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Leveraging the usage of GPUs in SAR processing for the NISAR mission

机译:利用NISAR任务在SAR处理中使用GPU

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The NASA ISRO Synthetic Aperture Radar (NISAR) mission will redefine the future of earth science in terms of both the quality as well as the quantity of data that will be downlinked daily. The current software architecture used to process this data is the InSAR Scientific Computing Environment (ISCE), a powerful and modular platform that applies a combination of novel and legacy processing modules to many sources of SAR data. Until recently, this architecture could process most images in a reasonable amount of time; however in the case of the NISAR mission (where the daily influx as well as the size of the images themselves are significantly larger) the current architecture can take hours to process even a single image. This paper explores new efforts to use a Graphics Processing Unit (GPU) to accelerate one of the processing modules to achieve unprecedented runtimes with no loss in precision, potentially setting a new standard in radar processing in the world of “Big Data”.
机译:NASA ISRO合成孔径雷达(NISAR)任务将从每天下行链路的数据质量和数量上重新定义地球科学的未来。用于处理此数据的当前软件体系结构是InSAR科学计算环境(ISCE),这是一个功能强大的模块化平台,将新颖的和传统的处理模块组合应用于许多SAR数据源。直到最近,这种架构仍可以在合理的时间内处理大多数图像。但是,在执行NISAR任务(每天的流入量以及图像本身的大小明显较大)的情况下,当前架构甚至需要花费数小时来处理单个图像。本文探讨了使用图形处理单元(GPU)加速处理模块之一以实现前所未有的运行时间而又不失精度的新努力,这有可能为“大数据”世界树立雷达处理的新标准。

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