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Calibration streams in the Event Filter.

Calibration streams in the Event Filter. Status report Mainz, Thursday 13 October 2005 Sander Klous – NIKHEF On behalf of the EF calibration team: Martine Bosman, Andrea Negri, Serge Sushkov and Sarah Wheeler. Definition and scope. Physics streams. Calibration streams. 40 MHz x 1.5 MByte.

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Calibration streams in the Event Filter.

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  1. Calibration streams in the Event Filter. Status report Mainz, Thursday 13 October 2005 Sander Klous – NIKHEF On behalf of the EF calibration team: Martine Bosman, Andrea Negri, Serge Sushkov and Sarah Wheeler.

  2. Definition and scope. Physics streams Calibration streams 40 MHz x 1.5 MByte Level 1 Level 2 Level 1 Level 2 Other people 75 kHz x 1.5 MByte ? Event Filter Processing time: 1 Sec/Evt Number of nodes: 1500 Output: 200 Hz 320 MB/s Calibration issues in the EF. • At the moment only EF output. • Identify calibration types. • Size, rate, contents. • Requirements for the EF. • Data flow. • Processing issues. • Implementation scenarios. • Design and modifications. • Processing. • Memory management. • Networking/Timing. • Plan of work. 2 kHz x 1.5 MByte TDAQ workshop - Mainz

  3. Use cases(identification of calibration streams). Based on the Hawkings/Gianotti document. • All listed calibration types are identified at HLT level (after PESA). • Known calibration types in the HLT. • Various duplicates of physics streams: e.g. inclusive high pT electrons and muons (tracking), Z to di-lepton (energy), minimum bias (background). • Total: 35 MB/s (10% of physics data). • Liquid Argon Calorimeter. Pulse shape analysis, timing calibration and tuning of filter coefficients. • High pT electron sample • Electro Magnetic data only. ROI only. • Raw data, 5 consecutive samples (i.e. special event type). • Calorimeters and TRT. Hadronic response studies, comparison to test beam data. TRT: e/ separation. • High pT isolated hadrons. • All subdetectors. ROI only. • RAW data. TDAQ workshop - Mainz

  4. Use cases – continued…(identification of calibration streams). • MDT small chambers. Hourly realignment. • Small muon sample. • MDT information only. Overlap regions only. • Reprocessing of raw data. • Inner Detector subdetectors (Pixel, SCT and TRT). ROD monitoring (TRT only) and alignment. • Generic high pT events. • All subdetectors. ROI only. • Post-processing of track fit information on HLT level. • Other foreseen calibration types. • Liquid Argon Calorimeter might need Z  ee calibration at HLT level. • High statistics (1 kHz) ROI muon sample, containing MDT, CSC and RPC/TGC information. • Your favorite missing calibration stream… TDAQ workshop - Mainz

  5. Data flow characterization. SFI SFI? Subdetector Fragment 1 Lvl 1/2 info SFO SFO SFO SFO SFO SFO SFO SFO Subdetector Fragment N Lvl 1/2 info Special events Physics High pT Z di-lepton Min. bias Subdetector Fragment 1 ROI info 32 MB/s 1.6 MB/s 1.6 MB/s 320 MB/s Partial event Transport time: LVL2Cal 0.01 ms EF Node n Stripping/Collecting LVL2Cal Transport times/rates: LAr OverlapMu IsoHad GenPT LAr OverlapMu IsoHad GenPT 0.5 ms 0.05 ms 5 ms 0.5 ms 50 Hz 5 Hz 5 Hz 100 Hz Output 1 MB/s 2.5 MB/s 5 kB/s 2 MB/s 4 MB/s Transport times: 19 ms EF Node n EF processing: 1 second/event Full calibration events Sorting EF processing: 1 second/event EF Node n Transport time: 19 ms Partial calibration events 1 kHz! Additional Processing

  6. EF processing issues. SFO SFO SFO SFI Node n EFD SharedHeap Event Input PT #1 PTIO Result ExtPTs PTIO PT cal ExtPTs PT #2 PTIO Trash Output Output Output Calibration Stream Diagnostic Main output stream • Definitions: • Sorting for calibration: CalID. • Stripping/Collecting for calibration: CalCollect. • Detector calibration: CalDetect or Calibration. • Full event streams. • Very similar to physics streams. • Output to multiple SFOs/streams. • Sorting of events for calibration (CalID). • Partial event streams. • Processing similar to physics stream. • Stripping and collecting (CalCollect). • Handling of different output event size. • Sometimes requires additional processing (CalDetect/Calibration). • Special event streams. • Processing times completely different from physics stream. • Handling of different input and output event sizes. • Central issue: Robustness of the EFD TDAQ workshop - Mainz

  7. EF processing issues. SFO SFI • Definitions: • Sorting for calibration: CalID. • Stripping/Collecting for calibration: CalCollect. • Detector calibration: CalDetect or Calibration. • Full event streams. • Very similar to physics streams. • Output to multiple SFOs/streams. • Sorting of events for calibration (CalID). • Partial event streams. • Processing similar to physics stream. • Stripping and collecting (CalCollect). • Handling of different output event size. • Sometimes requires additional processing (CalDetect/Calibration). • Special event streams. • Processing times completely different from physics stream. • Handling of different input and output event sizes. • Central issue: Robustness of the EFD Node n EFD SharedHeap Event Input ExtPTs Output Dataflow application Main output stream TDAQ workshop - Mainz

  8. Calibration stream scenarios (1). SFO SFI SFI SFO SFO Node n EFD Event Result Input PT #1 PTIO PT #1 PTIO ExtPTs ExtPTs PESA Trash Trash Output Output Output Calibration Stream Main output stream Main output stream Additional functionality: • CalID algorithm. • Parallel output streams. Full calibration events. e.g. Z di-lepton Physics only events Node n EFD Event Result Input CalID PESA TDAQ workshop - Mainz

  9. Calibration stream scenarios (2). SFI SFO SFI? SFO SFO Node n EFD Node n Event EFD Event Input Input Result PT #1 PTIO Sorting PT #1 PTIO ExtPTs ExtPTs PTIO PT cal CalID PESA ExtPTs CalID Stripping Collecting Output Output Output Output EF output Calibration Stream Calibration Stream 1 Calibration Stream 2 Main output stream Special streams. e.g. LVL2Cal Additional functionality: • PT for calibration. • Information handling • Stripping/collecting. • Memory management. Partial calibration events. e.g. GenPT CalResult Calibration • Networking/Timing issues.

  10. Design and modifications (1). • CalID algorithm. • Lightweight algorithm. • Runs after PESA in physics PT – Stability issues. Athena configuration: multiple top algorithms. • Workload: Low – implementation only, thorough testing required. • Impact: High – required for (almost) all calibration streams. • Coordination: Sorting – New PT answers should be discussed. • Parallel output streams. • Slight modification of existing algorithm. • Runs in EFD, probably required for PESA as well. • Workload: Low – Modification of standard EFD task. • Impact: High – Required for most (calibration) streams. TDAQ workshop - Mainz

  11. Design and modifications (2). • PT for calibration. • Create stripping/collection algorithm. • Requires new eformat (see next slide). • Requires modifications in output task. • Allow multiple PTs to run consecutively (works already). • Transfer information between these PTs. • Should be possible with new eformat for EFResult / CalResult. • It might be interesting to transfer “intermediate results”. • Would avoid to • Run calibration algorithms in the same PT as PESA. • Reanalyze complete event in second PT. • Since EF is a dataflow application, this should be accomplished by writing an extra “Intermediate Result” object in the Shared Heap. • This requires ByteStream conversion for complex classes. • Workload: Medium – With exception of item 4 (no use cases yet). • Impact: High – Maybe with exception of item 4. TDAQ workshop - Mainz

  12. Memory management and information handling. SFO SFI Virtual event Event fragments EFResult PT #1 PTIO Stripping PTIO PT cal PESA CalID CalResult Stripping Collecting Output New eformat. Node n 1 0 1 0 0 1 EFD SharedHeap 1 0 1 0 0 1 1 Event EFResult CalResult 1 0 1 0 0 1 1 Input - x - 1 - 0 x - - - - - - - 1 ExtPTs 1 1 1 0 0 1 ExtPTs • Integrate with: • Virtual event. • SharedHeap. • Event handling in the EF. • Event modification in EF, i.e. stripping/collecting. TDAQ workshop - Mainz

  13. Open issues Many new developments on a very tight schedule. • Memory and performance. • Management: move from open/close backpressure mechanism (barrier) to analog (Nano sleeps). • Timing: revise SFI – EFD – SFO protocol. • Coordination… • Investigate common/similar design issues with monitoring • 128 bit header word. First discussion yesterday. • 32 bits to register appropriate output streams. • Investigate usage of this header. Streaming only, since EFResult fragment contains much more detail and is “just around the corner”. • PT answer to EFD. Composite structure. • EFD – SFO sorting, i.e. how is an output stream defined? • Load balancing between calibration and physics. • Distribution of calibration constants to EF software. • Communication between Athena algorithms and configuration and calibration databases. • Could this be done via e.g. the information service? TDAQ workshop - Mainz

  14. Plan of work. • Short time scale. • Run calibration algorithm in PT. • Implement parallel output streams. • Medium time scale. • Implement CalID algorithm and sorting. • Eliminate dead time in input and output tasks. • Medium – Long timescale. • Change memory management. • Implement new eformat. • Implement stripping/collecting. • Long timescale. • Transfer of intermediate results between first and second PT TDAQ workshop - Mainz

  15. Conclusions. • Our understanding of calibration streams in the Event Filter improved a lot. • We think we have a realistic overview of the workload involved in modifications of the Event Filter. • Implementation has started and this will lead to even better understanding of the topic (and of the work involved). • There are still some (many) open issues. Coordination is important, especially because of the tight schedule. • More information: https://uimon.cern.ch/twiki/bin/view/Atlas/EventFilterCalibration TDAQ workshop - Mainz

  16. Conclusions. • Our understanding of calibration streams in the Event Filter improved a lot. • We think we have a realistic overview of the workload involved in modifications of the Event Filter. • Implementation has started and this will lead to even better understanding of the topic (and of the work involved). • There are still some (many) open issues. Coordination is important, especially because of the tight schedule. • More information: https://uimon.cern.ch/twiki/bin/view/Atlas/EventFilterCalibration TDAQ workshop - Mainz

  17. Appendix TDAQ workshop - Mainz

  18. Appears to fit with solutions shown in LVL2Mu presentations. Ultralight project (Manuela Cirilli). LVL2Mu calibration stream (Speranza Falciano). Etc. (Enrico Pasqualucci, Alessandro de Salvo). Additional functionality: HLT output A distributed trigger for calibration? SFI? PT #1 PTIO Event Distributor HLT output Calibration Stream Moore’s law for networking Gary Stix, Scientific American, January 2001 Node n EFD Input Event ExtPTs Output The Event Filter is CPU dominated. You would like it to be bandwidth dominated… TDAQ workshop - Mainz

  19. ByteStream conversion • Write converters? • No, a lot of work. • Robustness issues. • Generic ByteStream conversion? • No support for complicated classes (e.g. multiple inheritance, polymorphism). • Something else? • Not on the priority list. • Under discussion… TDAQ workshop - Mainz

  20. Memory management and networking/timing 19 milliseconds transport time 0.25 ms dead time SFI SFO Barrier PT #1 PTIO PTIO PT cal PESA CalID 1+ second processing time Stripping Collecting 19 milliseconds transport time 0.25 ms dead time Node n EFD SharedHeap Virtual event Event Event Event EFResult EFResult EFResult CalResult Intermediate Results Input ExtPTs ExtPTs Output TDAQ workshop - Mainz

  21. Memory management and networking/timing SFI SFO PT #1 PTIO PTIO PT cal PESA CalID Stripping Collecting 0.01 ms transport time 25 ms dead time • Eliminate dead time. • Redesign of SFI – EFD – SFO communication protocol. • Coordination with networking group. • Barrier is insufficient. • Oscillations. • Other memory requests. Node n EFD SharedHeap Virtual event Event Event Event EFResult Barrier EFResult EFResult CalResult CalResult CalResult Intermediate Results Intermediate Results Input Intermediate Results ExtPTs ExtPTs 0 sec. processing time Output 0.01 ms transport time 25 ms dead time TDAQ workshop - Mainz

  22. Memory management and networking/timing SFI SFO PT #1 PTIO PTIO PT cal PESA CalID Stripping Collecting 0.01 ms transport time 25 ms dead time • Eliminate dead time. • Barrier is insufficient. • Oscillations. • Other memory requests. Node n EFD SharedHeap Virtual event Event Event Event EFResult Barrier EFResult EFResult CalResult CalResult CalResult Intermediate Results Intermediate Results Input Intermediate Results ExtPTs ExtPTs 0 sec. processing time Output 0.01 ms transport time 25 ms dead time TDAQ workshop - Mainz

  23. Memory management and networking/timing SFO SFI PT #1 PTIO PTIO PT cal PESA CalID Stripping Collecting 0.01 ms transport time 25 ms dead time • Eliminate dead time. • Barrier is insufficient. • Oscillations. • Other memory requests. Node n EFD SharedHeap Virtual event Event Event Nano sleeps Event EFResult EFResult EFResult CalResult CalResult CalResult • Solution: Nano sleeps, • However… • multiple control loops. • Risk of oscillations. • Additional complexity. • Workload: • High – Especially testing. • Impact: • ??? Intermediate Results Intermediate Results Input Intermediate Results ExtPTs Nano sleeps ExtPTs 0 sec. processing time Output 0.01 ms transport time 25 ms dead time TDAQ workshop - Mainz

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