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1Ilkay ALTINTAS- September, 2013
Ilkay ALTINTAS, Ph.D.
San Diego Supercomputer Center, UCSD
http://users.sdsc.edu/~altintas
Roles and Challenges for!
Scientific Workflows and Provenance !
in the Age of Open Science, !
Cloud Computing and Web 2.0!
2Ilkay ALTINTAS- September, 2013
Workflows are a Part of Cyberinfrastructure!
Workflow
Design!
!
Reporting!
!
Workflow
Monitoring!
!
Workflow
Execution!
!
!
Workflow
Scheduling
and
Execution
Planning!
!
!
Run!
Review!
!
Provenance
Analysis!
!
!
Deploy!
and!
Publish!
!
Accelerate
Workflow Design
and Reuse via a
Drag-and-Drop
Visual Interface
Facilitate
Sharing
Schedule, Run and
Monitor Workflow
Execution
Promote Learning
Support for end-to-end computational scientific process
BUILD SHARE RUN LEARN
3Ilkay ALTINTAS- September, 2013
What motivated this?!
4Ilkay ALTINTAS- September, 2013
Facilitating and Accelerating XXX-Info or 

Comp-XXX Research using Scientific Workflows!
•  Important Attributes"
– Assemble complex processing easily"
– Access transparently to diverse resources "
– Incorporate multiple software tools "
– Assure reproducibility "
– Build around community development model "
5Ilkay ALTINTAS- September, 2013
In addition, workflows today are…!
•  Encapsulations of scientific knowledge"
•  Easy to share bits of scientific process"
– e.g., as research objects"
•  Mostly portable"
•  Facilitate and encourage reproducible science"
– Track provenance at each step of science… "
•  Key integrator for (big and small) data science"
•  A means to standardize scientific data
products"
6Ilkay ALTINTAS- September, 2013
Pushing the boundaries of
scientific computing created
new requirements.!
7Ilkay ALTINTAS- September, 2013
The ‘bioinformatics’ Bottleneck!
•  Resources needed for sequence analysis far
exceed the costs of sequence generation"
– Cloud computing is an attractive on-demand
decentralized model"
– Need new scheduling capabilities"
•  on-demand access to a shared configurable resources "
•  networks, servers, storage, applications, and services"
– Need ability to easily combine users environment
and community tools together with workflow "
– Various tools with different profiles"
8Ilkay ALTINTAS- September, 2013
The ‘sensor data’ bottleneck!
•  Data streaming in at various rates"
•  “Big Data” by definition in its volume, variety,
velocity and viscosity"
– Workflows can improve veracity and add value by
providing provenance- and standards-aware on-
the-fly archival capabilities"
– Workflows can QA/QC and automate (real-time)
analysis of streaming data before it is even
archived."
9Ilkay ALTINTAS- September, 2013
The ‘HPC’ bottleneck!
•  Scaling for exascale not happening very
naturally"
– Different memory architectures"
– Analysis codes being redeveloped"
– Just scheduling through the batch schedulers not
enough"
– HPC workflows are becoming more interactive "
– In-situ data analysis to deal with volumes of data"
10Ilkay ALTINTAS- September, 2013
As users see the value, they say:!
•  Increase reuse "
–  best development practices by the scientific community"
–  other bio packages"
•  Increase programmability by end users"
–  users with various skill levels "
–  to formulate actual domain specific workflows"
•  Increase resource utilization"
–  optimize execution across available computing resources "
–  in an efficient, transparent and intuitive manner"
•  Make workflows a part of the end-to-end scientific
model from data generation to publication"
11Ilkay ALTINTAS- September, 2013
What are some next steps?!
•  Specialize workflow systems with domain-specific "
–  Tools; Data models and formats; User interfaces;
Deployment "
•  Workflow publications and data repositories"
–  Treat workflows same as data"
–  Strong virtualization capability"
•  Standards for provenance needed"
–  For data and for process"
•  Build upon prior knowledge by detecting best
practice programming patterns and motifs"
•  Cater to cater to different hardware architectures"
12Ilkay ALTINTAS- September, 2013
Ilkay Altintas
altintas@sdsc.edu
@ilkayaltintas @bioKepler
@KeplerWorkflow @WIFIREProject
Thanks! & Questions…!
How to download Kepler?
https://kepler-project.org/users/downloads
Please start with the short Getting Started Guide:
https://kepler-project.org/users/documentation

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Invited Talk for EUDAT Workshop in Barcelona

  • 1. 1Ilkay ALTINTAS- September, 2013 Ilkay ALTINTAS, Ph.D. San Diego Supercomputer Center, UCSD http://users.sdsc.edu/~altintas Roles and Challenges for! Scientific Workflows and Provenance ! in the Age of Open Science, ! Cloud Computing and Web 2.0!
  • 2. 2Ilkay ALTINTAS- September, 2013 Workflows are a Part of Cyberinfrastructure! Workflow Design! ! Reporting! ! Workflow Monitoring! ! Workflow Execution! ! ! Workflow Scheduling and Execution Planning! ! ! Run! Review! ! Provenance Analysis! ! ! Deploy! and! Publish! ! Accelerate Workflow Design and Reuse via a Drag-and-Drop Visual Interface Facilitate Sharing Schedule, Run and Monitor Workflow Execution Promote Learning Support for end-to-end computational scientific process BUILD SHARE RUN LEARN
  • 3. 3Ilkay ALTINTAS- September, 2013 What motivated this?!
  • 4. 4Ilkay ALTINTAS- September, 2013 Facilitating and Accelerating XXX-Info or 
 Comp-XXX Research using Scientific Workflows! •  Important Attributes" – Assemble complex processing easily" – Access transparently to diverse resources " – Incorporate multiple software tools " – Assure reproducibility " – Build around community development model "
  • 5. 5Ilkay ALTINTAS- September, 2013 In addition, workflows today are…! •  Encapsulations of scientific knowledge" •  Easy to share bits of scientific process" – e.g., as research objects" •  Mostly portable" •  Facilitate and encourage reproducible science" – Track provenance at each step of science… " •  Key integrator for (big and small) data science" •  A means to standardize scientific data products"
  • 6. 6Ilkay ALTINTAS- September, 2013 Pushing the boundaries of scientific computing created new requirements.!
  • 7. 7Ilkay ALTINTAS- September, 2013 The ‘bioinformatics’ Bottleneck! •  Resources needed for sequence analysis far exceed the costs of sequence generation" – Cloud computing is an attractive on-demand decentralized model" – Need new scheduling capabilities" •  on-demand access to a shared configurable resources " •  networks, servers, storage, applications, and services" – Need ability to easily combine users environment and community tools together with workflow " – Various tools with different profiles"
  • 8. 8Ilkay ALTINTAS- September, 2013 The ‘sensor data’ bottleneck! •  Data streaming in at various rates" •  “Big Data” by definition in its volume, variety, velocity and viscosity" – Workflows can improve veracity and add value by providing provenance- and standards-aware on- the-fly archival capabilities" – Workflows can QA/QC and automate (real-time) analysis of streaming data before it is even archived."
  • 9. 9Ilkay ALTINTAS- September, 2013 The ‘HPC’ bottleneck! •  Scaling for exascale not happening very naturally" – Different memory architectures" – Analysis codes being redeveloped" – Just scheduling through the batch schedulers not enough" – HPC workflows are becoming more interactive " – In-situ data analysis to deal with volumes of data"
  • 10. 10Ilkay ALTINTAS- September, 2013 As users see the value, they say:! •  Increase reuse " –  best development practices by the scientific community" –  other bio packages" •  Increase programmability by end users" –  users with various skill levels " –  to formulate actual domain specific workflows" •  Increase resource utilization" –  optimize execution across available computing resources " –  in an efficient, transparent and intuitive manner" •  Make workflows a part of the end-to-end scientific model from data generation to publication"
  • 11. 11Ilkay ALTINTAS- September, 2013 What are some next steps?! •  Specialize workflow systems with domain-specific " –  Tools; Data models and formats; User interfaces; Deployment " •  Workflow publications and data repositories" –  Treat workflows same as data" –  Strong virtualization capability" •  Standards for provenance needed" –  For data and for process" •  Build upon prior knowledge by detecting best practice programming patterns and motifs" •  Cater to cater to different hardware architectures"
  • 12. 12Ilkay ALTINTAS- September, 2013 Ilkay Altintas altintas@sdsc.edu @ilkayaltintas @bioKepler @KeplerWorkflow @WIFIREProject Thanks! & Questions…! How to download Kepler? https://kepler-project.org/users/downloads Please start with the short Getting Started Guide: https://kepler-project.org/users/documentation