Accuracy and performance of the lattice Boltzmann method with 64-bit, 32-bit, and customized 16-bit number formats.


Journal

Physical review. E
ISSN: 2470-0053
Titre abrégé: Phys Rev E
Pays: United States
ID NLM: 101676019

Informations de publication

Date de publication:
Jul 2022
Historique:
received: 12 01 2022
accepted: 07 06 2022
entrez: 17 8 2022
pubmed: 18 8 2022
medline: 18 8 2022
Statut: ppublish

Résumé

Fluid dynamics simulations with the lattice Boltzmann method (LBM) are very memory intensive. Alongside reduction in memory footprint, significant performance benefits can be achieved by using FP32 (single) precision compared to FP64 (double) precision, especially on GPUs. Here we evaluate the possibility to use even FP16 and posit16 (half) precision for storing fluid populations, while still carrying arithmetic operations in FP32. For this, we first show that the commonly occurring number range in the LBM is a lot smaller than the FP16 number range. Based on this observation, we develop customized 16-bit formats-based on a modified IEEE-754 and on a modified posit standard-that are specifically tailored to the needs of the LBM. We then carry out an in-depth characterization of LBM accuracy for six different test systems with increasing complexity: Poiseuille flow, Taylor-Green vortices, Karman vortex streets, lid-driven cavity, a microcapsule in shear flow (utilizing the immersed-boundary method), and, finally, the impact of a raindrop (based on a volume-of-fluid approach). We find that the difference in accuracy between FP64 and FP32 is negligible in almost all cases, and that for a large number of cases even 16-bit is sufficient. Finally, we provide a detailed performance analysis of all precision levels on a large number of hardware microarchitectures and show that significant speedup is achieved with mixed FP32/16-bit.

Identifiants

pubmed: 35974647
doi: 10.1103/PhysRevE.106.015308
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

015308

Auteurs

Moritz Lehmann (M)

Biofluid Simulation and Modeling-Theoretische Physik VI, University of Bayreuth, Bayreuth, Germany.

Mathias J Krause (MJ)

Institute of Mechanical Process Engineering and Mechanics, Karlsruhe Institute of Technology, Karlsruhe, Germany.

Giorgio Amati (G)

CINECA, SCAI-SuperComputing Applications and Innovation Department, Rome Branch, Italy.

Marcello Sega (M)

Helmholtz Institute Erlangen-Nürnberg for Renewable Energy, Erlangen, Germany.

Jens Harting (J)

Helmholtz Institute Erlangen-Nürnberg for Renewable Energy, Erlangen, Germany.
Department of Chemical and Biological Engineering and Department of Physics, Friedrich-Alexander-Universität, Erlangen, Germany.

Stephan Gekle (S)

Biofluid Simulation and Modeling-Theoretische Physik VI, University of Bayreuth, Bayreuth, Germany.

Classifications MeSH