21โ€“25 May 2012
New York City, NY, USA
US/Eastern timezone

Session

Event Processing

02
21 May 2012, 16:35
New York City, NY, USA

New York City, NY, USA

Conveners

Event Processing

  • Adam Lyon (Fermilab)

Event Processing

  • Axel Naumann (CERN)

Event Processing

  • Adam Lyon (Fermilab)

Event Processing

  • Axel Naumann (CERN)

Event Processing

  • Adam Lyon (Fermilab)

Presentation materials

There are no materials yet.

  1. Dr Christopher Jones (Fermi National Accelerator Lab. (US))
    21/05/2012, 16:35
    Event Processing (track 2)
    Parallel
    Traditionally, HEP experiments exploit the multiple cores in a CPU by having each core process one event. However, future PC designs are expected to use CPUs which double the number of processing cores at the same rate as the cost of memory falls by a factor of two. This effectively means the amount of memory per processing core will remain constant. This is a major challenge for LHC...
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  2. Dr Marc Paterno (Fermilab)
    21/05/2012, 17:00
    Event Processing (track 2)
    Parallel
    Future "Intensity Frontier" experiments at Fermilab are likely to be conducted by smaller collaborations, with fewer scientists, than is the case for recent "Energy Frontier" experiments. *art* is an event-processing framework designed with the needs of such experiments in mind. The authors have been involved with the design and implementation of frameworks for several experiments,...
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  3. Wahid Bhimji (University of Edinburgh (GB))
    21/05/2012, 17:25
    Event Processing (track 2)
    Parallel
    We detail recent changes to ROOT-based I/O within the ATLAS experiment. The ATLAS persistent event data model continues to make considerable use of a ROOT I/O backend through POOL persistency. Also ROOT is used directly in later stages of analysis that make use of a flat-ntuple based "D3PD" data-type. For POOL/ROOT persistent data, several improvements have been made including implementation...
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  4. Peter Van Gemmeren (Argonne National Laboratory (US))
    21/05/2012, 17:50
    Event Processing (track 2)
    Parallel
    A critical component of any multicore/manycore application architecture is the handling of input and output. Even in the simplest of models, design decisions interact both in obvious and in subtle ways with persistence strategies. When multiple workers handle I/O independently using distinct instances of a serial I/O framework, for example, it may happen that because of the way data from...
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  5. Julia Yarba (Fermi National Accelerator Lab. (US))
    22/05/2012, 13:30
    Event Processing (track 2)
    Parallel
    In the past year several improvements in Geant4 hadronic physics code have been made, both for HEP and nuclear physics applications. We discuss the implications of these changes for physics simulation performance and user code. In this context several of the most-used codes will be covered briefly. These include the Fritiof (FTF) parton string model which has been extended to...
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  6. Dr Maria Grazia Pia (Universita e INFN (IT))
    22/05/2012, 13:55
    Event Processing (track 2)
    Parallel
    Quantitative results on Geant4 physics validation and computational performance are reported: they cover a wide spectrum of electromagnetic and hadronic processes, and are the product of a systematic, multi-disciplinary effort of collaborating physicists, nuclear engineers and statisticians. They involve comparisons with established experimental references in the literature and ad hoc...
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  7. Marco Cattaneo (CERN)
    22/05/2012, 14:20
    Event Processing (track 2)
    Parallel
    The LHCb experiment is a spectrometer dedicated to the study of heavy flavor at the LHC. The rate of proton-proton collisions at the LHC is 15 MHz, but disk space limitations mean that only 3 kHz can be written to tape for offline processing. For this reason the LHCb data acquisition system -- trigger -- plays a key role in selecting signal events and rejecting background. Because the trigger...
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  8. Gordon Watts (University of Washington (US))
    22/05/2012, 14:45
    Event Processing (track 2)
    Parallel
    Modern HEP analysis requires multiple passes over large datasets. For example, one has to first reweight the jet energy spectrum in Monte Carlo to match data before you can make plots of any other jet related variable. This requires a pass over the Monte Carlo and the Data to derive the reweighting, and then another pass over the Monte Carlo to plot the variables you are really interested in....
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  9. Marco Corvo (CNRS)
    22/05/2012, 17:00
    Event Processing (track 2)
    Parallel
    The SuperB asymmetric energy e+e- collider and detector to be built at the newly founded Nicola Cabibbo Lab will provide a uniquely sensitive probe of New Physics in the flavor sector of the Standard Model. Studying minute effects in the heavy quark and heavy lepton sectors requires a data sample of 75 ab-1 and a luminosity target of 10^36 cm-2 s-1. These parameters require a substantial...
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  10. Dr florian Uhlig (GSI)
    22/05/2012, 17:25
    Event Processing (track 2)
    Parallel
    The FairRoot framework is an object oriented simulation, reconstruction and data analysis framework based on ROOT. It includes core services for detector simulation and offline analysis. The project started as a software framework for the CBM experiment at GSI, and later became the standard software for simulation, reconstruction and analysis for CBM, PANDA, R3B and ASYEOS at GSI/FAIR, as...
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  11. Stefano Spataro (University of Turin)
    22/05/2012, 17:50
    Event Processing (track 2)
    Parallel
    The PANDA experiment will study the collisions of beams of anti-protons, with momenta ranging from 2-15 GeV/c, with fixed proton and nuclear targets in the charm energy range, and will be built at the FAIR facility. In preparation for the experiment, the PandaRoot software framework is under development for detector simulation, reconstruction and data analysis, running on an Alien2-based grid....
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  12. Mr Igor Kulakov (Goethe Universitaet Frankfurt)
    24/05/2012, 13:30
    Event Processing (track 2)
    Parallel
    Modern heavy-ion experiments operate with very high data rates and track multiplicities. Because of time constraints the speed of the reconstruction algorithms is crucial both for the online and offline data analysis. Parallel programming is considered nowadays as one of the most efficient ways to increase the speed of event reconstruction. Reconstruction of short-lived particles is one of...
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  13. Johannes Rauch (Technische Universitรคt Mรผnchen)
    24/05/2012, 13:55
    Event Processing (track 2)
    Parallel
    A pattern recognition software for a continuously operating high rate Time Projection Chamber with Gas Electron Multiplier amplification (GEM-TPC) has been designed and tested. A track-independent clustering algorithm delivers space points. A true 3-dimensional track follower combines them to helical tracks, without constraints on the vertex position. Fast helix fits, based on a conformal...
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  14. Mr Federico Carminati (CERN)
    24/05/2012, 14:20
    Event Processing (track 2)
    Parallel
    Detector simulation is one of the most CPU intensive tasks in modern High Energy Physics. While its importance for the design of the detector and the estimation of the efficiency is ever increasing, the amount of events that can be simulated is often constrained by the available computing resources. Various kind of "fast simulations" have been developed to alleviate this problem, however,...
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  15. Stephan G. Hageboeck (University of Bonn)
    24/05/2012, 14:45
    Event Processing (track 2)
    Parallel
    Three dimensional image reconstruction in medical imaging applies sophisticated filter algorithms to linear trajectories of coincident photon pairs in PET. The goal is to reconstruct an image of a source density distribution. In a similar manner, tracks in particle physics originate from vertices that need to be distinguished from background track combinations. We investigate if methods from...
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  16. Jakob Lettenbichler (HEPHY Vienna, Austria), Mr Moritz Nadler (Austrian Academy of Sciences (AT)), Rudolf Fruhwirth (Austrian Academy of Sciences (AT))
    24/05/2012, 15:10
    Event Processing (track 2)
    Parallel
    The Silicon Vertex Detector (SVD) of the Belle II experiment is a newly developed device with four measurement layers. The detector is designed to enable track reconstruction down to the lowest momenta possible, in order to significantly increase the effective data sample and the physics potential of the experiment. Both track finding and track fitting have to deal with these...
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  17. Gerben Stavenga (Fermilab)
    24/05/2012, 16:35
    Event Processing (track 2)
    Parallel
    We present a GPU-based parton level event generator for multi-jet events at the LHC. ย The current implementation generates up to 10 jets with a possible vector boson.ย  At leading order the speed increase over a single core CPU is in excess of a factor of 500 using ย a single desktop based NVIDIA Fermi GPU. ย  We will also present results for the next-to-leading order implementation.
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  18. Mr Heath Skarlupka (UW Madison)
    24/05/2012, 17:00
    Event Processing (track 2)
    Parallel
    GPGPU computing offers extraordinary increases in pure processing power for parallelizable applications. In IceCube we use GPUs for ray-tracing of cherenkov photons in the antarctic ice as part of detector simulation. We report on how we implemented the mixed simulation production chain to include the processing on the GPGPU cluster for the IceCube Monte-Carlo production. We also present ideas...
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  19. Dr Mohammad Al-Turany (GSI)
    24/05/2012, 17:25
    Event Processing (track 2)
    Parallel
    The high data rates expected from the planned detectors at FAIR (CBM, PANDA) call for dedicated attention with respect to the computing power needed in online (e.g. High level event selection) and offline analysis. The graphics processor units (GPUs) have evolved into high performance co-processors that can be easily programmed with common high-level language such as C, Fortran and C++. Todays...
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  20. Andrew John Washbrook (University of Edinburgh (GB))
    24/05/2012, 17:50
    Event Processing (track 2)
    Parallel
    Multivariate classification methods based on machine learning techniques are commonly used for data analysis at the LHC in order to look for signatures of new physics beyond the standard model. A large variety of these classification techniques are contained in the Toolkit for Multivariate Analysis (TMVA) which enables training, testing, performance evaluation and application of the chosen...
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