LEDDS: Portable LBM-DEM simulations on GPUs
Raphael Maggio-Aprile, Maxime Rambosson, Christophe Coreixas, Jonas Latt

TL;DR
LEDDS demonstrates a portable, high-performance GPU framework for complex physics simulations using algorithmic primitives, enabling efficient LBM-DEM modeling across diverse hardware.
Contribution
It introduces LEDDS, an open-source, primitive-based GPU framework for coupled LBM-DEM simulations, emphasizing portability and performance.
Findings
Achieves performance comparable to hand-tuned CUDA solvers.
Validates simulations across various physics benchmarks.
Maintains high code clarity and portability.
Abstract
Algorithmic formulations of GPU programs provide a high-level alternative to device-specific code by expressing computations as compositions of well-defined parallel primitives (e.g., map, sort, reduce), rather than through handcrafted GPU kernels. In this work, we demonstrate that this paradigm can be extended to complex and challenging problems in computational physics: the simulation of granular flows and fluid-particle interactions. LEDDS, our open-source framework, performs fully coupled Lattice Boltzmann -- Discrete Element Method (LBM-DEM) simulations using only algorithmic primitives, and runs efficiently on single-GPU platforms. The entire workflow, including neighbor search, collision detection, and fluid-particle coupling, is expressed as a sequence of portable primitives. While the current implementation illustrates these principles primarily through algorithms from the…
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