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Parallel Algorithm Design for Remote Sensing Image Processing in the PC Cluster Environment

机译:PC机群环境下遥感图像处理的并行算法设计

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In the PC cluster environment, parallel algorithms can significantly improve the efficiency of remote sensing image processing. The remote sensing dataset is the raster data stored by order of band, therefore, it is feasible to assign executable tasks to some computing nodes by band and complete the processing tasks together through communicating each other amount the computing nodes by MPI interface. In addition, the multi-thread processing algorithm is scheduled based on OpenMP library toward the single computing node with multi-core CPU. The experiment evaluates image radiation performance about the four-band HJ-1A CCD remote sensing image in the PC cluster environment which consists of 4 sets of dual-core computers. Its performance is increased by 6 times to 6.5 times comparing with a single PC. Through validating, the dual level design pattern is available based on integrating MPI and OpenMP to improve the efficiency of remote sensing image processing.
机译:在PC群集环境中,并行算法可以显着提高遥感图像处理的效率。遥感数据集是按波段顺序存储的栅格数据,因此,通过MPI接口将计算节点彼此通信,可以将可执行任务按波段分配给一些计算节点,并一起完成处理任务是可行的。此外,基于OpenMP库将多线程处理算法调度到具有多核CPU的单个计算节点。实验评估了由4套双核计算机组成的PC集群环境中有关四波段HJ-1A CCD遥感图像的图像辐射性能。与单台PC相比,其性能提高了6倍至6.5倍。通过验证,基于MPI和OpenMP的集成,可以使用双层设计模式,以提高遥感图像处理的效率。

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