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Near real-time parallel processing and advanced data management of SAR images in grid environments

机译:网格环境中SAR图像的近实时并行处理和高级数据管理

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In this paper, we describe the process of parallelizing an existing, production level, sequential Synthetic Aperture Radar (SAR) processor based on the Range-Doppler algorithmic approach. We show how, taking into account the constraints imposed by the software architecture and related software engineering costs, it is still possible with a moderate programming effort to parallelize the software and present an message-passing interface (MPI) implementation whose speedup is about 8 on 9 processors, achieving near real-time processing of raw SAR data even on a moderately aged parallel platform. Moreover, we discuss a hybrid two-level parallelization approach that involves the use of both MPI and OpenMP. We also present GridStore, a novel data grid service to manage raw, focused and post-processed SAR data in a grid environment. Indeed, another aim of this work is to show how the processed data can be made available in a grid environment to a wide scientific community, throughrnthe adoption of a data grid service providing both metadata and data management functionalities. In this way, along with near real-time processing of SAR images, we provide a data grid-oriented system for data storing, publishing, management, etc.
机译:在本文中,我们描述了基于Range-Doppler算法方法并行化现有的,生产水平的顺序合成孔径雷达(SAR)处理器的过程。我们展示了如何考虑到软件体系结构和相关软件工程成本带来的限制,仍然可以通过适当的编程工作来使软件并行化,并提出一种消息传递接口(MPI)实现,其实现速度约为8倍。 9个处理器,即使在适度老化的并行平台上也可以实现近实时的原始SAR数据处理。此外,我们讨论了混合的两级并行化方法,该方法涉及同时使用MPI和OpenMP。我们还介绍了GridStore,这是一种新颖的数据网格服务,用于在网格环境中管理原始,聚焦和后处理的SAR数据。确实,这项工作的另一个目的是展示通过采用提供元数据和数据管理功能的数据网格服务,如何在网格环境中向广泛的科学界提供处理后的数据。这样,连同SAR图像的近实时处理,我们提供了一个面向数据网格的系统,用于数据的存储,发布,管理等。

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