Journal article

GigaFRoST: the gigabit fast readout system for tomography.

  • Mokso R Swiss Light Source, Paul Scherrer Institute, Villigen, Switzerland.
  • Schlepütz CM Swiss Light Source, Paul Scherrer Institute, Villigen, Switzerland.
  • Theidel G Electronics for Measuring Systems, Paul Scherrer Institute, Villigen, Switzerland.
  • Billich H Information Technology Division, Paul Scherrer Institute, Villigen, Switzerland.
  • Schmid E Electronics for Measuring Systems, Paul Scherrer Institute, Villigen, Switzerland.
  • Celcer T Controls Section, GFA, Paul Scherrer Institute, Villigen, Switzerland.
  • Mikuljan G Swiss Light Source, Paul Scherrer Institute, Villigen, Switzerland.
  • Sala L Information Technology Division, Paul Scherrer Institute, Villigen, Switzerland.
  • Marone F Swiss Light Source, Paul Scherrer Institute, Villigen, Switzerland.
  • Schlumpf N Electronics for Measuring Systems, Paul Scherrer Institute, Villigen, Switzerland.
  • Stampanoni M Swiss Light Source, Paul Scherrer Institute, Villigen, Switzerland.
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  • 2017-11-02
Published in:
  • Journal of synchrotron radiation. - 2017
English Owing to recent developments in CMOS technology, it is now possible to exploit tomographic microscopy at third-generation synchrotron facilities with unprecedented speeds. Despite this rapid technical progress, one crucial limitation for the investigation of realistic dynamic systems has remained: a generally short total acquisition time at high frame rates due to the limited internal memory of available detectors. To address and solve this shortcoming, a new detection and readout system, coined GigaFRoST, has been developed based on a commercial CMOS sensor, acquiring and streaming data continuously at 7.7 GB s-1 directly to a dedicated backend server. This architecture allows for dynamic data pre-processing as well as data reduction, an increasingly indispensable step considering the vast amounts of data acquired in typical fast tomographic experiments at synchrotron beamlines (up to several tens of TByte per day of raw data).
Language
  • English
Open access status
hybrid
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https://sonar.ch/global/documents/899
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