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GPU Computing in High Energy Physics

10–12 Sept 2014
University of Pisa
Europe/Rome timezone

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Session

GPU in High Level Trigger (1/3)

10 Sept 2014, 09:45
University of Pisa

University of Pisa

<a target="_blank" href=https://www.google.com/maps/place/Dipartimento+di+Fisica/@43.720239,10.407985,17z/data=!3m1!4b1!4m2!3m1!1s0x12d591bb7d8c8ec9:0xbf91ddd442e32978>Polo Fibonacci</a> Largo Bruno Pontecorvo, 3 I-56127 Pisa <em>phone +39 050 2214 327</em>

Conveners

GPU in High Level Trigger (1/3)

  • Ivan Kisel (Goethe University Frankfurt am Main, FIAS Frankfurt Institute for Advanced Studies)

Presentation materials

There are no materials yet.

  1. 10. The GAP Project: GPU applications for high level trigger and medical imaging
    Matteo Bauce (ROMA1)
    10/09/2014, 09:45
    Talk
    The aim of the GAP project is the deployment of Graphic Processing Units (GPU) in real-time applications, ranging from high-energy physics online event selection (trigger) to medical imaging reconstruction. The final goal of the project is to demonstrate that GPUs can have a positive impact in sectors different for rate, bandwidth, and computational intensity. Most crucial aspects currently...
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  2. 1. GPU-based track quasi-real-time track recognition in imaging devices: from raw data to particle tracks
    Cristiano Bozza (SA)
    10/09/2014, 10:15
    Talk
    Nuclear emulsions as tracking devices suitable for high-energy physics experiments have been recently used by CHORUS, DONUT, PEANUT and OPERA. High statistics is accessible by fast automatic microscopes for emulsion readout. Former systems had to do most processing by the CPU; the next generation, entering duty at the present time, is based on GPU’s. Automatic microscopes need real-time 2D...
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  3. 37. GPGPU for track finding and triggering in High Energy Physics
    Lorenzo Rinaldi (BO)
    10/09/2014, 10:45
    Talk
    The LHC experiments are designed to detect large amount of physics events produced with a very high rate. Considering the future upgrades, the data acquisition rate will become even higher and new computing paradigms must be adopted for fast data-processing: General Purpose Graphical Processing Units (GPGPU) can be used in a novel approach based on massive parallel computing. The intense...
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