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Beamline Control and Data Acquisition

Beamline Control and Data Acquisition. Elder Matias on behalf of CLS. Challenges We Face?. Fiscal Reality (flat-line budgets) Increasing Number of Beamlines More sophisticated/demanding beamline More complex experiments Obsolescence Human Factors Reliability and Availability

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Beamline Control and Data Acquisition

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  1. Beamline Control and Data Acquisition Elder Matias on behalf of CLS

  2. Challenges We Face? • Fiscal Reality (flat-line budgets) • Increasing Number of Beamlines • More sophisticated/demanding beamline • More complex experiments • Obsolescence • Human Factors • Reliability and Availability • Stronger Focus on Scientific Results(Papers, HQI, benefit to society)

  3. Where we need to go • More effectively leveraging what we are doing across our beamlines • Making the facility more accessible across the entire experiment life cycle • Driving I&C Innovation into the beamlines in a strategic way • Exploiting emerging technology • Human Factors

  4. Where We Are? Mixed Environment: • All beamlines are EPICS Based • Most beamlines have QT based (IDA, IDEV, etc.) • User Centric GUI (Aquaman) • ScienceStudio based Remote Control

  5. Human Factors • Continue to move from device based to task based GUIs • Increased layers ofabstraction • Priority has been tailoring GUI applications to specific beamlines, we now need to look at a common look andfeel across the facility

  6. Scan Lib • Tradition Architect Insert a Scanning Library Slide here.

  7. ScienceStudio & ANISEDylan Maxwell, Dong Liu, Dioni Medrano and partners • Developed through in collaboration with partners at CLS, Western, IBM, LNLS, and ALS. • Uses: • REST & MQ. • HPC • Steams

  8. AquamanDavid Chevrier, Mark Boots, Daren Hunter • Integrate Experiment &Visualisation Platform • Qt based

  9. User Experiment Lifecycle

  10. Overview of User Cases

  11. High-level Data Model Terminology • Facility = CLS • Laboratory = Beamline • Instrument = Endstation • Project = Proposal

  12. Sequence

  13. Software Stack CSS BEAST SS Portal AM - GUI BL GUI AM - Technique PyEDM EDM MPlot AM - Scan Data Man EPICS Qt EPICS PyQt CDMA EPICS Connect SS Meta Data Store Qt CA Connect Area Detector IOC Control Gateway Services Drivers (Detector, Modbus IOC Services Devices Machine Protection Network and Directory Services

  14. µTCA • Conventional technology is VME(320 MB/s) or Compact PCI (528 MB/s) • Working with InstrumentationTechnology on µTCA (5 GB/s)beamline data acquisition solution

  15. Where we need to go • More effectively leveraging what we are doing across our beamlines • Making the facility more accessible across the entire experiment life cycle • Driving I&C Innovation into the beamlines in a strategic way • Exploiting emerging technology • Human Factors

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