This presentation contains an overview of my work at Nikhef, the Dutch national institute for subatomic physics, in the last few years.

1. Physics Data Processing -The online connection Nikhef colloquium 9/2/2009 Sander Klous

2. The steamboat view PDP Activities Bob Hertzberger 2 Physics Data Processing - Sander Klous 9/2/2009 Remote Online Farms Use Cases (i.e. trigger performance) My focus

3. Remote Online Farms What is a remote online farm? The connection to the online system Event routing and streaming Remote online farms in ATLAS (Hegoi Garitaonandia) Debug stream reprocessing Trigger menu validation Muon calibration stream Do we really need remote online farms? 9/2/2009 Physics Data Processing - Sander Klous 3

4. Concept Physics Data Processing - Sander Klous 4 Data Acquisition 40 MHz Level 1 Level 2 Level 3 Amsterdam Accept 1 in 500 NIKHEF/SARA Network switch Accept 1 in 50 Accept 1 in 10 Computing grid 9/2/2009

5. Why is this interesting? 9/2/2009 Physics Data Processing - Sander Klous 5 January 2001 Gary Stix, editor of Scientific American

6. Connection to the online system 9/2/2009 Physics Data Processing - Sander Klous 6 ROF ROF ROF ROF EF SFO Remote Event Processing Farms ROB ROB ROB ROB Data Collection Network Packet Switched (GEANT) SFI SFI SFI Routing and Streaming Level 2 Trigger Light path Back End Network L2PU Event Filter Mass storage Building 513 CatalinMeirosu DDM Local Farm

7. Routing and Streaming introduction 9/2/2009 Physics Data Processing - Sander Klous 7 Hans von der Schmitt Optimizing resources Online, different routes Offline, different streams Classification of events Physics Calibration Debug Express Remote

8. Regions of Interest andPartial Event Building 9/2/2009 Physics Data Processing - Sander Klous 8 Virtual Point 1 Ignacio Aracena

9. Inclusive or Exclusive streaming 9/2/2009 Physics Data Processing - Sander Klous 9 Hans von der Schmitt

10. Online monitoring of overlaps 9/2/2009 Physics Data Processing - Sander Klous 10 Brian Petersen

11. Luminosity blocks 9/2/2009 Physics Data Processing - Sander Klous 11 Hans von der Schmitt

12. Final Dress RehearsalData Quality Monitoring DDM/DQ2 TIER-0 RAW 320 TIER-1s 320 ESD 720 200 200 200 CASTOR AOD 200 720 TAG 440 Luc Goossens CPU farm Data acquisition TAG DB disk 150TB 1060 raid 25TB load TAG 320 130 recon EXPR 340 online SFO recon PHYS T0M DB c1 Cond DB calib/align c1 Express stream handling 9/2/2009 Physics Data Processing - Sander Klous 12 Rates in MB/s

13. Debug stream reprocessing 9/2/2009 Physics Data Processing - Sander Klous 13

14. Trigger menu validation 9/2/2009 Physics Data Processing - Sander Klous 14

15. Muon calibration 9/2/2009 Physics Data Processing - Sander Klous 15 MuonCalibrationGroup Virtual Point 1

16. Do we really need ROFs? At the moment: No, not really… Not for physics at least Transition will be gradual Example: debug stream reprocessing Limited resources in the CERN Analysis Facility Funding will play an important role Easier to fund online resources in home country Other factors: energy consumption, human resources What will be the first physics use case? 9/2/2009 Physics Data Processing - Sander Klous 16

17. Trigger performance Fully Hadronic decays of top pairs The jet trigger challenge Determining trigger efficiencies from data Tag and probe with leptons T&P with semi-leptonic decays of top pairs(Menelaos Tsiakiris) Turning the probe around, T&P with jets Jet trigger efficiencies and rates Beyond multi-jet triggers Topology triggers and remote online farms 9/2/2009 Physics Data Processing - Sander Klous 17

18. Fully Hadronic decaysof top-antitop pairs 9/2/2009 Physics Data Processing - Sander Klous 18

19. The jet trigger challenge QCD 6 jet background 1000 to 10000 x Signal Is this possible at all? Long term study First look at semi-leptonic decays Study the possibility to trigger on jets Extract jet trigger efficiency from data Cross correlate with muon triggers 9/2/2009 Physics Data Processing - Sander Klous 19 Turn on kicks in. Trigger problem Lambacher Munich O(1 fb-1)

20. Trigger efficiency from data 20 GeV muon turn on curve (CSC note) Tagged Tagged and Probed Tag and probe A first example:di-muon decays of Z bosons 9/2/2009 Physics Data Processing - Sander Klous 20

21. Semi leptonic decays of top pairs Tag on the jet side and probe on the muon side Extract number of signal events (1 fb-1) Invariant mass reconstruction on hadronic side 9/2/2009 Physics Data Processing - Sander Klous 21 Possible problem: contamination with tau to muon decays

22. Event by event trigger efficiency Determine individual object efficiencies Extrapolate T&P from di-muon decays of Z-bosons Combine objects into an event efficiency Weigh the event appropriately 9/2/2009 Physics Data Processing - Sander Klous 22 Correct isolation withrespect to closest jet Correct foreta dependency Without corrections Tamsett – Royal Holloway

23. Turning the probe around More complicated The jets are multi-object triggers,e.g. 4J_95: 4 jets above 95 GeV Thresholds are likely to change The missing link: Trigger efficiency of Semi Leptonic decays Fully Hadronic decays of top quark pairs Is it possible? If not, can we do better? 9/2/2009 Physics Data Processing - Sander Klous 23

24. Topology triggers and remote online farms Topology triggers Time consuming Invariant masses Likelihood fits Budget in point 1 1500 machines x 8 cores per machine = 12000 cores 3 kHz EF input rate from LVL2 12000 / 3000 = 4 seconds per event (all triggers) 9/2/2009 Physics Data Processing - Sander Klous 24 Xin Wu Event Filter Mean: 1.57 seconds (Erik van der Kraaij)

25. Conclusion Remote Online Farms An interesting research topic Several farms already in production Still far from enabling grid for online processing Physics Use Cases Most likely complicated topologies Fully hadronic decays of top quark pairs Studies ongoing to understand trigger efficiencies The future of grid is in the online connection 9/2/2009 Physics Data Processing - Sander Klous 25