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Cloud Computing

Cloud Computing. And Gartner predicts that by 2012, 20% percent of businesses will have no ownership of IT assets. Roy Campbell University of Illinois at Urbana-Champaign. Gartner’s View. Motivation. Economic parallel processing for Data intensive computing, Service provisioning,

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Cloud Computing

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  1. Cloud Computing And Gartner predicts that by 2012, 20% percent of businesses will have no ownership of IT assets Roy Campbell University of Illinois at Urbana-Champaign

  2. Gartner’s View

  3. Motivation • Economic parallel processing for • Data intensive computing, • Service provisioning, • Spatial scientific computing, • Embarrassingly parallel computation, • Fast prototyping Meeting requirements for elastic and scalable computing needs without concerns for power, maintenance, thermal conditioning

  4. Above the Clouds (Berkeley) • Experience with very large datacenters • Unprecedented economies of scale • Other factors • Pervasive broadband Internet • Fast x86 virtualization • Pay-as-you-go billing model • Standard software stack

  5. NCSA Cloud Computing Opportunities • As a Platform • Spatial Scientific computing • Data intensive computing • Embarrassingly parallel computations • As a Service • Accelerators, Application, Software, Platform, Infrastructure, Storage • Managed service provider • Internet integration • Educational • Web • Utility

  6. Scientific Computing • Toolkits: • K Keahey, R Figueiredo, J Fortes, T FreemanThe Nimbus CloudKit • R. Farivar, A. Verma, R. Campbell, Mithras (GGPU Cloud) • New HPC Areas: • Forees into Social networking • Computational models: • Coupled Atmosphere-Ocean Climate Models ConstantinosEvangelinos and Chris N. Hill • Watersheds • Monte Carlo methods, David Ceperely; Black Scholes, RHC • Genetic Algorithms, Gene Alignment, RHC • Flood Grid and the Polar Grid Portal Marlon E. Pierce1, Geoffrey C. Fox, Yu Ma, Jun Wang

  7. Principal Trends • Large enterprises are building their own private clouds. • Cloud computing will shift the skills needed by IT workers • IT departments will shrink as users go directly to the cloud for IT resources. • Concerns about information security will abate as CIOs “get” the cloud paradigm. • Professional services will be bundled with commodity cloud services. • SMBs, Government and University data processing, as well as large enterprises, will be run on the cloud. • Cloud-computing resources will become more customizable. • Large enterprises will become part-time cloud-computing vendors. • Support for mobile clients. • Cloud computing will unleash innovation. Local constraints on energy costs and capacities; space requirements for IT infrastructure; and up-front costs will disappear as companies become able to tap computing resources situated anywhere on the planet. • The browser will be all the desktop software you need. http://www.focus.com/articles/hosting-bandwidth/top-10-cloud-computing-trends/

  8. Driving Forces • Scientific Computation “as a service” • Eucalyptus, Dryad, Map/Reduce,… • Commoditization – Atom chip clouds (storage). Clouds on a chip Intel SCC • Inexpensive memory – RAMCLOUD Ousterhout, Flash, Phase Change, Memristor. • Vsphere commercial cloud OS. • 10 Gigabit or better networking

  9. Vendors • http://www.rackspacecloud.com hosting • http://www.cohesiveft.com/ Cloud Container Solutions • http://eucalyptus.com/ Open source Amazon • http://elastichosts.com/ European Cloud • http://www.flexiscale.com/ Utility computing • http://www.skytap.com/ Virtualization • http://www.rightscale.com/ Management • http://gogrid.com/ Services • http://gigaspaces.com/ Application platforms

  10. References • Arutyun I. Avetisyan, Roy Campbell, Indranil Gupta, Michael T. Heath, Steven Y. Ko, Gregory R. Ganger, Michael A. Kozuch, David O'Hallaron, Marcel Kunze, Thomas T. Kwan, Kevin Lai, Martha Lyons, Dejan S. Milojicic, Hing Yan Lee, YengChaiSoh, Ng Kwang Ming, Jing-Yuan Luke, Han Namgoong, "Open Cirrus: A Global Cloud Computing Testbed," Computer, vol. 43, no. 4, pp. 35-43, April, 2010. • Scientific Computing in the Cloud, J. J. Rehr, J. P. Gardner, M. Prange, L. Svec and F. Vila, Department of Physics, University of Washington, Seattle, WA 98195 serial and parallelized versions of the widely used x-ray spectroscopy and electronic structure code FEFF • Using Clouds for Metagenomics: A Case Study, Jared Wilening, Argonne National Lab. Cluster 2009 • Science CloudsEarly Experiences in Cloud Computing for Scientific Applications, Kate Keahey and Tim Freeman • The Nimbus Cloud: http://workspace.globus.org/clouds/nimbus.html. • Hoffa, C., T. Freeman, G. Metha, E. Deelman, and K. Keahey, Exploration of the Applicability of Cloud Computing to Large-Scale Scientific Workflows. to be submitted to SWBES08: Challenging Issues in Workflow Applications, 2008. • Matsunaga, A., M. Tsugawa, and J. Fortes, CloudBLAST: Combining MapReduce and Virtualization on Distributed Resources for Bioinformatics Applications. submitted to eScience 2008, 2008. • Scientific Computing in the Cloud, John Rehr, Fernando Vila, Jeffrey Gardner, Lukas Svec, Micah Prange, "Scientific Computing in the Cloud," Computing in Science and Engineering, vol. 99, no. 1, pp. , , 5555. • R. Buyya, C. S. Yeo, S. Venugopal, J. Broberg, and I. Brandic. “Cloud Computing and Emerging IT Platforms: Vision, Hype, and Reality for Delivering Computing as the 5th Utility,” Future Generation Computer Systems, vol. 25, no. 6, June 2009, pp 599–616, Elsevier Science, Amsterdam, The Netherlands. • High-Performance Cloud Computing: A View of Scientific Applications, Christian Vecchiola1, Suraj Pandey1, and RajkumarBuyya • M. Armbrust, A. Fox, R. Griffith, A. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica, M. Zaharia. Above the Clouds: A Berkeley View of Cloud computing. Technical Report No. UCB/EECS-2009-28, University of California at Berkley, USA, Feb. 10, 2009. • K. Keahey, T. Freeman. “Science Clouds: Early Experiences in Cloud computing for Scientific Applications,” Cloud Computing and Its Applications 2008 (CCA-08), Chicago, IL. October 2008. • C. Evangelinos, C. N. Hill, “Cloud Computing for Parallel Scientific HPC Applications: Feasibility of Running Coupled Atmosphere-Ocean Climate Models on Amazon's EC2,” Cloud Computing and Its Applications 2008 (CCA-08), Chicago, IL. October 2008.

  11. “the moral of this story is, just because something is over-hyped doesn’t mean its still not important.  Ignore the cloud at your peril” Gartner summary

  12. Questions?

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