ICALEPCS2017 - List of Authors (Sala, L.)

Paper	Title	Page
TUCPA06	SwissFEL - Beam Synchronous Data Acquisition - The First Year	276
	S.G. Ebner, H. Brands, B. Kalantari, R. Kapeller, F. Märki, L. Sala, C. Zellweger PSI, Villigen PSI, Switzerland
	The SwissFEL beam-synchronous data-acquisition system is based on several novel concepts and technologies. It is targeted on immediate data availability and online processing and is capable of assembling an overall data view of the whole machine, thanks to its distributed and scalable back-end. Load on data sources is reduced by immediately streaming data as soon as it becomes available. The streaming technology used provides load balancing and fail-over by design. Data channels from various sources can be efficiently aggregated and combined into new data streams for immediate online monitoring, data analysis and processing. The system is dynamically configurable, various acquisition frequencies can be enabled, and data can be kept for a defined time window. All data is available and accessible enabling advanced pattern detection and correlation during acquisition time. Accessing the data in a code-agnostic way is also possible through the same REST API that is used by the web-frontend. We will give an overview of the design and specialities of the system as well as talk about the findings and problems we faced during machine commissioning.
	Slides TUCPA06 [5.107 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2017-TUCPA06
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

SwissFEL - Beam Synchronous Data Acquisition - The First Year

276

S.G. Ebner, H. Brands, B. Kalantari, R. Kapeller, F. Märki, L. Sala, C. Zellweger
PSI, Villigen PSI, Switzerland

The SwissFEL beam-synchronous data-acquisition system is based on several novel concepts and technologies. It is targeted on immediate data availability and online processing and is capable of assembling an overall data view of the whole machine, thanks to its distributed and scalable back-end. Load on data sources is reduced by immediately streaming data as soon as it becomes available. The streaming technology used provides load balancing and fail-over by design. Data channels from various sources can be efficiently aggregated and combined into new data streams for immediate online monitoring, data analysis and processing. The system is dynamically configurable, various acquisition frequencies can be enabled, and data can be kept for a defined time window. All data is available and accessible enabling advanced pattern detection and correlation during acquisition time. Accessing the data in a code-agnostic way is also possible through the same REST API that is used by the web-frontend. We will give an overview of the design and specialities of the system as well as talk about the findings and problems we faced during machine commissioning.

Slides TUCPA06 [5.107 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2017-TUCPA06

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)