Design Metrics in Quantum Turbulence Simulations: How Physics Influences Software Architecture

The information hiding philosophy of object‐oriented programming encourages localizing data structures within objects rather than sharing data globally across different classes of objects. This emphasis on local data leads naturally to fine‐grained data abstractions, particularly in scientific simulations involving large collections of small, discrete physical or mathematical objects. This paper focuses on a subset of such simulations where dynamically reconfigurable links bind the objects together. It is demonstrated that fine‐grained data structures reduce the complexity of local operations on the data at the potential expense of increased global operation complexity. Two metrics are used to describe data structures: granularity is the number of instantiations required to cover the data space, whereas extent is the continuously traversable length of the data along a given direction. These definitions are applied to two abstractions for simulating the turbulent motion of quantum vortices in superfluid liquid helium. Several local and global operations on a fine‐grained linked list are compared with those on a coarse‐grained array. It is demonstrated that fine‐grained data structures recover the simplicity of more coarse‐grained structures if maximal extent is maintained as the granularity increases.