Dennis Gannon
ABSTRACT
Microsoft Research is now in its fourth year of awarding Windows Azure cloud resources to the academic community. As of April 2014, over 200 research projects have started. In this paper we review the results of this effort to date. We also characterize the computational paradigms that work well in public cloud environments and those that are usually disappointing. We also discuss many of the barriers to successfully using commercial cloud platforms in research and ways these problems can be overcome.
- http://www.reasearch.microsoft.com/azureGoogle Scholar
- Keith R. Jackson, Lavanya Ramakrishnan, Krishna Muriki, Shane Canon, Shreyas Cholia, John Shalf, Harvey J. Wasserman, and Nicholas J. Wright. 2010. Performance Analysis of High Performance Computing Applications on the Amazon Web Services Cloud. In Proceedings of the 2010 IEEE Second International Conference on Cloud Computing Technology and Science (CLOUDCOM '10). IEEE Computer Society, Washington, DC, USA, 159--168. DOI=10.1109/CloudCom.2010.69. Google ScholarDigital Library
- Lavanya Ramakrishnan, Piotr T. Zbiegel, Scott Campbell, Rick Bradshaw, Richard Shane Canon, Susan Coghlan, Iwona Sakrejda, Narayan Desai, Tina Declerck, and Anping Liu. 2011. Magellan: experiences from a science cloud. In Proceedings of the 2nd international workshop on Scientific cloud computing (ScienceCloud '11). ACM, New York, NY, USA, 49--58. DOI=10.1145/1996109.1996119. Google ScholarDigital Library
- M. Humphrey, N. Beekwilder, J. Goodall, and M. Ercan. Calibration of Watershed Models using Cloud Computing. Proceedings of the 8th IEEE International Conference on eScience (eScience 2012). Oct 8--12 2012. Google ScholarDigital Library
- AzureBlast: a case study of developing science applications on the cloud., Wei Lu, Jared Jackson, Roger S. Barga. 01/2010; DOI:10.1145/1851476.1851537 In proceeding of: Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing, HPDC 2010, Chicago, Illinois, USA, June 21--25, 2010. Google ScholarDigital Library
- Radu Tudoran, Alexandru Costan, Gabriel Antoniu, Hakan Soncu. "TomusBlobs: Towards Communication-Efficient Storage for MapReduce Applications in Azure." In Proc. 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid'2012), May 2012, Ottawa, Canada. Google ScholarDigital Library
- Puri, S., Agarwal D., He, X., and Prasad, S.K. MapReduce algorithms for GIS Polygonal Overlay Processing, in: IEEE International Parallel and Distributed Processing Symposium workshops, to appear, Boston, USA, May 2013 Google ScholarDigital Library
- Thompson, J.M., N.G. Sgourakis, G. Liu, P. Rossi, Y. Tang, J.L. Mills, T. Szyperski, G.T. Montelione, and D. Baker, Accurate protein structure modeling using sparse NMR data and homologous structure information. Proceedings of the National Academy of Sciences, 2012. 109(25): p. 9875--9880.Google Scholar
- Nabeel M. Mohamed, Heshan Lin, Wuchun Feng. Accelerating Data-Intensive Genome Analysis in the Cloud. In Proceedings of the 5th International Conference on Bioinformatics and Computational Biology (BICoB), Honolulu, Hawaii, USA, March 2013.Google Scholar
- Thilina Gunarathne, Judy Qiu, and Geoffrey Fox, Iterative MapReduce for Azure Cloud in CCA11 Cloud Computing and Its Applications. April 12--13, 2011. Chicago, ILL.Google Scholar
- Wilkins-Diehr, N.; Gannon, D.; Klimeck, G.; Oster, S.; Pamidighantam, S., "TeraGrid Science Gateways and Their Impact on Science," Computer, vol.41, no.11, pp.32--41, Nov. 2008 doi: 10.1109/MC.2008.470 Google ScholarDigital Library
- Ignacio Blanquer, Goetz Brasche, Jacek Cala, Fabrizio Gagliardi, Dennis Gannon, Hugo Hiden, Hakan Soncu, Kenji Takeda, Andrés Tomás, Simon Woodman, Supporting NGS pipelines in the cloud, 2013 - journal.embnet.orgGoogle Scholar
- J Cała, H Hiden, S Woodman, P Watson, Fast Exploration of the QSAR Model Space with e-Science Central and Windows Azure. 2012 - esciencecentral.co.ukGoogle Scholar
- Neo D. Martinez, Perrine Tonin, Barbara Bauer, Rosalyn C. Rael, Rahul Singh, Sangyuk Yoon, Ilmi Yoon , and Jennifer A. Dunne, Sustaining Economic Exploitation of Complex Ecosystems in Computational Models of Coupled Human-Natural Networks, Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2013.Google Scholar
- http://fetchclimate.cloudapp.net/Google Scholar
- Matthew J. Smith, Paul I. Palmer, Drew W. Purves, Mark C. Vanderwel, Vassily Lyutsarev, Ben Calderhead, Lucas N. Joppa, Christopher M. Bishop, and Stephen Emmott, Changing how Earth System Modelling is done to provide more useful information for decision making, science and society., in Bulletin of the American Meteorological Society, American Meteorological Society, February 2014Google Scholar
- DataUp: Describe, Manage and Share Your Data, http://dataup.cdlib.org and http://research.microsoft.com/en-us/projects/dataup/Google Scholar
- Dazhi Chong, Kurt Maly, Elizabeth Rasnick, Harris Wu and Mohammad Zubair, "Social Curation of large multimedia collections on the cloud", Digital Humanities 2012, Hamburg, Germany, July 16--22, 2012Google Scholar
- B Howe, F Ribalet, S Chitnis, G Armbrust, D Halperin, SQLShare: Scientific Workflow Management via Relational View Sharing - 2013 Computing in Science and Engineering 15:22--31. Google ScholarDigital Library
- http://www.flickr.com/photos/britishlibrary/Google Scholar
- http://mechanicalcurator.tumblr.com/Google Scholar
- http://vmdepot.msopentech.com/List/IndexGoogle Scholar
- http://thedata.org/Google Scholar
- http://research.microsoft.com/apps/video/default.aspx?id=175587Google Scholar
- Clouds in Space: Scientific Computing using Windows Azure, Steven J Johnston*, Neil S O'Brien, Hugh G Lewis, Elizabeth E Hart, Adam White and Simon J Cox, Journal of Cloud Computing: Advances, Systems and Applications 2013, 2:2Google Scholar
Index Terms
- Science in the cloud: lessons from three years of research projects on microsoft azure
Recommendations
Cloud computing - The business perspective
The evolution of cloud computing over the past few years is potentially one of the major advances in the history of computing. However, if cloud computing is to achieve its potential, there needs to be a clear understanding of the various issues ...
Comparing public and private iaas cloud models
RIIT '14: Proceedings of the 3rd annual conference on Research in information technologyTo better understand the advantages and disadvantages of deploying a private cloud or employing a public cloud for computing resources, a fully featured private cloud of infrastructure as a service (IaaS) was built from bare metal servers using Xen ...
Comments