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A SEGMENTED BLOCK PROCESSING APPROACH TO FOCUS SYNTHETIC APERTURE RADAR DATA ON MULTICORE PROCESSORS

机译:分段块处理方法,用于对多核处理器上的综合孔径雷达数据聚焦

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A general-purpose parallel scheme for efficiently focusing synthetic aperture radar (SAR) data on multicore-based shared-memory architectures is presented. The proposed parallel solution is based on a canonical processing pattern that exploit a segmented-block-based approach, and it works successfully on data acquired by different SAR platforms. Insofar as significant portion of the focusing algorithm is amenable to tiling, our approach decomposes the problem into simpler subproblems of the same type, also providing a suitable mechanism to explicitly control the granularity of computation through the proper specification of the tiling. Relevant implementation makes use of multithreading and high-performance libraries. Achievable performances are then experimentally investigated by quantifying the benefit of the parallelism incorporated into the prototype solution, thus demonstrating the validity of our approach.
机译:提出了一种用于有效地聚焦合成孔径雷达(SAR)数据关于基于多核的共享内存架构的通用并行方案。所提出的并行解决方案基于分割基于块的方法的规范处理模式,并且它成功地处理了由不同SAR平台获取的数据。 INSOMAR随着聚焦算法的重要部分是百口序的,我们的方法将问题分解成相同类型的更简单的子问题,还提供了一种通过平铺的适当规范明确地控制计算的粒度。相关实施利用多线程和高性能库。然后通过量化掺入原型解决方案中的平行化的益处来实验地研究了可实现的性能,从而展示了我们方法的有效性。

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