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Distributed data structure templates for data-intensive remote sensing applications

机译:用于数据密集型遥感应用程序的分布式数据结构模板

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摘要

The remotely sensed images continuously acquired by satellite and airborne sensors are increasing dramatically. Remote sensing applications are overwhelmed with tons of remote sensing data with complex data structures. Efficient programming in parallel systems for data-intensive applications like massive remote sensing data processing will be a challenge. We propose a generic data-structure oriented programming template to support massive remote sensing data processing in high-performance clusters. These templates provide distributed abstractions for large remote sensing image data with complex data structure and allow these distributed data to be accessed as a global one. Through data serialization and one-sided message passing primitives provided by message passing interface, the distributed remote sensing data template whose sliced data blocks are scattered among nodes could offer a simple and effective way to distribute and communicate massive remote sensing data. Efficient parallel input/output directly to and from the distributed data structure will also be offered to address the input/output bottleneck caused by massive image data. Developers can take the advantage of our templates to program efficient parallel remote sensing algorithms without dealing with data slicing and communication through low-level message passing interface APIs. Through experiments on remote sensing applications, we confirmed that our templates were productive and efficient.
机译:卫星和机载传感器连续获取的遥感图像正在急剧增加。大量具有复杂数据结构的遥感数据使遥感应用不堪重负。对于像海量遥感数据处理这样的数据密集型应用程序,在并行系统中进行高效编程将是一个挑战。我们提出了一种面向数据结构的通用编程模板,以支持高性能集群中的大规模遥感数据处理。这些模板为具有复杂数据结构的大型遥感影像数据提供了分布式抽象,并允许将这些分布式数据作为全局数据进行访问。通过消息传递接口提供的数据序列化和单边消息传递原语,其切片数据块分散在节点之间的分布式遥感数据模板可以提供一种简单有效的方式来分发和传递海量遥感数据。还将提供直接与分布式数据结构之间的有效并行输入/输出,以解决由大量图像数据引起的输入/输出瓶颈。开发人员可以利用我们的模板来编程高效的并行遥感算法,而无需通过低级消息传递接口API来处理数据切片和通信。通过遥感应用实验,我们确认我们的模板高效且高效。

著录项

  • 来源
    《Concurrency and Computation》 |2013年第12期|1784-1797|共14页
  • 作者单位

    Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, China,Institute of Electronics, Chinese Academy of Sciences, China,Graduate University of Chinese Academy of Sciences, China;

    Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, China;

    Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, China;

    Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, China,Graduate University of Chinese Academy of Sciences, China;

    Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, China;

    Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, China,Graduate University of Chinese Academy of Sciences, China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    parallel programming; generic programming; data-intensive computing; remote sensing image processing;

    机译:并行编程通用编程;数据密集型计算;遥感图像处理;

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