WHEN is a grid not a grid? It depends whom you ask. According to many in the computer industry, grid computing—which roughly means the harnessing of the collective processing power of many computers in different places—is here today, and is already widespread. Yet according to others, grid computing, while promising, is still years away from becoming a reality. Who is right?
The problem is that “grid” has been co-opted as a buzzword and applied to a number of entirely different things. The term “grid computing” was originally coined by Ian Foster of America's Argonne National Laboratory in the late 1990s. He meant to draw an analogy between the supply of computing power and the supply of electricity, which is delivered along a wire, when you need it and with no need to worry about where it came from.
In 2002, Dr Foster drew up his own three-part definition of grid computing. A grid, he proposed, should co-ordinate computing resources that are not centrally controlled, rely on open standards, and provide more reliability than stand-alone machines. Alas for Dr Foster, his checklist immediately raised hackles within the computer industry, since much existing “grid computing” software fails to meet these criteria. Linking many small computers together to create a more powerful machine, for example, is not new, and is usually called clustering. For marketing purposes, however, some firms like to call it grid instead.
Similarly, grid is often confused—sometimes deliberately, for marketing reasons—with equally nebulous terms such as utility computing, on-demand computing, autonomic computing and data-centre virtualisation. Behind all this terminology is the idea of continuously and automatically adjusting the configuration of a corporate data-centre to meet the demands made on it. But Andrew Chien, a grid pioneer at the University of California at San Diego, notes that though useful, such approaches generally eschew the harder part of the grid vision, which requires automated sharing of computing resources between different organisations, not just within one firm.
A well-known example of the sharing of computing resources across the internet is SETI@home, in which over half a million people help to sift radio-telescope readings for evidence of extraterrestrial life using a glorified screensaver running on their PCs. Other similar projects, such as IBM's new World Community Grid, conduct medical research. But David Anderson, the director of SETI@home, rejects the grid label, preferring the term “public resource computing”. Others call it “internet computing” or “cycle scavenging”. While it is grid-like in some respects, this approach is very task-specific and is centrally controlled—so it is not truly grid.
Some firms, such as United Devices, sell proprietary software for cycle scavenging within a single company. Idle PCs can, for example, run drug-design software in a pharmaceuticals company or evaluate a derivatives portfolio for a financial-services firm. Early adopters of this technology claim impressive benefits. Yet since all the resources are controlled by a single organisation, purists argue that this is at best an “intragrid”, just as an intranet is a private, internal version of the internet.
What of those deliberately decentralised systems, peer-to-peer file-sharing networks? Some of them, at least, operate using open standards, and they are certainly robust: repeated attempts to close them down have failed (see article). But they do not count as grid computing either, since they are mostly storage and distribution systems, and do not perform general purpose data-processing.
Grid computing is not entirely fictional, however: scientists have been building grids on a national or even global scale for several years. A good example is the LHC Computing Grid, which links large clusters and storage systems in 87 computer centres around the world, for the benefit of particle physicists. Another example is TeraGrid, an American effort to link nine large supercomputing centres for scientific use. Even within the academic arena, though, convergence towards common standards is slow, partly because each grid project tends to reinvent the wheel. To tackle this problem, the European Union launched a major initiative called EGEE this year to provide a common grid infrastructure for scientists; America has a similar initiative.
The hope is that such projects will provide the first glimpse of “the grid”, a single global computing grid that will do for data processing what the world wide web did for online publishing. Wolfgang Gentzsch, a former grid guru at Sun Microsystems who is now director of MCNC, North Carolina's statewide grid initiative, says the term “grid” really refers to this ultimate goal, towards which today's systems are merely stepping stones. But it would, he admits, be more accurate to refer to them as “grid-like” or using “grid technology”.
Constructing a single, global grid will mean solving difficult security, privacy and billing problems. Scientists have a tradition of sharing their results and resources, but others do not. Yet the hurdles are not so much technological as political, economic and terminological. The dream of a single grid, akin to the web in its simplicity and pervasiveness, still seems a long way off—as does agreement about what “grid” really means.