Grid computing

Grid computing coordinates independent computers, often spread across locations and organizations, to share processing power, storage, or other resources for large tasks.

Grid middleware: Software that coordinates resource discovery, job submission, security, and data movement across a computing grid. It provides the coordination layer that lets grid resources act together.
Worldwide LHC Computing Grid: A global computing infrastructure that stores and analyzes data from experiments at CERN’s Large Hadron Collider. It is a major grid built to process particle-physics data across institutions.
Cloud computing: On-demand access to configurable computing resources delivered as services, typically through provider-managed data centers. Clouds emphasize elastic service delivery, while grids federate resources across administrative domains.
Ian Foster: A computer scientist known for foundational work on grid computing and the Globus Toolkit. His work helped define the architecture and vocabulary of grid computing.
Data locality: The principle of placing computation near the data it uses to reduce transfer costs and delays. Moving large datasets between grid sites can dominate a job’s cost and runtime.
High-throughput computing: A computing approach that maximizes the amount of computation completed over long periods, often by running many independent jobs. Grid systems commonly pursue sustained throughput across many distributed machines.
Folding@home: A distributed computing project that uses volunteered personal computers to simulate protein dynamics. It shows a volunteer-computing model distinct from institutionally coordinated grids.
Cluster computing: The use of closely connected computers, often managed as one system, to perform parallel or shared workloads. Clusters usually share centralized management and location, unlike geographically dispersed grids.
Carl Kesselman: A computer scientist whose work helped develop grid computing and its supporting software infrastructure. He co-developed influential approaches and tools for coordinating distributed resources.
Resource allocation: The assignment of limited computing resources among competing tasks or users. Grid policies must reconcile local priorities with shared community workloads.

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