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Lattice and Model

Lattice and Model. Paul Chu. Outline. Motivation Model Server design LCLS Model Database Service layer Prototype and path forward. Motivation. Providing a universal model environment Different accelerators may use different modeling tools but some applications can be shared

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Lattice and Model

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  1. Lattice and Model Paul Chu

  2. Outline • Motivation • Model Server design • LCLS Model Database • Service layer • Prototype and path forward P. Chu, Controls Database Collaboration, 17 Nov 2011

  3. Motivation • Providing a universal model environment • Different accelerators may use different modeling tools but some applications can be shared • Universal API useful for future application development • Connection to control systems • Centralized model computation • Reducing application complexity • Model results shared • Client apps same for both online tuning and offline analysis • Simple, clean API for all model needs P. Chu, Controls Database Collaboration, 17 Nov 2011

  4. Overview P. Chu, Controls Database Collaboration, 17 Nov 2011

  5. Preliminary Design • Using XAL data structure • XAL accelerator hierarchy suitable for holding model data • Set/get model data to/from XAL (data access API) • Advantage: it is in Java, i.e. supporting Matlab, Jython • Using Java or scripting language to generate non-XAL model input files • Prototyped for IMPACT (in Python) • Using scripting language to parse non-XAL model output files • Using scripting language for model run control • Start/stop/abort a model run • Scheduling on cluster • Monitoring run status by checking a meta file • Saving data to file system, then relational database • Data storage similar to LCLS MACHINE_MODEL schema P. Chu, Controls Database Collaboration, 17 Nov 2011

  6. Model Run Control [1] • Initialization • Establish CA and DB connection • Construct Accelerator object • For live machine model, programmatically generate the input file • Schedule/run model, monitor progress • Collect model run result • Insert model run result into XAL data structure • Update model service data • In-memory DB for quick access • Store persistent data in RDB • Client apps access model data via API P. Chu, Controls Database Collaboration, 17 Nov 2011

  7. Model Run Control [2] • Adapters between XAL and non-XAL models for both input and output • Arrange/schedule model runs • Monitoring run status for offline tracking • Hook to service provider P. Chu, Controls Database Collaboration, 17 Nov 2011

  8. LCLS Machine_Model Schema [1] • Model run on standalone app, on-demand based • 3 databases – production, QA and production-for-external-use • Model data entered in Oracle DB with JDBC • PL/SQL procedural calls for data validation, integrity check • Failover protection • Model data indexed for better performance P. Chu, Controls Database Collaboration, 17 Nov 2011

  9. LCLS Machine_Model Schema [2] • 10 tables • 29 views mainly for individual beamlines and grouped parameters Courtesy E. Grunhaus P. Chu, Controls Database Collaboration, 17 Nov 2011

  10. LCLS Machine_ModelSize Estimate • 29 views mainly for individual beamlines • 5 beamlines • ~2500 elements for the LCLS “FULL MACHINE” line • Total data after 3 years ~2 GB, ~10 runs per day while operating • Support DESIGN and EXTANT models P. Chu, Controls Database Collaboration, 17 Nov 2011

  11. LCLS Machine_ModelSchema details • DEVICE_TYPES: link to the component tables • ELEMENT_MODELS: actual model data • GOLD: keep track of GOLD model history • HARDWARE_SETTINGS: link to SCORE (data correlation) • INITIAL_CONDITIONS: can be used for different initial beam conditions. Not in use for now. • MODEL_DEVICES: machine settings for model run input • MODEL_LINES: beamlines • MODEL_MODES: can distinguish, say, different MPS or running modes • RUNS: different model runs, e.g. date, design/extant, comments etc. • XML_DOCS: can save model data as XML files P. Chu, Controls Database Collaboration, 17 Nov 2011

  12. Service Layer • Communication protocol – TBD • XML-RPC, JSON-RPC for simple data types • PVAccess? • How to package and transport model data • Mainly simple data such as getBetaX(), getEmitX(), getEnergy() • Maybe getAllBetaFor(a_beamline_section), getAllBetaFor(all_magnets) • Broadcasting/on-demand pulling/Subscription to a service P. Chu, Controls Database Collaboration, 17 Nov 2011

  13. Prototype and Path Forward • XAL data structure and access API is basically ready • Maybe need convenient wrapper API • XML-RPC based service prototyped for data communication • Is PVAccess/PVData ready for complex data structure? • Lattice DB schema can base on LCLS MACHINE_MODEL • Need IRMIS data access API for Lattice P. Chu, Controls Database Collaboration, 17 Nov 2011

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