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GGF10 Workflow Workshop Summary

GGF10 Workflow Workshop Summary. March 9 2004 Berlin The Organizers. Topics. General Issues Application Requirements Language/User Interface Execution Engine (Run-time) 3 Grid Workflow Issues. General Issues. Grain Size for “science” and efficiency of distributed service model

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GGF10 Workflow Workshop Summary

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  1. GGF10 WorkflowWorkshop Summary March 9 2004Berlin The Organizers

  2. Topics • General Issues • Application Requirements • Language/User Interface • Execution Engine (Run-time) • 3 Grid Workflow Issues

  3. General Issues • Grain Size for “science” and efficiency of distributed service model • Hierarchy (workflow of workflows) • Data versus Control • Security • Metadata and Provenance • Dynamic/Event based or Static • Component Models/Architecture -- CCA, OGSI, WSRF. Web Services • Error Handling (Detect, Specify action, Take action) • Ease of Use (for real users not Grid hackers) • Collaborative use by several users • Open Source?

  4. Application Requirements • Time of running (seconds to months) • People in loop • Interactivity: real-time v batch • Number of entities (10's to 100000's) • Stream-based (communicate via pipes) OR • Job-based (communicate via files) • Spatial versus temporal interactions • Multiple “workflow job” instances handled in or outside workflow

  5. Language/User Interface • Abstract versus High level (specification) versus low-level (“workflow virtual machine” ) • Virtual Data • Abstraction level • Language: Kepler, Triana. BPEL WSCL WSCI ….. • BPEL is inevitable? • Diversity via Different “towers” in BPEL • And/Or another language • Does “other language” map to BPEL as low level interoperable Workflow VM • Scripts: Perl, Python, Ant, Matlab, Specialized • Petri Nets • Functional Language specification • Graphical UI • Dataflow (stream) versus Control (message) model • Web Service ports can be data and control?

  6. Execution Engine (Run-time) • Performance • Robustness • Support Streams and Messages • Discovery of Services and Resources (computers, data repositories, networks) • Support Scheduling/Planning of tasks and/or streams and/or data resources (“Towers”?) • Support of Monitoring, Factories, Life-times etc • Type checking • Support Debugging • Support "Workflow" (Computational) Steering • Distributed versus centralized implementation

  7. 3 Grid Workflow Issues • 1) Analyze issues such as dataflow, scheduling, virtual data, “science state” • Map into WSRF and BPEL Correlation Identifiers/Extensibility or find “inadequacies”? • 2) Look at scale and data size, data locality issues in science workflow • What are implications for runtime engine? • 3) Examine Semantic Grid (metadata/ provenance) issues for workflow • 2) and 3) can be examined for both BPEL and “other approaches”

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