New Python-based methods for data processing

Current pixel‐array detectors produce diffraction images at extreme data rates (of up to 2 TB h−1) that make severe demands on computational resources. New multiprocessing frameworks are required to achieve rapid data analysis, as it is important to be able to inspect the data quickly in order to gu...

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Bibliographic Details
Published in:Acta crystallographica. Section D, Biological crystallography. Vol. 69; no. 7; pp. 1274 - 1282
Main Authors: Sauter, Nicholas K., Hattne, Johan, Grosse-Kunstleve, Ralf W., Echols, Nathaniel
Format: Journal Article
Language:English
Published: 5 Abbey Square, Chester, Cheshire CH1 2HU, England International Union of Crystallography 01.07.2013
Wiley Subscription Services, Inc
Subjects:
Algorithms
cctbx
Coherent light
Computation
Crystallography
Crystallography, X-Ray
Data Interpretation, Statistical
Data processing
Diffraction
Electronic Data Processing - methods
Electrons
Humans
Lasers
Methods
multiprocessing
Multiprocessing (computers)
Muramidase - chemistry
Research Papers
reusable code
Software
Software reviews
Spots
Synchrotrons - instrumentation
XFEL
multiprocessing
cctbx
reusable code
data processing
ISSN:1399-0047, 0907-4449, 1399-0047
Online Access:Get full text
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Summary:Current pixel‐array detectors produce diffraction images at extreme data rates (of up to 2 TB h−1) that make severe demands on computational resources. New multiprocessing frameworks are required to achieve rapid data analysis, as it is important to be able to inspect the data quickly in order to guide the experiment in real time. By utilizing readily available web‐serving tools that interact with the Python scripting language, it was possible to implement a high‐throughput Bragg‐spot analyzer (cctbx.spotfinder) that is presently in use at numerous synchrotron‐radiation beamlines. Similarly, Python interoperability enabled the production of a new data‐reduction package (cctbx.xfel) for serial femtosecond crystallography experiments at the Linac Coherent Light Source (LCLS). Future data‐reduction efforts will need to focus on specialized problems such as the treatment of diffraction spots on interleaved lattices arising from multi‐crystal specimens. In these challenging cases, accurate modeling of close‐lying Bragg spots could benefit from the high‐performance computing capabilities of graphics‐processing units.
Bibliography:istex:782600E8CDC63E7DF7B3798A13EE4E121CF04F38
ark:/67375/WNG-L3LF2V52-9
ArticleID:AYDBA5193
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USDOE Office of Science (SC)
AC02-76SF00515
SLAC-REPRINT-2014-078
ISSN:1399-0047
0907-4449
1399-0047
DOI:10.1107/S0907444913000863