M
Michael Wilde
Researcher at Argonne National Laboratory
Publications - 132
Citations - 7060
Michael Wilde is an academic researcher from Argonne National Laboratory. The author has contributed to research in topics: Workflow & Scripting language. The author has an hindex of 36, co-authored 131 publications receiving 6613 citations. Previous affiliations of Michael Wilde include University of Chicago & United States Department of Energy.
Papers
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Journal ArticleDOI
OpenMx: An Open Source Extended Structural Equation Modeling Framework
Steven M. Boker,Michael C. Neale,Hermine H. Maes,Michael Wilde,Michael Spiegel,Timothy R. Brick,Jeffrey R. Spies,Ryne Estabrook,Sarah Kenny,Timothy C. Bates,Paras D. Mehta,John Fox +11 more
TL;DR: The OpenMx data structures are introduced—these novel structures define the user interface framework and provide new opportunities for model specification and a discussion of directions for future development.
Proceedings ArticleDOI
Chimera: a virtual data system for representing, querying, and automating data derivation
TL;DR: The Chimera virtual data system is developed, which combines avirtual data catalog for representing data derivation procedures and derived data, with a virtual data language interpreter that translates user requests into data definition and query operations on the database.
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The Open Science Grid
Ruth Pordes,Don Petravick,Bill Kramer,Doug Olson,Miron Livny,Alain Roy,Paul Avery,Kent Blackburn,Torre Wenaus,Frank Würthwein,Ian Foster,Robert Gardner,Michael Wilde,Alan Blatecky,John McGee,Rob Quick +15 more
TL;DR: The Open Science Grid provides support for and evolution of the infrastructure through activities that cover operations, security, software, troubleshooting, addition of new capabilities, and support for existing and engagement with new communities.
Journal ArticleDOI
Swift: A language for distributed parallel scripting
TL;DR: This work presents Swift's implicitly parallel and deterministic programming model, which applies external applications to file collections using a functional style that abstracts and simplifies distributed parallel execution.
Proceedings ArticleDOI
Swift: Fast, Reliable, Loosely Coupled Parallel Computation
Yong Zhao,Mihael Hategan,Ben Clifford,Ian Foster,G. von Laszewski,Veronika Nefedova,Ioan Raicu,T. Stef-Praun,Michael Wilde +8 more
TL;DR: Swift adopts and adapts ideas first explored in the GriPhyN virtual data system, improving on that system in many regards and describes application experiences and performance experiments that quantify the cost of Swift operations.