Open Source Framework for Enabling HPC and Cloud Geoprocessing Services

云计算 计算机科学 分析 大数据 互操作性 地理空间分析 地球观测 地理处理 数据科学 万维网 工程类 操作系统 遥感 卫星 地质学 航空航天工程
作者
José Miguel Montañana,Paolo Marangino,Antonio Hervás
出处
期刊:AGRIS on-line Papers in Economics and Informatics [Czech University of Life Sciences Prague]
卷期号:12 (4): 61-76 被引量:2
标识
DOI:10.7160/aol.2020.120405
摘要

Geoprocessing is a set of tools that can be used to efficiently address several pressing chal-lenges for the global economy ranging from agricultural productivity, the design of transport networks, to the prediction of climate change and natural disasters. This paper describes an Open Source Framework developed, within three European projects, for Ena-bling High-Performance Computing (HPC) and Cloud geoprocessing services applied to agricultural challenges. The main goals of the European Union projects EUXDAT (EUro-pean e-infrastructure for eXtreme Data Analytics in sustainable developmenT), CYBELE (fostering precision agriculture and livestock farming through secure access to large-scale HPC-enabled virtual industrial experimentation environment empowering scalable big data analytics), and EOPEN (opEn interOperable Platform for unified access and analysis of Earth observatioN data) are to enable the use of large HPC systems, as well as big data management, user-friendly access and visualization of results. In addition, these projects focus on the development of software frameworks, and fuse Earth-observation data, such as Copernicus data, with non-Earth-observation data, such as weather, environmental and social media information. In this paper, we describe the agroclimatic-zones pilot used to validate the framework. Finally, performance metrics collected during the execution (up to 182 times speedup with 256 MPI processes) of the pilot are presented.
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