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Pegasus: Planning for Execution in
Grids
Ewa DeelmanInformation Sciences Institute
University of Southern California
Ewa Deelman Information Sciences Institute
Pegasus Acknowledgements
Ewa Deelman, Carl Kesselman, Saurabh Khurana, Gaurang Mehta, Sonal Patil, Gurmeet Singh, Mei-Hui Su, Karan Vahi (ISI)
James Blythe, Yolanda Gil (ISI) http://pegasus.isi.edu Research funded as part of the NSF
GriPhyN, NVO and SCEC projects.
Ewa Deelman Information Sciences Institute
Outline
General Scientific Workflow Issues on the Grid Mapping complex applications onto the Grid
Pegasus Pegasus Application Portal
LIGO-gravitational-wave physics Montage-astronomy
Incremental Workflow Refinement Futures
Ewa Deelman Information Sciences Institute
Grid Applications Increasing in the level of complexity Use of individual application components Reuse of individual intermediate data products (files) Description of Data Products using Metadata Attributes
Execution environment is complex and very dynamic Resources come and go Data is replicated Components can be found at various locations or staged in on
demand
Separation between the application description the actual execution description
Ewa Deelman Information Sciences Institute
FFT
FFT filea
/usr/local/bin/fft /home/file1
transfer filea from host1://home/filea
to host2://home/file1
ApplicationDomain
AbstractWorkflow
ConcreteWorkflow
ExecutionEnvironment
host1 host2
Data
Data
host2
App
licat
ion
Dev
elop
men
t and
Exe
cutio
n P
roce
ss
DataTransfer
Resource SelectionData Replica Selection
Transformation InstanceSelection
ApplicationComponentSelection
Retry
Pick different Resources
Specify aDifferentWorkflow
Failure RecoveryMethod
Abstract Workflow
Generation
ConcreteWorkflow
Generation
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Why Automate Workflow Generation?
Usability: Limit User’s necessary Grid knowledge Monitoring and Directory Service Replica Location Service
Complexity: User needs to make choices
Alternative application components Alternative files Alternative locations
The user may reach a dead end Many different interdependencies may occur among
components Solution cost:
Evaluate the alternative solution costs Performance Reliability Resource Usage
Global cost: minimizing cost within a community or a virtual organization requires reasoning about individual user’s choices in light of
other user’s choices
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Executable Workflow Construction Chimera builds an abstract workflow based
on VDL descriptions Pegasus takes the abstract workflow and
produces and executable workflow for the Grid
Condor’s DAGMan executes the workflow
AbstractWorfklow
Concrete Workflow
Jobs
Chimera Pegasus DAGMan
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Pegasus:Planning for Execution in Grids
Maps from abstract to concrete workflow Algorithmic and AI based techniques
Automatically locates physical locations for both components (transformations) and data Use Globus RLS and the Transformation Catalog
Finds appropriate resources to execute via Globus MDS
Reuses existing data products where applicable Publishes newly derived data products
Chimera virtual data catalog
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GridGridGrid
workflow executor (DAGman)Execution
WorkflowPlanning
Globus Replica Location Service
Globus Monitoring and Discovery
Service
Information and Models
detector
Raw data
Co
ncr
ete
Wo
rkfl
ow
Replica LocationAvailable Reources
Abstract Worfklow
Dyn
amic
in
form
atio
n
Request Manager
Replica and Resource SelectorSubmission and
Monitoring System
Workflow Reduction
DataPublication
Virtual Data Language Chimera
Data Management
TransformationCatalog
Chimera is developed at ANLBy I. Foster, M. Wilde, and J. Voeckler
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Example Workflow Reduction
Original abstract workflow
If “b” already exists (as determined by query to the RLS), the workflow can be reduced
d1 d2ba c
d2b c
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Mapping from abstract to concrete
Query RLS, MDS, and TC, schedule computation and data movement
Execute d2 at B
Move b from A
to B
Move c from B
to U
Register c in the
RLS
d2b c
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LIGO-specific interface
Montage-specific
Interface
Globus MDS
Globus RLS
Chimera
User
Metadata/
VDLMetadata/
Abstract Workflow
PegasusPortal
The Grid
Metadata CatalogService
TransformationCatalog
MyProxy
DAGMan
Authentication
VDL/
Abst
ract
Wor
fklo
w
Execution
records
Abstract Workflow/
Information
Information
Concr
ete
Wor
kflo
w/
Info
rmat
ion
Jobs/Information
Information
Sim
plifi
ed V
iew
of S
C 2
003
Por
tal
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LIGO Scientific Collaboration
Continuous gravitational waves are expected to be produced by a variety of celestial objects
Only a small fraction of potential sources are known Need to perform blind searches, scanning the regions of
the sky where we have no a priori information of the presence of a source
Wide area, wide frequency searches Search is performed for potential sources of continuous
periodic waves near the Galactic Center and the galactic core
The search is very compute and data intensive LSC used the occasion of SC2003 to initiate a month-long
production run with science data collected during 8 weeks in the Spring of 2003
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LIGO Acknowledgements Bruce Allen, Scott Koranda, Brian Moe, Xavier Siemens,
University of Wisconsin Milwaukee, USA
Stuart Anderson, Kent Blackburn, Albert Lazzarini, Dan Kozak, Hari Pulapaka, Peter Shawhan, Caltech, USA
Steffen Grunewald, Yousuke Itoh, Maria Alessandra Papa, Albert Einstein Institute, Germany
Many Others involved in the Testbed
www.ligo.caltech.edu www.lsc- group.phys.uwm.edu/lscdatagrid/ http://pandora.aei.mpg.de/merlin/
LIGO Laboratory operates under NSF cooperative agreement PHY-0107417
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Montage Montage (NASA and NVO) Deliver science-grade
custom mosaics on demand
Produce mosaics from a wide range of data sources (possibly in different spectra)
User-specified parameters of projection, coordinates, size, rotation and spatial sampling.
Mosaic created by Pegasus based Montage from a run of the M101 galaxy images on the Teragrid.
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Montage Acknowledgments Bruce Berriman, John Good, Anastasia Laity,
Caltech/IPAC Joseph C. Jacob, Daniel S. Katz, JPL http://montage.ipac. caltech.edu/
Testbed for Montage: Condor pools at USC/ISI, UW Madison, and Teragrid resources at NCSA, PSC, and SDSC.
Montage is funded by the National Aeronautics and Space Administration's Earth Science Technology Office, Computational Technologies Project, under Cooperative Agreement Number NCC5-626 between NASA and the California Institute of Technology.
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Other Applications Using Chimera and Pegasus
Other GriPhyN applications: High-energy physics: Atlas, CMS (many) Astronomy: SDSS (Fermi Lab, ANL)
Astronomy: Galaxy Morphology (NCSA, JHU, Fermi,
many others, NVO-funded) Biology
BLAST (ANL, PDQ-funded) Neuroscience
Tomography (SDSC, NIH-funded)
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Current System
Original Abstract Workflow
Current Pegasus
Pegasus(Abstract Workflow)
DAGMan(CW))
Co
ncre
te W
orfklo
w
Workflow Execution
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time
Levels ofabstraction
Application-level
knowledge
Logicaltasks
Tasksbound toresources
and sent forexecution
User’sRequest
Relevantcomponents
Fullabstractworkflow
Partialexecution
Not yetexecuted
executed
Workflow refinement
Taskmatchmaker
Workflow repair
Policyinfo
Workflow Refinement and execution
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Incremental Refinement Partition Abstract workflow into partial
workflows
PW A
PW B
PW C
A Particular PartitioningNew Abstract
Workflow
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Meta-DAGMan
Pegasus(A)
Pegasus(B)
Pegasus(C)
DAGMan(Su(A))
Su(B)
Su(C)
DAGMan(Su(B))
DAGMan(Su(C))
Pegasus(X) –Pegasus generates the concrete workflow and the submit files for X = Su(X)
DAGMan(Su(X))—DAGMan executes the concrete workflow for X
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Future Directions
Incorporate AI-planning technologies in production software (Virtual Data Toolkit)
Investigate various scheduling techniques Investigating fault tolerance issues
Selecting resources based on their reliability Responding to failures
http://pegasus.isi.edu