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The performance of lattice-Boltzmann solver implementations usually depends mainly on memory access patterns. Achieving high performance requires then complex code which handles careful data placement and ordering of memory transactions. In…

分布式、并行与集群计算 · 计算机科学 2021-08-31 Tadeusz Tomczak

We describe a high-performance implementation of the lattice-Boltzmann method (LBM) for sparse geometries on graphic processors. In our implementation we cover the whole geometry with a uniform mesh of small tiles and carry out calculations…

分布式、并行与集群计算 · 计算机科学 2018-05-30 Tadeusz Tomczak , Roman G. Szafran

Computational fluid dynamics (CFD) requires a vast amount of compute cycles on contemporary large-scale parallel computers. Hence, performance optimization is a pivotal activity in this field of computational science. Not only does it…

分布式、并行与集群计算 · 计算机科学 2015-12-24 M. Wittmann , T. Zeiser , G. Hager , G. Wellein

We describe a high-performance implementation of the lattice Boltzmann method (LBM) for sparse 3D geometries on graphic processors (GPU). The main contribution of this work is a data layout that allows to minimise the number of redundant…

分布式、并行与集群计算 · 计算机科学 2017-10-10 Tadeusz Tomczak , Roman G. Szafran

A high-performance implementation of a multiphase lattice Boltzmann method based on the conservative Allen-Cahn model supporting high-density ratios and high Reynolds numbers is presented. Metaprogramming techniques are used to generate…

流体动力学 · 物理学 2020-12-14 Markus Holzer , Martin Bauer , Ulrich Rüde

Sparse-dense linear algebra is crucial in many domains, but challenging to handle efficiently on CPUs, GPUs, and accelerators alike; multiplications with sparse formats like CSR and CSF require indirect memory lookups. In this work, we…

硬件体系结构 · 计算机科学 2020-12-15 Paul Scheffler , Florian Zaruba , Fabian Schuiki , Torsten Hoefler , Luca Benini

The lattice Boltzmann method exhibits excellent scalability on current supercomputing systems and has thus increasingly become an alternative method for large-scale non-stationary flow simulations, reaching up to a trillion grid nodes.…

分布式、并行与集群计算 · 计算机科学 2016-05-11 Florian Schornbaum , Ulrich Rüde

High-performance computing systems are more and more often based on accelerators. Computing applications targeting those systems often follow a host-driven approach in which hosts offload almost all compute-intensive sections of the code…

分布式、并行与集群计算 · 计算机科学 2017-05-15 E. Calore , A. Gabbana , S. F. Schifano , R. Tripiccione

Current GPU-accelerated supercomputers promise to enable large-scale simulations of turbulent flows. Lattice Boltzmann Methods (LBM) are particularly well-suited to fulfilling this promise due to their intrinsic compatibility with highly…

计算物理 · 物理学 2025-06-30 Adrian Kummerländer , Fedor Bukreev , Yuji Shimojima , Shota Ito , Mathias J. Krause

We present thread-safe, highly-optimized lattice Boltzmann implementations, specifically aimed at exploiting the high memory bandwidth of GPU-based architectures. At variance with standard approaches to LB coding, the proposed strategy,…

分布式、并行与集群计算 · 计算机科学 2023-04-14 Andrea Montessori , Marco Lauricella , Adriano Tiribocchi , Mihir Durve , Michele La Rocca , Giorgio Amati , Fabio Bonaccorso , Sauro Succi

We employ the Partially Saturated Cells Method (PSM) to model the interaction between the fluid flow and solid moving objects as an extension to the conventional lattice Boltzmann method. We introduce an efficient and accurate method for…

分布式、并行与集群计算 · 计算机科学 2025-02-28 P. Suffa , S. Kemmler , H. Koestler , U. Ruede

Leveraging spatial sparsity has become a popular approach to accelerate 3D computer graphics applications. Spatially sparse data structures and efficient sparse kernels (such as parallel stencil operations on active voxels), are key to…

编程语言 · 计算机科学 2021-06-23 Yuanming Hu , Mingkuan Xu , Ye Kuang , Frédo Durand

A GPU-accelerated version of the lattice Boltzmann method for efficient simulation of soft materials is introduced. Unlike standard approaches, this method reconstructs the distribution functions from available hydrodynamic variables…

Despite decades of research, creating accurate, robust, and efficient lattice Boltzmann methods (LBM) on non-uniform grids with seamless GPU acceleration remains challenging. This work introduces a novel strategy to address this challenge…

计算物理 · 物理学 2026-01-06 Christophe Coreixas , Jonas Latt

We present a novel, hardware-agnostic implementation strategy for lattice Boltzmann (LB) simulations, which yields massive performance on homogeneous and heterogeneous many-core platforms. Based solely on C++17 Parallel Algorithms, our…

计算物理 · 物理学 2021-05-11 Jonas Latt , Christophe Coreixas , Joël Beny

A upscaled lattice Boltzmann method (LBM) for flow simulations in heterogeneous porous media, at both pore and Darcy scales, is proposed in this paper. In the micro-scale simulations, we model flows using LBM with the modified Guo et al.…

计算物理 · 物理学 2013-12-03 Jun Li , Donald Brown

GPUs offer several times the floating point performance and memory bandwidth of current standard two socket CPU servers, e.g. NVIDIA C2070 vs. Intel Xeon Westmere X5650. The lattice Boltzmann method has been established as a flow solver in…

The Lattice Boltzmann method (LBM) for solving fluid flow is naturally well suited to an efficient implementation for massively parallel computing, due to the prevalence of local operations in the algorithm. This paper presents and analyses…

分布式、并行与集群计算 · 计算机科学 2017-01-04 Mark Mawson , Alistair Revell

In this paper, a new progressive mesh algorithm is introduced in order to perform fast physical simulations by the use of a lattice Boltzmann method (LBM) on a single-node multi-GPU architecture. This algorithm is able to mesh automatically…

分布式、并行与集群计算 · 计算机科学 2015-10-14 Julien Duchateau , François Rousselle , Nicolas Maquignon , Gilles Roussel , Christophe Renaud

Fluid-particle systems are very common in many natural processes and engineering applications. However, accurately and efficiently modelling fluid-particle systems with complex particle shapes is still a challenging task. Here, we present a…

流体动力学 · 物理学 2023-03-22 Pei Zhang , Ling Qiu , S. A. Galindo-Torres , Yilin Chen , A. Scheuermann , Ling Li
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