article

Montage: a grid portal and software toolkit for science-grade astronomical image mosaicking

Authors:

Joseph C. Jacob,

Daniel S. Katz,

G. Bruce Berriman,

Anastasia C. Laity,

Carl Kesselman,

Thomas A. Prince,

Roy WilliamsAuthors Info & Claims

International Journal of Computational Science and Engineering, Volume 4, Issue 2

Pages 73 - 87

https://doi.org/10.1504/IJCSE.2009.026999

Published: 01 July 2009 Publication History

Abstract

Montage is a portable software toolkit to construct custom, science-grade mosaics that preserve the astrometry and photometry of astronomical sources. The user specifies the dataset, wavelength, sky location, mosaic size, coordinate system, projection, and spatial sampling. Montage supports massive astronomical datasets that may be stored in distributed archives. Montage can be run on both single- and multi-processor computers, including clusters and grids. Standard grid tools are used to access remote data or run Montage on remote computers. This paper describes the architecture, algorithms, performance, and usage of Montage as both a software toolkit and a grid portal.

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Montage: a grid portal and software toolkit for science-grade astronomical image mosaicking
1. Software and its engineering
  1. Software organization and properties
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Published In

cover image International Journal of Computational Science and Engineering

International Journal of Computational Science and Engineering Volume 4, Issue 2

July 2009

62 pages

ISSN:1742-7185

EISSN:1742-7193

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Publisher

Inderscience Publishers

Geneva 15, Switzerland

Publication History

Published: 01 July 2009

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Cited By

Yildirim IDevarajan HKougkas ASun XMohror K(2023)IOMax: Maximizing Out-of-Core I/O Analysis Performance on HPC SystemsProceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis10.1145/3624062.3624191(1209-1215)Online publication date: 12-Nov-2023
https://dl.acm.org/doi/10.1145/3624062.3624191
Coleman TCasanova HFerreira da Silva R(2023)Automated generation of scientific workflow generators with WfChefFuture Generation Computer Systems10.1016/j.future.2023.04.031147:C(16-29)Online publication date: 1-Oct-2023
https://dl.acm.org/doi/10.1016/j.future.2023.04.031
Samandi VTiňo PBahsoon R(2023)Real-Time Workflow Scheduling in Cloud with Recursive Neural Network and List SchedulingHybrid Artificial Intelligent Systems10.1007/978-3-031-40725-3_21(244-255)Online publication date: 5-Sep-2023
https://dl.acm.org/doi/10.1007/978-3-031-40725-3_21
McGough AForshaw M(2022)Analysis of Reinforcement Learning for Determining Task Replication in WorkflowsComputer Performance Engineering10.1007/978-3-031-25049-1_8(117-132)Online publication date: 21-Sep-2022
https://dl.acm.org/doi/10.1007/978-3-031-25049-1_8
Mollajafari MShojaeefard M(2021)TC3PoP: a time-cost compromised workflow scheduling heuristic customized for cloud environmentsCluster Computing10.1007/s10586-021-03285-524:3(2639-2656)Online publication date: 1-Sep-2021
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Brinkmann AMohror KYu WCarns PCortes TKlasky SMiranda APfreundt FRoss RVef M(2020)Ad Hoc File Systems for High-Performance ComputingJournal of Computer Science and Technology10.1007/s11390-020-9801-135:1(4-26)Online publication date: 1-Jan-2020
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