Accelerating Lattice Boltzmann Fluid Flow Simulations Using Graphics Processors

—Lattice Boltzmann Methods (LBM) are used for the computational simulation of Newtonian fluid dynamics. LBM-based simulations are readily parallelizable; they have been implemented on general-purpose processors [1][2][3], field-programmable gate arrays (FPGAs) [4], and graphics processing units (GPUs) [5][6][7]. Of the three methods, the GPU implementations achieved the highest simulation performance per chip. With memory bandwidth of up to 141 GB/s and a theoretical maximum floating point performance of over 600 GFLOPS [8], CUDA-ready GPUs from NVIDIA provide an attractive platform for a wide range of scientific simulations, including LBM. This paper improves upon prior GPU LBM results for the D3Q19 model [7] by increasing GPU multiprocessor occupancy, resulting in an increase in maximum performance by 20%, and by introducing a space-efficient storage method which reduces GPU RAM requirements by 50% at a slight detriment to performance. Both GPU versions are over 28 times faste...

• Type: Conference
• Year: 2009
• Where: ICPP
• Authors: Peter Bailey, Joe Myre, Stuart D. C. Walsh, David J. Lilja, Martin O. Saar
• Keywords: Distributed And Parallel Computing, GPU Implementations, GPU Multiprocessor Occupancy, ICPP 2009, Prior Gpu Lbm