High performance 2-D Laplace equation solver through massive hybrid parallelism
Muhammad Usman Ashraf, Fathy Alboraei Eassa, Aiiad Ahmad Albeshri · 2017
High Performance Computing (HPC) is a strategical resource that allows research communities and developers to fulfill the processing demand (1 ExaFlops/Sec) for future Exascale Computing system which is expected in the end of current decade. In order to provide an extensive level of performance, many powerful and energy efficient devices (MIC, GPU) and parallel programming models have been proposed. One solution deal HPC applications is optimized utilization of these parallel computing based devices and programming models. In this paper we have proposed a novel approach hybrid Tri-level parallel computing model. The objective of proposed model was to provide a platform that can render both fine-grain and course-grain parallelism for massive computation. For hybrid proposed model, three promising parallel computing models were considered including CUDA (parallelize GPU thread), OpenMP (parallelize CPU threads) and MPI (communicate among homogeneous / heterogeneous cores). Further to validate proposed model, we considered Gauss Jacobi iterative solver for 2-D Laplace equation and implemented in proposed hybrid model. Experiments performed at various mesh size on conventional CPU and proposed hybrid model. Consequently, hybrid model performed much faster as compared to serial and single GPU computation. Nevertheless, based on significant results, hybrid parallel model could be considered as initiative model to solve other HPC applications in linear / non-linear system.