Resumo

CASTILLO REYES, Grethell. Parallel programming techniques applied to raster data processing using GDAL library. Rev cuba cienc informat [online]. 2016, vol.10, n.1, pp. 71-94. ISSN 2227-1899.

ABSTRACT The raster data model is one of the geospatial data models commonly used to store and analyze information of the Earth's surface. Generally, to perform operations over these data, it is used the Geospatial Data Abstraction Library, known as GDAL, capable of handling about a hundred raster file formats. The response time of these library during data analysis, has been conditioned by the trend of gradually increasing the volume of these, thanks to the continuous improvement of the technical data acquisition of the land surface. For this reason, this work focuses on the critical study of the major contributions that mark their interest in applying parallel programming techniques to process raster data analysis in order to increase performance in terms of speed. As a result of the study, it was determined that the use of volunteer computing for the utilization of hardware resources available in organizations and the use of techniques to ensure the heterogeneity between computing platforms, emerge as interesting alternatives to combine and include in the design of strategies for parallel processing of raster data. These variants are applicable in institutions dedicated to the analysis of geospatial information in Cuba, considering the limitations of the computational environment that characterize them.

Palavras-chave : heterogeneity; parallel programming techniques; raster data model; volunteer computing.

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