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A New EPICS Database Field Type for Abstract Data

A New EPICS Database Field Type for Abstract Data. Jeffrey Hill. Overview. LANSCE Requirements – a Review EPICS Paradigm Shift – a Review Status – What is Implemented What is an Abstract Data Type? Benefits of Abstract Types A New EPICS Database Field Type for Abstract Data

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A New EPICS Database Field Type for Abstract Data

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  1. A New EPICS Database Field Type for Abstract Data Jeffrey Hill

  2. Overview LANSCE Requirements – a Review EPICS Paradigm Shift – a Review Status – What is Implemented What is an Abstract Data Type? Benefits of Abstract Types A New EPICS Database Field Type for Abstract Data LANSCE Schedule Conclusion

  3. LANSCE Requirements • LANSCE, a versatile machine • Originally producing H+, H-, and polarized H- • Each with different intensities, duty factors, and even energies • depending on experimental and medical isotope production needs • LANSCE timing and flavoring of data • Flavoring • Selection based on - logical combinatorial of beam gates • Timing • Selection based on - time window sampling • Many permutations • Too many to, a-priori, install records for all of them • Subscription update filtering is needed

  4. EPICS Paradigm Shift EPICS EPICS Distributed Control Physics Control Data Acquisition Open Source OS Neutral Vendor Neutral Small Footprint

  5. EPICS Paradigm Shift • What is a Data Acquisition System? • Replacing …

  6. EPICS Paradigm Shift • What is a Distributed Data Acquisition System? • Must efficiently filter, and archive data • Selecting interesting occurrences • for future processing /evaluation • Flexible reconfigurable by clients at runtime • Don’t expect to know initially, when designing/compiling runtime system, what experiments/filters might be devised later on • Experiments/filters configured when client subscribes • Don’t expect to know initially, when designing/compiling runtime system, what data aggregations will be on different data branches to different clients

  7. EPICS Paradigm Shift • Current weaknesses deploying EPICS into Data Acquisition situations? • Record processing provides good flexibility to create event filters, but … • Frequently, it isn't possible to know all of the experiments when the IOC’s database is designed • A distributed data acquisition system needs runtime reconfiguration, initiated by client side tools • Limited data model • No runtime aggregation, or user defined types

  8. EPICS Paradigm Shift • Current weaknesses deploying EPICS into Data Acquisition situations? • No support for site specific tagging of the data • If a site needs to filter for LANSCE H- beam, then forcing this to occur based on the time-stamp • Inflexible solution - from a LANSCE perspective • Our solution • Site specific parasitic PV attribute data can be filtered by the CA server

  9. EPICS Paradigm Shift Device Support Record Support DB Common CA Server Time Stamp Signal Data PV Value Alarm State Device Specific Values Record Specific Values

  10. Status – What is Implemented CA Client Multicast Enhancements Mostly Implemented CA Server Multicast Enhancements Implemented • Multicast Enhancements • Simplified configuration of EPICS Systems with • Multiple IOCs on one host • Installations with multiple subnets

  11. Status – What is Implemented CA Server Event Queue Upgrade CA Server Event Filtering Upgrade CA Server Service Interface Upgrade Implemented Database CA Service Database Enhancements Under Design Device Support LANSCE Specific

  12. Status – What is Implemented >camonitor "fred$F $(PV:)>30 && $(PV)<40" fred$F $(PV:)>30 && $(PV)<40 2010-06-03 07:58:47.224969 36.6466 fred$F $(PV:)>30 && $(PV)<40 2010-06-03 07:58:47.227964 37.1654 fred$F $(PV:)>30 && $(PV)<40 2010-06-03 07:58:47.267460 33.9427 fred$F $(PV:)>30 && $(PV)<40 2010-06-03 07:58:47.276013 33.9976 fred$F $(PV:)>30 && $(PV)<40 2010-06-03 07:58:47.299041 37.8033 fred$F $(PV:)>30 && $(PV)<40 2010-06-03 07:58:47.319065 33.549 >camonitor "fred$F $(PV:flavor)==30 " fred$F $(PV:flavor)==30 2010-06-03 07:58:18.906049 44.1145 fred$F $(PV:flavor)==30 2010-06-03 07:58:21.899019 39.2743 fred$F $(PV:flavor)==30 2010-06-03 07:58:24.885000 54.3352 fred$F $(PV:flavor)==30 2010-06-03 07:58:27.855063 93.9634 fred$F $(PV:flavor)==30 2010-06-03 07:58:30.811997 97.7081 Subscription update event filtering

  13. What is an Abstract Data Type? • An Abstract Data Type is defined by • Operations that may be performed on it • Some mathematical constraints on these operations • Our goal, always … • Separation of interface from implementation • Isolate from each other … • The details of the internal encoding of the data structures of the implementation • The interface used to manipulate the implementation

  14. What is an Abstract Data Type? • Defining Abstract Data Type’s Interface • Specify Abstract Type’s name • Specify Abstract Type’s Nmethods • Specify method’s name • Specify method’s I input, and O output, parameters • The parameter’s name • The parameter’s data type class • i.e. integer, real, string, enumerated • The parameter’s acceptable range • The parameter’s optional default

  15. What is an Abstract Data Type? • Type Safety – user specified parameter must match with the specification of the interface • All parameters passed by users must match • The parameter’s name • The parameter’s data type class • i.e. integer, real, string, enumerated • The parameter’s acceptable range • Input Parameters • All input parameters must be supplied if the interface doesn't specify a default • Output Parameters • All interface specified output parameters must be supplied • Additional optional output parameters may be present w/o violating interface specification • If properly qualified by a standardized path name – i.e. project/LANSCE/flavor

  16. Benefits of Abstract Types • Users can manipulate an entity more complex than a Process Variable • Implementation is free to evolve without impacting the users • We can pass in N parameters atomically • Example, we can set the x, y, z coordinates together as a unit • We can pass out N parameters atomically • Example, we can extend the set of parameters passed with a subscription update to include the LANSE flavor

  17. A New EPICS Database Field Type for Abstract Data • New field type • Field size is sizeof ( pointer ) • Field content • Reference counting C++ smart pointer • Smart pointer points to C++ pure virtual interface class • This is the C++ interface used to interface to an Abstract Data Type

  18. A New Data Base Field Type for Abstract Data • How do database links work? • If the source is ordinary data and the destination is an Abstract Data Type instance • Not permitted unless the destination abstract type has value set method • If the source is an Abstract Data Type instance and the destination is ordinary data • Not permitted unless the source abstract type has value get method • If the source is an Abstract Data Type instance and and the destination is an Abstract Data Type instance • Not permitted unless • Both source and destination have same Abstract Data Type name • If permitted then smart pointer in the destination is simply changed to become a new reference to the source • Or there is a matching set/get

  19. A New Data Base Field Type for Abstract Data • Implementation issues • Parameter interfacing • Presumably Data Access interface is used • Parameter conversion and range checking • Presumably Data Access library is used

  20. A New Data Base Field Type for Abstract Data • Implementation issues • Presumably these capabilities are evaluated first only in new record types • Therefore, minimal impact on existing installations

  21. A New Data Base Field Type for Abstract Data • Data Access, is it Easy CA? • In the EPICS community we have • Application developers (well adjusted, etc) • EPICS database, screens, matlab, python, tcl, etc • System programmers (geeks) • Device drivers, EPICS internals, etc • Implementing Data Access interface for particular data structure / class • System programmer job

  22. A New Data Base Field Type for Abstract Data • Data Access, is it Easy CA? • Once interfaced with Data Access • A high level (i.e. easy ca interface is available) • DA is not the data manipulation interface used by application level users • Users use the public interface of the data structure / class which has been interfaced • Communities develop around the data structures / classes standardized by particular applications, industries, and instruments

  23. LANSCE Schedule Orders for our new klystrons are in place We will provide production subscription update filtering capabilities for the LANSCE upgraded RF system and the LANSCE upgraded diagnostic systems in 2013 Prototypes will need to function considerably before that time frame

  24. Conclusion • A significant upgrade for EPICS is in progress, significant milestones have been completed • Multicasting – easier configuration • Subscription update filtering – client specified filter expression • Upgraded server event queue – optimal order preservation and transport of user defined types • Upgraded server interface – user defined types • Others are in early design phases • New Abstract Data EPICS database field types • A delivery schedule is in place at LANSCE

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