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Towards petascale spectral simulations for transition analysis in wall bounded flow

机译:趋向于皮法光谱模拟,以进行壁面有限流中的过渡分析

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An efficient parallel spectral method for direct numerical simulations of transitional and turbulent flows is described in this paper. The parallelization is classically based on a bidimensional domain decomposition, but has been specifically developed for a solenoidal Fourier-Chebyshev spectral approximation where in one Fourier direction, the number of modes is very large compared with the two other directions. The approach therefore differs from classical libraries developed for cubic Fourier boxes. The strategy uses message-passing interface (MPI) for message-passing among nodes and is fairly portable. One of the originalities of this paper is the use of an efficient hybrid programming with MPI for internodes communications and a coarse grain parallelism using OpenMP for core shared-memory computation, instead of the classical hybrid programming with MPI and a fine granularity parallelism at the loop level with OpenMP directives. This hybrid parallelism has been tested on the recent generation of high-performance parallel supercomputers involving a few tens of cores per node. Performances are evaluated on different low-frequency and high-frequency processors massively parallel platforms. We demonstrate that spectral methods, which are known to be inherently ill-fitted for the new generation of high-performance distributed-memory computers, can be implemented efficiently using this hybrid programming with good scalability and a very fast wall-clock time per iteration. New numerical experiments are therefore now accessible on petascale computers, while keeping the attractive features of spectral methods such as accuracy, exponential convergence, computational efficiency and conservative properties. This is illustrated by a direct numerical simulation of the transition of the boundary layers developing from the entrance section of a plane channel and interacting to merge into a fully turbulent flow.
机译:本文描述了一种有效的平行谱方法,用于对湍流和湍流进行直接数值模拟。并行化通常基于二维域分解,但是专门针对螺线管傅里叶-切比雪夫光谱逼近而开发,其中在一个傅里叶方向上,模数与其他两个方向相比非常大。因此,该方法不同于为立方傅立叶盒开发的经典库。该策略使用消息传递接口(MPI)进行节点之间的消息传递,并且非常便于移植。本文的独创性之一是使用带有MPI的高效混合编程进行节点间通信,以及使用OpenMP进行粗粒度并行处理,以进行核心共享内存计算,而不是使用带有MPI和精细粒度并行处理的经典混合编程进行循环OpenMP指令级别。这种混合并行性已经在新一代高性能并行超级计算机上进行了测试,每个节点涉及数十个内核。在不同的低频和高频处理器大规模并行平台上评估性能。我们证明,频谱方法是众所周知的,它固有地不适用于新一代高性能分布式内存计算机,可以使用这种具有良好可伸缩性和每次迭代非常快的挂钟时间的混合编程来有效地实现频谱方法。因此,现在可以在petascale计算机上进行新的数值实验,同时保持频谱方法的诱人特征,例如准确性,指数收敛,计算效率和保守性质。通过边界层过渡的直接数值模拟可以说明这一点,该边界层从平面通道的入口部分开始发展并相互作用以合并成完全湍流。

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