What is granularity?

Granularity indicates how the system is divisible. Fine -grained systems that have high granularity are divided into a larger number of smaller parts, while the coarse -grained system has a smaller number of larger parts. For example, the weight measurement of the object in ounces is more detailed than measuring the weight of the same object in pounds, which is granular than tonne measurement. This concept is important in many areas, including science, computer technology and business.

In parallel computer processing, this term concerns how the tasks are divided. The fine -grained parallel processing divides the task into a large number of smaller tasks, usually a short duration, while the coarse -grained parallel processing has larger longer tasks. The finer granularity increases the amount of work that can be done simultaneously, so it is potentially faster, but at the cost of requiring multiple resources to communicate between processors.

Granularity is also used to describe data distribution. Low granularity data is divided into a small number of fields, burdenMCO data with high granularity is divided into a larger number of more specific areas. For example, a recording of the physical characteristics of a high data could have separate fields for height, weight, age, sex, sex, hair color, eye color, etc., while low data record would notice the same information in a smaller number of more general areas and even lower records would give all information in one field. Greater granularity increases more flexible data by allowing more specific parts to be processed separately, but requires larger computing sources.

In physical sciences, this term concerns the level of details in scientific models. The fine -grained model is highly detailed, while the coarse -grained model of the low -level diameter at a low level rather than displaying them individually. For example, a fine -grained computer model interaction between atoms will model them at a subatomical level according to the laws of quantum mechanics, while somewhat coarser models can handle the entire atom core as one pointICE, which is then modeled according to classical physics, and still starts with a single unit as a single unit. Coarse -grained models are less accurate, but require less computing forces for modeling a given system than fine -grained models. They also allow modeling of large systems that would be impractical or impossible to portray on finer models.

This concept is also used in business and finance. In banking, granularity in the risk of loan portfolio management concerns the diversity of portfolio. Highly granular portfolios have a larger number of exposures extended in different economic areas, which protects the bank from large, suddenly due to the default value of a single large debtor or a decline in one industry. The term may also refer to a similar principle to reducing the risk of investment in shares, bonds or currencies.