grid computing, the concurrent application of the processing and data storage resources of many computers in a network to a single problem. It also can be used for load balancing as well as high availability by employing multiple computers—typically personal computers and workstations—that are remote from one another, multiple data storage devices, and redundant network connections. Grid computing requires the use of parallel processing software that can divide a program among as many as several thousand computers and restructure the results into a single solution of the problem. Primarily for security reasons, grid computing is typically restricted to multiple computers within the same enterprise, but a number of scientific projects—including SETI, CERN's Large Hadron Collider, and the study of protein folding—have utilized computers volunteered by individuals and connected to the Internet.

Grid computing evolved from the parallel processing systems of the 1970s, the large-scale cluster computing systems of the 1980s, and the distributed processing systems of the 1990s, and is often referred to by these names. Grid computing can make a more cost-effective use of computer resources, harnessing computer microprocessors when they otherwise would be unused, and can be applied to solve problems that require large amounts of computing power.

See A. S. Tanenbaum and M. van Steen, Distributed Systems (2001); F. Berman, G. Fox, and A. J. G. Hey, Grid Computing (2003); A. Abbas, Grid Computing (2003).