GPU Port of A Parallel Incompressible Navier-Stokes Solver

OpenACC is a directive-based programing standard aim to provide a highly portable programming model for massively-parallel accelerators, such as General-purpose Com-puting on Graphics Processing Units (GPGPU), Accelerated Processing Unit (APU) and Many Integrated Core Architecture (MIC). The heterogeneous nature of these accelera-tors stresses a demand for careful planning of data movement and novel approaches of parallel algorithms not commonly involved in scientific computation. By following a simi-lar concept of OpenMP, the directive-based approach of OpenACC hides many underlying implementation details, thus significantly reduces the programming complexity and in-creases code portability. However, many challenges remain, due to the relatively narrow interconnection bandwidth among GPUs and the very fine granularity of GPGPU archi-tecture. The first is particularly restrictive when cross-node data exchange is involved in a cluster environment. Furthermore, GPGPU’s fine-grained parallelism is in conflict with certain types of inherently serial algorithms, posing further restrictions on performance. In our study, an implicit multi-block incompressible Navier-Stokes solver is ported for GPGPU using OpenACC and MVAPICH2. A performance analysis is carried out based on the profiling of this solver running in a InfiniBand cluster with nVidia GPUs, which helps to identify the potentials of directive-based GPU programming and directions for further improvement.