miniLB: A Performance Portability Study of Lattice-Boltzmann Simulations

TL;DR

This paper introduces miniLB, a SYCL-based Lattice Boltzmann Method mini-application, to evaluate and improve performance portability across heterogeneous GPU architectures, providing insights for optimizing large-scale fluid dynamics simulations.

Contribution

We present miniLB, the first SYCL-based LBM mini-app, to analyze performance portability and compare it with a tuned FORTRAN version across multiple GPU architectures.

Findings

miniLB effectively assesses LBM performance on diverse hardware.

SYCL semantics influence performance portability.

miniLB provides insights for optimizing large-scale LBM frameworks.

Abstract

The Lattice Boltzmann Method (LBM) is a computational technique of Computational Fluid Dynamics (CFD) that has gained popularity due to its high parallelism and ability to handle complex geometries with minimal effort. Although LBM frameworks are increasingly important in various industries and research fields, their complexity makes them difficult to modify and can lead to suboptimal performance. This paper presents miniLB, the first, to the best of our knowledge, SYCL-based LBM mini-app.miniLB addresses the need for a performance-portable LBM proxy app capable of abstracting complex fluid dynamics simulations across heterogeneous computing systems. We analyze SYCL semantics for performance portability and evaluate miniLB on multiple GPU architectures using various SYCL implementations. Our results, compared against a manually-tuned FORTRAN version, demonstrate effectiveness of miniLB in assessing LBM performance across diverse hardware, offering valuable insights for optimizing large-scale LBM frameworks in modern computing environments.