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@ARTICLE{Adinets:279938,
      author       = {Adinets, Andrey and Herten, Andreas and Kraus, Jiri and
                      Mertens, Marius C. and Pleiter, Dirk and Stockmanns, Tobias
                      and Wintz, Peter},
      title        = {{T}riplet {F}inder: {O}n the way to triggerless online
                      reconstruction with {GPU}s for the
                      $\overline{\mathrm{{P}}}\mathrm{{ANDA}}$ experiment},
      journal      = {Journal of computational science},
      volume       = {10},
      issn         = {1877-7503},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier},
      reportid     = {FZJ-2015-07811},
      pages        = {317 - 326},
      year         = {2015},
      abstract     = {PANDA is a state-of-the-art hadron physics experiment
                      currently under construction at FAIR, Darmstadt. In order to
                      select events for offline analysis, PANDA will use a
                      software-based triggerless online reconstruction, performed
                      with a data rate of 200 GB/s.To process the raw data rate of
                      the detector in realtime, we design and implement a GPU
                      version of the Triplet Finder, a fast and robust first-stage
                      tracking algorithm able to reconstruct tracks with good
                      quality, specially designed for the Straw Tube Tracker
                      sub-detector of PANDA. We reduce the algorithmic complexity
                      of processing many hits together by splitting them into
                      bunches, which can be processed independently. We evaluate
                      different ways of processing bunches, GPU dynamic
                      parallelism being one of them. We also propose an optimized
                      technique for associating hits with reconstructed track
                      candidates.The evaluation of our GPU implementation
                      demonstrates that the Triplet Finder can process almost 6
                      Mhits/s on a single K20X GPU, making it a promising
                      algorithm for the online event filtering scheme of PANDA.},
      cin          = {JSC},
      ddc          = {004},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {513 - Supercomputer Facility (POF3-513)},
      pid          = {G:(DE-HGF)POF3-513},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000362134900034},
      doi          = {10.1016/j.jocs.2015.03.010},
      url          = {https://juser.fz-juelich.de/record/279938},
}