0vch v0v0ChCh_vch ChChChCh_v0v0 v0ChChCh_v0vch Strangelet Good potential for new discoveries (Strangelets, di-Ω etc.) with GL3 upgrades Aihong Tang Pusan Nov. 2012

  21. Secondary Vertex Finder Tracking + v0 Finding Tracking STAR Preliminary v0 reconstruction is CPU intensive (~M2). Aihong Tang Pusan Nov. 2012

  22. Secondary Vertex Finder with GPU comformal mapping tracking Kalman filter tracking Secondary vertex finder strategy Good task for GPU: Input data amount Communication between tasks Frequency of accessing to input data Complicacy of each task Output data amount Secondary Vertex Finder is best candidate suited for GPU acceleration Aihong Tang Pusan Nov. 2012

  23. Secondary Vertex Finder with GPU Test result: GTX280 VS 2.8CPU GPU is 60 times faster than single CPU core considering data transmission. Lambda reconstructed by GPU (real data, HLT tracks) GPU significantly accelerates v0 reconstruction. Aihong Tang Pusan Nov. 2012

  24. Summary • STAR’s HLT has successfully selected events of interests in real time. • It is demonstrated that STAR can deliver important physics fast with the HLT. • Future upgrade plan is presented. With the upgrade, STAR will be in an excellent position for exploring a wide range of new physics opportunities. Aihong Tang Pusan Nov. 2012

  25. Backup Aihong Tang Pusan Nov. 2012

  26. Online Calibration HLT calibration and offline computing are mutual beneficial. Identify issues early (for example, the TOF Time Over Threshold issue) Aihong Tang Pusan Nov. 2012

  27. Secondary Vertex Finder with GPU DCA Dca between daughters is the most time consuming part. 1, Calculation of dca between daughters is more complicated than other parameters 2, The combination of candidates is much higher that other parameters. Aihong Tang Pusan Nov. 2012

  28. HLT-HFT Precision Consideration Good work-in-progress Expect more collaborations with HFT experts Aihong Tang Pusan Nov. 2012

  29. Related History • STAR’s old Level-3 system had been in limited function, phased out since then ~2002 • Propose of HLT at 2007 DAQ 1k workshop. • Proof of principle in 2008. • Prototype in 2009 with real data taking. DAQ 1k installed in 2009. • In function in 2010. Aihong Tang Pusan Nov. 2012

  30. Speed Performance (AuAu 200 GeV) ✔ Assuming half CPU cores of DAQ machine can be used by HLT, we expect that HLT can handle ~1k Hz for Au+Au collisions in RHIC-II era, however we have to keep in mind HLT is sharing CPUs with DAQ cluster finding code. Aihong Tang Pusan Nov. 2012

  31. Speed Performance (pp 200 GeV) ✔ Aihong Tang Pusan Nov. 2012

  32. Speed Performance (pp 500 GeV) Problematic for handling pp 500 GeV collisions. Aihong Tang Pusan Nov. 2012

  33. Online Monitoring Watch J/ψ peak grow online. Early discovery for possible run condition changes Aihong Tang Pusan Nov. 2012

  34. HLT-2010 STAR 200 GeV, 10 wks 62 GeV, 4 wks 39 GeV, 2 wks 7.7 GeV, 5 wks 11 GeV, 11 wks Jan 1st HLT Tagger Tagger Tagger Tagging “HLT-good” Jan 14th Tagger Trigger “HLT-good” • Jan 9th. First TPX and TOF calibration ready. • Jan 14th. HLT is up and running. • Jan 15th. L2 crashed. HLT running with TPX and TOF only for some period. • Feb. 05. HLT is decoupled from L2. Instead, HLT receives BTOWs from Tonko/Jeff. Aihong Tang Pusan Nov. 2012

  35. HLT-2011 STAR pp 500 GeV, 11 wks 19 GeV, 3 wks AuAu 200 GeV, 7 wks 27 GeV, 2 wks Jan ~28st HLT Tagger Tagging “HLT-good” Tagger Tagging “HLT-good” Feb 6th Tagger “HLT-good” Aihong Tang Pusan Nov. 2012

  36. HLT-2012 STAR Pp 200 GeV, 5 wks pp500 GeV, 7 wks UU 193 GeV, 3 wks cuAu 200 GeV, 5 wks Jan ~2nd HLT Tagger Tagger Tagger Feb 27th Aihong Tang Pusan Nov. 2012

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