Advertisement

Using of FPGA Coprocessor for Improving the Execution Speed of the Pattern Recognition Algorithm for ATLAS – High Energy Physics Experiment

  • Christian Hinkelbein
  • Andrei Khomich
  • Andreas Kugel
  • Reinhard Männer
  • Matthias Müller
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3203)

Abstract

Pattern recognition algorithms are used in experimental High Energy physics for getting parameters (features) of particles tracks in detectors. It is particularly important to have fast algorithms in trigger system. This paper investigates the suitability of using FPGA coprocessor for speedup of the TRT-LUT algorithm – one of the feature extraction algorithms for second level trigger for ATLAS experiment (CERN). Two realization of the same algorithm have been compared: C++ realization tested on a computer equipped with dual Xeon 2.4 GHz CPU, 64-bit, 66 MHz PCI bus, 1024 Mb DDR RAM main memories with Red Hat Linux 7.1 and hybrid C++ – VHDL realisation tested on same PC equipped in addition by MPRACE board (FPGA-Coprocessor board based on Xilinx Virtex-II FPGA and made as 64-bit, 66 MHz PCI card developed at the University of Mannheim). Usage of the FPGA coprocessor can give some reasonable speedup in contrast to general purpose processor only for those algorithms (or parts of algorithms), for which there is a possibility to fulfil calculations with a major degree of parallelism. In case of TRT-LUT algorithm it is the most time consuming parts and using of FPGA coprocessor can give us speed-up by factor more then two for hybrid FPGA/CPU realisation in comparison with CPU only implementation.

Keywords

Execution Speed FPGA Implementation Pattern Recognition Algorithm Feature Extraction Algorithm General Purpose Processor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    ATLAS Collaboration: ATLAS technical proposal. CERN/LHCC 94-13, CERN, Geneva (1994) Google Scholar
  2. 2.
    ATLAS Collaboration: ATLAS detector and physics performance TDR. CERN/LHCC 99-14, CERN, Geneva (1999) Google Scholar
  3. 3.
    Kugel, A.: MPRACE, preliminary documentation. CERN intranet, CERN (2002), http://akugel.home.cern.ch/akugel/mpRace/
  4. 4.
    ATLAS Inner Detector Community: ATLAS Inner Detector Technical Design Report. CERN/LHCC 97-16, CERN, Geneva (1997) Google Scholar
  5. 5.
    Clarke, P., Falciano, S., Le, D.P., Lane, J., Abolins, M., Schwick, C., Wickens, F.: Detector and readout specifications, and buffer-RoI relations, for the level-2 studies. ATL-DAQ-99-014, CERN (1999)Google Scholar
  6. 6.
    Hinkelbein, C., Kugel, A., Männer, R., Müller, M., Sessler, M., Singpiel, H., Baines, J., Bock, R., Smizanska, M.: Pattern recognition in the TRT for the ATLAS B-Physics trigger. ATL-DAQ-99-012, CERN (1999) Google Scholar
  7. 7.
    Illingworth, J., Kittler, J.: A survey of the Hough transform. Comput. Vision Graphics, Image Processing 44, 87–116 (1988)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Christian Hinkelbein
    • 1
  • Andrei Khomich
    • 1
  • Andreas Kugel
    • 1
  • Reinhard Männer
    • 1
  • Matthias Müller
    • 1
  1. 1.Institute of Computer Science VUniversity of MannheimMannheimGermany

Personalised recommendations