JUNGFRAU detector for brighter x-ray sources: Solutions for IT and data science challenges in macromolecular crystallography
| Autor: | Martin Brückner, Andrej Babic, Meitian Wang, Heinrich Billich, Leonardo Sala, C. Lopez-Cuenca, Aldo Mozzanica, Bernd Schmitt, S. Redford, Filip Leonarski, Oliver Bunk |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Radiation
Computer science Macromolecular crystallography Detector Context (language use) 02 engineering and technology Lossy compression 021001 nanoscience & nanotechnology Condensed Matter Physics Experimental Methodologies 01 natural sciences Data science ARTICLES Workflow Server 0103 physical sciences lcsh:QD901-999 lcsh:Crystallography IBM 010306 general physics 0210 nano-technology Instrumentation Spectroscopy |
| Zdroj: | Structural Dynamics, 7 (1) Structural Dynamics, Vol 7, Iss 1, Pp 014305-014305-13 (2020) Structural Dynamics |
| ISSN: | 2329-7778 |
| Popis: | In this paper, we present a data workflow developed to operate the adJUstiNg Gain detector FoR the Aramis User station (JUNGFRAU) adaptive gain charge integrating pixel-array detectors at macromolecular crystallography beamlines. We summarize current achievements for operating at 9 GB/s data-rate a JUNGFRAU with 4 Mpixel at 1.1 kHz frame-rate and preparations to operate at 46 GB/s data-rate a JUNGFRAU with 10 Mpixel at 2.2 kHz in the future. In this context, we highlight the challenges for computer architecture and how these challenges can be addressed with innovative hardware including IBM POWER9 servers and field-programmable gate arrays. We discuss also data science challenges, showing the effect of rounding and lossy compression schemes on the MX JUNGFRAU detector images. Structural Dynamics, 7 (1) ISSN:2329-7778 |
| Databáze: | OpenAIRE |
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