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High Level Triggering. Fred Wickens. High Level Triggering (HLT). Introduction to triggering and HLT systems What is Triggering What is High Level Triggering Why do we need it Case study of ATLAS HLT (+ some comparisons with other experiments) Summary.
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High Level Triggering Fred Wickens
High Level Triggering (HLT) • Introduction to triggering and HLT systems • What is Triggering • What is High Level Triggering • Why do we need it • Case study of ATLAS HLT (+ some comparisons with other experiments) • Summary
Why do we Trigger and why multi-level • Over the years experiments have focussed on rarer processes • Need large statistics of these rare events • DAQ system (and off-line analysis capability) under increasing strain • limiting useful event statistics • Aim of the trigger is to record just the events of interest • i.e. Trigger selects the events we wish to study • Originally - only read-out the detector if Trigger satisfied • Larger detectors and slow serial read-out => large dead-time • Also increasingly difficult to select the interesting events • Introduced: Multi-level triggers and parallel read-out • At each level apply increasingly complex algorithms to obtain better event selection/background rejection • These have: • Led to major reduction in Dead-time – which was the major issue • Managed growth in data rates – this remains the major issue
Summary of ATLAS Data Flow Rates • From detectors > 1014 Bytes/sec • After Level-1 accept ~ 1011 Bytes/sec • Into event builder ~ 109 Bytes/sec • Onto permanent storage ~ 108 Bytes/sec ~ 1015 Bytes/year
Level 1 • Time: few microseconds • Hardware based • Using fast detectors + fast algorithms • Reduced granularity and precision • calorimeter energy sums • tracking by masks • During Level-1 decision time event data is stored in front-end electronics • at LHC use pipeline - as collision rate shorter than Level-1 decision time • For details of Level-1 see Dave Newbold talk
High Level Trigger - Levels 2 + 3 • Level-2 : Few milliseconds (10-100) • Partial events received via high-speed network • Specialised algorithms • 3-D, fine grain calorimetry • tracking, matching • Topology • Level-3 : Up to a few seconds • Full or partial event reconstruction • after event building (collection of all data from all detectors) • Level-2 + Level-3 • Processor farm with Linux server PC’s • Each event allocated to a single processor, large farm of processors to handle rate
Summary of Introduction • For many physics analyses, aim is to obtain as high statistics as possible for a given process • We cannot afford to handle or store all of the data a detector can produce! • The Trigger • selects the most interesting events from the myriad of events seen • I.e. Obtain better use of limited output band-width • Throw away less interesting events • Keep all of the good events(or as many as possible) • must get it right • any good events thrown away are lost for ever! • High level Trigger allows: • More complex selection algorithms • Use of all detectors and full granularity full precision data
Case study of the ATLAS HLT system Concentrate on issues relevant forATLAS (CMS very similar issues), but try to address some more general points
Starting points for any Trigger system • physics programme for the experiment • what are you trying to measure • accelerator parameters • what rates and structures • detector and trigger performance • what data is available • what trigger resources do we have to use it • Particularly network b/w + cpu performance
Physics at the LHC 7 TeV Interesting events are buried in a seaof soft interactions B physics High energy QCD jet production top physics Higgs production
The LHC and ATLAS/CMS • LHC has • Design luminosity 1034 cm-2s-1 • 2010: 1027 – 2x1032 ; 2011: up to 3.6x1033 ; 2012: up to 6x1033 • Design bunch separation 25 ns (bunch length ~1 ns) • Currently running with 50 ns • This results in • ~ 23 interactions / bunch crossing (Already exceeded!) • ~ 80 charged particles (mainly soft pions) / interaction • ~2000 charged particles / bunch crossing • Total interaction rate 109 sec-1 • b-physics fraction ~ 10-3 106 sec-1 • t-physics fraction ~ 10-8 10 sec-1 • Higgs fraction ~ 10-11 10-2 sec-1
Physics programme • Higgs signal extraction important - but very difficult • There is lots of other interesting physics • B physics and CP violation • quarks, gluons and QCD • top quarks • SUSY • ‘new’ physics • Programme evolving with: luminosity and HLT capacity • i.e. Balance between • high PT programme (Higgs etc.) • b-physics programme (CP measurements) • searches for new physics
Trigger strategy at LHC • To avoid being overwhelmed use signatures with small backgrounds • Leptons • High mass resonances • Heavy quarks • The trigger selection looks for events with: • Isolated leptons and photons, • -, central- and forward-jets • Events with high ET • Events with missing ET
~ 200 Hz Physics ~ 300 MB/s ARCHITECTURE Trigger DAQ 40 MHz ~1 PB/s(equivalent) Three logical levels Hierarchical data-flow LVL1 - Fastest:Only Calo and MuHardwired On-detector electronics: Pipelines ~2.5 ms LVL2 - Local:LVL1 refinement +track association Event fragments buffered in parallel ~40 ms LVL3 - Full event:“Offline” analysis Full event in processor farm ~4 sec.
Trigger design – Level-1 • Level-1 • sets the context for the HLT • reduces triggers to ~75 kHz • Limited detector data • Calo + Muon only • Reduced granularity • Trigger on inclusive signatures • muons; • em/tau/jet calo clusters; missing and sum ET • Hardware trigger • Programmable thresholds • CTP selection based on multiplicities and thresholds
Level-1 Selection • The Level-1 trigger • an “or” of a large number of inclusive signals • set to match the current physics priorities and beam conditions • Precision of cuts at Level-1 is generally limited • Adjust the overall Level-1 accept rate (and the relative frequency of different triggers) by • Adjusting thresholds • Pre-scaling (e.g. only accept every 10th trigger of a particular type) higher rate triggers • Can be used to include a low rate of calibration events • Menu can be changed at the start of run • Pre-scale factors may change during the course of a run
Trigger design - HLT strategy • Level 2 • confirm Level 1, some inclusive, some semi-inclusive,some simple topology triggers, vertex reconstruction(e.g. two particle mass cuts to select Zs) • Level 3 • confirm Level 2, more refined topology selection,near off-line code
Trigger design - Level-2 • Level-2 reduce triggers to ~4 kHz (was ~2 kHz) • Note CMS does not have a physically separate Level-2 trigger, but the HLT processors include a first stage of Level-2 algorithms • Level-2 trigger has a short time budget • ATLAS ~40 milli-sec average • Note for Level-1 the time budget is a hard limit for every event, for the High Level Trigger it is the average that matters, so OK for a small fraction of events to take times much longer than this average • Full detector data is available, but to minimise resources needed: • Limit the data accessed • Only unpack detector data when it is needed • Use information from Level-1 to guide the process • Analysis proceeds in steps - can reject event after each step • Use custom algorithms
Regions of Interest • The Level-1 selection is dominated by local signatures (I.e. within Region of Interest - RoI) • Based on coarse granularity data from calo and mu only • Typically, there are 1-2 RoI/event • ATLAS uses RoI’s to reduce network b/w and processing power required
Trigger design - Level-2 - cont’d • Processing scheme • extract features from sub-detectors in each RoI • combine features from one RoI into object • combine objects to test event topology • Precision of Level-2 cuts • Limited (although better than at Level-1) • Emphasis is on very fast algorithms with reasonable accuracy • Do not include many corrections which may be applied off-line • Calibrations and alignment available for trigger not as precise as ones available for off-line
Trigger DAQ Calo MuTrCh Other detectors ~ 1 PB/s 40 MHz 40 MHz LVL1 2.5 ms LVL1 accept Calorimeter Trigger Muon Trigger ROD ROD ROD Read-Out Drivers 75 kHz RoI’s 120 GB/s Read-Out Links RoI requests LVL2 ROB ROB ROB ~ 10 ms ROS Read-Out Buffers ROIB L2SV Read-Out Sub-systems RoI data = 1-2% ~2 GB/s L2P L2P L2P ~4 kHz ~6 GB/s L2N LVL2 accept Event Builder Event Filter ~ 1 sec EB ~6 GB/s EFN EFP EFP EFP ~ 600 MB/s ~ 400 Hz ~ 600 MB/s ARCHITECTURE FE Pipelines 2.5 ms H L T
CMS Event Building • CMS perform Event Building after Level-1 • Simplifies the architecture, but places much higher demand on technology: • Network traffic ~100 GB/s • 1st stage use Myrinet • 2nd stage has 8 GbE slices
Signature + e30i e30i Iso– lation Iso– lation STEP 4 Signature + e30 e30 pt> 30GeV pt> 30GeV STEP 3 Signature t i m e e + e track finding track finding STEP 2 Signature ecand ecand + Cluster shape Cluster shape STEP 1 Level1 seed + EM20i EM20i Example for Two electron trigger LVL1 triggers on two isolated e/m clusters with pT>20GeV (possible signature: Z–>ee) HLT Strategy: • Validate step-by-step • Check intermediate signatures • Reject as early as possible Sequential/modular approach facilitates early rejection
Trigger design - Event Filter / Level-3 • Event Filter reduce triggers to ~400 Hz • (was ~200 Hz) • Event Filter budget ~ 4 sec average • Full event detector data is available, but to minimise resources needed: • Only unpack detector data when it is needed • Use information from Level-2 to guide the process • Analysis proceeds in steps with – can reject event after each step • Use optimised off-line algorithms
EM ROI Execution of a Trigger Chain L2 calorim. Level1: Region of Interest is found and position in EM calorimeter is passed to Level 2 Electromagnetic clusters cluster? L2 tracking track? • Level 2 seeded by Level 1 • Fast reconstruction algorithms • Reconstruction within RoI match? E.F.calorim. E.F.tracking track? • Ev.Filter seeded by Level 2 • Offline reconstruction algorithms • Refined alignment and calibration e/ reconst. e/ OK?
e/γ Trigger L1 EM trigger pT > 5GeV pT≈3-20 GeV: b/c/tau decays, SUSY pT≈20-100 GeV: W/Z/top/Higgs pT>100 GeV: exotics Level 1: local ET maximum in ΔηxΔφ = 0.2x0.2 with possible isolation cut Level 2: fast tracking and calorimeter clustering – use shower shape variables plus track-cluster matching Event Filter: high precision offline algorithms wrapped for online running
Discriminate against hadronic showers based on shower shape variables Use fine granularity of LAr calorimeter Resolution improved in Event Filter with respect to Level 2
Muon Trigger 80% acceptance due to support structures etc. • Low PT: J/Y, U and B-physics • High PT: H/Z/W/τ➝μ, SUSY, exotics • Level 1: look for coincidence hits in muon trigger chambers • Resistive Plate Chambers (barrel) and Thin Gap Chambers (endcap) • pT resolved from coincidence hits in look-up table • Level 2: refine Level 1 candidate with precision hits from Muon Drift Tubes (MDT) and combine with inner detector track • Event Filter: use offline algorithms and precision; complementary algorithm does inside-out tracking and muon reconstruction
The Trigger Menu • Collection of trigger signatures • In LHC GPD’s menus there can be 100’s of algorithm chains – defining which objects, thresholds and algorithms, etc should be used • Selections set to match the current physics priorities and beam conditions within the bandwidth and rates allowed by the TDAQ system • Includes calibration & monitoring chains • Principal mechanisms to adjust the accept rate (and the relative frequency of different triggers) • Adjusting thresholds • Pre-scaling higher rate triggers (e.g. only accept every 10th trigger of a particular type) • Can be used to include a low rate of calibration events
Trigger Menu cont’d • Basic Menu is defined at the start of a run • Pre-scale factors can be changed during the course of a run • Adjust triggers to match current luminosity • Turn triggers on/off
Background Off-line Physics channel On-line Matching problem • Ideally • off-line algorithms select all the physics channel and no background • trigger algorithms select all the physics accepted by the off-line selection (and no background) • In practice, neither of these happen • Need to optimise the combinedselection • For this reason many trigger studies quote trigger efficiency wrt events which pass off-line selection • BUT remember off-line can change algorithm, re-process and recalibrate at a later stage • So, make sure on-line algorithm selection is well known, controlled and monitored
Other issues for the Trigger • Optimisation of cuts • Balance background rejection vs efficiency • Efficiency and Monitoring • In general need high trigger efficiency • Also for many analyses need a well known efficiency • Monitor efficiency by various means • Overlapping triggers • Pre-scaled samples of triggers in tagging mode (pass-through) • Final detector calibration and alignment constants not available for the trigger • keep as up-to-date as possible • allow for the lower precision in the trigger cuts • Code used in trigger needs to be fast + very robust • low memory leaks, low crash rate
Summary • High-level triggers allow complex selection procedures to be applied as the data is taken • Thus allow large samples of rare events to be recorded • The trigger stages - in the ATLAS example • Level 1 uses inclusive signatures (mu’s; em/tau/jet; missing and sum ET) • Level 2 refines Level 1 selection, adds simple topology triggers, vertex reconstruction, etc • Level 3 refines Level 2 adds more refined topology selection • Trigger menus need to be defined, taking into account: • Physics priorities, beam conditions, HLT resources • Include items for monitoring trigger efficiency and calibration • Try to match trigger cuts to off-line selection • Trigger efficiency should be as high as possible and well monitored • Must get it right - events thrown away are lost for ever! • Triggering closely linked to physics analyses – so enjoy!
Physics Letters B cover ATLAS and CMS “Higgs discovery” papers published side by side in Phys. Lett. B716 (2012)
2e2μcandidate with m2e2μ= 123.9 GeV pT(e,e,μ,μ)= 18.7, 76, 19.6, 7.9 GeV, m(e+e-)= 87.9 GeV, m(μ+μ-) =19.6 GeV 12 reconstructed vertices 41
Evolution of the excess with time Significance increase from 4th July to now from including 2012 data for H WW* search
Evolution of the excess with time Significance increase from 4th July to now from including 2012 data for H WW* search
ATLAS HLT Hardware • Each rack of HLT (XPU) processors contains • ~30 HLT PC’s (PC’s very similar to Tier-0/1 compute nodes) • 2 Gigabit Ethernet Switches • a dedicated Local File Server • Final system will contain ~2300 PC’s
LFS nodes UPS for CFS XPUs CFS nodes SDX1|2nd floor|Rows 3 & 2
Price to pay for the high luminosity: larger-than-expected pile-up Pile-up = number of interactions per crossing Tails up to ~20 comparable to design luminosity (50 ns operation; several machine parameters pushed beyond design) LHC figures used over the last 20 years: ~ 2 (20) events/crossing at L=1033 (1034) Period A: up to end August Period B: Sept-Oct Event with 20 reconstructed vertices (ellipses have 20 σsizefor visibility reasons) Z μμ Challenging for trigger, computing resources, reconstruction of physics objects (in particular ETmiss, soft jets, ..) Precise modeling of both in-time and out-of-time pile-up in simulation is essential 49
threshold threshold MU 20 I name name isolated isolated EF in tagging mode mu 20 i _ passEF Naming Convention First Level Trigger (LVL1) Signatures in capitals e.g. HLT in lower case: • New in 13.0.30: • Threshold is cut value applied • previously was ~95% effic. point. • More details : see :https://twiki.cern.ch/twiki/bin/view/Atlas/TriggerPhysicsMenu