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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},
}