Raúl Moreno, Enrique Arias, José L. Sánchez, D. Cazorla, Jesús Garrido, J. González-Piqueras
{"title":"HidroMORE 2: An optimized and parallel version of HidroMORE","authors":"Raúl Moreno, Enrique Arias, José L. Sánchez, D. Cazorla, Jesús Garrido, J. González-Piqueras","doi":"10.1109/IACS.2017.7921936","DOIUrl":null,"url":null,"abstract":"HidroMORE software was developed in the Remote Sensing and Geographic Information Systems (GIS) section from the University of Castilla-la Mancha to extend the Evapotranspiration assessment to a regional scale, implementing the FAO-56 methodology and the assimilation of the basal crop coefficient from Normalized Difference Vegetation Index (NDVI) images calculated from satellite images. However, when this software deals with high dimension images, the performance greatly decays. Currently, HidroMORE is being required for carring out calculations that result unapproachable in its current state. In this work HidroMORE 2 is presented where a High Performance Computing approach has been considered to manage the complexity of HidroMORE software. The work presented here takes into account two main aspects in order to improve the performance: improvements on input/output operations, that is, a better manage of hard disk operations; and on the other hand the use of Parallel Computing by exploiting current computer architectures, in particular, multicore architectures.","PeriodicalId":180504,"journal":{"name":"2017 8th International Conference on Information and Communication Systems (ICICS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 8th International Conference on Information and Communication Systems (ICICS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IACS.2017.7921936","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
HidroMORE software was developed in the Remote Sensing and Geographic Information Systems (GIS) section from the University of Castilla-la Mancha to extend the Evapotranspiration assessment to a regional scale, implementing the FAO-56 methodology and the assimilation of the basal crop coefficient from Normalized Difference Vegetation Index (NDVI) images calculated from satellite images. However, when this software deals with high dimension images, the performance greatly decays. Currently, HidroMORE is being required for carring out calculations that result unapproachable in its current state. In this work HidroMORE 2 is presented where a High Performance Computing approach has been considered to manage the complexity of HidroMORE software. The work presented here takes into account two main aspects in order to improve the performance: improvements on input/output operations, that is, a better manage of hard disk operations; and on the other hand the use of Parallel Computing by exploiting current computer architectures, in particular, multicore architectures.