Granularity
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Granularity(also calledgraininess) is the degree to which a material orsystemis composed ofdistinguishablepieces,"granules"or"grains"(metaphorically). It can either refer to the extent to which a larger entity is subdivided, or the extent to which groups of smaller indistinguishable entities have joined together to become larger distinguishable entities.
Precision and ambiguity[edit]
Coarse-grainedmaterials or systems have fewer, larger discrete components thanfine-grainedmaterials or systems.
- Acoarse-graineddescription of a system regards large subcomponents.
- Afine-graineddescription regards smaller components of which the larger ones are composed.
The conceptsgranularity,coarseness,andfinenessare relative; and are used when comparing systems or descriptions of systems. An example of increasingly fine granularity: a list of nations in theUnited Nations,a list of all states/provinces in those nations, a list of all cities in those states, etc.
Physics[edit]
Afine-graineddescription of a system is a detailed, exhaustive, low-level model of it. Acoarse-graineddescription 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 calledcoarse-graining.(See for examplethe second law of thermodynamics)
Molecular dynamics[edit]
Inmolecular dynamics,coarse grainingconsists of replacing an atomistic description of a biological molecule with a lower-resolution coarse-grained model that averages or smooths away fine details.
Coarse-grained models have been developed for investigating the longer time- and length-scale dynamics that are critical to many biological processes, such as lipid membranes and proteins.[1]These concepts not only apply to biological molecules but also inorganic molecules.
Coarse graining may remove certaindegrees of freedom,such as the vibrational modes between two atoms, or represent the two atoms as a single particle. The ends to which systems may be coarse-grained is simply bound by the accuracy in the dynamics and structural properties one wishes to replicate. This modern area of research is in its infancy, and although it is commonly used in biological modeling, the analytic theory behind it is poorly understood.
Computing[edit]
Inparallel computing,granularity means the amount ofcomputationin relation to communication, i.e., the ratio of computation to the amount of communication.[2]
Fine-grained parallelism means individual tasks are relatively small in terms of code size and execution time. The data is transferred among processors frequently in amounts of one or a few memory words. Coarse-grained is the opposite: data is communicated infrequently, after larger amounts of computation.
The finer the granularity, the greater the potential for parallelism and hence speed-up, but the greater the overheads of synchronization and communication.[3]Granularity disintegrators exist as well and are important to understand in order to determine the accurate level of granularity.[4]
In order to attain the best parallel performance, the best balance between load and communication overhead needs to be found. If the granularity is too fine, the performance can suffer from the increased communication overhead. On the other side, if the granularity is too coarse, the performance can suffer from load imbalance.
Reconfigurable computing and supercomputing[edit]
Inreconfigurable computingand insupercomputingthese terms refer to the data path width. The use of about one-bit wide processing elements like the configurable logic blocks (CLBs) in anFPGAis called fine-grained computing or fine-grained reconfigurability, whereas using wide data paths, such as, for instance, 32 bits wide resources, likemicroprocessorCPUsor data-stream-driven data path units (DPUs) like in a reconfigurable datapath array (rDPA) is called coarse-grained computing or coarse-grained reconfigurability.
Data and information[edit]
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Thegranularityof data refers to the size in which data fields are sub-divided. For example, a postal address can be recorded, withcoarse granularity,as a single field:
- address = 200 2nd Ave. South #358, St. Petersburg, FL 33701-4313 USA
or withfine granularity,as multiple fields:
- street address = 200 2nd Ave. South #358
- city = St. Petersburg
- state = FL
- postal code = 33701-4313
- country = USA
or even finer granularity:
- street = 2nd Ave. South
- address number = 200
- suite/apartment = #358
- city = St. Petersburg
- state = FL
- postal-code = 33701
- postal-code-add-on = 4313
- country = USA
Finer granularity hasoverheadsfor data input and storage. This manifests itself in a higher number ofobjectsandmethodsin theobject-oriented programmingparadigm or moresubroutinecalls forprocedural programmingandparallel computingenvironments. It does however offer benefits in flexibility of data processing in treating each data field in isolation if required. A performance problem caused by excessive granularity may not reveal itself untilscalabilitybecomes an issue.
Withindatabase designanddata warehousedesign,data graincan also refer to the smallest combination of columns in a table which makes the rows (also called records) unique.[5]
See also[edit]
Notes[edit]
- ^Kmiecik, S.; Gront, D.; Kolinski, M.; Wieteska, L.; Dawid, A. E.; Kolinski, A. (2016)."Coarse-Grained Protein Models and Their Applications".Chemical Reviews.116(14): 7898–936.doi:10.1021/acs.chemrev.6b00163.PMID27333362.
- ^Spacey et al. 2012.
- ^FOLDOC
- ^"Software Architecture: The Hard Parts".Thoughtworks.Retrieved2023-01-15.
- ^Data grain: What granularity means in terms of data modeling
References[edit]
- de Pablo, J. J. (2011). "Coarse-grained simulations of macromolecules: From DNA to nanocomposites".Annual Review of Physical Chemistry.62:555–74.Bibcode:2011ARPC...62..555D.doi:10.1146/annurev-physchem-032210-103458.PMID21219152.
- Spacey, S.; Luk, W.; Kelly, P. H. J.; Kuhn, D. (2012). "Improving Communication Latency with the Write-Only Architecture".Journal of Parallel and Distributed Computing.72(12): 1617–1627.doi:10.1016/j.jpdc.2012.08.007.