Thread-safe lattice Boltzmann for high-performance computing on GPUs

TL;DR

This paper introduces a thread-safe, high-performance lattice Boltzmann method optimized for GPU architectures, improving memory efficiency and scalability for large-scale fluid dynamics simulations.

Contribution

It proposes a novel Hermite projection-based reconstruction approach that ensures data locality and thread safety, enabling efficient GPU implementation of lattice Boltzmann methods.

Findings

Achieves peak performance in 2D and 3D simulations

Reduces memory usage significantly for large-scale problems

Enables high-performance complex flow simulations on GPUs

Abstract

We present thread-safe, highly-optimized lattice Boltzmann implementations, specifically aimed at exploiting the high memory bandwidth of GPU-based architectures. At variance with standard approaches to LB coding, the proposed strategy, based on the reconstruction of the post-collision distribution via Hermite projection, enforces data locality and avoids the onset of memory dependencies, which may arise during the propagation step, with no need to resort to more complex streaming strategies. The thread-safe lattice Boltzmann achieves peak performances, both in two and three dimensions and it allows to sensibly reduce the allocated memory ( tens of GigaBytes for order billions lattice nodes simulations) by retaining the algorithmic simplicity of standard LB computing. Our findings open attractive prospects for high-performance simulations of complex flows on GPU-based architectures.