在多达197万个核和4.1万亿个网格点上解决可压缩的Navier-Stokes方程

I. Bermejo-Moreno, J. Bodart, J. Larsson, Blaise M. Barney, J. Nichols, Steve Jones
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引用次数: 57

摘要

我们提出了弱尺度和强尺度研究以及混合代码的性能分析,混合代码是用于直接数值模拟各向同性湍流及其与激波相互作用的结构网格上的可压缩Navier-Stokes方程的有限差分求解器。并行化是通过MPI实现的,强调在并发计算中使用非阻塞通信。模拟,缩放和性能研究是在Sequoia, Vulcan和Vesta Blue Gene/Q系统上完成的,前两个系统在组合使用时总共占1,966,080个内核。模拟的网格点的最大数量为4.12万亿,内存使用量约为1.6 PB。我们讨论了超线程的使用,它显著提高了该体系结构上代码的并行性能。
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Solving the compressible Navier-Stokes equations on up to 1.97 million cores and 4.1 trillion grid points
We present weak and strong scaling studies as well as performance analyses of the Hybrid code, a finite-difference solver of the compressible Navier-Stokes equations on structured grids used for the direct numerical simulation of isotropic turbulence and its interaction with shock waves. Parallelization is achieved through MPI, emphasizing the use of nonblocking communication with concurrent computation. The simulations, scaling and performance studies were done on the Sequoia, Vulcan and Vesta Blue Gene/Q systems, the first two accounting for a total of 1,966,080 cores when used in combination. The maximum number of grid points simulated was 4.12 trillion, with a memory usage of approximately 1.6 PB. We discuss the use of hyperthreading, which significantly improves the parallel performance of the code on this architecture.
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