Parallelizing a high-order WENO scheme for complicated flow structures on GPU and MIC

Abstract

As a conservative, high-order accurate, shock-capturing method, weighted essentially non-oscillatory (WENO) scheme have been widely used to effectively resolve complicated flow structures in computational fluid dynamics (CFD) simulations. However, using a high-order WENO scheme can be highly time-consuming, which greatly limits the CFD application's performance efficiency. In this paper, we present various parallel strategies base on the latest many-core platform such as NVIDIA Fermi GPU, NVIDIA Kepler GPU and Intel MIC coprocessor to accelerate a high-order WENO scheme. Comparison analysis of the two generations GPUs between Fermi and Kepler, and cross-platform performance analysis (focusing on Kepler GPU and MIC) are also detailed discussed. The experiments show that the Kepler GPU offers a clear advantage in contrast to the previous Fermi GPU maintaining exactly the same source code. Furthermore, while Kepler GPU can be several times faster than MIC without utilizing the increasingly available SIMD computing power on Vector Processing Unit (VPU), MIC can provide the computing capability equivalent to Kepler GPU when VPU is utilized. Our implementations and optimization techniques can serve as case studies for paralleling high-order schemes on many-core architectures.