Scheduling strategies for enabling meteorological simulation on hybrid clouds

Journal of Computational and Applied Mathematics - Tập 273 - Trang 438-451 - 2015
Alfonso Quarati1, Emanuele Danovaro1, Antonella Galizia1, Andrea Clematis1, Daniele D’Agostino1, Antonio Parodi2
1Institute of Applied Mathematics and Information Technologies, National Research Council of Italy, Genoa, Italy#TAB#
2CIMA Research Foundation, Savona, Italy

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Tài liệu tham khảo

Shukla, 2010, Toward a new generation of world climate research and computing facilities, Bull. Am. Meteorol. Soc., 91, 1407, 10.1175/2010BAMS2900.1

Michalakes, 2008, WRF nature run, J. Phys.: Conf. Ser., 125, 1

Clematis, 2012, DRIHM: distributed research infrastructure for hydro-meteorology, 149

Marru, 2008, LEAD cyberinfrastructure to track real-time storms using SPRUCE urgent computing, CTWatch Q., 4, 5

The Weather Research & Forecasting model, http://wrf-model.org/index.php.

Michalakes, 1998, 117

W.C. Skamarock, J.B. Klemp, J. Dudhia, D.O. Gill, D.M. Barker, M.G. Duda, X.Y. Huang, W. Wang, J.G. Powers, A description of the advanced research WRF Version 3, NCAR/TN-475+STR, NCAR TECHNICAL NOTE, June 2008.

Michalakes, 2008, GPU acceleration of numerical weather prediction, Parallel Process. Lett., 18, 531, 10.1142/S0129626408003557

V. Simek, R. Dvorak, F. Zboril, J. Kunovsky, Towards accelerated computation of atmospheric equations using CUDA, in: IEEE Proceedings of the International Conference on Computer Modelling and Simulation, 2009, pp. 449–454.

Michalakes, 2008, WRF nature run, SciDAC 2008, J. Phys.: Conf. Ser., 125

WRF V3 parallel benchmark page. http://www.mmm.ucar.edu/wrf/WG2/bench/.

GPU acceleration of NWP: Benchmark kernels web page: http://www.mmm.ucar.edu/wrf/WG2/GPU/.

User-oriented WRF Benchmarking collection. http://weather.arsc.edu/WRFBenchmarking/index.html.

Fiori, 2010, Turbulence closure parameterization and grid spacing effects in simulated supercell storms, J. Atmospheric Sci., 67, 3870, 10.1175/2010JAS3359.1

Fowley, 2013, A comparison framework and review of service brokerage solutions for Cloud architectures

D’Agostino, 2013, A QoS-aware broker for hybrid clouds, Computing, 95, 89, 10.1007/s00607-012-0254-4

J. Hellerstein, The use of the Cloud for e-Science, in: IEEE Proceedings of the 8th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS’13, 2013, p. 1.

e-IRG Task Force on Cloud Computing, cloud computing for research and science: a holistic overview, policy, and recommendations, e-IRG Techincal Report, 2012. Available at: http://www.e-irg.eu/images/stories/dissemination/e-irg_Cloud_computing_paper_v.final.pdf.

J. Li, D. Agarwal, M. Humphrey, C. van Ingen, K. Jackson, Y. Ryu, eScience in the Cloud: a MODIS satellite data reprojection and reduction pipeline in the windows azure platform, in: Proceedings of the 24th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2010, April 19–23, Atlanta, Georgia, 2010.

Shi, 2012, Hybrid cloud computing platform for hazardous chemicals releases monitoring and forecasting, J. Comput., 7, 2306, 10.4304/jcp.7.9.2306-2311

Tablan, 2013, GATECloud.net: a platform for large-scale, open-source text processing on the Cloud, Phil. Trans. R. Soc. A, 371, 10.1098/rsta.2012.0071

Cofino, 2007, A web portal for regional projection of weather forecast using GRID middleware, vol. 4489, 82

K.A. Brewster, D.B. Weber, S. Marru, K.W. Thomas, D. Gannon, K. Droegemeier, J. Alameda, S.J. Weiss, On-demand severe weather forecasts using TeraGrid via the LEAD portal, in: Proceedings of the Third Annual TeraGrid Conference, 2008.

O. Terzo, L. Mossucca, A. Albanese, R. Vigna, N.P. Premachandra, A distributed environment approach for a worldwide rainfall hydrologic analysis, in: IEEE Proceeding of the International Conference on Complex, Intelligent, and Software Intensive Systems, 2011, pp. 271–276.

T. Einfalt, A. Lobbrechtm, I. Poortinga, Decision support for urban drainage using radar data of HydroNET-SCOUT, in: Proceeding of the International Symposium on Weather Radar and Hydrology, IAHS, 2011.

D.K. Krishnappa, D. Irwin, E. Lyons, M. Zink, CloudCast: cloud computing for short-term mobile weather forecasts, in: IEEE proceeding of the 31st International Performance Computing and Communications Conference, IPCCC, 2012, pp. 61–70.

V. Fernandez-Quiruelas, J. Fernandez Fernandez, A.S. Cofino, L. Fita, WRF4G: The Weather Research Forecasting model workflow for the GRID, in: EGU General Assembly Conference Abstracts, vol. 12, 2010, p. 12973.

Davidović, 2010, Grid implementation of the weather research and forecasting model, Earth Sci. Inf., 3, 199, 10.1007/s12145-010-0060-5

Ploski, 2009, Grid-based deployment and performance measurement of the Weather Research & Forecasting model, Future Gener. Comput. Syst., 25, 346, 10.1016/j.future.2008.05.003

Menascé, 2004

Nou, 2007, Building online performance models of grid middleware with fine-grained load-balancing: a globus toolkit case study, vol. 4748, 125

Martinez, 2009, Experimental study of large-scale computing on virtualized resources, 35

Duran-Limon, 2011, Using lightweight virtual machines to achieve resource adaptation in middleware, IET Software, 5, 229, 10.1049/iet-sen.2009.0091