Granularity
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- See also: grain and film grain (disambiguation)
Granularity is a measure of the size of the components, or descriptions of components, that make up a system. Systems of, or description in terms of, large components are called coarse-grained, and systems of small components are called fine-grained; here coarse and fine are descriptions of the granularity of the system, or the granularity of description of the system.
An example of increasingly fine 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, etc.
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[edit] 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 Maximum entropy thermodynamics)
[edit] 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-grained, or "tightly coupled", parallelism means individual tasks are relatively small in terms of code size and execution time. The data are transferred among processors frequently in amounts of one or a few memory words. Coarse-grained, or "loosely coupled", is the opposite: data are communicated infrequently, after larger amounts of computation.
The smaller the granularity, the greater the potential for parallelism and hence speed-up, but the greater the overheads of synchronization and communication. (The last two paragraphs are based on FOLDOC.)
[edit] 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".
[edit] See also
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