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Sub-workflow parallel implementation of aerosol optical depth retrieval from MODIS data case on a Grid platform

机译:网格平台上基于MODIS数据案例的气溶胶光学深度检索的子工作流并行实现

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Aerosol Optical Depth (AOD) is an significant parameter of aerosol optical properties. Operational production of AOD datasets over long time series, large-scale coverage puts on a severe challenge to computing technologies due to both the complexity of retrieval algorithm and the huge data amounts. The Grid computing solution-Remote Sensing Service Node (RSSN) was constructed as a high-throughput platform for remote sensing applications. Taking the sub-workflow level characteristics of some remote sensing retrieval applications into consideration, a sub-workflow parallel implementation for the Synergetic Retrieval of Aerosol Properties (SRAP) algorithm from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor data was taken on the RSSN, and an initial experiment result proved that the subworkflow parallel could further reduce the runtime of data parallel solutions commonly used.
机译:气溶胶光学深度(AOD)是气溶胶光学特性的重要参数。由于检索算法的复杂性和庞大的数据量,AOD数据集在较长时间序列上的业务生产,大规模覆盖对计算技术提出了严峻挑战。网格计算解决方案-遥感服务节点(RSSN)被构建为用于遥感应用程序的高吞吐量平台。考虑到某些遥感检索应用程序的子工作流级别特征,在RSSN上采用了中分辨率成像光谱仪(MODIS)传感器数据的气溶胶特性协同检索(SRAP)算法的子工作流并行实现,初步的实验结果证明,子工作流并行可以进一步减少常用数据并行解决方案的运行时间。

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