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Workflow-Driven Science using Kepler. Ilkay Altintas, PhD San Diego Supercomputer Center, UCSD altintas@sdsc.edu. words.sdsc.edu. Scientific Workflow-Driven Science. Accelerate Workflow Design and Reuse via a Drag-and-Drop Visual Interface. Analyze Results. Facilitate Sharing.
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Workflow-Driven Science using Kepler Ilkay Altintas, PhD San Diego Supercomputer Center, UCSD altintas@sdsc.edu words.sdsc.edu
Scientific Workflow-Driven Science Accelerate Workflow Design and Reuse via a Drag-and-Drop Visual Interface Analyze Results Facilitate Sharing Schedule, Run and Monitor Workflow Execution Reporting Workflow Execution • Experiment-oriented workflow notebook • Moving large-scale data efficiently Run Review Workflow Scheduling and Execution Planning Workflow Design Deploy and Publish Workflow Monitoring Provenance Analysis SHARE BUILD RUN LEARN Support for end-to-end computational scientific process • Building multi-scale workflows that enable large scale model assembly • Tracking provenance for reproducibility
Ptolemy II: A laboratory for investigating design KEPLER: A problem-solving environment for Scientific Workflow KEPLER = “Ptolemy II + X” for Scientific Workflows Kepler is a Scientific Workflow System www.kepler-project.org • A cross-project collaboration … initiated August 2003… 2.4 released 04/2013 • Builds upon the open-source Ptolemy II framework
A Typical Kepler Workflow A green box is called an ‘actor’ , which performs a task. Data flow is divided. This special actor represents an annotation component, such as BLAST search. Workflow parameters, which can be specified by users in the portal, are passed to workflow components.
Ptolemy II Kepler is a Team Effort NIMROD/K Cross-project collaboration Initiated August 2003 Kepler 2.4 release: April, 2013 Full list of contributors, projects, individuals and funding info are at the Kepler website!!
Data Science Workflows in Kepler- Programmable Scalability - Real-Time Hazards Management wifire.ucsd.edu Data-Parallel Bioinformatics bioKepler.org • Access and query data • Scale computational analysis • Increase reuse • Save time, energy and money • Formalize and standardize kepler-project.org words.sdsc.edu Scalable Automated Molecular Dynamics and Drug Discovery nbcr.ucsd.edu