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@ARTICLE{White:600990,
      author       = {White, Thomas and Schoof, Tim and Yakubov, Sergey and
                      Tolstikova, Aleksandra and Middendorf, Philipp and
                      Karnevskiy, Mikhail and Mariani, Valerio and Henkel,
                      Alessandra and Klopprogge, Bjarne and Hannappel, Juergen and
                      Oberthür, Dominik and De Gennaro Aquino, Ivan and Egorov,
                      Dmitry and Munke, Anna Carina and Sprenger, Janina and
                      Pompidor, Guillaume and Taberman, Helena and Gruzinov,
                      Andrey and Meyer, Jan and Hakanpaeae, Johanna and Gasthuber,
                      Martin},
      title        = {{R}eal-time data processing for serial crystallography
                      experiments},
      journal      = {IUCrJ},
      volume       = {12},
      number       = {1},
      issn         = {2052-2525},
      address      = {Chester},
      publisher    = {[Verlag nicht ermittelbar]},
      reportid     = {PUBDB-2024-00039},
      pages        = {97-108},
      year         = {2024},
      abstract     = {We report the use of streaming data interfaces to perform
                      fully on-line data processing for serial crystallography
                      experiments, without storing intermediate data on disk. The
                      system produces Bragg reflection intensity measurements
                      suitable for scaling and merging, with a latency of less
                      than one second per frame.Our system uses the CrystFEL
                      software in combination with the ASAP::O data framework. In
                      a series of user experiments at PETRA III, frames from a 16
                      megapixel Dectris EIGER2 X detector were searched for peaks,
                      indexed and integrated at the maximum full-frame readout
                      speed of 133 frames per second. The computational resources
                      required depend on various factors, most significantly the
                      fraction of non-blank frames (“hits”). The average
                      single-thread processing time per frame was 242 ms for blank
                      frames and 455 ms for hits, meaning that a single 96-core
                      computing node was sufficient to keep up with the data with
                      ample headroom for unexpected throughput reductions. Further
                      significant improvements are expected, for example by
                      binning pixel intensities together to reduce the pixel
                      count. We discuss the implications of real-time data
                      processing on the “data deluge” problem from recent and
                      future photon science experiments, in particular on
                      calibration requirements, computing access patterns and the
                      need for preservation of raw data.},
      cin          = {FS-SC / IT / CFEL-I / FS-PETRA-D},
      ddc          = {530},
      cid          = {I:(DE-H253)FS-SC-20210408 / I:(DE-H253)IT-20120731 /
                      I:(DE-H253)CFEL-I-20161114 / I:(DE-H253)FS-PETRA-D-20210408},
      pnm          = {623 - Data Management and Analysis (POF4-623) / 6G9 - IDAF
                      (DESY) (POF4-6G9) / 6G3 - PETRA III (DESY) (POF4-6G3) /
                      ExPaNDS - EOSC Photon and Neutron Data Services (857641)},
      pid          = {G:(DE-HGF)POF4-623 / G:(DE-HGF)POF4-6G9 /
                      G:(DE-HGF)POF4-6G3 / G:(EU-Grant)857641},
      experiment   = {EXP:(DE-H253)P-P11-20150101},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {39714221},
      UT           = {WOS:001395741400012},
      doi          = {10.1107/S2052252524011837},
      url          = {https://bib-pubdb1.desy.de/record/600990},
}