Granularity

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See also: grain (disambiguation)

Granularity is the extent to which a system contains discrete components of ever-smaller size. An example of increasing granularity: a list of nations in the United Nations, a list of all states/provinces in those nations, a list of all counties in those states, and so on until you have a list of all people in the countries that belong to the U.N.

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In physics

A fine-grained description of a system is a detailed, low-level model of it. A coarse-grained description is a model where some of this fine detail has been smoothed over or averaged out. The replacement of a fine-grained description with a lower-resolution coarse-grained model is called coarse graining. (See for example the view of the second law of thermodynamics in the article MaxEnt thermodynamics)

In computing

In parallel computing, granularity means the amount of computation in relation to communication, i.e., the ratio of computation to the amount of communication.

"Fine-grain, or tightly coupled, parallelism" means individual tasks are relatively small in terms of code size and execution time. The data are transferred among processors infrequently. "Coarse grain", or loosely coupled, is the opposite: data are communicated frequently in amounts of one or a few memory words.

The smaller the granularity, the greater the potential for parallelism and hence speed-up but the greater the overheads of synchronisation and communication. (The last two paragraphs are base on FOLDOC.)

In credit portfolio risk management

In credit portfolio risk modeling, granularity refers to the number of the exposures in the portfolio. The higher the granularity, the more positions are in a credit portfolio, providing a higher degree of size diversification, which in turn reduces concentration risk. This is colloquially known as "not putting all your eggs in one basket".

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