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SNS Update DANSE Workshop. Steve Miller September 20-21, 2004. SNS Software Plans. Phase 1 – initiate framework Currently underway Phase 2 – Day 1 instrument support DANSE for ARCS DAVE for Backscatter Spectrometer ISAW for visualization Phase 3 – NeSSI SW on-line

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SNS Update DANSE Workshop


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    1. SNS UpdateDANSE Workshop Steve Miller September 20-21, 2004

    2. SNS Software Plans • Phase 1 – initiate framework • Currently underway • Phase 2 – Day 1 instrument support • DANSE for ARCS • DAVE for Backscatter Spectrometer • ISAW for visualization • Phase 3 – NeSSI SW on-line • Keep this development out of critical path

    3. Some Plan Considerations • Phase 1 • Portal performance and responsiveness – both within facility and external • Evaluate different portal types – currently evaluating window server implementation • Phase 2 • Can DANSE be ready for “Day 1” at SNS? • Is it necessary for DANSE to be ready on Day 1? • Where to host reflectometer software for Day 1? • Soon afterward need SANS and Diffractometer SW • Phase 3 • How long to get here?

    4. Current Events • NeSSI Workshop just took place - sponsored by ISIS • Collaboration holding regular video conferences – how to better include DANSE team? • E-notebooks setup for NeSSI and task groups • Currently updating Functional Requirements document utilizing interfaces diagram • Recent meeting at ORNL between SNS, HFIR, and NIST – discussing 3-way DAVE software collaboration • SNS-ORNL working with IPNS team to integrate ISAW tools within the data portal • Leveraging existing software where it makes sense

    5. NeSSI Collaboration and Workshop • Participating Organizations: • ANSTO, Caltech, CCLRC e-Science, HFIR, IPNS, ISIS, J-PARC/KEK/KENS, LANL, NIST, ORNL, SNS • Task Groups: • Access and Portals • Visualization • Analysis • Data Management • NeSSI gaining momentum

    6. Hardware Software SNS Software Architecture & Responsibilities real time control Intelligent Control Automation High Performance Computing Controls Diagnostics simulation analysis Instrument Simulation Materials simulation Treatment Instrument Acquisition Analysis Sample & Environment Vis Vis Vis Vis Vis acquisition visualization data Electronic notebook Instrument simulation Materials simulation Raw Intermediate Scientific Database Database Sample & environment Notebook Raw Intermediate Scientific Simulation Simulation Proposal Documentation Publications Software repository Data User Community Web Portal to Data, Software, and Analysis Metadata Modules Responsibilities SNS Directed Local and remote users SNS Responsible

    7. Facilities Play Bigger Role – Interfaces provide extensibility, integration, multiple frameworks Facilities have no control over SW users run on their own computers Using data downloaded from SNS data Visualization Minimum requirement Analysis Users Web browser Desktop client User Application SW defines interfaces through which user desktop programs can access facility resources Users and SNS write components to standard well defined interfaces Security Interface Access and authorization control Function Interface Control portal Data portal Analysis portal Acquisition SNS Validated software New User code Legacy code Commercial packages Data Management Data Interface Database and flat file access protocols Computer interface Meta data Documentation data Analysis results data Publications

    8. Some Portal Considerations • Pros • Offers facility single point of control for user software • Enables control of user access • Can provide user transparent access to high performance networking, data, and computing • Facilities can provide users SW licenses and workspace • Sending screen images rather than data • Cons • Requires network access • Remote access performance adequate? • Adequately host high end viz software? • Can same software running via portal run via desktop? • Sending screen images rather than data

    9. Visualization and GUI Group Access and Portal Interfaces Group Analysis Group Data Management Group Task Group Areas – Bringing Structure to Interfaces data User’s Own Computers Visualization Analysis Users Web browser Desktop client User Application Security Interface Access and authorization control Function Interface Control portal Data portal Analysis portal Acquisition SNS Validated software New User code Legacy code Commercial packages Data Management Data Interface Database and flat file access protocols Computer interface Meta data Documentation data Analysis results data Publications

    10. Access and Portals – Workshop Summary • Portals • Start with web portal interaction with functional interfaces • Define portal interfaces to data management and analysis/visualization layers • Software repository – to allow download of released SW versions • Access • Determine access use cases – who gets access to what • Draft a policy document • Determine methods for implementing access control • Outline necessities for “single-sign-on” across facilities • Grid access – eScience, TeraGrid, federated grid

    11. Visualization – Workshop Summary • Visualization to be controllable through a user interface or a script and specified through a public API • The visualization routines need to have input via either file or a pointer to memory • The controls (GUI or script) shall be separate from the data and the view(s) of the data • It will be possible to use some analysis routines to operate on the data before passing it to the viewer(s) • Needs to be easy for users to develop viz tools • New consideration – interactive visualization may be a tool to spawn batch processing resulting in new (3D or 4D) visualizations

    12. Analysis – Workshop Summary • Very large data sets driving development • Open Source and Commercial SW • Structured software needed. • Software repository – what to put in. • Automation and Intelligent Control. • Interfaces to data and visualization. • Analysis framework definition task group formed

    13. Data Management – Workshop Summary • A number of key databases have been identified • User • Proposals • Sample safety • Sample environment • Scheduling • Metadata (icat/scat) • Publications • Data • There is a pool of metadata and data available to populate these databases • Expressing relationships between various data types (e.g. RAW, processed, published) is key to preserving the analysis chain

    14. Where DANSE sits today DANSE presently runs on users local sites using data and analysis modules located there data Visualization Analysis Web browser Desktop client User Application Security Interface Access and authorization control Function Interface Control portal Data portal Analysis portal Acquisition UNDER CONSTRUCTION SNS Validated software New User code Legacy code Commercial packages Data Management Data Interface Database and flat file access protocols Computer interface Meta data Documentation data Analysis results data Publications

    15. DANSE as a Portal Client DANSE as a user application accesses data via the data portal interface data Visualization Analysis Possibly help support ARCS instrument integration remotely Web browser Desktop client User Application Security Interface Access and authorization control Function Interface Control portal Data portal Analysis portal Acquisition SNS Validated software New User code Legacy code Commercial packages Data Management Data Interface Database and flat file access protocols Computer interface Meta data Documentation data Analysis results data Publications

    16. DANSE as a Portal Server data Visualization User accesses DANSE via web portal, desktop client or user app Analysis Web browser Desktop client User Application Security Interface Access and authorization control Function Interface Control portal Data portal Analysis portal Acquisition SNS Validated software New User code Legacy code Commercial packages Data Management Data Interface Database and flat file access protocols Computer interface Meta data Documentation data Analysis results data Publications

    17. DANSE – Fully Integrated 1. DANSE runs remotely accessing resources at SNS data Visualization Analysis Web browser Desktop client User Application 2. DANSE fully integrated utilizing local/remote resources Security Interface Access and authorization control Function Interface Control portal Data portal Analysis portal Acquisition SNS Validated software New User code Legacy code Commercial packages Data Management Data Interface Database and flat file access protocols Computer interface Meta data Documentation data Analysis results data Publications

    18. Using the Portal Web Browser Interface • Using WiredX… • Portal can run either in a browser or as a “rootless” window on client machine. • Portal sends screen • Images rather than data

    19. Using the Portal – Selecting Data Selecting Input User clicks on “Select Input” button

    20. Using the Portal – Launching DANSE User clicks on “DANSE” button

    21. Using the Portal – More Applications ISAW Matlab Launch more applications such as… DAVE

    22. Using the Portal – Metadata Search Here RAW Metadata searched by owner

    23. Visualization Components Data Sources: URL, ptr or file Local or remote Data Reader Data Manipulation (local analysis) Visualization Engine Renderer Viewer 1 … Viewer N UI Control To Analysis Components User Interface

    24. Analysis Components Data Sources: URL, ptr or file Analysis Engine Local or remote computation Data Writer Data Reader Analysis Performer UI Control sequences performing analysis UI Control

    25. Considerations • Interface to NeXus files and data management layer • Interface to visualization – support multiple packages • Ability to support data provenance and pedigree – supply metadata to database records • Growing need to support batch processing • How to leverage existing software such as Netsolve, ISAW, DAVE? • Visual programming interface – existing options (CCA, SCIRUN, Caffeine, Kepler, IE, …)? • Documentation – architecture, interfaces, design, etc. • Incorporation of DANSE into NeSSI framework via interfaces • Simple, rapid installation wizard • Legacy code incorporation wizard • ARCS instrument – status of this SW? • SW transition plans to SNS • Collaborative development with SNS and with NeSSI – how to manage? • Any licensing or software ownership issues? • IMPACT Software – incorporating new science via software perhaps the biggest contribution the DANSE project can make

    26. SNS Considerations • Minimize Resources – personnel, costs, variety of software to maintain, etc. • Independently change code based upon user feedback – especially GUI applications • Must see the “big picture” for SW development • Design criteria contention – user vs developer • Support SNS Instrument Scientists • Support NeSSI collaborations • DANSE Integration

    27. Facility Software “Musts” • Software must be: • Reliable • Easy to use, but capable • Accessible via web or desktop • Documented – design, references, guides • Tested – with feedback paths for improvements • Easy to train people to use the software • low maintenance • Scaleable and Upgradeable • High performance where needed • Low cost • Facility must have means for self-sufficiency

    28. NeSSI  Culture Changes • Mutual trust among collaborators • Designs must be inclusive • Leverage collaborator strengths • Sensitive to timelines • Common vision and goals • Regular communication • Stakeholders share risks equitably • Software suite defined by natural selection • More anonymity among facility contributions • Teams must remain responsible to their facilities

    29. Summary • It’s a good time to align DANSE framework development efforts within the SNS/NeSSI framework • Let’s work together in conjunction with NeSSI