Compute Unified Device Architecture Implementation of Euler/Navier-Stokes Solver on Graphics Processing Unit Desktop Platform for 2-D Compressible Flows  

作　　者：Zhang Jiale Chen Hongquan 

机构地区：[1]College of Aerospace Engineering,Nanjing University of Aeronautics and Astronautics

出　　处：《Transactions of Nanjing University of Aeronautics and Astronautics》2016年第5期536-545,共10页南京航空航天大学学报（英文版）

基　　金：supported by the National Natural Science Foundation of China (No.11172134);the Funding of Jiangsu Innovation Program for Graduate Education (No.CXLX13_132)

摘　　要：Personal desktop platform with teraflops peak performance of thousands of cores is realized at the price of conventional workstations using the programmable graphics processing units(GPUs).A GPU-based parallel Euler/Navier-Stokes solver is developed for 2-D compressible flows by using NVIDIA′s Compute Unified Device Architecture(CUDA)programming model in CUDA Fortran programming language.The techniques of implementation of CUDA kernels,double-layered thread hierarchy and variety memory hierarchy are presented to form the GPU-based algorithm of Euler/Navier-Stokes equations.The resulting parallel solver is validated by a set of typical test flow cases.The numerical results show that dozens of times speedup relative to a serial CPU implementation can be achieved using a single GPU desktop platform,which demonstrates that a GPU desktop can serve as a costeffective parallel computing platform to accelerate computational fluid dynamics(CFD)simulations substantially.Personal desktop platform with teraflops peak performance of thousands of cores is realized at the price of conventional workstations using the programmable graphics processing units （GPUs）. A GPU-based parallel Euler/Navier-Stokes solver is developed for 2-D compressible flows by using NVIDIA＇s Compute Unified Device Architecture （CUDA） programming model in CUDA Fortran programming language. The techniques of imple- mentation of CUDA kernels, double-layered thread hierarchy and variety memory hierarchy are presented to form the GPU-based algorithm of Euler/Navier-Stokes equations. The resulting parallel solver is validated by a set of typical test flow cases. The numerical results show that dozens of times speedup relative to a serial CPU imple- mentation can be achieved using a single GPU desktop platform, which demonstrates that a GPU desktop can serve as a cost-effective parallel computing platform to accelerate computational fluid dynamics（CFD） simulations sub- stantially.

关 键 词：graphics processing unit(GPU) GPU parallel computing compute unified device architecture(CUDA)Fortran finite volume method(FVM) acceleration 

分 类 号：V211.3[航空宇航科学与技术—航空宇航推进理论与工程]