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A Fast Algorithm for Classifying Seismic Events Using Distributed Computations in Apache Spark Framework

机译:一种使用分布式计算在Apache Spark框架中对地震事件进行分类的快速算法

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摘要

The main ideas of the development of the software implementation of an algorithm for the fast automatic classification of seismic signals based on diagnostic patterns are described. The process of adaptation and integration of this implementation into the distributed computations system Apache Spark is described in detail. A software solution for the preliminary processing of the signals and optimization of the mathematical model for parallel computations using broadcast variables is presented. Performance tests for the classification algorithm on a set of day-long signals are carried out. The execution time of the algorithm in the context of massively parallel computations was reduced tenfold compared with the sequential execution.
机译:描述了基于诊断模式的快速自动分类的算法软件实现的主要思想。详细描述了将该实现的自适应和集成的过程进行详细描述。呈现了一种用于使用广播变量的并行计算的信号和数学模型的信号和优化的软件解决方案。执行了一组天长信号的分类算法的性能测试。与顺序执行相比,算法在大规模并行计算的上下文中的执行时间减少了十倍。

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  • 来源
    《Programming and Computer Software》 |2020年第1期|35-48|共14页
  • 作者

    Popov S. E.; Zamaraev R. Yu.;

  • 作者单位

    Russian Acad Sci Inst Comp Technol Siberian Branch Novosibirsk 630090 Russia;

    Russian Acad Sci Inst Comp Technol Siberian Branch Novosibirsk 630090 Russia;

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  • 正文语种 eng
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