ICALEPCS2023 - List of Keywords (SRF)

Paper	Title	Other Keywords	Page
MO2AO01	Facing the Challenges of Experiment Control and Data Management at ESRF-EBS	experiment, data-acquisition, GUI, framework	66
	J.M. Meyer, W. De Nolf, S. Debionne, S. Fisher, A. Götz, M. Guijarro, P. Guillou, A. Homs Puron, V. Valls ESRF, Grenoble, France
	In 2020 the new ESRF-EBS (Extremely Brilliant Source) took-up operation. With the much higher photon flux, experiments are faster and produce more data. To meet the challenges, a complete revision of data acquisition, management and analysis tools was undertaken. The result is a suite of advanced software tools, deployed today on more than 30 beamlines. The main packages are BLISS for experiment control and data acquisition, LIMA2 for high-speed detector control, EWOKS for data reduction and analysis workflows, and Daiquiri the web GUI framework. BLISS is programmed in Python, to allow easy sequence programming for scientists and easy integration of scientific software. BLISS offers: Configuration of hardware and experimental set-ups, a generic scanning engine for step-based and continuous data acquisition, live data display, frameworks to handle 1D and 2D detectors, spectrometers, monochromators, diffractometers (HKL) and regulation loops. For detectors producing very high data rates, data reduction at the source is important. LIMA2 allows parallel data processing to add the necessary computing power (CPU and GPU) for online data reduction in a flexible way. The EWOKS workflow system can use online or offline data to automate data reduction or analysis. Workflows can run locally or on a compute cluster, using CPUs or GPUs. Results are saved or fed back to the control system for display or to adapt the next data acquisition.
	Slides MO2AO01 [2.766 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-MO2AO01
About •	Received ※ 03 October 2023 — Revised ※ 07 October 2023 — Accepted ※ 12 October 2023 — Issued ※ 29 October 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUMBCMO14	Initial Test of a Machine Learning Based SRF Cavity Active Resonance Control	cavity, controls, resonance, simulation	379
	F.Y. Wang, J. Cruz SLAC, Menlo Park, California, USA
	We’ll introduce a high precision active motion controller based on machine learning (ML) technology and electric piezo actuator. The controller will be used for SRF cavity active resonance control, where a data-driven model for system motion dynamics will be developed first, and a model predictive controller (MPC) will be built accordingly. Simulation results as well as initial test results with real SRF cavities will be presented in the paper.
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUMBCMO14
About •	Received ※ 03 October 2023 — Revised ※ 14 November 2023 — Accepted ※ 27 November 2023 — Issued ※ 09 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

WE3BCO07	Extending the ICAT Metadata Catalogue to New Scientific Use Cases	experiment, site, synchrotron, interface	1033
	A. Götz, M. Bodin, A. De Maria Antolinos, M. Gaonach ESRF, Grenoble, France M. AlMohammad, S.A. Matalgah SESAME, Allan, Jordan P. Austin, V. Bozhinov, L.E. Davies, A. Gonzalez Beltran, K.S. Phipps STFC/RAL/SCD, Didcot, United Kingdom R. Cabezas Quirós ALBA-CELLS, Cerdanyola del Vallès, Spain R. Krahl HZB, Berlin, Germany A. Pinto LNLS, Campinas, Brazil K. Syder DLS, Oxfordshire, United Kingdom
	The ICAT metadata catalogue is a flexible solution for managing scientific metadata and data from a wide variety of domains following the FAIR data principles. This paper will present an update of recent developments of the ICAT metadata catalogue and the latest status of the ICAT collaboration. ICAT was originally developed by UK Science and Technology Facilities Council (STFC) to manage the scientific data of ISIS Neutron and Muon Source and Diamond Light Source. They have since been joined by a number of other institutes including ESRF, HZB, SESAME, and ALBA who together now form the ICAT Collaboration [1]. ICAT has been used to manage petabytes of scientific data for ISIS, DLS, ESRF, HZB, and in the future SESAME and ALBA and make these data FAIR. The latest version of the ICAT core as well as the new user interfaces, DataGateway and DataHub, and extensions to ICAT for implementing free text searching, a common search interface across Photon and Neutron catalogues, a protocol-based interface that allows making the metadata available for findability, electronic logbooks, sample tracking, and web-based data and domain specific viewers developed by the community will be presented. Finally recent developments to use ICAT to develop applications for processed data with rich metadata in the fields of small angle scattering, macromolecular crystallography and cryo-electron microscopy will be described. [1] https://icatproject.org
	Slides WE3BCO07 [7.888 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-WE3BCO07
About •	Received ※ 05 October 2023 — Revised ※ 23 October 2023 — Accepted ※ 14 December 2023 — Issued ※ 14 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THMBCMO31	LImA2: Edge Distributed Acquisition and Processing Framework for High Performance 2D Detectors	detector, controls, GPU, experiment	1269
	S. Debionne, L. Claustre, P. Fajardo, A. Götz, A. Homs Puron, J. Kieffer, R. Ponsard ESRF, Grenoble, France
	LImA* is a framework born at the ESRF for 2D Data Acquisition (DAQ), basic Online Data Analysis (ODA) and processing with high-throughput detectors. While in production for 15 years in several synchrotron facilities, the ever-increasing detector frame rates make more and more difficult performing DAQ & ODA tasks on a single computer. LImA2 is designed to scale horizontally, using multiple hosts for DAQ & ODA. This enables more advanced strategies for data feature extraction while keeping a low latency. LImA2 separates three functional blocks: detector control, image acquisition, and data processing. A control process configures the detector, while one or more receiver processes perform the DAQ and ODA, like the generation of fast feedback signals. The detectors currently supported in LImA2 are the PSI/Jungfrau, the ESRF/Smartpix and the Dectris/Eiger2. The former performs pixel assembly and intensity correction in GPU; the second exploits RoCE capabilities; and the latter features dual threshold, multi-band images. Raw data rates up to 8 GByte/s can be handled by a single computer, scalable if necessary. In addition to a classic processing, advanced pipelines are also implemented. A Serial-MX/pyFAI* pipeline extracts diffraction peaks in GPU in order to filter low quality data. NVIDIA GPUDirect is used by a third pipeline providing 2D processing with remarkable low latency. IBM Power9 optimizations like the NX GZIP compression and the PCI-e multi-host extension are exploited. * LIMA - https://accelconf.web.cern.ch/ICALEPCS2013/papers/frcoaab08.pdf Jungfraujoch - https://doi.org/10.1107/S1600577522010268 * pyFAI - https://doi.org/10.1107/S1600576715004306
	Slides THMBCMO31 [0.572 MB]
	Poster THMBCMO31 [14.959 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THMBCMO31
About •	Received ※ 06 October 2023 — Revised ※ 08 October 2023 — Accepted ※ 11 December 2023 — Issued ※ 13 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THPDP010	Update on the EBS Storage Ring Beam Dynamics Digital Twin	controls, optics, storage-ring, TANGO	1306
	S.M. Liuzzo, N. Carmignani, L.R. Carver, L. Hoummi, N. Leclercq, T.P. Perron, J.L. Pons, S.M. White ESRF, Grenoble, France
	The EBS storage ring control system is presently paired with an electron beam dynamics digital twin (the EBS control system simulator, EBSS). The EBSS reproduces many of the beam dynamics related quantities relevant for machine operation. This digital twin is used for the preparation and debug of software to deploy for operation. The EBSS is presently working only for the main storage ring and it is not directly connected to the machine operation but works in parallel and on demand. We present here the steps taken towards an on-line continuous use of the EBSS to monitor the evolution of not directly observable parameters such as beam optics. Simone Liuzzo, et al. The ESRF-EBS Simulator: A Commissioning Booster. 18th ICALEPCS, Oct 2021, Shanghai, China. MOPV012
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THPDP010
About •	Received ※ 27 September 2023 — Revised ※ 25 October 2023 — Accepted ※ 10 December 2023 — Issued ※ 16 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Other Keywords

Page

MO2AO01

Facing the Challenges of Experiment Control and Data Management at ESRF-EBS

experiment, data-acquisition, GUI, framework

66

J.M. Meyer, W. De Nolf, S. Debionne, S. Fisher, A. Götz, M. Guijarro, P. Guillou, A. Homs Puron, V. Valls
ESRF, Grenoble, France

In 2020 the new ESRF-EBS (Extremely Brilliant Source) took-up operation. With the much higher photon flux, experiments are faster and produce more data. To meet the challenges, a complete revision of data acquisition, management and analysis tools was undertaken. The result is a suite of advanced software tools, deployed today on more than 30 beamlines. The main packages are BLISS for experiment control and data acquisition, LIMA2 for high-speed detector control, EWOKS for data reduction and analysis workflows, and Daiquiri the web GUI framework. BLISS is programmed in Python, to allow easy sequence programming for scientists and easy integration of scientific software. BLISS offers: Configuration of hardware and experimental set-ups, a generic scanning engine for step-based and continuous data acquisition, live data display, frameworks to handle 1D and 2D detectors, spectrometers, monochromators, diffractometers (HKL) and regulation loops. For detectors producing very high data rates, data reduction at the source is important. LIMA2 allows parallel data processing to add the necessary computing power (CPU and GPU) for online data reduction in a flexible way. The EWOKS workflow system can use online or offline data to automate data reduction or analysis. Workflows can run locally or on a compute cluster, using CPUs or GPUs. Results are saved or fed back to the control system for display or to adapt the next data acquisition.

Slides MO2AO01 [2.766 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-MO2AO01

About •

Received ※ 03 October 2023 — Revised ※ 07 October 2023 — Accepted ※ 12 October 2023 — Issued ※ 29 October 2023

Cite •

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

TUMBCMO14

Initial Test of a Machine Learning Based SRF Cavity Active Resonance Control

cavity, controls, resonance, simulation

379

F.Y. Wang, J. Cruz
SLAC, Menlo Park, California, USA

We’ll introduce a high precision active motion controller based on machine learning (ML) technology and electric piezo actuator. The controller will be used for SRF cavity active resonance control, where a data-driven model for system motion dynamics will be developed first, and a model predictive controller (MPC) will be built accordingly. Simulation results as well as initial test results with real SRF cavities will be presented in the paper.

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUMBCMO14

About •

Received ※ 03 October 2023 — Revised ※ 14 November 2023 — Accepted ※ 27 November 2023 — Issued ※ 09 December 2023

Cite •

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

WE3BCO07

Extending the ICAT Metadata Catalogue to New Scientific Use Cases

experiment, site, synchrotron, interface

1033

A. Götz, M. Bodin, A. De Maria Antolinos, M. Gaonach
ESRF, Grenoble, France
M. AlMohammad, S.A. Matalgah
SESAME, Allan, Jordan
P. Austin, V. Bozhinov, L.E. Davies, A. Gonzalez Beltran, K.S. Phipps
STFC/RAL/SCD, Didcot, United Kingdom
R. Cabezas Quirós
ALBA-CELLS, Cerdanyola del Vallès, Spain
R. Krahl
HZB, Berlin, Germany
A. Pinto
LNLS, Campinas, Brazil
K. Syder
DLS, Oxfordshire, United Kingdom

The ICAT metadata catalogue is a flexible solution for managing scientific metadata and data from a wide variety of domains following the FAIR data principles. This paper will present an update of recent developments of the ICAT metadata catalogue and the latest status of the ICAT collaboration. ICAT was originally developed by UK Science and Technology Facilities Council (STFC) to manage the scientific data of ISIS Neutron and Muon Source and Diamond Light Source. They have since been joined by a number of other institutes including ESRF, HZB, SESAME, and ALBA who together now form the ICAT Collaboration [1]. ICAT has been used to manage petabytes of scientific data for ISIS, DLS, ESRF, HZB, and in the future SESAME and ALBA and make these data FAIR. The latest version of the ICAT core as well as the new user interfaces, DataGateway and DataHub, and extensions to ICAT for implementing free text searching, a common search interface across Photon and Neutron catalogues, a protocol-based interface that allows making the metadata available for findability, electronic logbooks, sample tracking, and web-based data and domain specific viewers developed by the community will be presented. Finally recent developments to use ICAT to develop applications for processed data with rich metadata in the fields of small angle scattering, macromolecular crystallography and cryo-electron microscopy will be described. [1] https://icatproject.org

Slides WE3BCO07 [7.888 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-WE3BCO07

About •

Received ※ 05 October 2023 — Revised ※ 23 October 2023 — Accepted ※ 14 December 2023 — Issued ※ 14 December 2023

Cite •

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

THMBCMO31

LImA2: Edge Distributed Acquisition and Processing Framework for High Performance 2D Detectors

detector, controls, GPU, experiment

1269

S. Debionne, L. Claustre, P. Fajardo, A. Götz, A. Homs Puron, J. Kieffer, R. Ponsard
ESRF, Grenoble, France

LImA* is a framework born at the ESRF for 2D Data Acquisition (DAQ), basic Online Data Analysis (ODA) and processing with high-throughput detectors. While in production for 15 years in several synchrotron facilities, the ever-increasing detector frame rates make more and more difficult performing DAQ & ODA tasks on a single computer**. LImA2 is designed to scale horizontally, using multiple hosts for DAQ & ODA. This enables more advanced strategies for data feature extraction while keeping a low latency. LImA2 separates three functional blocks: detector control, image acquisition, and data processing. A control process configures the detector, while one or more receiver processes perform the DAQ and ODA, like the generation of fast feedback signals. The detectors currently supported in LImA2 are the PSI/Jungfrau, the ESRF/Smartpix and the Dectris/Eiger2. The former performs pixel assembly and intensity correction in GPU; the second exploits RoCE capabilities; and the latter features dual threshold, multi-band images. Raw data rates up to 8 GByte/s can be handled by a single computer, scalable if necessary. In addition to a classic processing, advanced pipelines are also implemented. A Serial-MX/pyFAI*** pipeline extracts diffraction peaks in GPU in order to filter low quality data. NVIDIA GPUDirect is used by a third pipeline providing 2D processing with remarkable low latency. IBM Power9 optimizations like the NX GZIP compression and the PCI-e multi-host extension are exploited.
* LIMA - https://accelconf.web.cern.ch/ICALEPCS2013/papers/frcoaab08.pdf
** Jungfraujoch - https://doi.org/10.1107/S1600577522010268
*** pyFAI - https://doi.org/10.1107/S1600576715004306

Slides THMBCMO31 [0.572 MB]

Poster THMBCMO31 [14.959 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THMBCMO31

About •

Received ※ 06 October 2023 — Revised ※ 08 October 2023 — Accepted ※ 11 December 2023 — Issued ※ 13 December 2023

Cite •

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

THPDP010

Update on the EBS Storage Ring Beam Dynamics Digital Twin

controls, optics, storage-ring, TANGO

1306

S.M. Liuzzo, N. Carmignani, L.R. Carver, L. Hoummi, N. Leclercq, T.P. Perron, J.L. Pons, S.M. White
ESRF, Grenoble, France

The EBS storage ring control system is presently paired with an electron beam dynamics digital twin (the EBS control system simulator, EBSS*). The EBSS reproduces many of the beam dynamics related quantities relevant for machine operation. This digital twin is used for the preparation and debug of software to deploy for operation. The EBSS is presently working only for the main storage ring and it is not directly connected to the machine operation but works in parallel and on demand. We present here the steps taken towards an on-line continuous use of the EBSS to monitor the evolution of not directly observable parameters such as beam optics.
* Simone Liuzzo, et al. The ESRF-EBS Simulator: A Commissioning Booster. 18th ICALEPCS, Oct 2021, Shanghai, China. MOPV012

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THPDP010

About •

Received ※ 27 September 2023 — Revised ※ 25 October 2023 — Accepted ※ 10 December 2023 — Issued ※ 16 December 2023

Cite •

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