Acceleration of a 2D unsteady Euler solver with GPU on nested Cartesian grid

Abstract

Graphics processing unit (GPU) parallel computation is used to accelerate a solver, which computes the 2D unsteady compressible Euler equation discretized with the finite-volume method on a nested Cartesian grid. In this solver, a second-order accurate upwind scheme is adopted, with explicit time-stepping by using the third-order total-variation-diminishing Runge–Kutta method. An improved parallel strategy is implemented, and through dealing with a test case on a three-level nested Cartesian grid, speedup ratios of 9.98–14.04 are achieved respectively at different grid sizes. Furtherly, through a numerical experiment, the relation between the kernel performance and the execution configuration at different grid sizes is examined by monitoring and analyzing the performance indicators. Moreover, approaches to improve kernel performances are explored.