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The study on infrared image parallel computing based on improved BSP model

机译:基于改进BSP模型的红外图像并行计算研究

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This paper analyzes the characteristics of Parallel Algorithm for Image and real-time processing of image which base on the cluster-computer. An improved double-sync(the Bulk Synchronous and the cycle of synchronization)BSP model is proposed, which provides the capability of the real-time processing. Under the clustered computer system, we adopt the leaping task allocation algorithm and the method of border extrapolation and interpolation with which the problem of loss of super-step in real-time parallel computing is solved. Moreover, the paper sets up the cluster computer system architecture for real-time image processing, and the parallel algorithms of image by application of Lifting Wavelet Transform has been implemented. The same time, we build the speedup-ratio model and then analyzes the performance of the calculation. In addition, the improved BSP model, the leaping task allocation mechanism and the border task method of the validity have been verified by experiments, which are effectual for increasing the real-time of image.
机译:本文分析了在群集计算机上基于群体的图像和实时处理的并行算法的特征。提出了一种改进的双同步(散装同步和同步循环)BSP模型,提供了实时处理的能力。在聚类计算机系统下,我们采用跨越任务分配算法和边界外推和插值,解决了实时并行计算中超级步骤丢失的问题。此外,该纸张设置了用于实时图像处理的集群计算机系统架构,并且已经实现了通过应用提升小波变换的图像的并行算法。同时,我们构建了Speedup-比率模型,然后分析了计算的性能。此外,通过实验验证了改进的BSP模型,跨越任务分配机制和有效性的边界任务方法,这是有效地增加图像的实时。

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