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

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.