Grids seem to be a natural evolution in the history of distributed computing. If you look at some of the early supercomputers, these machines were refrigerator-size cabinets that would divide the computing workload among multiple processors. Then came clusters, groups of relatively cheap, off-the-shelf computers, typically PCs running Linux, that would form large parallel processing systems sprawling across entire rooms, buildings, or even campuses. But with computer networks becoming faster and cheaper, some researchers figured that an even more diverse and dispersed union of machines would be possible.

These researchers envisioned an infrastructure that, unlike supercomputers or clusters, would be owned, managed, and used by multiple organizations. And instead of a monolithic hardware and software design, this infrastructure would run on a mix of operating systems, file systems, and networking technologies. Thus emerged the idea of grid computing, and a bunch of grid pioneers went to work on realizing that vision. Ian Foster of the Argonne National Laboratory, in Illinois, and Carl Kesselman of the University of Southern California, in Los Angeles, were among the pioneers, and in 1998 they published The Grid: Blueprint for a New Computing Infrastructure (Morgan Kaufmann), a book that became an instant bible for the new field.

At least in theory, grids would include all kinds of systems: supercomputers, giant clusters, and desktop PCs, as well as storage devices, databases, sensors, and scientific instruments. But although many grid projects are evolving in that direction, most still amass a more homogeneous collection of systems.

The EGEE grid consists mainly of multiple clusters of PCs—some institutions have a dozen machines, others thousands—connected to “farms” of disk servers and specialized magnetic tape silos that are used for backup and long-term storage of data. The grid relies on the Internet and on high-speed, dedicated research networks to distribute computing tasks among the clusters owned by different parties, just as if the machines were sitting in the same room. Of the EGEE's networks, the most important is called Géant2, an academic fiber-optic backbone that links 34 European countries and has connections to similar research networks elsewhere in the world.

The sheer computational power of some supercomputers today still exceeds EGEE's, although that could change someday, depending on how fast this grid grows and how quickly it can join forces with other major national and international grid efforts. For example, the Open Science Grid, a U.S. initiative that already links a large number of data centers in more than 50 institutions, mirrors in many ways the European Union's grid initiative and should be interoperable with EGEE soon. In Japan, a project called the National Research Grid Initiative is developing a grid infrastructure for science very similar to EGEE, and collaboration between the projects has already started.

But the fact is that such grids, even joined together, won't replace supercomputers quite yet. Some problems—certain types of climate simulations, for instance—involve calculations that are so intertwined that a supercomputer's multiple processors need to exchange data at dazzlingly fast speeds, a capability difficult to achieve with grids. Grids like EGEE aim at what's called high-throughput computing—dealing with large amounts of similar but independent calculations. In other words, the applications that benefit best from grids are those that can be chopped into many smaller pieces and processed in parallel.

Although grids remain mostly an academic research tool, they are making strides into the corporate world. Many large firms, after investing in technology for e-business, customer relationship management, and supply chain systems, are now putting computing grids high on their acquisition lists. Early adopters include financial institutions, some of which are using grids to perform sophisticated risk analysis, and pharmaceutical companies, which are using grids to study the effects of new drugs.

With an eye on this market, all the major computer vendors, including Hewlett-Packard, IBM, Microsoft, and Sun, now offer hardware and software that enable servers, PCs, and mainframes to tap into the power of a grid. Useful though such commercial offerings are, they can't yet manage the number of computers, networks, and systems in a massive grid like the EGEE. What's more, different vendors ended up developing different grid technologies. So unlike the Web—developed at CERN, incidentally—which is based on a common set of standards, existing grids are based on a wide variety of technologies. The field, it seems, is too immature for any one company to risk launching products and services on a large scale. Industry in this case adopted a wait-and-see policy, letting the academic community take the lead, as has often happened with emerging technologies.

Indeed, this is why major grid projects still need public funding. International grid initiatives such as EGEE aim to take the grid model one step further by developing and testing computing, networking, and security technologies and pushing for common standards. This complements the efforts of international standards bodies, such as the Global Grid Forum, which champions technological convergence and interoperability.

But despite such efforts toward standardization, the term grid computing—as is often the case with technological buzzwords—has come to mean different things to different people. A source of confusion is the concept of on‑demand or utility computing created by computer vendors. The idea is that a customer needing extra processing power can tap into a vendor's data center, paying for what it uses. This is an interesting concept, but it doesn't strictly require grid technology.

And then there are systems for scavenging computing power such as SETI@home, the popular screen saver that relies on ordinary people's PCs to search radio-astronomy data for signs of extraterrestrial intelligence. Considering that SETI@home has been downloaded onto more than 5 million PCs around the globe, the ambitions of a project such as EGEE to federate 100 000 computers seem modest by comparison. But the similarities belie major differences. The sort of scientific software running on the EGEE grid involves complex configurations and requires reliable and secure data transfers that casually connected PCs cannot provide.