2026-08-13 –, Room 3
TrixiParticles.jl is an open-source framework for accessible particle-based multiphysics. In this talk, we demonstrate how to leverage modern, GPU-centric HPC hardware for complex fluid–structure interaction (FSI) simulations. Using a carbon-fiber freediving fin as a case study, we discuss the numerical challenges of extremely stiff and thin blades, and present performance benchmarks across different CPU and GPU architectures to showcase cross-platform efficiency.
TrixiParticles.jl is an open-source numerical simulation framework designed for accessible particle-based multiphysics simulations and implemented in Julia as part of the Trixi Framework. Two years after introducing the package at JuliaCon 2024, we return to demonstrate how the framework leverages modern HPC hardware to support both rapid prototyping and complex applications.
In the first part of the talk, we present the latest developments in GPU usability and performance.
As modern clusters become increasingly GPU-centric, simulation software must adapt to utilize this hardware effectively. We show how TrixiParticles.jl allows users to seamlessly run simulations on GPUs with minimal code changes, and present benchmarks comparing modern dual-socket CPU nodes against various GPU architectures.
In the second part, we take a "deep dive" into a challenging real-world application: the hydrodynamics of a carbon-fiber freediving fin. Simulating the propulsion generated by a foot-driven, extremely stiff, and thin blade presents significant numerical difficulties, particularly regarding Fluid-Structure Interaction (FSI). We will discuss numerical instabilities caused by the high stiffness and thin geometry of the carbon-fiber blade.
PhD Student in the Numerical Simulation Group at University of Cologne, Germany.