Computing Activities for

the Experiment at xxx

JOHAN MESSCHENDORP FOR THE PANDA COLLABORATION

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PANDA, NAMESPACE PROBLEM...?

PANDA PRODUCTION AND DISTRIBUTED ANALYSIS SYSTEM

JOHAN MESSCHENDORP

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ACRONYM DEFINITIONPANDA ANTIPROTON ANNIHILATION AT DARMSTADTPANDA PASSIVE NONDESTRUCTIVE ASSAYPANDA PERFECT ATTENDANCE - NO DAYS ABSENTPANDA PERFORMANCE AND ASSESSMENT (OFSTED)PANDA PERSONNEL AND ADMINISTRATIONPANDA PETRI NET ANALYSIS AND DESIGN ASSISTANTPANDA PREVENT ABUSE AND NEGLECT THROUGH DENTAL AWARENESSPANDA PREVENT AND NEUTRALIZE DRUG ABUSEPANDA PRODUCTION AND DISTRIBUTED ANALYSIS SYSTEMPANDA PROSPECTIVE ASSESSMENT IN NEWBORNS OF DIABETES AUTOIMMUNITYPANDA PROTOCOL FOR THE ASSESSMENT OF NON-VIOLENT DIRECT ACTIONSUBMIT NEW DEFINITION

PANDA-

HTTP://ACRONYMS.THEFREEDICTIONARY.COM

JOHAN MESSCHENDORP

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PANDA, NAMESPACE PROBLEM...?

THE PANDA EXPERIMENTHadron

physics Particle

physics Nuclear

physics Study of the strong force using anti-protons

~450 physicists52 institutions17 countries

Charmonium spectroscopySearch for glueballs & hybridsCharm in-mediumHypernucleiDrell-Yan physicsElectromagnetic form factorsRare decays...

GSI FAIR

JOHAN MESSCHENDORP

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THE COMPUTING CHALLENGES OF PANDA

Technological & Organizational Aspects

•Broad physics program: huge spectrum of software tools

•Broad user community, geographically & physics background

•Compact & modular detector: precision simulations and analysis prior to experiments crucial

•Rates ~107/s; data sizes ~10 PB/yr, computing GSI2k: ...

•Trigger: continuously sampling, real-time feature extraction

•Exps earliest in 2015: future computing technology uncertain!

JOHAN MESSCHENDORP

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We have advantages!

•Moore’s law!•We can use existing software & infrastructures•We can learn from experiences with LHC computing

2015!

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COMPUTING ACTIVITIES IN PANDA

Simulation & Data Analysis

Tools

Detector Design

Physics Benchmarks

Distributed and HP

Computing

•Variety of synergetically coupled computing activities

•Mostly driven by large-scale simulations for detector design and physics benchmark studies

•Activities contributed to •1st PANDA physics book•Approved technical design report (EMC)•Computing Model (soon online!)•Various R&D experiments

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Software Framework

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SOFTWARE FRAMEWORK

The PandaROOT framework

•The computing framework for full simulations & data analyses, third generation

•Under development since end 2006: ~30 developers (ITs, staff, PDs, PhDs)

•Presently 200.000 lines of code, pre-dominantly C++

•“learn along the way” development process, e.g. short-term objectives, early deployment, etc.

Software Framework

JOHAN MESSCHENDORP

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THE PANDAROOT FRAMEWORK

Software Framework

The key features: modular & versatile

•Fully based on FairROOT, inheriting all its (many) features:•Virtual Monte Carlo, e.g. runs with G3,G4, and Fluka•ROOT task mechanism, modular design, dynamic event structure•steering via ROOT macros•event display interface based on EVE•interfaces to Root, Ascii, Oracle database•release management based on subversion•...

•Interfaces to various eventgenerators•EvtGen, DPM, Pluto++, Pythia, UrQMD

•Option: “fast simulation” (detector parametrization), K. Goetzen•Runs and continuously tested on many platforms and compilers

•gcc3.3 - gcc4.3•huge spectrum of Linux flavors, Mac OS X•QA: advanced build & test system (CMake/CTest/Dashboard/RuleChecker)

•Inherits well-tested code from running experiments•Communication platforms: forum, wiki, etc.

JOHAN MESSCHENDORP

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M. Al-TuranyD. BertiniR. KarabowiczI. Koenig (HADES) F. Uhlig

SOFTWARE FOR DATA ANALYSIS

Software development for reconstruction & analysis

•Detector response & reconstruction•full digitization including electronic responses•various reconstruction algorithms

•Track finding & fitting•pattern recognition: Conformal Mapping, Riemann track finder•track following+fitting: GEANE+GenFit

•Particle-type identification•pattern recognition•multi-variate analysis

•Higher-level analysis tools•Rho analysis framework•Vertex and kinematic fitting: KFitter

Data Analysis Tools

JOHAN MESSCHENDORP

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TRACK FINDING & FITTING

Track finding in the central tracker

DPM @ 3.6 GeV/c

10 events

S. Spataro, S. Lange (Giessen)

conformal map NIM A 380 (1996) 583

•Track recognition via Conformal Mapping

•Complementary approach: Riemann track finder (T. Stockmanns, Juelich)

Data Analysis Tools

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TRACK FINDING & FITTING

Data Analysis Tools

Global Tracking

•Based on GEANE track follower:•Calculates average trajectories, transport matrix, and error matrix •...taking into account energy losses, multiple scattering, magnetics fields, etc.•Uses the same geometry as for the simulations (bonus of using VMC)!

•Kalman filter: GenFit - Generic Tracking Framework•Separation of geometric representations from algorithms•Plugin interface for detector specific hits & various track models•Fitting algorithms: Kalman Filter•Implementation C++, generic programming & abstract interfaces & templates•Matrix operations based on ROOT classes

Tosca: J. Luehning (GSI)

JOHAN MESSCHENDORP

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nFit

(C. H

oeppner,

S. N

eube

rt)

TRACK FINDING & FITTING

Global Tracking & Central Detector Design

•Muon response to Micro Vertex Detector and Straw Tube Tracker of the central tracking system of PANDA

energy loss correction at low momenta

Detector Design

Stefano Spataro (Giessen), Christian Hoeppner, Sebastian Neubert (Muenich), Lia Lavezzi, Susanna Constanza (Pavia)

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SOFTWARE FOR DATA ANALYSIS

Particle identification (PID)

•Various detectors with PID capabilities

•Multi-dimensional problem!•many “classes”: pion, kaons, protons, electrons, muons•many PID parameters: p,dE/dx,Θc,EMC shower shapes,...

•Particle ID based on multi-variate analysis•interface TMVA (only 2 classes at the moment)•multilayer perceptron (Babar)•n-dim likelihood estimators (kNN’s)•self-organizing maps (LVQ’s)•combinations of classifiers

Data Analysis Tools

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e p

µ/!

EMC: E/p

Momentum [GeV/c]

EM

C E

Lo

ss / M

om

en

tum

[c]

_ P P

!+ !-

K+ K-

DPM events @ 6 GeV/c

DIRC: Cherenkov Angle

EMC: shower shapes

MVD: dE/dx

MLP: Bertram Kopf, Panda physics book

Mohammad Babai, Vanni Suyam Jothi (KVI), Bertram Kopf (Bochum),Stefano Spataro (Giessen)

DISTRIBUTED & HIGH PERFORMANCE COMPUTING

PandaGRID: a collaborative supercomputer

•Large amount of resources available within the PANDA collaboration: single computers, batch farms, national grids

•Objectives: •collaborative computing infrastructure for job submission and storage•highly transparent & low-threshold for users•compatible with the software developments•possibility to use other Grid infrastructures

Dan Protopopescu!

#com

putersDistributed

and HP Computing

JOHAN MESSCHENDORP

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DISTRIBUTED & HIGH PERFORMANCE COMPUTING

PandaGRID: a collaborative supercomputer

•Middleware: AliEn2 : Alice Environment•lightweight Grid built around OS components•developed by ALICE

•Administration site: Glasgow (Dan Protopopescu)

•Currently: 19 participating sites

•Monitoring via MonaLISA

•Regular data challenges

•PandaROOT applications are running on Grid!

“COMPUTING RESOURCES AT PANDA INSTITUTES PROVIDE THE SKELETON,ALIEN THE FLESH AND BLOOD,

PANDAROOT THE SPIRIT”Paul Buehler (production manager)

Distributed and HP

Computing

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pA simulations, flux distribution for MVD(DrawEveHisto), Tobias Stockmanns (Juelich)

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DISTRIBUTED & HIGH PERFORMANCE COMPUTING

High-Performance Computing (HPC) activities

•GPUs+CUDA: track fitting

•OpenMP/MPI: clusters & multi-core architectures

•PROOF: interactive analysis

•FPGA-based compute node: online feature extraction

General purpose GPU (GSI)

Thursday 14:40, Club A: M. Al-Turany et al.

R&D: track finding for HADES

Distributed and HP

Computing

JOHAN MESSCHENDORP

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COUNTDOWNFPGA Compute Node, Ming Liu (Giessen)

COMPUTING ACTIVITIES FOR THE PANDA EXPERIMENT AT FAIR

•The future PANDA experiment imposes many computing-related challenges

•Preparations are ongoing in the development of a simulations & analysis framework running on various computing environments

•PANDA has the advantage to learn along the way from existing and near-future experiments: Alice, Babar, Belle, Hades, Star

•A large part of the activities are performed in complete synergy with the development of the FairROOT framework (used by CBM, HADES, PANDA, NuSTAR?)

•So far, PANDA initiated many new computing developments which are/will be deployed in other experiments as well

JOHAN MESSCHENDORP

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JOHAN MESSCHENDORP

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Stay tuned!!!