Grid computing

The SETI@home project, launched in 1999, is a widely-known example of a very simple grid computing project. Although it was not the first to use such techniques, and doesn't use all of the facilities of current grid capabilities, it has been followed by many others, covering tasks such as protein folding, research into drugs for cancer, mathematical problems and climate models. Most of these projects work by running as a screensaver on users' personal computers, which process small pieces of the overall data while the computer is either completely idle or lightly used. The first general purpose commercial grid (U.S. patent 6,463,457) was launched by Parabon Computation in 1999. A "general purpose" grid is a grid that is not "hardwired" to perform a specific task. For example, SETI@home's screensaver contains both code to processes radio telescope data and code to handle retrieving work and returning results. The two bodies of code are intertwined into a single program. In a general purpose grid, only the code required for retrieving work and returning results persists on the nodes. Code required to perform the distributed work is sent to the nodes separately. In this way, the nodes of a general purpose grid can be easily reprogrammed.

Related Topics:
SETI@home - 1999 - Protein folding - Screensaver - Parabon Computation

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Grid computing offers a model for solving massive computational problems by making use of the unused resources (CPU cycles and/or disk storage) of large numbers of disparate, often desktop, computers treated as a virtual cluster embedded in a distributed telecommunications infrastructure. Grid computing's focus on the ability to support computation across administrative domains sets it apart from traditional computer clusters or traditional distributed computing.

Related Topics:
Cluster - Embedded - Telecommunications - Distributed computing

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Grids offer a way to solve Grand Challenge problems like protein folding, financial modelling, earthquake simulation, climate/weather modelling etc. Grids offer a way of using the information technology resources optimally inside an organisation. They also provide a means for offering information technology as a utility bureau for commercial and non-commercial clients, with those clients paying only for what they use, as with electricity or water.

Related Topics:
Grand Challenge problem - Protein folding - Modelling - Earthquake - Climate - Weather - Utility - Bureau

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Grid computing has the design goal of solving problems too big for any single supercomputer, whilst retaining the flexibility to work on multiple smaller problems. Thus grid computing provides a multi-user environment. Its secondary aims are: better exploitation of the available computing power, and catering for the intermittent demands of large computational exercises.

Related Topics:
Solving problem - Supercomputer - Multi-user

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This implies the use of secure authorization techniques to allow remote users to control computing resources.

Related Topics:
Authorization - User - Computing resource

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Grid computing involves sharing heterogeneous resources (based on different platforms, hardware/software architectures, and computer languages), located in different places belonging to different administrative domains over a network using open standards. In short, it involves virtualizing computing resources.

Related Topics:
Platform - Architectures - Computer language - Network - Open standard - Virtualizing

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Grid computing is often confused with cluster computing. The key difference is the resources which comprise the grid are not all within the same administrative domain.

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Functionally, one can classify grids into several types:

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• Computational Grids (including CPU scavenging grids), which focuses primarily on computationally-intensive operations.
• Data grids, or the controlled sharing and management of large amounts of distributed data.
• Equipment Grids which have a primary piece of equipment e.g. a telescope, and where the surrounding Grid is used to control the equipment remotely and to analyse the data produced.
 
Grid computing: Definitions of Grid Computing ►