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Ancillary Data Handling Strategies for Raw Data Processing

Explore possibilities for offline handling of ancillary data in raw data processing, including separate DAQ streams, merging data, using Gaudi algorithms, considering different detector types, synchronizing data, and optimizing data processing flow.

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Ancillary Data Handling Strategies for Raw Data Processing

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  1. Offline Possibilitiesfor Ancillary Data Handling

  2. Raw Data • Separate DAQ streams • Would both streams be sent off together via FastCopy or merged beforehand? • If - Merge ancillary data into LDF between spills? • As “user contribution”? • Could consider Gaudi algs to reconstruct beamline elements with simple calibrations • Would involve the different detector types and calibrations – would need consulting from Joanne for the calibrations definitions if we want them time dependent • Add in to svac tuple; add parallel beamtest digi tree? • Else - Separate app to reconstruct beamline elements • What is the form of the raw data? • Would be nice if this was not reconstructed with a PAW macro! • Code should be in cvs for all to see and use • Presumably output would be form of Root tree/ntuple • How to synch data: • Want same run/event number • Who verifies the synch? Ric has ideas for slaved scalars to track synch • Output Root data files – ntuple for summary info • Separate BT tuple or additions to svac? • Input to data server to allow easy association with merit, svac/beamtest

  3. Near Real Time • LATTE multicasts events • would/could LATTE wait until it gets the ancillary data into LDF before sending the event to Gleam listener? • could consider socket connection to Gleam to sample events for digi+engUnits & FRED viewing • Would need to develop this for Gleam • Would have other uses too – eg Gleam server pool for event display, etc • See Leon’s talk for throughput in this mode • Otherwise run Gleam after the end of run • For quicker turnaround on digi + engUnits

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