A parallel workload balanced and memory efficient lattice-Boltzmann algorithm with single unit BGK relaxation time for laminar Newtonian flows

A parallel workload balanced and memory efficient lattice-Boltzmann algorithm for laminar Newtonian fluid flow through large porous media is investigated. It relies on a simplified LBM scheme using a single unit BGK relaxation time, which is implemented by means of a shift algorithm and comprises an even fluid node partitioning domain decomposition strategy based on a vector data structure. It provides perfect parallel workload balance, and its two-nearest-neighbour communication pattern combined with a simple data transfer layout results in 20–55% lower communication cost, 25–60% higher computational parallel performance and 40–90% lower memory usage than previously reported LBM algorithms. Performance tests carried out using scale-up and speed-up case studies of laminar Newtonian fluid flow through hexagonal packings of cylinders and a random packing of polydisperse spheres on two different computer architectures reveal parallel efficiencies with 128 processors as high as 75% for domain sizes comprising more than 5 billion fluid nodes.