一种用于流体turbulence可扩展并行伪谱计算的混合MPI-OpenMP方案
A hybrid MPI-OpenMP scheme for scalable parallel pseudospectral computations for fluid turbulence
摘要：
提出了一种利用MPI实现分布式存储并行和利用OpenMP实现共享存储并行的混合方案。这项工作的动机是希望实现非常高的雷诺数的拟谱计算的流体湍流新兴千万亿次，高核心数，大规模并行处理系统。混合实现源自并增强了经过良好测试的可扩展MPI并行化伪谱代码。混合范式导致一个新的图片的区域分解的伪谱网格，这是有帮助的理解，除其他事项外，3D转置的全球数据，这是必要的并行快速傅立叶变换的数值离散化的中心组成部分。混合实现的细节，并提供性能测试说明了该方法的实用性。结果表明，该混合方案实现了接近理想的可扩展性高达~20000计算核心的最大平均效率为83%。数据演示了如何选择MPI进程和OpenMP线程的最佳数量，以优化两个不同平台上的代码性能。
英文摘要：
A hybrid scheme that utilizes MPI for distributed memory parallelism and OpenMP for shared memory parallelism is presented. The work is motivated by the desire to achieve exceptionally high Reynolds numbers in pseudospectral computations of fluid turbulence on emerging petascale, high core-count, massively parallel processing systems. The hybrid implementation derives from and augments a well-tested scalable MPI-parallelized pseudospectral code. The hybrid paradigm leads to a new picture for the domain decomposition of the pseudospectral grids, which is helpful in understanding, among other things, the 3D transpose of the global data that is necessary for the parallel fast Fourier transforms that are the central component of the numerical discretizations. Details of the hybrid implementation are provided, and performance tests illustrate the utility of the method. It is shown that the hybrid scheme achieves near ideal scalability up to ~20000 compute cores with a maximum mean efficiency of 83%. Data are presented that demonstrate how to choose the optimal number of MPI processes and OpenMP threads in order to optimize code performance on two different platforms.
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