M
Mihael Hategan
Researcher at University of Chicago
Publications - 29
Citations - 1859
Mihael Hategan is an academic researcher from University of Chicago. The author has contributed to research in topics: Grid computing & Grid. The author has an hindex of 16, co-authored 28 publications receiving 1775 citations. Previous affiliations of Mihael Hategan include Argonne National Laboratory.
Papers
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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.
Proceedings ArticleDOI
GridAnt: a client-controllable grid workflow system
TL;DR: This paper discusses the design principles, functionality, and application of the proposed GridAnt workflow manager, an extensible client-side workflow management system, called GridAnt, developed.
Journal ArticleDOI
Parallel Scripting for Applications at the Petascale and Beyond
Michael Wilde,Ian Foster,Kamil Iskra,Pete Beckman,Zhao Zhang,Allan Espinosa,Mihael Hategan,Ben Clifford,Ioan Raicu +8 more
TL;DR: Parallel scripting extends this technique to allow for the rapid development of highly parallel applications that can run efficiently on platforms ranging from multicore workstations to petascale supercomputers.
Journal ArticleDOI
Computing environments for reproducibility: Capturing the “Whole Tale”
Adam Brinckman,Kyle Chard,Kyle Chard,Niall Gaffney,Mihael Hategan,Mihael Hategan,Matthew B. Jones,Kacper Kowalik,Sivakumar Kulasekaran,Bertram Ludäscher,Bryce Mecum,Jarek Nabrzyski,Victoria Stodden,Ian Taylor,Ian Taylor,Matthew J. Turk,Kandace Turner +16 more
TL;DR: The Whole Tale project as discussed by the authors aims to connect computational, data-intensive research efforts with the larger research process, transforming the knowledge discovery and dissemination process into one where data products are united with research articles to create "living publications" or tales.