T. Baumbach, V. Altapova, D. Hänschke, T. dos Santos Rolo, A. Ershov, L. Helfen, T. van de Kamp, J.-T. Reszat, M. Weber, M. Caselle, M. Balzer, S. Chilingaryan, A. Kopmann, I. Dalinger, A. Myagotin, V. Asadchikov, A. Buzmakov, S. Tsapko, I. Tsapko, V. Vichugov, M. Sukhodoev, UFO collaboration
Final report, BMBF Programme: “Development and Use of Accelerator-Based Photon Sources”, 2016
Recent progress in X-ray optics, detector technology, and the tremendous increase of processing speed of commodity computational architectures gave rise to a paradigm shift in synchrotron X-ray imaging. In order to explore these technologies within the two UFO projects the UFO experimental station for ultra-fast X-ray imaging has been developed. Key components, an intelligent detector system, vast computational power, and sophisticated algorithms have been designed, optimized and integrated for best overall performance. New methods like 4D cine-tomography for in-vivo measurements have been established. This online assessment of sample dynamics not only made active image-based control possible, but also resulted in unprecedented image quality and largely increased throughput. Typically 400-500 high-quality datasets with 3D images and image sequences are recorded with the UFO experimental station during a beam time of about 3-4 days.
A flexible and fully automated sample environment and a detector system for a set of up to three complementary cameras has been realized. It can be equipped with commercial available scientific visible-light cameras or a custom UFO camera. To support academic sensor development a novel platform for scientific cameras, the UFO camera framework, has been developed. It is a unique rapid-prototyping environment to turn scientific image sensors into intelligent smart camera systems. All beamline components, sample environment, detector station and the computing infrastructure are seamlessly integrates into the high-level control system “Concert” designed for online data evaluation and feedback control.
As a new element computing nodes for online data assessment have been introduced in UFO. A powerful computing infrastructure based on GPUs and real-time storage has been developed. Optimized reconstruction algorithms reach a throughput of several GB/s with a single GPU server. For scalability also clusters are supported. Highly optimized reconstruction and image processing algorithms are key for real-time monitoring and efficient data analysis. In order to manage these algorithms the UFO parallel computing framework has been designed. It supports the implementation of efficient algorithms as well as the development of data processing workflows based on these. The library of optimized algorithms supports all modalities of operation at the UFO experimental station: tomography laminography and diffraction imaging as well as numerous pre- and post-processing steps.
The results of the UFO project have been reported at several national and international workshops and conferences. The UFO project contributes with developments like the UFO- camera framework or its GPU computing environment to other hard- and software projects in the synchrotron community (e.g. Tango Control System, High Data Rate Processing and Analysis Initiative, Nexus data format, Helmholtz Detector Technology and Systems Initiative DTS). Further follow-up projects base on the UFO results and improve imaging methods (like STROBOS-CODE) or add sophisticated analysis environments (like ASTOR).
The UFO project has successfully developed key components for ultra-fast X-ray imaging and serves as an example for future data intense applications. It demonstrates KIT’s role as technology center for novel synchrotron instrumentation.