Work

Performance evaluation of mixed-precision Runge–Kutta methods for the solution of partial differential equations

Year: 2025

Type: article

Abstract: This work focuses on the numerical study of a recently published class of Runge–Kutta methods designed for mixed-precision arithmetic. We employ the methods in solving partial differential equations on modern hardware. In particular, we investigate what speedups are achievable by the use of mixed precision and the dependence of the methods algorithmic compatibility with the computational hardware. We use state-of-the-art software, utilizing the Ginkgo library, which is designed to incorporate mixed precision arithmetic, and perform numerical tests of 3D problems on both GPU and CPU architectures. We show that significant speedups can be achieved but that performance depends on solver parameters and performance of software kernels.

Source: The International Journal of High Performance Computing Applications

DOI: 10.1177/10943420251392963

Authors: Ivo Dravins, Marcel Koch, Victoria Griehl, Katharina Kormann

Institutions: Ruhr University Bochum, Karlsruhe Institute of Technology

Language: English

Topic: Parallel Computing and Optimization Techniques

Subfield: Hardware and Architecture

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: European Commission, Bundesministerium für Bildung und Forschung

Awards: Verbundprojekt: Optimierte Softwaremethoden für die Lösung partieller Differentialgleichungen auf Exascale-Supercomputern - PDExa -, Verbundprojekt: Optimierte Softwaremethoden für die Lösung partieller Differentialgleichungen auf Exascale-Supercomputern - PDExa -