Term: Granularity

– Precision and ambiguity
– Coarse-grained materials/systems have fewer, larger discrete components than fine-grained ones.
– Coarse-grained description regards large subcomponents.
– Fine-grained description regards smaller components composing larger ones.
– Granularity, coarseness, and fineness are relative concepts.
– Example of increasing granularity: list of nations, states/provinces, cities, etc.

– Physics
– Fine-grained system description is detailed and exhaustive.
– Coarse-grained description smooths over fine details.
– Replacement of fine-grained with coarse-grained model is coarse-graining.
– Relevant in contexts like the second law of thermodynamics.
– Coarse-grained models critical for studying biological processes.

– Molecular dynamics
– Coarse-graining in molecular dynamics replaces atomistic descriptions with lower-resolution models.
– Models developed for investigating longer time- and length-scale dynamics.
– Applicable to both biological and inorganic molecules.
– Coarse-graining may remove certain degrees of freedom.
– Bound by the desired accuracy in replicating dynamics and structural properties.

– Computing
– Granularity in parallel computing is computation-to-communication ratio.
– Fine-grained parallelism involves small tasks and frequent data transfer.
– Coarse-grained parallelism involves infrequent data communication after more computation.
– Balance between load and communication overhead crucial for parallel performance.
– Optimal granularity level minimizes communication overhead and load imbalance.

– Reconfigurable computing and supercomputing
– Fine-grained computing uses one-bit wide processing elements like CLBs in FPGA.
– Coarse-grained computing uses wider data paths like microprocessor CPUs.
– Terms refer to data path width in reconfigurable computing and supercomputing.
– Fine-grained reconfigurability vs. coarse-grained reconfigurability.
– Different widths have implications for processing and data handling.

– Data and information
– Granularity of data refers to size of sub-divided data fields.
– Coarse granularity records data in fewer fields.
– Fine granularity records data in multiple fields.
– Overheads in data input and storage increase with finer granularity.
– Data grain can refer to smallest unique combination of columns in a table.

Concrete Leveling Solutions