Physically based visual simulation of the Lattice Boltzmann method on the GPU: a survey

被引：0
作者：
Octavio Navarro-Hinojosa
Sergio Ruiz-Loza
Moisés Alencastre-Miranda
机构：
[1] Tecnológico de Monterrey,IT and Computer Department
来源：
The Journal of Supercomputing | 2018年 / 74卷
关键词：
LBM; GPU; CFD; CUDA; OpenCL; OpenACC;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The rapid increase in performance, programmability, and availability of graphics processing units (GPUs) has made them a compelling platform for computationally demanding tasks in a wide variety of application domains. One of these is real-time computational fluid dynamics, which are computationally expensive due to a large number of grid points that require calculations. One commonly used tool to simulate fluid flows is the Lattice Boltzmann method (LBM), mainly due to its simpler formulation when compared to solving the Navier–Stokes equations, and because of its scalability on parallel processing systems. In this paper, we give an up-to-date survey on the research regarding the LBM for fluid simulation using GPUs. We discuss how the method was implemented with different GPU architectures and software frameworks, focusing on optimization techniques and their performance. Additionally, we mention some applications of the method in different areas of study.
引用
收藏
页码：3441 / 3467
页数：26
相关论文
共 224 条
[1]  
Astorino M(2012)A modular lattice Boltzmann solver for GPU computing processors SeMA J 56 53-78
[2]  
Becerra Sagredo J(2010)A flexible high-performance lattice Boltzmann GPU code for the simulations of fluid flows in complex geometries Concurr Comput Pract Exp 22 1-14
[3]  
Quarteroni A(2009)Graphics processing unit implementation of lattice Boltzmann models for flowing soft systems Phys Rev E 80 066,707-62
[4]  
Bernaschi M(2013)An optimized D2Q37 lattice Boltzmann code on GP-GPUs Comput Fluids 80 55-64
[5]  
Fatica M(2012)Multiscale hemodynamics using GPU clusters Commun Comput Phys 11 48-1748
[6]  
Melchionna S(2007)Acceleration of a two-dimensional Euler flow solver using commodity graphics hardware Proc Inst Mech Eng Part C J Mech Eng Sci 221 1745-24
[7]  
Succi S(2016)Massively parallel lattice-Boltzmann codes on large GPU clusters Parallel Comput 58 1-3502
[8]  
Kaxiras E(2016)Performance and portability of accelerated lattice Boltzmann applications with OpenACC Concurr Comput Pract Exp 28 3485-49
[9]  
Bernaschi M(2014)A portable OpenCL lattice Boltzmann code for multi-and many-core processor architectures Proc Comput Sci 29 40-82
[10]  
Rossi L(2016)Lattice Boltzmann method for parallel simulations of cardiac electrophysiology using GPUs J Comput Appl Math 295 70-475
12345678910