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Time-Dimension Communication Characterization of Representative Scientific Applications on Tianhe-2

机译:天河二号代表性科学应用的时空通信特征

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Exascale computing is one of the major challenges of this decade, and several studies have shown that the communication is becoming one of the bottlenecks for scaling parallel applications. The characteristic analysis of communication is an important means to improve the performance of scientific applications. In this paper, we focus on the statistical regularity in time-dimension communication characteristics of representative scientific applications and find that the distribution of interval of communication events has a power-law decay, which is widely found in scientific interests and human activities. For a quantitative study on characteristics of power-law distribution, we count two groups of typical measures: bursty vs. memory and periodicity vs. dispersion. Our analysis shows that the communication events reflect a "strong-bursty and weak-memory" characteristic and we also capture the periodicity and dispersion in interval distribution. All of the quantitative results are verified with eight representative scientific applications on Tianhe-2 supercomputer with a fat-tree-like interconnection network. Finally, our study provides an insight on the relationship between communication optimization and time-dimension communication characteristics.
机译:百亿亿次计算是这十年的主要挑战之一,并且多项研究表明,通信已成为扩展并行应用程序的瓶颈之一。通信的特征分析是提高科学应用性能的重要手段。在本文中,我们着眼于代表性科学应用的时空通信特征的统计规律,发现通信事件间隔的分布具有幂律衰减,这在科学兴趣和人类活动中得到了广泛发现。为了对幂律分布的特征进行定量研究,我们计算了两组典型的量度:突发性vs.内存以及周期性vs.分散。我们的分析表明,通信事件反映了“强力爆发和弱记忆”特征,并且我们还捕获了间隔分布中的周期性和离散性。所有定量结果均在具有脂肪树状互连网络的天河2号超级计算机上通过八个具有代表性的科学应用进行了验证。最后,我们的研究提供了关于沟通优化与时空沟通特征之间关系的见解。

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