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DOI:10.18429/JACoW-IBIC2016-WEPG07
Title A Heterogeneous FPGA/GPU Architecture for Real-Time Data Analysis and Fast Feedback Systems
Authors
  • M. Vogelgesang, L.E. Ardila Perez, M. Caselle, S.A. Chilingaryan, A. Kopmann, L. Rotapresenter, M. Weber
    KIT, Eggenstein-Leopoldshafen, Germany
Abstract We propose a versatile and modular approach for a real-time data acquisition and evaluation system used for monitoring and feedback control in beam diagnostic and photon science experiments. Our hybrid architecture is based on an FPGA readout card* and a GPU for data processing. To increase throughput, lower latencies and reduce overall system strain, the FPGA write data directly in the GPU. After real-time data analysis the GPU writes back results either directly to the FPGA in case of fast feedback systems or to the CPU host system for storage. Communication and scheduling are handled transparently by our processing framework**. However, users can customize and extend it with their own processing plugins. Although the system is designed for real-time purposes, the modular approach also allows standalone usage for high-speed off-line analysis. We evaluated the performance of our solution measuring both processing times of data analysis algorithms used with beam instrumentation detectors as well as transfer times between FPGA and GPU. The latter suggests throughputs of up to 6.5 GB/s with latencies down to tens of microseconds, thus making it suitable for fast feedback systems.
Footnotes & References * A PCIe DMA Architecture for Multi-Gigabyte Per Second Data Transmission, 10.1109/TNS.2015.2426877
** A Scalable GPU-based Image Processing Framework for On-line Monitoring, 10.1109/HPCC.2012.116
Paper download WEPG07.PDF [0.103 MB / 4 pages]
Poster download WEPG07_POSTER.PDF [17.144 MB]
Conference IBIC2016, Barcelona, Spain
Series International Beam Instrumentation Conference (5th)
Proceedings Link to full IBIC2016 Proccedings
Session Wednesday Poster Session
Date 14-Sep-16   16:00–18:00
Main Classification BPMs and Beam Stability
Keywords GPU, FPGA, monitoring, detector, data-analysis
Publisher JACoW, Geneva, Switzerland
Editors Isidre Costa (ALBA-CELLS, Barcelona, Spain); Ubaldo Iriso (ALBA-CELLS, Barcelona, Spain); Francis Pérez (ALBA-CELLS, Barcelona, Spain); Volker RW Schaa (GSI, Darmstadt, Germany)
ISBN 978-3-95450-177-9
Published February 2017
Copyright
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cc Creative Commons Attribution 3.0