A Hybrid Optimization Based on GPU Parallel Computing Method and its Application of Three Dimensional Large Eddy Simulations

Abstract

Using compute Unified device architecture (CUDA), a traditional computational fluid dynamics (CFD) program is paralleled and optimized based on graphic processing unit (GPU). The calculation process is divided into two parts as serial and parallel. Their main characteristics are analyzed and different optimization schemes are given. CPU (central processing unit) and GPU work respectively as flow control and high-speed parallel computation. Bandwidth between devices is applied effectively. Data transfer between devices is moderately improved to simplify algorithm. Finally, the method is verified by simulating a three-dimensional isotropic homogeneous turbulence flow field. The calculation uses large eddy simulation (LES) method with secondary filter and solves the three-dimensional N-S equations. The maximum grid number achieves 8,000,000 and takes 33 seconds each step. All calculations are using ordinary single desktop computer, optimized acceleration ratio can reach 9.