1. LHC data processing challenges: from Detector data to Physics July 2007 Pere Mat ó CERN

2. Pere Mato, CERN/PH 2 The goal is to understand in the most general; that’s usually also the simplest. - A. Eddington We use experiments to inquire about what “reality” does. Theory & Parameters Reality This talk is about filling this gap

3. Pere Mato, CERN/PH 3 Theory “Clear statement of how the world works formulated mathematically in term of equations” Particle Data Group, Barnett et al Additional term goes here

4. Pere Mato, CERN/PH 4 Experiment 0x01e84c10: 0x01e8 0x8848 0x01e8 0x83d8 0x6c73 0x6f72 0x7400 0x0000 0x01e84c20: 0x0000 0x0019 0x0000 0x0000 0x01e8 0x4d08 0x01e8 0x5b7c 0x01e84c30: 0x01e8 0x87e8 0x01e8 0x8458 0x7061 0x636b 0x6167 0x6500 0x01e84c40: 0x0000 0x0019 0x0000 0x0000 0x0000 0x0000 0x01e8 0x5b7c 0x01e84c50: 0x01e8 0x8788 0x01e8 0x8498 0x7072 0x6f63 0x0000 0x0000 0x01e84c60: 0x0000 0x0019 0x0000 0x0000 0x0000 0x0000 0x01e8 0x5b7c 0x01e84c70: 0x01e8 0x8824 0x01e8 0x84d8 0x7265 0x6765 0x7870 0x0000 0x01e84c80: 0x0000 0x0019 0x0000 0x0000 0x0000 0x0000 0x01e8 0x5b7c 0x01e84c90: 0x01e8 0x8838 0x01e8 0x8518 0x7265 0x6773 0x7562 0x0000 0x01e84ca0: 0x0000 0x0019 0x0000 0x0000 0x0000 0x0000 0x01e8 0x5b7c 0x01e84cb0: 0x01e8 0x8818 0x01e8 0x8558 0x7265 0x6e61 0x6d65 0x0000 0x01e84cc0: 0x0000 0x0019 0x0000 0x0000 0x0000 0x0000 0x01e8 0x5b7c 0x01e84cd0: 0x01e8 0x8798 0x01e8 0x8598 0x7265 0x7475 0x726e 0x0000 0x01e84ce0: 0x0000 0x0019 0x0000 0x0000 0x0000 0x0000 0x01e8 0x5b7c 0x01e84cf0: 0x01e8 0x87ec 0x01e8 0x85d8 0x7363 0x616e 0x0000 0x0000 0x01e84d00: 0x0000 0x0019 0x0000 0x0000 0x0000 0x0000 0x01e8 0x5b7c 0x01e84d10: 0x01e8 0x87e8 0x01e8 0x8618 0x7365 0x7400 0x0000 0x0000 0x01e84d20: 0x0000 0x0019 0x0000 0x0000 0x0000 0x0000 0x01e8 0x5b7c 0x01e84d30: 0x01e8 0x87a8 0x01e8 0x8658 0x7370 0x6c69 0x7400 0x0000 0x01e84d40: 0x0000 0x0019 0x0000 0x0000 0x0000 0x0000 0x01e8 0x5b7c 0x01e84d50: 0x01e8 0x8854 0x01e8 0x8698 0x7374 0x7269 0x6e67 0x0000 0x01e84d60: 0x0000 0x0019 0x0000 0x0000 0x0000 0x0000 0x01e8 0x5b7c 0x01e84d70: 0x01e8 0x875c 0x01e8 0x86d8 0x7375 0x6273 0x7400 0x0000 0x01e84d80: 0x0000 0x0019 0x0000 0x0000 0x0000 0x0000 0x01e8 0x5b7c 0x01e84d90: 0x01e8 0x87c0 0x01e8 0x8718 0x7377 0x6974 0x6368 0x0000 1/5000th of an event in the CMS detector –Get about 100 events per second

5. Pere Mato, CERN/PH 5 What does the Data Mean?  Digitization: “Address”: what detector element took the reading “Value”: What the electronics wrote down Look up type, calibration info Look up/calculate spatial position Check valid, convert to useful units/form Draw

6. Pere Mato, CERN/PH 6 Graphical Representation

7. Pere Mato, CERN/PH 7 Bridging the Gap Raw Data Theory & Parameters Reality A small number of general equations, with specific input parameters (perhaps poorly known) The imperfect measurement of a (set of) interactions in the detector Very strong selection Observables Specific lifetimes, probabilities, masses, branching ratios, interactions, etc Events A unique happening: Run 21007, event 3916 which contains a H -> xx decay Reconstruction Analysis Phenomenology

8. Pere Mato, CERN/PH 8 Physics Selection at LHC

9. Pere Mato, CERN/PH 9 Trigger Task: inspect detector information and provide a first decision on whether to keep the event or throw it out The trigger is a function of : Detector data not (all) promptly available Selection function highly complex  T(...) is evaluated by successive approximations, the TRIGGER LEVELS (possibly with zero dead time) Event data & Apparatus Physics channels & Parameters T () ACCEPTED REJECTED

10. Pere Mato, CERN/PH 10 Trigger Levels Lvl-1 Lvl-2 HLT Front end pipelines Readout buffers Processor farms Switching network Detectors “Traditional”: 3 physical levels  Level-1 trigger: reduce 40 MHz to 10 5 Hz –This step is always there  Level-2 trigger: from 10 5 Hz to 10 3 Hz –Not always there if next level can take the rate and bandwidth  High Level Trigger (HTL) –Need to get to 10 2 Hz that is what is affordable to be permanently stored and processed offline

11. Pere Mato, CERN/PH 11 Trigger and DAQ Challenges  N (channels) ~ O(10 7 ); ≈20 interactions every 25 ns –need huge number of connections –need information super-highway  Calorimeter information should correspond to tracker info –need to synchronize detector elements to (better than) 25 ns  In some cases: detector signal/time of flight > 25 ns –integrate more than one bunch crossing's worth of information –need to identify bunch crossing...  Can store data at ≈ 10 2 Hz –need to reject most interactions  It's On-Line (cannot go back and recover events) –need to monitor selection

12. Pere Mato, CERN/PH 12 Trigger/DAQ Summary for LHC No.LevelsLevel-1Event ReadoutFilter Out TriggerRate (Hz)Size (Byte) Bandw.(GB/s)MB/s (Event/s) 310 5 10 6 10 100 (10 2 ) LV-2 10 3 210 5 10 6 100100 (10 2 ) 3 LV-0 10 6 2x10 5 440 (2x10 2 ) LV-1 4 10 4 4 Pp-Pp 5005x10 7 51250 (10 2 ) p-p 10 3 2x10 6 200 (10 2 ) ATLAS CMS LHCb ALICE

13. Pere Mato, CERN/PH 13 individual physics analysis batch physics analysis batch physics analysis detector Event Summary Data (ESD) raw data event reconstruction event reconstruction event simulation event simulation event filter (selection & reconstruction) event filter (selection & reconstruction) processed data Offline Processing Stages and Datasets Analysis Object Data (AOD) (extracted by physics topic)

14. Pere Mato, CERN/PH 14 Main Software Requirements  The new software being developed by the LHC experiments must cope with the unprecedented conditions and challenges that characterizes these experiments (trigger rate, data volumes, etc.)  The software should not become the limiting factor for the trigger, detector performance and physics reach for these experiments  In spite of its complexity it should be easy-to-use –Each one of the ~ 4000 LHC physicists (including people from remote/isolated countries, physicists who have built the detectors, software-old-fashioned senior physicists) should be able to run the software, modify part of it (reconstruction,...), analyze the data, extract physics results  Users demand simplicity (i.e. hiding complexity) and stability

15. Pere Mato, CERN/PH 15 Software Structure non-HEP specific software packages Experiment Framework Event Det Desc. Calib. Applications Core Libraries Simulation Data Mngmt. Distrib. Analysis Every experiment has a framework for basic services and various specialized frameworks: event model, detector description, visualization, persistency, interactivity, simulation, calibrarion, etc. General purpose non-HEP libraries Applications are built on top of frameworks and implementing the required algorithms Core libraries and services that are widely used and provide basic functionality Specialized domains that are common among the experiments

16. Pere Mato, CERN/PH 16 Software Components  Foundation Libraries –Basic types –Utility libraries –System isolation libraries  Mathematical Libraries –Special functions –Minimization, Random Numbers  Data Organization –Event Data –Event Metadata (Event collections) –Detector Conditions Data  Data Management Tools –Object Persistency –Data Distribution and Replication  Simulation Toolkits –Event generators –Detector simulation  Statistical Analysis Tools –Histograms, N-tuples –Fitting  Interactivity and User Interfaces –GUI –Scripting –Interactive analysis  Data Visualization and Graphics –Event and Geometry displays  Distributed Applications –Parallel processing –Grid computing

17. Pere Mato, CERN/PH 17 Programming Languages  Object-Oriented (O-O) programming languages have become the norm for developing the software for HEP experiments  C++ is in use by (almost) all Experiments –Pioneered by Babar and Run II (D0 and CDF) –LHC experiments with an initial FORTRAN code base have basically completed the migration to C++  Large common software projects in C++ have been in production for many years aready –ROOT, Geant4, …  FORTRAN still in use mainly by the MC generators –Large developments efforts are put for the migration to C++ (Pythia8, Herwig++, Sherpa,…)

18. Pere Mato, CERN/PH 18 Scripting Languages  Scripting has been an essential component in the HEP analysis software for the last decades –PAW macros (kumac) in the FORTRAN era –C++ interpreter (CINT) in the C++ era –Python recently introduced and gaining momentum  Most of the statistical data analysis and final presentation is done with scripts –Interactive analysis –Rapid prototyping to test new ideas –Driving complex procedures  Scripts are also used to “configure” complex C++ programs developed and used by the LHC experiments –“Simulation” and “Reconstruction” programs with hundreds or thousands of options to configure

19. Pere Mato, CERN/PH 19 Object-Orientation  The object-oriented paradigm has been adopted for HEP software development –Basically all the code for the new generation experiments is O-O –O-O has enabled us to handle reasonably well higher complexity  The migration to O-O was not easy and took longer than expected –The process was quite long and painful (between 4-8 years) »The community had to be re-educated to new languages and tools –C++ is not a simple language »Only specialists master it completely –Mixing interpreted and compiled languages (e.g. C++ and Python) is a workable compromise

20. Pere Mato, CERN/PH 20 Non-HEP Packages widely used in HEP  Non-HEP specific functionality required by HEP programs can be implemented using existing packages –Favoring free and open-source software –About 30 packages are currently in use by the LHC experiments  Here are some examples –Boost »Portable and free C++ source libraries intended to be widely useful and usable across a broad spectrum of applications –GSL »GNU Scientific Library –Coin3D »High-level 3D graphics toolkit for developing cross-platform real-time 3D visualization –XercesC »XML parser written in a portable subset of C++ non-HEP specific software packages Experiment Framework Applications Core Libraries Simulation Data Mngmt. Distrib. Analysis

21. Pere Mato, CERN/PH 21 HEP Generic Packages (1)  Core Libraries –Library of basic types (e.g. 3-vector, 4-vector, points, particle, etc.) –Extensions to C++ Standard Library –Mathematical libraries –Statistics libraries  Utility Libraries –Operating system isolation libraries –Component model –Plugin management –C++ Reflexion  Examples: ROOT, CLHEP, etc. non-HEP specific software packages Experiment Framework Applications Core Libraries Simulation Data Mngmt. Distrib. Analysis

22. Pere Mato, CERN/PH 22 HEP Generic Packages (2)  MC Generators –This is the best example of common code used by all the experiments »Well defined functionality and fairly simple interfaces  Detector Simulation – Presented in form of toolkits/frameworks (Geant4, FLUKA) »The user needs to input the geometry description, primary particles, user actions, etc.  Data Persistency and Management –To store and manage the data produced by experiments  Data Visualization –GUI, 2D and 3D graphics  Distributed and Grid Analysis –To support end-users using the distributed computing resources (PROOF, Ganga,…) non-HEP specific software packages Experiment Framework Applications Core Libraries Simulation Data Mngmt. Distrib. Analysis

23. Pere Mato, CERN/PH 23 ROOT I/O  ROOT provides support for object input/output from/to platform independent files –The system is designed to be particularly efficient for objects frequently manipulated by physicists: histograms, ntuples, trees and events –I/O is possible for any user class. Non-intrusive, only the class “dictionary” needs to be defined –Extensive support for “schema evolution”. Class definitions are not immutable over the life-time of the experiment  The ROOT I/O area is still moving after 10 years –Recent additions: Full STL support, data compression, tree I/O from ASCII, tree indices, etc.  All new experiments rely on ROOT I/O to store its data

24. Pere Mato, CERN/PH 24 Persistency Framework  FILES - based on ROOT I/O –Targeted for complex data structure: event data, analysis data –Management of object relationships: file catalogues –Interface to Grid file catalogs and Grid file access  Relational Databases – Oracle, MySQL, SQLite –Suitable for conditions, calibration, alignment, detector description data - possibly produced by online systems –Complex use cases and requirements, multiple ‘environments’ – difficult to be satisfied by a single solution –Isolating applications from the database implementations with a standardized relational database interface »facilitate the life of the application developers »no change in the application to run in different environments »encode “good practices” once for all

25. Pere Mato, CERN/PH 25 Monte Carlo simulation’s role Raw Data Theory & Parameters Reality Observables Events Calculate expected branching ratios Randomly pick decay paths, lifetimes, etc for a number of events Calculate what imperfect detector would have seen for those events Treat that as real data and reconstruct it Compare to original to understand efficiency

26. Pere Mato, CERN/PH 26 MC Generators  Many MC generators and tools are available to the experiments provided by a solid community –Each experiment chooses the tools more adequate for their physics  Example: ATLAS alone uses currently –Generators »AcerMC: Zbb~, tt~, single top, tt~bb~, Wbb~ »Alpgen (+ MLM matching): W+jets, Z+jets, QCD multijets »Charbydis: black holes »HERWIG: QCD multijets, Drell-Yan, SUSY... »Hijing: Heavy Ions, Beam-gas.. »MC@NLO: tt~, Drell-Yan, boson pair production »Pythia: QCD multijets, B-physics, Higgs production... –Decay packages »TAUOLA: Interfaced to work with Pythia, Herwig and Sherpa, »PHOTOS: Interfaced to work with Pythia, Herwig and Sherpa, »EvtGen: Used in B-physics channels.

27. Pere Mato, CERN/PH 27 Detector Simulation - Geant 4  Geant4 has become an established tool, in production for the majority of LHC experiments during the past two years, and in use in many other HEP experiments and for applications in medical, space and other fields  On going work in the physics validation  Good example of common software LHCb : ~ 18 million volumes ALICE : ~3 million volumes

28. Pere Mato, CERN/PH 28 Analysis - Brief History  1980s: mainframes, batch jobs, histograms back. Painful.  Late 1980s, early 1990s: PAW arrives. –NTUPLEs bring physics to the masses –Workstations with “large” disks (holding data locally) arrive; looping over data, remaking plots becomes easy  Firmly in the 1990s: laptops arrive; –Physics-in-flight; interactive physics in fact.  Late 1990s: ROOT arrives –All you could do before and more. In C++ this time. –FORTRAN is still around. The “ROOT-TUPLE” is born –Side promise: reconstruction and analysis form a continuum  2000s: two categories of analysis physicists: those who can only work off the ROOT-tuple and those who can create/modify it  Mid-2000s: WiFi arrives; Physics-in-meeting

29. Pere Mato, CERN/PH 29 PROOF – Parallel ROOT Facility  PROOF aims to provide the necessary functionality that allows to run ROOT data analysis in parallel –A major upgrade of the PROOF system has been started in 2005. –The system is evolving from processing interactive short blocking queries to a system that also supports long running queries in a stateless client mode. –Currently working with ALICE to deploy it on the CERN Analysis Facility (CAF)

30. Pere Mato, CERN/PH 30 Experiment Data Processing Frameworks  Experiments develop Software Frameworks –General Architecture of any Event processing applications (simulation, trigger, reconstruction, analysis, etc.) –To achieve coherency and to facilitate software re-use –Hide technical details to the end-user Physicists –Help the Physicists to focus on their physics algorithms  Applications are developed by customizing the Framework –By the “composition” of elemental Algorithms to form complete applications –Using third-party components wherever possible and configuring them  ALICE: AliROOT; ATLAS+LHCb: Athena/Gaudi  CMS: moved to a new framework recently non-HEP specific software packages Experiment Framework Applications Core Libraries Simulation Data Mngmt. Distrib. Analysis

31. Pere Mato, CERN/PH 31 Example: The GAUDI Framework  User “algorithms” consume event data from the “transient data store” with the help of “services” and “tools” with well defined interfaces and produce new data that is made available to other “algorithms”.  Data can have various representations and “converters” take care of their transformation  The GAUDI framework is used by LHCb, ATLAS, Harp, Glast, BES III

32. Pere Mato, CERN/PH 32 Application Software on the Grid  What I have been describing until now is the software that runs on the Grid, it is not the Grid software itself (middleware)  Experiments have developed tools to facilitate the usage of the Grid  Example: GANGA –Help configuring and submitting analysis jobs (Job Wizard) –Help users to keep track of what they have done –Hide completely all technicalities –Provide a palette of possible choices and specialized plug- ins: »pre-defined application configurations »batch/grid systems, etc. »GANGA ‘knows’ what the user is running, so it can really help him/her –Single desktop for a variety of tasks –Friendly user interface is essential GAUDI Program GANGA GUI JobOptions Algorithms Collective & Resource Grid Services Histograms Monitoring Results

33. Pere Mato, CERN/PH 33 Summary  The online multi-level trigger is essential to select interesting collisions (1 in 10 5 -10 6 ) –Level1: custom hardware, huge fanin/out problem, fast algorithms on coarse-grained, low-resolution data –HTL: software/algorithms (offline) on large processor farm of PCs  Reconstruction and analysis is how we get from raw data to physics papers –Huge programs (10 7 lines of code) developed by 100’s of physicists –Unprecedented need of computing resources  The next generation of software for experiments needs to cope with more stringent requirements and new challenging conditions –The software should not be the limiting factor and should allow the physicists extract the best physics from the experiment –The new software is more powerful but at the same time more complex