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https://doi.org/10.18429/JACoW-ICALEPCS2017-TUPHA091
Title A Reliable White Rabbit Network for the FAIR General Timing Machine
Authors
  • C. Prados, J.N. Bai, A. Hahn
    GSI, Darmstadt, Germany
  • A. Suresh. Suresh
    Hochschule Darmstadt, University of Applied Science, Darmstadt, Germany
Abstract A new timing system based on White Rabbit (WR) is being developed for the upcoming FAIR facility at GSI in collaboration with CERN and other partners. The General Timing Machine (GTM) is responsible for the synchronization of nodes and distribution of timing events, which allows the real-time control of the accelerator equipment. WR is a time-deterministic, low latency Ethernet-based network for general data transfer and sub-ns time and frequency distribution. The FAIR WR network is considered operational only if it provides deterministic and resilient data delivery and reliable time distribution. In order to achieve this level of service, methods and techniques to increase the reliability of the GTM and WR network has been studied and evaluated. Besides, GSI has developed a network monitoring and logging system to measure the performance and detect failures of the WR network. Finally, we describe the continuous integration system at GSI and how it has improve the overall reliability of the GTM.
Paper download TUPHA091.PDF [0.368 MB / 6 pages]
Poster download TUPHA091_POSTER.PDF [0.630 MB]
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Conference ICALEPCS2017, Barcelona, Spain
Series International Conference on Accelerator and Large Experimental Control Systems (16th)
Proceedings Link to full ICALEPCS2017 Proccedings
Session Poster Session
Date 10-Oct-17   16:45–19:00
Main Classification Timing and Synchronization
Keywords ion, network, timing, Ethernet, monitoring
Publisher JACoW, Geneva, Switzerland
Editors Volker RW Schaa (GSI, Darmstadt, Germany); Isidre Costa (ALBA-CELLS, Cerdanyola del Vallès, Spain); David Fernández (ALBA-CELLS, Cerdanyola del Vallès, Spain); Óscar Matilla (ALBA-CELLS, Cerdanyola del Vallès, Spain)
ISBN 978-3-95450-193-9
Published January 2018
Copyright
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cc Creative Commons Attribution 3.0