Cluster computing links multiple computers to act as a single entity for high-performance computing tasks. It is used for redundancy in computer networks, website hosting, game servers, and high-performance computing projects. Grid computing distributes workloads across many computers, such as in @home projects.
Cluster computing is a form of computing in which a group of computers are linked together so that they can act as a single entity. There are a variety of reasons why people use cluster computers for computing tasks, ranging from an inability to afford a single computer with the processing capacity of a cluster, to a desire to ensure that a computer system is always available. The precise date this technique was developed is unknown, and there are competing claims for credit for the invention, with some people suggesting that individual users likely independently developed it to meet their computing needs long before the technique was used in industrial environments.
A common reason for using cluster computing is the desire to create redundancy in a computer network to ensure that it is always available and does not fail. A common application for this form of computing is website hosting, with the cluster distributing the visitor load across a number of machines so that many visitors can be hosted. This technique is also used for game servers used by large groups, to avoid lag and access problems.
High availability (HA) cluster computing is often used in this way, to create a redundant network that will always be accessible to users, with fail-safe systems in case parts of the cluster fail. Load balancing clusters are designed to handle a large load of incoming requests, coordinating requests to maximize efficiency and usability.
Another application is in large projects that require high performance computing. Some calculations are extremely complex and require the use of multiple computers that can communicate rapidly with each other, as changes in one can change the entire system. For example, simulations used to test theories in meteorology are often run on computing clusters. Without a cluster, computation may be impossible to perform or processing may take a long time.
Cluster computing can also be used to distribute a workload in the form of many small blocks of data, a technique known as grid computing. In this case, a single computer couldn’t handle all the work, but many small computers could. The various @home projects use this technique to distribute a data processing workload across a huge network that includes many home computers that are busy doing work when idle.
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