Lightweight Lattice Boltzmann

TL;DR

This paper introduces a GPU-accelerated lattice Boltzmann method that reconstructs distribution functions from hydrodynamic variables, reducing memory use and enabling efficient soft matter simulations on high-performance computers.

Contribution

It presents a novel, memory-efficient lattice Boltzmann scheme that reconstructs distributions from hydrodynamic variables, suitable for GPU acceleration and large-scale soft matter simulations.

Findings

Demonstrates satisfactory numerical stability.

Significantly reduces memory requirements.

Validates with benchmark tests on soft matter phenomena.

Abstract

A GPU-accelerated version of the lattice Boltzmann method for efficient simulation of soft materials is introduced. Unlike standard approaches, this method reconstructs the distribution functions from available hydrodynamic variables (density, momentum, and pressure tensor) without storing the full set of discrete populations. This scheme shows satisfactory numerical stability, significantly lower memory requirements, and data access cost. A series of benchmark tests of relevance to soft matter, such as collisions of fluid droplets, is discussed to validate the method. The results can be of particular interest for high-performance simulations of soft matter systems on future exascale computers.