J
Jim Blythe
Researcher at Information Sciences Institute
Publications - 109
Citations - 6075
Jim Blythe is an academic researcher from Information Sciences Institute. The author has contributed to research in topics: Workflow & Grid. The author has an hindex of 34, co-authored 108 publications receiving 5891 citations. Previous affiliations of Jim Blythe include Carnegie Mellon University & University of Maryland, College Park.
Papers
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Journal ArticleDOI
Pegasus: A framework for mapping complex scientific workflows onto distributed systems
Ewa Deelman,Gurmeet Singh,Mei-Hui Su,Jim Blythe,Yolanda Gil,Carl Kesselman,Gaurang Mehta,Karan Vahi,G. Bruce Berriman,John C. Good,Anastasia C. Laity,Joseph C. Jacob,Daniel S. Katz +12 more
TL;DR: The results of improving application performance through workflow restructuring which clusters multiple tasks in a workflow into single entities are presented.
Book ChapterDOI
Pegasus: Mapping Scientific Workflows onto the Grid
Ewa Deelman,Jim Blythe,Yolanda Gil,Carl Kesselman,Gaurang Mehta,Sonal Patil,M. H. Su,Karan Vahi,Miron Livny +8 more
TL;DR: The Pegasus system that can map complex workflows onto the Grid and takes an abstract description of a workflow and finds the appropriate data and Grid resources to execute the workflow is described.
Journal ArticleDOI
Mapping Abstract Complex Workflows onto Grid Environments
Ewa Deelman,Jim Blythe,Yolanda Gil,Carl Kesselman,Gaurang Mehta,Karan Vahi,Kent Blackburn,Albert Lazzarini,Adam Arbree,Richard Cavanaugh,Scott Koranda +10 more
TL;DR: The current ACWG based on AI planning technologies is described and it is outlined how these technologies can play a crucial role in developing complex application workflows in Grid environments.
Journal ArticleDOI
Integrating planning and learning: the PRODIGY architecture
TL;DR: This article describes the PRODIGY planner, briefly reports on several learning modules developed earlier along the project, and presents in more detail two recently explored methods to learn to generate plans of better quality.
Proceedings ArticleDOI
Task scheduling strategies for workflow-based applications in grids
TL;DR: This work identifies two families of resource allocation algorithms: task-based algorithms that greedily allocate tasks to resources, and workflow- based algorithms that search for an efficient allocation for the entire workflow.