lhcb software vanya belyaev vanya belyaev. preface it is not a tutorial for beginners it is not a...

LHCb Software

Vanya BELYAEV

mailto:[email protected]?subject=Bender%20Tutorial%20v7r0

Vanya BELYAEV 2

Preface

• It is NOT a tutorial for beginners• If you need – the tutorial will follow

• It is NOT a tutorial for advanced users • If you need – the tutorial could be organized

• It is NOT an commercial for new or advanced software

• It is just some general “introduction” • Introduction to the Terminology?

• One does not need be a software expert• One does not need know well LHCb

10 Oct'2k+7 Syracuse

Vanya BELYAEV 3

The language

• LHCb software is mainly OO: • C++

• Blueprint-1998 has stated the possibility to keep/(re)use Java and • Was very promising and attractive at the end of XX. There

were even speculations to build pure Java framework • Set certain limitation for the software structure and many

conventions, which are a bit cryptic now

• Java is dead

• Python appears to be very attractive and gets more and more fans in LHCb • Appears to be well consistent with C++ code due to easy

coexistence of C++ and python

• Now: C++, Python and a little bit of pure C


Vanya BELYAEV 4

The concept

• Different applications:• Simulation• Digitization • Reconstruction • Physics Analysis • Event Display

• One common framework has many advantages:• Share the common work, define proper common

conventions and rules, reuse the experience, lines and all goodies form your colleagues, avoid duplication of lines and bugs

• Shorten the learning curve


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Many reusable components

• Detector/Material Description:• Simulation, Reconstruction, Event Display

• Particle Description/Particle Properties• Simulation, Analysis, Event Display

• Magnetic field description• Simulation, Reconstruction and analysis

•More Basic stuff, like statistical analysis, Histograms, N-tuples, Counters, Printout,…

•Many purely technical, but important stuff, like profiling, configuration, …


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LHCb major applications


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Simulation: Gauss

• Two major phases• Event generation:

• Event production• Pythia

• Weak decays• EvtGen

• Options: Hijing, Herwig(++), Sherpa, Alpgen, HiddenValley, BcVegPy

• Detector simulation: • “GiGa” • Geant4 toolkit


Vanya BELYAEV 8

Gauss (ii)

• We do not have any concrete C++ lines for Gauss• except HPD Quantum efficiency

• Automatic conversion of Geometry• The most painful part of Geant4 is eliminated

• “The physics” is specified through configuration • Difficult but much easier than C++

• Input: none or “world wide standard format”• At least one theoretician knows it

• Output:• Generator Particles + vertices • Monte Carlo Particles and Vertices and Hits

• All above plus almost all secondaries from interactions• Smart algorithm for selection (need time to describe)…


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Digitization: Boole

• Again two phases:• Convert Monte Carlo hits into “Digits”

• with few possible next steps, e.g. to “Clusters”• The concept if detector-dependent

• Emulate the raw data from detector (TELL1 boards), the input to Event Filter Farm

• “Raw Bank”

• For some detectors (VELO) this format is VERY advanced. It is not the individual strips, it is already the clusters..

• For some detectors is it just a Digits…• zero-suppressed or not..

• The output: Raw-tapes with Raw-banks


0110100111011010100010101010110100B00le

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Reconstruction: Brunel

• Reconstruction: the phases are implicit and only partly ordered• There are also some “formal” phases, interesting

only from pure computing point of view, thus out of discussion today

• Unpacking input data from Raw Bank• Perform 0-suppression, if needed

• The first pass of reconstruction, tracks-independent

• Reconstruct the tracks

• The second pass: track dependent actions

• Output: Various kind DST tapes: DST and rDST with tracks, proto-particles and some additional PID info.


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Analysis: DaVinci

•Make a physics analysis

• The natural phases:• Create Particles from Proto-Particles • Make the analysis itself…

• Essentially the collection of various tools (e.g. vertex fit, mass-vertex fit, lifetime fit, etc)

• Output: Histograms, N-Tuples, Event Tag collections, (nano,micro,mini,reduced,full)DSTs, …


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Trigger: Moore

• Trigger reconstruction:• Runs both online and offline• Special version of reconstruction:

• Partial• Induced by the L0 information• Essentially no or greatly reduced PID

• Still not clear now

• HLT selections:• Simplified version with loose cuts of

algorithms for “the final” event selection


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Event Display: Panoramix

• Event Display (and a bit more)

• Visualization of • Detector Data • Event Data:

• Particles, Vertices, hits, digits, clusters, links to Monte Carlo truth

• Statistical Data + Statistical Analysis

• Initially GUI

•Many scripting abilities (command line)• … , Python, …


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Python is cool!

• Python converts Panoramix into almost universal interactive environment• Interactivity• Data Access & Inspection• Use of underlying C++ tools and algorithms• The great flexibility• Easy to start • Many enthusiasts

• Appears to be very friendly and useful


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Bender

• Interactive Python-based physics analysis environments

• Combines Python + LoKi:• Nice semantics and interactivity• Ideal for

• Prototyping• Supervising


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LoKi

• Toolkit for easy and user-friendly physics analysis• Try to hide the technicalities • Concentrate on physics needs

• Make the perfect match between physics algorithm and C++

• 1 page of cuts description -> 1 page of pseudocode• 1 idiom corresponds to O(1) line of code

• The actual base for new trigger implementation • Generic part “HLT alleys” • Exclusive part

• Many features appear initially in LoKi and then migrate to other projects: Gaudi, Tracking, Trigger, DaVinci, …• And the process continues


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Other applications

• ONLINE, EULER, ORWELL, VETRA, Alignment, …

• ALL of them (except Bender & Panoramix) are just preconfigured Gaudi application• The same executable for all applications• Everything is loaded dynamically (and often

only on-demand)

• One can combine all application in one go (if needed)


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Gaudi

• Framework Definition • An architectural pattern that codifies a particular

domain. It provides the suitable knobs, slots and tabs that permit clients to use and adapt to specific applications within a given range of behavior.

• In practice• A skeleton of an application into which developers

plug in their code and provides most of the common functionality.


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Framework benefits

• Common vocabulary, better specifications of what needs to be done, better understanding of the system.

• Low coupling between concurrent developments. Smooth integration. Organization of the development.

• Robustness, resilient to change (change-tolerant).

• Fostering code re-use


Vanya BELYAEV 20

Gaudi

• GAUDI is an architecture and framework for event-processing applications (simulation, reconstruction, etc.)• Initially developed for LHCb, it has been adopted and

extended by ATLAS and adopted by several other experiments including GLAST and HARP

• Main Design Choices• Separation between “data” and “algorithms”• Three basic categories of “data”: event data, detector data,

statistical data• Separation between “transient” and “persistent”

representations of data• Data store-centered (“blackboard”) architectural style• “User code” encapsulated in few specific places• Well defined component “interfaces”


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How it works


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And stop here…

• Here I prefer to stop for today.

• The next possible steps/options:• The basic Gaudi tutorial

• with optional hands-on session

• Analysis tutorials:• The basic DaVinci tutorial • The basic LoKi tutorial • The basic Bender (GaudiPython) tutorial

• All of them with optional hands-on session• How to proceed?• Who needs them?


lhcb software vanya belyaev vanya belyaev. preface it is not a tutorial for beginners it is not a...

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