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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Proceedings ArticleDOI
Grid middleware services for virtual data discovery, composition, and integration
Yong Zhao,Michael Wilde,Ian Foster,Jens Voeckler,Thomas H. Jordan,Elizabeth Quigg,James E. Dobson +6 more
TL;DR: The services, architecture and application of the GriPhyN Virtual Data System, a suite of components and services that allow users to describe virtual data products in declarative terms, discover definitions and assemble workflows based on those definitions, and execute the resulting workflows on Grid resources are described.
Proceedings ArticleDOI
A Tool for Prioritizing DAGMan Jobs and Its Evaluation
TL;DR: This paper presents the design, implementation, and evaluation of a practical scheduling tool inspired by a recently developed scheduling theory, given a DAGMan input file with interdependent jobs, that significantly outperforms currently used schedules under a wide range of system parameters.
Journal ArticleDOI
Middleware support for many-task computing
Ioan Raicu,Ian Foster,Michael Wilde,Zhao Zhang,Kamil Iskra,Pete Beckman,Yong Zhao,Alexander S. Szalay,Alok Choudhary,Philip Little,C. Moretti,Amitabh Chaudhary,Douglas Thain +12 more
TL;DR: Falkon has shown orders of magnitude improvements in performance and scalability than traditional approaches to resource management across many diverse workloads and applications at scales of billions of tasks on hundreds of thousands of processors across clusters, specialized systems, Grids, and supercomputers.
Journal Article
Accelerating medical research using the swift workflow system.
Tiberiu Stef-Praun,Benjamin Clifford,Ian Foster,Ian Foster,Uri Hasson,Mihael Hategan,Steven L. Small,Michael Wilde,Michael Wilde,Yong Zhao,Yong Zhao +10 more
TL;DR: The use of Swift for medical research is described, showing how SwiftScript is used to encode an application workflow, and performance results are presented that demonstrate the ability to achieve significant speedups on both a local parallel computing cluster and multiple parallel clusters at distributed sites.
Journal ArticleDOI
Improving the analysis, storage and sharing of neuroimaging data using relational databases and distributed computing.
TL;DR: This work presents an approach that overcomes many current limitations in data analysis and data sharing based on open source database management systems that support complex data queries as an integral part of data analysis, flexible data sharing, and parallel and distributed data processing using cluster computing and Grid computing resources.