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Published January 28, 2013 | public
Journal Article

The application of cloud computing to scientific workflows: a study of cost and performance

Abstract

The current model of transferring data from data centres to desktops for analysis will soon be rendered impractical by the accelerating growth in the volume of science datasets. Processing will instead often take place on high-performance servers co-located with data. Evaluations of how new technologies such as cloud computing would support such a new distributed computing model are urgently needed. Cloud computing is a new way of purchasing computing and storage resources on demand through virtualization technologies. We report here the results of investigations of the applicability of commercial cloud computing to scientific computing, with an emphasis on astronomy, including investigations of what types of applications can be run cheaply and efficiently on the cloud, and an example of an application well suited to the cloud: processing a large dataset to create a new science product.

Additional Information

© 2012 The Author(s). Published by the Royal Society. Published online December 10, 2012. G.B.B. is supported by the NASA Exoplanet Science Institute at the Infrared Processing and Analysis Center, operated by the California Institute of Technology in coordination with the Jet Propulsion Laboratory (JPL). Montage was funded by the National Aeronautics and Space Administration's Earth Science Technology Office, Computation Technologies Project, under Cooperative agreement number NCC5-626 between NASA and the California Institute of Technology. Montage is maintained by the NASA/IPAC Infrared Science Archive. This work was supported in part by the National Science Foundation under grants nos 0910812 (FutureGrid) and OCI-0943725 (CorralWMS). The use of Amazon EC2 resources were supported by the AWS in Education research grant. One contribution of 13 to a Theme Issue 'e-Science–towards the cloud: infrastructures, applications and research'.

Additional details

Created:
August 22, 2023
Modified:
October 23, 2023