1. NeSCR Dec-3 -2003 Bertram Ludaescher Scientific Workflows Based on Dataflow Process Networks (or from Ptolemy to Kepler) (or Workflow Considered Harmful …) Bertram Ludäscher San Diego Supercomputer Center ludaesch@SDSC.edu

2. NeSCR Dec-3 -2003 Bertram Ludaescher Overview 1.Scientific Workflow (SWF) Examples 2.SWF Requirements & Characteristics 3. Workflow standards considered harmful for SWF!? 4.Dataflow Process Networks (Ptolemy II) 5.Scientific Workflows (Kepler = Ptolemy II + X)

3. NeSCR Dec-3 -2003 Bertram Ludaescher Acknowledgements I NSF, NIH, DOENSF, NIH, DOE GEOsciences Network (NSF)GEOsciences Network (NSF) –www.geongrid.org Biomedical Informatics Research Network (NIH)Biomedical Informatics Research Network (NIH) –www.nbirn.net Science Environment for Ecological Knowledge (NSF)Science Environment for Ecological Knowledge (NSF) –seek.ecoinformatics.org Scientific Data Management Center (DOE)Scientific Data Management Center (DOE) –sdm.lbl.gov/sdmcenter/

4. NeSCR Dec-3 -2003 Bertram Ludaescher Acknowledgements II Ilkay Altintas SDMIlkay Altintas SDM Chad Berkley SEEKChad Berkley SEEK Shawn Bowers SEEKShawn Bowers SEEK Jeffrey Grethe BIRNJeffrey Grethe BIRN Christopher H. Brooks Ptolemy IIChristopher H. Brooks Ptolemy II Zhengang Cheng SDMZhengang Cheng SDM Efrat Jaeger GEONEfrat Jaeger GEON Matt Jones SEEKMatt Jones SEEK Edward A. Lee Ptolemy IIEdward A. Lee Ptolemy II Kai Lin GEONKai Lin GEON Bertram Ludaescher BIRN, GEON, SDM, SEEKBertram Ludaescher BIRN, GEON, SDM, SEEK Stephen Neuendorffer Ptolemy IIStephen Neuendorffer Ptolemy II Mladen Vouk SDMMladen Vouk SDM Yang Zhao Ptolemy IIYang Zhao Ptolemy II … Coming soon!?:Coming soon!?: –ROADNet, myGrid, GriPhyN,... Ptolemy II

5. NeSCR Dec-3 -2003 Bertram Ludaescher Promoter Identification Workflow (PIW) Source: Matt Coleman (LLNL)

6. NeSCR Dec-3 -2003 Bertram Ludaescher Promoter Identification Workflow in Ptolemy-II (SSDBM’03) Execution Semantics

7. NeSCR Dec-3 -2003 Bertram Ludaescher GARP Invasive Species Pipeline Training sample (d) GARP rule set (e) Test sample (d) Integrated layers (native range) (c) Species presence & absence points (native range) (a) EcoGrid Query EcoGrid Query Layer Integration Layer Integration Sample Data + A3 + A2 + A1 Data Calculation Map Generation Validation User Validation Map Generation Integrated layers (invasion area) (c) Species presence &absence points (invasion area) (a) Native range prediction map (f) Model quality parameter (g) Environmental layers (native range) (b) Generate Metadata Archive To Ecogrid Registered Ecogrid Database Registered Ecogrid Database Registered Ecogrid Database Registered Ecogrid Database Environmental layers (invasion area) (b) Invasion area prediction map (f) Model quality parameter (g) Selected prediction maps (h) Source: NSF SEEK (Deana Pennington et. al, UNM)

8. NeSCR Dec-3 -2003 Bertram Ludaescher Rock & Mineral Classification Workflow

9. NeSCR Dec-3 -2003 Bertram Ludaescher A Look Inside Classification Diagrams information and transitions between them. Extracted from the mineral composition and this level’s diagram coordinates. SVG to polygons. Classifier: Locates the point’s region. Finer granularity Displays the point in the diagram for this level.

10. NeSCR Dec-3 -2003 Bertram Ludaescher Source: NIH BIRN (Jeffrey Grethe, UCSD)

11. NeSCR Dec-3 -2003 Bertram Ludaescher SWF Requirements & Characteristics Scientist friendly "problem solving environment"Scientist friendly "problem solving environment" –WF design –WF execution –WF steering and UI pause; revise; resume; rollback (cf. SCIRun) –repositories of reusable components –data and WF provenance (virtual data concept) logging, cache reuse/partial re-derive, reports, … –Conceptual modeling support complex data (semantics) support “wiring” support (cf. web service composition) planning support

12. NeSCR Dec-3 -2003 Bertram Ludaescher SWF Requirements & Characteristics "Modeling" support"Modeling" support –Abstraction, hierarchical modeling –Models of Computation (MoC) –component interaction; combination of MoCs (cf. CCA) –WF multi-grain/granola: powder to bolders (and back) Boolean (N)AND, (N)OR,… vs. chaining together Grid-apps –Rich data structures and type systems End user "programming" supportEnd user "programming" support –high-level programming constructs e.g. map/3 for iteration, filter, select, branch, merge,... –data transformations –legacy tool integration (plug-ins) –data streaming How to tame (e.g., starve a dataflow; then resume)?  Zauberlehrling’s problem

13. NeSCR Dec-3 -2003 Bertram Ludaescher SWF Requirements & Characteristics Grid-enabling SWFsGrid-enabling SWFs –transparent use of (remote) resources –big data –big computation requirements –early/late binding of logical to physical resources, … –planning, scheduling, …  cf. Chimera, Pegasus, DAGman, Condor(-G)

14. NeSCR Dec-3 -2003 Bertram Ludaescher Scientific Workflows: Some Findings More dataflow than (business) workflowMore dataflow than (business) workflow –but some branching looping, merging, … –not: documents/objects undergoing modifications –instead often: dataset-out = analysis(dataset-in) Need for “programming extension”Need for “programming extension” –Iterations over lists (foreach); filtering; functional composition; generic & higher-order operations (zip, map(f), …) Need for abstraction and nested workflowsNeed for abstraction and nested workflows Need for data transformations (compute/transform alternations)Need for data transformations (compute/transform alternations) Need for rich user interaction & workflow steering:Need for rich user interaction & workflow steering: –pause / revise / resume –select & branch; e.g., web browser capability at specific steps as part of a coordinated SWF Need for high-throughput transfers (“grid-enabling”, “streaming”)Need for high-throughput transfers (“grid-enabling”, “streaming”) Need for persistence of intermediate productsNeed for persistence of intermediate products  data provenance (“virtual data” concept)

15. NeSCR Dec-3 -2003 Bertram Ludaescher Scientific WF vs Business WF Scientific “Workflows”Scientific “Workflows” –Dataflow and data transformations –Data problems: volume, complexity, heterogeneity –Grid-aspects Distributed computation Distributed data –User-interactions/WF steering –Data, tool, and analysis integration  Dataflow and control-flow are married! Business WorkflowsBusiness Workflows –Process composition –Tasks, documents, etc. undergo modifications (e.g., flight reservation from reserved to ticketed), but modified WF objects still identifiable throughout –Complex control flow, task-oriented: travel reservations; credit approval  Dataflow and control-flow are divorced!

16. NeSCR Dec-3 -2003 Bertram Ludaescher A ZOO of Workflow Standards and Systems Source: W.M.P. van der Aalst et al. http://tmitwww.tm.tue.nl/research/patterns/ Source: W.M.P. van der Aalst et al. http://tmitwww.tm.tue.nl/research/patterns/

17. NeSCR Dec-3 -2003 Bertram Ludaescher Business Workflows Business WorkflowsBusiness Workflows –show their office automation ancestry –documents and “work-tasks” are passed –no data streaming, no data-intensive pipelines –lots of standards to choose from: WfMC, WSFL, BMPL, BPEL4WS,.. XPDL,… –but often no clear execution semantics for constructs as simple as this: Source: Expressiveness and Suitability of Languages for Control Flow Modelling in Workflows, PhD thesis, Bartosz Kiepuszewski, 2002

18. NeSCR Dec-3 -2003 Bertram Ludaescher On Workflow Standards… http://tmitwww.tm.tue.nl/staff/wvdaalst/Publications/publications.html

19. NeSCR Dec-3 -2003 Bertram Ludaescher Workflow “Standards” Debunked Source: Don’t go with the flow:Web services composition standards exposed,W.M.P. van der Aalst, Trends & Controversies, Jan/Feb 2003 issue of IEEE Intelligent Systems Web Services - Been there done that?

20. NeSCR Dec-3 -2003 Bertram Ludaescher Workflow “Standards” Debunked Source: Don’t go with the flow:Web services composition standards exposed,W.M.P. van der Aalst, Trends & Controversies, Jan/Feb 2003 issue of IEEE Intelligent Systems Web Services - Been there done that?

21. NeSCR Dec-3 -2003 Bertram Ludaescher But never mind the standards discussion: Many Scientific Workflows are Dataflows! (Check YOUR examples …)

22. NeSCR Dec-3 -2003 Bertram Ludaescher Commercial Workflow/Dataflow Systems

23. NeSCR Dec-3 -2003 Bertram Ludaescher SCIRun: Component-Based Problem Solving Environments for Large-Scale Scientific Computing SCIRun: problem solving environment for interactive construction, debugging, and steering of large-scale scientific computationsSCIRun: problem solving environment for interactive construction, debugging, and steering of large-scale scientific computations Component model, based on generalized dataflow programmingComponent model, based on generalized dataflow programming Source: Steve Parker (cs.utah.edu); SciDAC/SDM collaborationSource: Steve Parker (cs.utah.edu); SciDAC/SDM collaboration

24. NeSCR Dec-3 -2003 Bertram Ludaescher Workflow and distributed computation grid created with Kensington Discovery Edition from InforSense.

25. NeSCR Dec-3 -2003 Bertram Ludaescher Dataflow Process Networks: Putting Computation Models first! Synchronous Dataflow Network (SDF)Synchronous Dataflow Network (SDF) –Statically schedulable single-threaded dataflow Can execute multi-threaded, but the firing-sequence is known in advance –Maximally well-behaved, but also limited expressiveness Process Network (PN)Process Network (PN) –Multi-threaded dynamically scheduled dataflow –More expressive than SDF (dynamic token rate prevents static scheduling) –Natural streaming model Other Execution Models (“Domains”)Other Execution Models (“Domains”) –Implemented through different “Directors” actor typed i/o ports FIFO advanced push/pull

26. NeSCR Dec-3 -2003 Bertram Ludaescher Dataflow Process Networks and Ptolemy-II see!see! try!try! read!read! Source: Edward Lee et al. http://ptolemy.eecs.berkeley.edu/ptolemyII/

27. NeSCR Dec-3 -2003 Bertram Ludaescher Why Ptolemy-II? PTII Objective:PTII Objective: –“The focus is on assembly of concurrent components. The key underlying principle in the project is the use of well-defined models of computation that govern the interaction between components. A major problem area being addressed is the use of heterogeneous mixtures of models of computation.” Data & Process oriented:Data & Process oriented: –Dataflow process networks Natural Data Streaming SupportNatural Data Streaming Support End user “WF console” (Vergil GUI)End user “WF console” (Vergil GUI) PRAGMATICSPRAGMATICS –mature, actively maintained, well-documented –open source system –leverage “sister projects” activities (e.g. SEEK, SDM, BIRN,…)

28. NeSCR Dec-3 -2003 Bertram Ludaescher Source: Edward Lee et al. http://ptolemy.eecs.berkeley.edu/ptolemyII/

29. NeSCR Dec-3 -2003 Bertram Ludaescher Source: Edward Lee et al. http://ptolemy.eecs.berkeley.edu/ptolemyII/

30. NeSCR Dec-3 -2003 Bertram Ludaescher Marrying & Divorcing Control- & Dataflow Source: Edward Lee et al. http://ptolemy.eecs.berkeley.edu/ptolemyII/

31. NeSCR Dec-3 -2003 Bertram Ludaescher Another Goodie: Ptolemy-II Type System

32. NeSCR Dec-3 -2003 Bertram Ludaescher Support for Multiple Workflow Granularities Bolders Abstraction: Sand to Rocks Sand Powder Plumbing

33. NeSCR Dec-3 -2003 Bertram Ludaescher Scientific Workflows = Dataflow Process Networks + X X = …X = … –Database plug-ins –Legacy application plug-ins (via command line, as web services, …) –Grid extensions: Actors as web/grid services 3 rd party data transfer, high-throughput data streaming Dealing with thousands of files (cf. astrophysics, astronomy, HEP, … examples) Data and service repositories, discovery Extended type system (structural & semantic extensions) –Programming extensions (declarative/FP) and –Rich user interactions/workflow steering –Rich data transformations (compute/transform alternations) –Data provenance (semi-)automatic meta-data creation Kepler = Ptolemy-II + X

34. NeSCR Dec-3 -2003 Bertram Ludaescher Status update / specific tasks for Kepler $DONE, %ONGOING, *NEW User interaction, workflow steeringUser interaction, workflow steering –$ Pause/revise/resume –$ BrowserUI actor (browser as a 0-learning display and selection tool) Distributed executionDistributed execution –$ Dynamically port-specializing WSDL actor –* Dynamically specializing Grid service actor Port & actor type extensions (SEEK leverage)Port & actor type extensions (SEEK leverage) –* Structural types (XML Schema) –* Semantic types (OWL) incl. unit types w/ automatic conversion Programming extensionsProgramming extensions –% Data transformation actors (XSLT, XQuery, Python, Perl,…) –* map, zip, zipWith, …, loop, switch “patterns” Specialized Data SourcesSpecialized Data Sources –$ EML (SEEK), –% MS Access (GEON), *JDBC, –*XML, *NetCDF, …

35. NeSCR Dec-3 -2003 Bertram Ludaescher Some specific tasks for Kepler (all NEW) Design & develop transparent, Grid-enabled PNs:Design & develop transparent, Grid-enabled PNs: –Communication protocol details –Grid-actor extensions and/or –Grid-Process Network director (G-PN) –Host/Source-location becomes actor parameter add “active-inline” parameter display for grid-actors (@exec-loc), channels (@transport-protocol), source-actors (@{src-loc|catalog-loc}) Activity MonitoringActivity Monitoring –Add “activity status” display (green, yellow, red) to replace PtII animation (needed for concurrently executing PN!) Registration & Deployment mechanismsRegistration & Deployment mechanisms –Actor/Data/Workflow repository (=composite actors) –Shows up as (config’able) actor library –OGSA Service Registry approach? ( SEEK leverage; UDDI complex & limited says MattJ ) http://www-unix.globus.org/toolkit/draft-ggf-ogsi-gridservice-33_2003-06-27.pdf Extensions to deal with failures (fault tolerance)Extensions to deal with failures (fault tolerance)

36. NeSCR Dec-3 -2003 Bertram Ludaescher Example: Database actors for Ptolemy II (Kepler-GEON; Efrat Jaeger)

37. Database Actors Database Connection actor:Database Connection actor: Database Query actor:Database Query actor:

38. Database Actors Example

40. NeSCR Dec-3 -2003 Bertram Ludaescher Example: Web service-enabling Ptolemy II (Kepler-SDM; Ilkay Altintas)

41. NeSCR Dec-3 -2003 Bertram Ludaescher A Generic Web Service Actor Configure – select WSDL url from repository Configure - select service operation

42. NeSCR Dec-3 -2003 Bertram Ludaescher Set Parameters and Commit  Specialized Actor Set parameters and commit

43. NeSCR Dec-3 -2003 Bertram Ludaescher Web Service Actor after Instantiation

44. NeSCR Dec-3 -2003 Bertram Ludaescher Composing Third-Party Web Services Output of previous web service User interaction & Transformations Input of next web service

45. NeSCR Dec-3 -2003 Bertram Ludaescher Results of the Execution User I/O via standard brower! Run Window / WF Deployment

46. NeSCR Dec-3 -2003 Bertram Ludaescher Composing Legacy Applications (here: Phylogeny): Shell / Command-Line Actors Source: Alex Borchers, UCSD

47. NeSCR Dec-3 -2003 Bertram Ludaescher Example: Grid-enabling Ptolemy II ( Kepler-SEEK, Chad Berkley Kepler-SDM, Ilkay Altintas, … myGrid?, … …GriPhyN?, … … OGS{I|A}-[DAI]...)

48. NeSCR Dec-3 -2003 Bertram Ludaescher Transparently Grid-Enabling PTII: Handles AB GAGB 1.A  GA: get_handle 2.GA  A: return &X 3.A  B: send &X 4.B  GB: request &X 5.GB  GA: request &X 6.GA  GB: send *X 7.GB  B: send done(&X) Example: &X = “GA.17” *X = 1 2 3 4 5 6 7 PTII space Grid space Logical token transfer (3) requires get_handle(1,2); then exec_handle(4,5,6,7) for completion.

49. NeSCR Dec-3 -2003 Bertram Ludaescher Transparently Grid-Enabling PTII Different phasesDifferent phases –Register designed WF (could include external validation service) –Find suitable grid service hosts for actors –Pre-stage execution –Execute (w/ provenance) Interactively steer (pause; revise; resume) Batch process; re-run parts later –Register/store data products and execution logs Kepler implementation choices:Kepler implementation choices: –Grid-actors (no change of Director necessary!?) and/or –Grid-(PN)-director (also need to change actors!?) –Add grid service host id as actor parameter: A@GA –Similar for data: myDB@GA

50. NeSCR Dec-3 -2003 Bertram Ludaescher “C-z ; bg &” – Detach your WF execution! Currently in PTIICurrently in PTII –tight coupling of WF execution and PTII Java client (also Vergil GUI) To-do for Kepler:To-do for Kepler: –detaching WF console (Vergil) from a Grid-aware execution engine Grid-PN Director! Transport protocol parameter Data location parameter Host location parameter

51. NeSCR Dec-3 -2003 Bertram Ludaescher Semantic Type-enabling Ptolemy II (OWL – here we go… ;-) (Kepler-SEEK; Shawn Bowers)

52. NeSCR Dec-3 -2003 Bertram Ludaescher Semantic Type Extensions Take concepts and relationships from an ontology to “semantically type” the data-in/out portsTake concepts and relationships from an ontology to “semantically type” the data-in/out ports Application: e.g., design support:Application: e.g., design support: –smart/semi-automatic wiring, generation of “massaging actors” m 1 (normalize) p3p3 p4p4 Takes Abundance Count Measurements for Life Stages Returns Mortality Rate Derived Measurements for Life Stages

53. NeSCR Dec-3 -2003 Bertram Ludaescher

55. Semantic Types The semantic type signatureThe semantic type signature –Type expressions over the (OWL) ontology m 1 (normalize) p3p3 p4p4 SemType m1 :: Observation & itemMeasured.AbundanceCount & hasContext.appliesTo.LifeStageProperty -> DerivedObservation & itemMeasured.MortalityRate & hasContext.appliesTo.LifeStageProperty

56. NeSCR Dec-3 -2003 Bertram Ludaescher Extended Type System (here: OWL Semantic Types) SemType m1 :: Observation & itemMeasured.AbundanceCount & hasContext.appliesTo.LifeStageProperty  DerivedObservation & itemMeasured.MortalityRate & hasContext.appliesTo.LifeStageProperty Substructure association: XML raw-data =(X)Query=> object model =link => OWL ontology

57. NeSCR Dec-3 -2003 Bertram Ludaescher Programming Extensions (some lessons from SciDAC/SSDBM demo)

58. NeSCR Dec-3 -2003 Bertram Ludaescher Promoter Identification Workflow in Ptolemy-II (SSDBM’03) hand-crafted control solution; also: forces sequential execution! designed to fit hand-crafted Web-service actor Complex backward control-flow No data transformations available

59. NeSCR Dec-3 -2003 Bertram Ludaescher Promoter Identification Workflow in FP genBankG :: GeneId -> GeneSeq genBankP :: PromoterId -> PromoterSeq blast :: GeneSeq -> [PromoterId] promoterRegion :: PromoterSeq -> PromoterRegion transfac :: PromoterRegion -> [TFBS] gpr2str :: (PromoterId, PromoterRegion) -> String d0 = Gid "7" -- start with some gene-id d1 = genBankG d0 -- get its gene sequence from GenBank d2 = blast d1 -- BLAST to get a list of potential promoters d3 = map genBankP d2 -- get list of promoter sequences d4 = map promoterRegion d3 -- compute list of promoter regions and... d5 = map transfac d4 --... get transcription factor binding sites d6 = zip d2 d4 -- create list of pairs promoter-id/region d7 = map gpr2str d6 -- pretty print into a list of strings d8 = concat d7 -- concat into a single "file" d9 = putStr d8 -- output that file

60. NeSCR Dec-3 -2003 Bertram Ludaescher Cleaned up Process Network PIW Back to purely functional dataflow process networkBack to purely functional dataflow process network (= also a data streaming model!) Re-introducing map (f) to Ptolemy-II (was there in PT Classic)Re-introducing map (f) to Ptolemy-II (was there in PT Classic)  no control-flow spaghetti  data-intensive apps  free concurrent execution  free type checking  automatic support to go from piw(GeneId) to PIW := map (piw) over [GeneId] map (f)-style iterators Powerful type checking Generic, declarative “programming” constructs Generic data transformation actors Forward-only, abstractable sub- workflow piw(GeneId)

61. NeSCR Dec-3 -2003 Bertram Ludaescher Optimization by Declarative Rewriting I PIW as a declarative, referentially transparent functional processPIW as a declarative, referentially transparent functional process  optimization via functional rewriting possible e.g. map(f o g) = map(f) o map(g) Details:Details: –Technical report &PIW specification in Haskell map(f o g) instead of map(f) o map(g) Combination of map and zip http://kbi.sdsc.edu/SciDAC-SDM/scidac-tn-map-constructs.pdf

62. NeSCR Dec-3 -2003 Bertram Ludaescher Optimizing II: Streams & Pipelines Clean functional semantics facilitates algebraic workflow (program) transformations (Bird-Meertens); e.g. mapS f mapS g  mapS (f g)Clean functional semantics facilitates algebraic workflow (program) transformations (Bird-Meertens); e.g. mapS f mapS g  mapS (f g) Source: Real-Time Signal Processing: Dataflow, Visual, and Functional Programming, Hideki John Reekie, University of Technology, Sydney

63. NeSCR Dec-3 -2003 Bertram Ludaescher Summary Many (most of ours anyways) scientific workflows are dataflowsMany (most of ours anyways) scientific workflows are dataflows –lots of workflow “standards” (messy and not focused on SWF problems) –should we start a new wave of dataflow standards?? Importance of clear semantics forImportance of clear semantics for –different MoCs (models of computation: PN, SDF, DE, CT, …) –component composition across MoCs –component interaction –  Ptolemy II directors Kepler:Kepler: –Based on extensible Ptolemy II system –Cross-project activity (SEEK, SDM, Ptolemy II, GEON, BIRN, and counting) –Plug-in / interface with your SWF planner, execution engine, grid-WF tool!

64. NeSCR Dec-3 -2003 Bertram Ludaescher Your Projects & Icons Your Projects & Icons

65. NeSCR Dec-3 -2003 Bertram Ludaescher A Note on the Style of these Slides Due to lack of time, most of the following slides are “by reference” only ;-) – …Each speaker was given four minutes to present his paper, as there were so many scheduled -- 198 from 64 different countries. To help expedite the proceedings, all reports had to be distributed and studied beforehand, while the lecturer would speak only in numerals, calling attention in this fashion to the salient paragraphs of his work.... Stan Hazelton of the U.S. delegation immediately threw the hall into a flurry by emphatically repeating: 4, 6, 11, and therefore 22; 5, 9, hence 22; 3, 7, 2, 11, from which it followed that 22 and only 22!! Someone jumped up, saying yes but 5, and what about 6, 18, or 4 for that matter; Hazelton countered this objection with the crushing retort that, either way, 22. I turned to the number key in his paper and discovered that 22 meant the end of the world… [The Futurological Congress, Stanislaw Lem, translated from the Polish by Michael Kandel, Futura 1977]