Impact of Kernel-Assisted MPI Communication over Scientific Applications: CPMD and FFTW
Impact of Kernel-Assisted MPI Communication over Scientific Applications: CPMD and FFTW
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内核辅助 MPI 通信对科学应用的影响：CPMD 和 FFTW
DOI：
10.1007/978-3-642-24449-0_28
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
J. Dongarra
中科院分区：
文献类型：
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作者：
Teng Ma;A. Bouteiller;G. Bosilca;J. Dongarra
集合通信是最强大的消息传递概念之一，它使并行应用程序能够表达复杂的通信模式，同时允许底层MPI提供高效的实现，以最大限度地减少数据移动的成本。然而，随着节点内部异构性的增加，更具体地说是内存层次结构，利用最大计算能力变得越来越困难。本文研究了核辅助MPI通信在两个科学应用中的影响：1)CAR-Parrinello分子动力学(CPMD)，一个化学分子动力学应用；2)FFTW，一个离散傅立叶变换(DFT)。通过对消息传递接口(MPI)的使用，我们发现了每个应用程序的通信特征和模式。我们的实验表明，特定机器上的集体通信实现的质量对整个应用程序的性能起着至关重要的作用。
Collective communication is one of the most powerful message passing concepts, enabling parallel applications to express complex communication patterns while allowing the underlying MPI to provide efficient implementations to minimize the cost of the data movements. However, with the increase in the heterogeneity inside the nodes, more specifically the memory hierarchies, harnessing the maximum compute capabilities becomes increasingly difficult. This paper investigates the impact of kernel-assisted MPI communication, over two scientific applications: 1) Car-Parrinello molecular dynamics(CPMD), a chemical molecular dynamics application, and 2) FFTW, a Discrete Fourier Transform (DFT). By focusing on the usage of Message Passing Interface (MPI), we found the communication characteristics and patterns of each application. Our experiments indicate that the quality of the collective communication implementation on a specific machine plays a critical role on the overall application performance.