GPU acceleration of a 2D compressible Euler solver on CUDA-based block-structured Cartesian meshes

Abstract

A novel block-structured Cartesian mesh method is developed that is well designed for the graphics processing unit (GPU) acceleration of flow simulations. The size of the mesh block is set based on the thread hierarchy in Compute Unified Device Architecture which is an easy-to-use GPU programming model. The mesh method is implemented in a finite-volume compressible flow solver, where the two-dimension steady Euler equations are solved by using the AUSM + scheme in spatial discretization and third-order total-variation-diminishing Runge-Kutta method in time discretization. For the GPU implementation, the redundant computation, data structure reorganization and Structure-of-Arrays (SoA) mesh layout are utilized to reduce the frequency and data size for information transfer between host and device. Two test cases, the supersonic flow over a circular cylinder and a NACA0012 airfoil, are presented to validate numerical approaches and valuate computational performance. Additionally, numerical experiments are carried out on a test case at different mesh sizes and execution configurations to investigate properties of the proposed method.