Next-Generation Information Technology Systems for Fast Detectors in Electron Microscop

March 25, 2020 Β· Declared Dead Β· πŸ› Handbook on Big Data and Machine Learning in the Physical Sciences

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Authors Dieter Weber, Alexander Clausen, Rafal E. Dunin-Borkowski arXiv ID 2003.11332 Category cs.DC: Distributed Computing Cross-listed cond-mat.mtrl-sci, cs.PF, physics.ins-det Citations 4 Venue Handbook on Big Data and Machine Learning in the Physical Sciences Last Checked 4 months ago
Abstract
The Gatan K2 IS direct electron detector (Gatan Inc., 2018), which was introduced in 2014, marked a watershed moment in the development of cameras for transmission electron microscopy (TEM) (Pan & Czarnik, 2016). Its pixel frequency, i.e. the number of data points (pixels) recorded per second, was two orders of magnitude higher than the fastest cameras available only five years before. Starting from 2009, the data rate of TEM cameras has outpaced the development of network, mass storage and memory bandwidth by almost two orders of magnitude. Consequently, solutions based on personal computers (PCs) that were adequate until then are no longer able to handle the resulting data rates. Instead, tailored high-performance setups are necessary. Similar developments have occurred for advanced X-ray sources such as the European XFEL, requiring special information technology (IT) systems for data handling (Sauter, Hattne, Grosse-Kunstleve, & Echols, 2013) (Fangohr, et al., 2018). Information and detector technology are currently under rapid development and involve disruptive technological innovations. This chapter briefly reviews the technological developments of the past 20 years, presents a snapshot of the current situation at the beginning of 2019 with many practical considerations, and looks forward to future developments.
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