Grid Computing

Listen to the Computerworld TechCast: Grids

In a sort of digital interpretation of the adage, "Waste not, want not," the basic idea of grid computing is to use the computational power of idle PCs and harness those heretofore wasted cycles to form a virtual supercomputer.

The most well-known grid computing implementation—as well as the world's largest distributed computer—is that of the Search for Extraterrestrial Intelligence project (SETI@home).

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A brainchild of the University of California, Berkeley, SETI@home uses idle, Internet-connected PCs all over the globe to supplement the work done on a supercomputer at the Berkeley campus . SETI@home has raised awareness of grid computing, but it has also relegated it to the realm of science fiction in many people's minds.

On the contrary, thanks to advances in grid computing's underlying technology, businesses can use their networks to undertake complex computing tasks such as designing machinery and performing what-if scenarios based on vast financial databases. Someday, it may be possible for grid computing service providers to create virtual supercomputers and rent processing time to businesses anywhere in the world.

Grid computing works by distributing computational resources but maintaining central control of the process. A central server acts as a team leader and traffic monitor.

This controlling cluster server divides a task into subtasks, then assigns the work to computers with surplus processing power on the grid. It also monitors the processing and, if the subtask routine fails, it will restart or reassign it. When all the subtasks have been completed, the controlling cluster server aggregates the results and advances to the next task until the whole job is completed.

In a grid campus, a hierarchical structure of many grid servers may handle subtasks, but all processing occurs on a single network.

In a global grid, machines can be on many different networks and on the Web. Because they're processing in so many different circumstances, network latency can be a problem. But before any processing can occur, available resources must be identified and located. Access to them must be negotiated, and the hardware and software must be configured to effectively use the resources, which often are many smaller computers.

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