Category:	Science and Technology
Domain:	Computer Science
Keywords:	Computer Science - supercomputing, grid computing, cluster computing, utility computer, on-demand computing
Outlook:	New applications for supercomputing may develop over the next decade as large-scale supercomputing services become accessible over broadband terrestrial and wireless Internet networks by 2015.
Summary Analysis:	Today, effective applications of supercomputing are mostly limited to industries such as petroleum and energy, aircraft and automotive design, and pharmaceuticals. Over time, these capabilities will migrate to mass markets as new applications in media, gaming, and ubiquitous computing will demand increasing speed and require massive computing resources. The major computer and Internet companies are already recognising and tapping into the huge market opportunity this offers. On-demand supercomputing is only one of many names for the idea of very high-performance computing programs linking supercomputer systems across broadband networks. This technology, currently under development in a whole family of research programs, is also known as grid computing, autonomic computing, adaptable computing, cluster computing, utility computing, and agile IT. The intention is to make computational power accessible in the same way that electricity is available from the electric grid -- users simply plug into it without worrying about where the power is coming from or how it got there. In this method of computing, if more computing power is required, spare cycles on other computers are used. This means that the power of supercomputing is accessible without the huge costs of supercomputing, and that CPU cycles that would otherwise be wasted are put to good use. So far, the fundamental building blocks of most research grids are commodity microprocessors linked into Linux clusters. According to a DARPA study released July 16, 2005, only a fraction of available online high-performance computing resources are actually being used. The main reason for this is the difficulty and expense of programming new applications. But given the relentless progress of multicore and nanoscale processor design, the demand will increase for programmers to learn how to program massively parallel and threaded applications. By 2015 the programming obstacles to development could largely be solved. On-demand supercomputing may increasingly be used for ordinary pervasive computing, sensor nets, speech recognition, language translation, image recognition, online games, and ubiquitous media. Additionally, industries will increasingly benefit from capabilities to casually use huge numerical models, very high-resolution simulations, and real-time interactive graphic models. For instance, media companies like George Lucas’s Industrial Light and Magic, Steven Speilberg’s Dreamworks, and Steve Jobs’s Pixar Productions are already using massively parallel process to render movie graphics. Increasingly, media companies are sending jobs over the Internet to centralised ‘render farms’ rather than maintaining their own computing resources. Those that do maintain their own render-farms can sell spare clock-cycles to others. Interestingly, the idea of using networking to share computer power rather than just data is not new – it was the original role conceived for the Internet. Contrary to popular belief, the Internet was not originally conceived as a communication medium. Arpanet (the precursor to the Internet) was designed to give geographically distant researchers access to computing resources because the only alternative – building computers in every institution – was, in the 1960s, too expensive to be considered. The idea of linking researchers through their computers only came later.

	Implications:	Decreased cost and expanded availability of supercomputing to ordinary computer users Enhanced photo-realistic capabilities for interactive entertainment and other new high-resolution media Potential for enhanced signal-sensing and cryptographic applications
	Early Indicators:	Current offerings by IBM, HP, Sun, Oracle, SAS, and others of grid service extensions to existing ASP-hosted Web services Google's use of a massively distributed load-balanced network of thousands of generic Linux computers to build one of the largest and fastest growing cluster-based services, offering anyone on the Web free storage of videos and unlimited mail storage, and offering professional users of a premium version of Google Earth a broadcast quality, real-time interactive, zoomable, navigable globe of the Earth Current offerings by Yahoo, Microsoft, and AOL of services using massive distributed resources Current offering by Apple's XGrid of instant distributed computing capabilities for any application The emergence of commercial 'render-farms' selling services over the Internet to special effects houses and film studios The development of grid computing Increasing number of applications for distributed computing
	What to Watch:	Rate of consumer adoption of high-resolution graphic network applications like multiplayer games, Google Earth, Microsoft Virtural Earth, and Internet HDTV shows a steady increase. Applications for interactive high-resolution graphics continue to expand in enterprises like pharmaceuticals and energy production.
	Parallels/Precedents:	The early design and motivation of Arpanet (the precursor to the Internet)
	Enablers/Drivers:	Increasing supply of skilled programmers of massively parallel applications Continued research that improves the ease of use of software development programs for massively parallel and threaded applications
	Leaders:	Regions: UK, US, Europe, Asia Institutions: Globus Alliance (development of the Globus Toolkit for grid computing by an international community of researchers, and responsibility for the reference implementations of defacto standards for grid computing) [link] National e-Science Centre (support of research into grid computing architecture) [link] Google (construction of one of the largest and fastest-growing cluster-based services) Sun (September 2004 introduction of a managed, on-demand grid computing service starting at $1 per processor per hour) CPUShare [link] Australian Partnership for Advanced Computing [link] UK Research Councils' E-Science Programme [link] Heriot-Watt University [link] University of Westminster, Centre for Parallel Computing [link] European Commission Information Society directorate general [link] Grid Computing Info Centre [link]
	Figures:
	Sources:	Graham, Susan L., Marc Snir, and Cynthia A. Patterson, Editors. "Getting Up To Speed: The Future Of Supercomputing," Washington, D.C: The National Academies Press. 2004 [link] Joseph, Earl, Addison Snell , Christopher G. Willard, Ph.D., Suzy Tichenor, Dolores Shaffer, Steve Conway. "High Performance Computing Software Survey." Defense Advanced Research Projects Agency, Council on Competitiveness. IDC. July 2005 [link] Joseph, Earl, Christopher Willard, Phd. Addison Snell. "Survey of US HPC Industrial Users." Defense Advanced Research Projects Agency, Council on Competitiveness. IDC. July 2004 [link] Marson, Ingrid. "Grid computing 'overhyped'." ZDNet UK. 19 May 2005. [link] Pawlikowski, Andrew and Donald C. McNickle. "Grid Computing: the Current State and Future Trends." University of Canterbury, Christchurch, New Zealand. [link] "Google and Akamai: Cult of Secrecy vs. Kingdom of Openness: The king of search is tapping into what may be the largest grid of computers on the planet." [link] Tsuruoka, Doug. "Three Years Later, On-Demand Remains Palmisano Quest." Investors Business Daily. 8 May 2005. Ian Foster, The Grid [link] Background paper on Grid Computing [link] Oracle Grid Computing [link] IBM, Fundamentals of Grid Computing [link]

	At A Glance:	When:	3–10 years
		Where:	Global
		How Fast:	Years
		Likelihood:	Medium-High
		Impact:	Medium-Low
		Controversy:	Low

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