Transcript Scientific Workflows - San Diego Supercomputer Center

Scientific Workflows Based on
Dataflow Process Networks
(or from Ptolemy to Kepler)
(or Workflow Considered Harmful …)
Bertram Ludäscher
San Diego Supercomputer Center
[email protected]
NeSCR Dec-3 -2003 Bertram Ludaescher
Overview
1.
2.
3.
4.
5.
Scientific Workflow (SWF) Examples
SWF Requirements & Characteristics
Workflow standards considered harmful for SWF!?
Dataflow Process Networks (Ptolemy II)
Scientific Workflows (Kepler = Ptolemy II + X)
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• NSF, NIH, DOE
Acknowledgements I
• GEOsciences Network (NSF)
– www.geongrid.org
• Biomedical Informatics Research Network (NIH)
– www.nbirn.net
• Science Environment for Ecological Knowledge (NSF)
– seek.ecoinformatics.org
• Scientific Data Management Center (DOE)
– sdm.lbl.gov/sdmcenter/
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Acknowledgements II
•
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•
•
Ilkay Altintas SDM
Chad Berkley SEEK
Shawn Bowers SEEK
Jeffrey Grethe BIRN
Christopher H. Brooks Ptolemy II
Zhengang Cheng SDM
Efrat Jaeger GEON
Matt Jones SEEK
Edward A. Lee Ptolemy II
Kai Lin GEON
Bertram Ludaescher BIRN, GEON, SDM, SEEK
Stephen Neuendorffer Ptolemy II
Mladen Vouk SDM
Yang Zhao Ptolemy II
…
• Coming soon!?:
– ROADNet, myGrid, GriPhyN, ...
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Ptolemy II
Promoter Identification Workflow (PIW)
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Source: Matt Coleman (LLNL)
Execution
Semantics
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Promoter
Identification
Workflow
in Ptolemy-II
(SSDBM’03)
GARP Invasive Species Pipeline
Test sample (d)
Registered
Ecogrid
Database
EcoGrid
Query
Species
presence &
absence points
(native range)
(a)
Registered
Ecogrid
Database
+A1
+A2
+A3
Sample
Data
Training
sample
(d)
Data
Calculation
GARP
rule set
(e)
Map
Generation
Native
range
prediction
map (f)
Model quality
parameter (g)
Integrated
layers
(native range) (c)
Environmental
layers (native
range) (b)
Invasion
area prediction
map (f)
Map
Generation
Layer
Integration
Registered
Ecogrid
Database
Environmental
layers (invasion
area) (b)
Layer
Integration
User
Model quality
parameter (g)
Integrated layers
(invasion area) (c)
EcoGrid
Query
Registered
Ecogrid
Database
Validation
Validation
Archive
To Ecogrid
Selected
prediction
maps (h)
Generate
Metadata
Species presence
&absence points
(invasion area) (a)
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Source: NSF SEEK (Deana Pennington et. al, UNM)
Rock & Mineral Classification Workflow
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A Look Inside Classification
Finer granularity
Extracted from the mineral
composition and this level’s
diagram coordinates.
Diagrams information and
transitions between them.
Classifier: Locates
the point’s region.
SVG to polygons.
Displays the point in the
diagram for this level.
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Source: NIH BIRN (Jeffrey Grethe, UCSD)
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SWF Requirements & Characteristics
• 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
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SWF Requirements & Characteristics
• "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" 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
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SWF Requirements & Characteristics
• Grid-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)
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Scientific Workflows: Some Findings
• More 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”
– Iterations over lists (foreach); filtering; functional composition; generic &
higher-order operations (zip, map(f), …)
• Need for abstraction and nested workflows
• Need for data transformations (compute/transform alternations)
• 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 persistence of intermediate products
 data provenance (“virtual data” concept)
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A ZOO of Workflow Standards and Systems
Source: W.M.P. van der Aalst et al.
http://tmitwww.tm.tue.nl/research/patterns/
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Business Workflows
• Business 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
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On Workflow Standards…
http://tmitwww.tm.tue.nl/staff/wvdaalst/Publications/publications.html
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Workflow “Standards” Debunked
Source: Don’t go with the flow:Web services composition standards exposed,W.M.P. van der Aalst,
Trends
Controversies,
NeSCR
Dec-3&
-2003
Bertram Ludaescher Jan/Feb 2003 issue of IEEE Intelligent Systems Web Services - Been there done that?
Workflow “Standards” Debunked
Source: Don’t go with the flow:Web services composition standards exposed,W.M.P. van der Aalst,
Trends
Controversies,
NeSCR
Dec-3&
-2003
Bertram Ludaescher Jan/Feb 2003 issue of IEEE Intelligent Systems Web Services - Been there done that?
But never mind the standards discussion:
Many Scientific Workflows are Dataflows!
(Check YOUR examples …)
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Commercial Workflow/Dataflow Systems
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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 computations
Component model, based on generalized dataflow programming
Source: Steve Parker (cs.utah.edu); SciDAC/SDM collaboration
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Workflow and distributed
computation grid created
with Kensington Discovery
Edition from InforSense.
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Dataflow Process Networks:
Putting Computation Models first!
typed i/o ports
FIFO
actor
actor
• Synchronous Dataflow Network (SDF)
advanced push/pull
– 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)
– Multi-threaded dynamically scheduled dataflow
– More expressive than SDF (dynamic token rate prevents static scheduling)
– Natural streaming model
• Other Execution Models (“Domains”)
– Implemented through different “Directors”
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Dataflow Process
Networks and Ptolemy-II
see!
read!
try!
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Source: Edward Lee et al. http://ptolemy.eecs.berkeley.edu/ptolemyII/
Why Ptolemy-II?
• 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:
– Dataflow process networks
• Natural Data Streaming Support
• End user “WF console” (Vergil GUI)
• PRAGMATICS
– mature, actively maintained, well-documented
– open source system
– leverage “sister projects” activities (e.g. SEEK, SDM, BIRN,…)
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Source: Edward Lee et al. http://ptolemy.eecs.berkeley.edu/ptolemyII/
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Source: Edward Lee et al. http://ptolemy.eecs.berkeley.edu/ptolemyII/
Marrying & Divorcing Control- & Dataflow
Source: Edward Lee et al. http://ptolemy.eecs.berkeley.edu/ptolemyII/
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Another Goodie: Ptolemy-II Type System
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Support for Multiple Workflow Granularities
Bolders
Plumbing
Powder
Sand
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Abstraction:
Sand to
Rocks
Scientific Workflows = Dataflow Process Networks + X
Kepler
=
Ptolemy-II
+
X
• X=…
– Database plug-ins
– Legacy application plug-ins (via command line, as web services, …)
– Grid extensions:
•
•
•
•
–
–
–
–
Actors as web/grid services
3rd 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
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Status update / specific tasks for Kepler
$DONE, %ONGOING, *NEW
• User interaction, workflow steering
– $ Pause/revise/resume
– $ BrowserUI actor (browser as a 0-learning display and selection tool)
• Distributed execution
– $ Dynamically port-specializing WSDL actor
– * Dynamically specializing Grid service actor
• Port & actor type extensions (SEEK leverage)
– * Structural types (XML Schema)
– * Semantic types (OWL) incl. unit types w/ automatic conversion
• Programming extensions
– % Data transformation actors (XSLT, XQuery, Python, Perl,…)
– * map, zip, zipWith, …, loop, switch “patterns”
• Specialized Data Sources
– $ EML (SEEK),
– % MS Access (GEON), *JDBC,
– *XML, *NetCDF, …
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Some specific tasks for Kepler
(all NEW)
• 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 Monitoring
– Add “activity status” display (green, yellow, red) to replace PtII animation
(needed for concurrently executing PN!)
• Registration & 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)
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Example: Database actors for Ptolemy II
(Kepler-GEON; Efrat Jaeger)
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Database Actors
• Database Connection actor:
• Database Query actor:
Database Actors Example
Database Actors Example
Example: Web service-enabling Ptolemy II
(Kepler-SDM; Ilkay Altintas)
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A Generic Web Service Actor
Configure
Configure
– select
- selectWSDL
service
url
from
operation
repository
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Set Parameters and Commit Specialized Actor
Set parameters
and commit
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Web Service Actor after Instantiation
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Composing Third-Party Web Services
Output of previous
web service
User interaction &
Transformations
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Input of next
web service
Results of the Execution
User I/O via
standard brower!
Run Window /
WF Deployment
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Composing Legacy Applications (here: Phylogeny):
Shell / Command-Line Actors
Source: Alex Borchers, UCSD
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Example: Grid-enabling Ptolemy II
( Kepler-SEEK, Chad Berkley
Kepler-SDM, Ilkay Altintas,
… myGrid?, …
…GriPhyN?, …
… OGS{I|A}-[DAI] ...)
NeSCR Dec-3 -2003 Bertram Ludaescher
Transparently Grid-Enabling PTII: Handles
Logical token transfer (3)
requires get_handle(1,2);
then exec_handle(4,5,6,7)
for completion.
PTII
space
A
3
4
1 2
Grid
space
B
7
1.
2.
3.
4.
5.
6.
7.
AGA: get_handle
GAA: return &X
AB: send &X
BGB: request &X
GBGA: request &X
GA GB: send *X
GBB: send done(&X)
5
GA
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6
GB
Example:
&X = “GA.17”
*X =<some_huge_file>
Transparently Grid-Enabling PTII
• Different 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:
– 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
NeSCR Dec-3 -2003 Bertram Ludaescher
“C-z ; bg &” – Detach your WF execution!
• Currently in PTII
– tight coupling of WF execution and PTII Java client (also Vergil GUI)
• To-do for Kepler:
– detaching WF console (Vergil) from a Grid-aware execution engine
Grid-PN Director!
Transport protocol
parameter
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Data location
parameter
Host location
parameter
Semantic Type-enabling Ptolemy II
(OWL – here we go… ;-)
(Kepler-SEEK; Shawn Bowers)
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Semantic Type Extensions
• Take concepts and relationships from an ontology to
“semantically type” the data-in/out ports
• Application: e.g., design support:
– smart/semi-automatic wiring, generation of “massaging actors”
m1
p3
(normalize)
Takes Abundance Count
Measurements for Life Stages
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p4
Returns Mortality Rate Derived
Measurements for Life Stages
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Semantic Types
• The semantic type signature
– Type expressions over the (OWL) ontology
m1
p3
(normalize)
p4
SemType m1 ::
Observation & itemMeasured.AbundanceCount &
hasContext.appliesTo.LifeStageProperty
->
DerivedObservation & itemMeasured.MortalityRate &
hasContext.appliesTo.LifeStageProperty
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
NeSCR Dec-3 -2003 Bertram Ludaescher
Programming Extensions
(some lessons from SciDAC/SSDBM demo)
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Promoter
Identification
Workflow
in control
Ptolemy-II
hand-crafted
(SSDBM’03)
solution; also:
forces
designed to fit
designed to fit
sequential execution!
hand-crafted
Web-service actor
No data transformations
available
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Complex backward
control-flow
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
d1
d2
d3
d4
d5
d6
d7
d8
d9
=
=
=
=
=
=
=
=
=
=
Gid "7"
-- start with some gene-id
genBankG d0
-- get its gene sequence from GenBank
blast d1
-- BLAST to get a list of potential promoters
map genBankP d2
-- get list of promoter sequences
map promoterRegion d3 -- compute list of promoter regions and ...
map transfac d4
-- ... get transcription factor binding sites
zip d2 d4
-- create list of pairs promoter-id/region
map gpr2str d6
-- pretty print into a list of strings
concat d7
-- concat into a single "file"
putStr d8
-- output that file
NeSCR Dec-3 -2003 Bertram Ludaescher
Cleaned up Process Network PIW
• Back to purely functional
dataflow process network
map(f)-style
iterators
(= also a data streaming model!)
Powerful type
checking
Generic, declarative
“programming”
constructs
Generic data
transformation actors
• 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]
Forward-only, abstractable subworkflow piw(GeneId)
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Optimization by Declarative Rewriting I
• PIW as a declarative,
referentially transparent
functional process
map(f
o
 optimization via functional
rewriting possible
g)
instead of
map(f) o map(g)
e.g. map(f o g) = map(f) o map(g)
• Details:
Combination of
map and zip
– Technical report &PIW specification
in Haskell
http://kbi.sdsc.edu/SciDAC-SDM/scidac-tn-map-constructs.pdf
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Optimizing II: Streams & Pipelines
Source: Real-Time Signal
Processing: Dataflow, Visual, and
Functional Programming, Hideki
John Reekie, University of
Technology, Sydney
• Clean functional semantics facilitates algebraic workflow (program)
transformations (Bird-Meertens); e.g. mapS f • mapS g  mapS (f • g)
NeSCR Dec-3 -2003 Bertram Ludaescher
Summary
• Many (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 for
–
–
–
–
different MoCs (models of computation: PN, SDF, DE, CT, …)
component composition across MoCs
component interaction
 Ptolemy II directors
• 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!
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Your Projects & Icons <HERE>
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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]
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