Grid computing is sometimes called virtual supercomputing, but grid computing differs from supercomputing in several important ways. A supercomputer consists of a massive set of processors running in parallel in a confined area, such as a specialized data center. The grid environment can be – and often is – distributed around the world.
Supercomputers also use high-speed networks and run highly connected applications rather than independently functional nodes. Grid systems, on the other hand, share little or no data between nodes and typically communicate over an Internet connection from geographically dispersed locations.
Grid computing is also different from cloud computing, another form of distributed computing. Cloud computing is somewhere between grid computing and supercomputing.
Cloud environments are much more granular than grid environments and can handle time-sensitive workloads more efficiently. While cloud resources can be geographically distributed, they are typically limited to just a few locations, compared to the thousands or millions of widely distributed nodes that participate in a grid network.
Grid computing is often seen as a precursor to cloud computing, which has come to play a prominent role in global computing. In fact, cloud computing may pose a threat to grid computing in the long run. Centralizing servers in the cloud leaves fewer downtime cycles to clean up local servers while reducing the number of underutilized desktops.
However, it is possible to use the cloud to support grid-based applications, either entirely or in a hybrid configuration. In this way, organizations can take advantage of some of the benefits of the cloud, such as elastic scaling and a pay-as-you-go service model, while still enjoying the advantages of the grid model. This approach can be useful for organizations that are already investing resources in maintaining network nodes.