Grids vs Clusters
Grid computing and cluster computing are often confused, and for good reason as they are very similar in nature. Both involve the combination (in some form) of different resources into a "single" whole that works towards a particular purpose (if you are unfamiliar with cluster computing read our overview to HPC first.) Some say that clusters are strictly homogenous computing, but that is not quite accurate since clusters can run multiple operating systems across different nodes.
The biggest difference with grid computing is simply the scope and sacle. Grid represents a bigger framework and architecture, and focuses on the broader scope or objective. It incorporates many of the key characteristics of clusters, and clusters often become one of the many components of grids. By enabling the sharing, selection, and aggregation of a wide variety of geographically distributed resources including supercomputers, storage systems, data sources, and specialized devices, grid computing allows large organizations and separate organizations to collaborate internally and amongst themselves.
Put in one sentence, clusters can fit into grid architecture and grid computing for the ultimate sharing of resources at a higher level of aggregation.
