Abstract：Alternating Direction Implicit (ADI) scheme is a typical discretization scheme for solving partial differential equations. However, there are few researches on the implementations and optimizations of ADI scheme on GPUs for practical Computational Fluid Dynamics (CFD) applications. In this paper, through analysis of the characteristics and calculation processes of ADI solver in a practical CFD application, the authors implemented fine-grained GPU parallelization algorithm for the ADI solver based on grid points and grid lines by a Compute Unified Device Architecture (CUDA) model. Some performance optimization methods were discussed. The experimental results on the TianHe-1A supercomputer show that the proposed GPU-enabled ADI solver can achieve overall speedup of 17.3 compared to single CPU core when simulating a 128×128×128 grid. The speedups for inviscid flux calculation, viscous flux calculation and ADI iteration are 100.1, 40.1 and 10.3 respectively.
邓亮 徐传福 刘巍 张理论. 交替方向隐式CFD解法器的GPU并行计算及其优化[J]. 计算机应用, 2013, 33(10): 2783-2786.
Liang DENG XU Chuanfu LIU Wei ZHANG Lilun. Parallelization and optimization of alternating direction implicit CFD solver on GPU. Journal of Computer Applications, 2013, 33(10): 2783-2786.
2013, Vol. 33 
