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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 10, issue 2
Geosci. Model Dev., 10, 811–826, 2017
https://doi.org/10.5194/gmd-10-811-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 10, 811–826, 2017
https://doi.org/10.5194/gmd-10-811-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Development and technical paper 21 Feb 2017

Development and technical paper | 21 Feb 2017

Enabling BOINC in infrastructure as a service cloud system

Diego Montes et al.
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Cited articles  
Allen, M.: Do-it-yourself climate prediction, Nature, 401, 642, https://doi.org/10.1038/44266, 1999.
Añel, J. A.: The importance of reviewing the code, Commun. ACM, 54, 40–41, https://doi.org/10.1145/1941487.1941502, 2011.
Añel, J. A., López-Moreno, J. I., Otto, F. E. L., Vicente-Serrano, S., Schaller, N., Massey, N., Buisán, S., and Allen, M. R.: The extreme snow accumulation in the western Spanish Pyrenees during winter and spring 2013, B. Am. Meterol. Soc., 95, S73–S76, 2014.
Anderson, D. P.: Boinc: A system for public-resource computing and storage, in: 5th IEEE/ACM International Workshop on Grid Computing, GRID 2004, Pittsburgh, USA, 8 November 2004, IEEE Computer Society Washington, DC, USA, 4–10, https://doi.org/10.1109/GRID.2004.14, 2004.
AWS: S3 Princing, available at: https://aws.amazon.com/s3/pricing/ (last access: 22 December 2016), 2016a.
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This paper discusses the how the combination of cloud and volunteer computing can be a feasible solution to address large, complex, and expensive computing problems such as climate modelling.
This paper discusses the how the combination of cloud and volunteer computing can be a feasible...
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