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Título : Big data infrastructure: a survey
Autor : Salvador, Jaime
Ruiz, Zoila
García-Rodríguez, José
Palabras clave : APRENDIZAJE AUTOMÁTICO
DATOS
GPU
MAPA REDUCIDO
Fecha de publicación : 2017
Editorial : [s.l.]: Springer
Citación : Salvador, Jaime; Ruiz, Zoila y García Rodríguez, José (2017). Big data infrastructure: a survey. Springer International Publishing AG 2017, pp. 249–258
Resumen : In the last years, the volume of information is growing faster than ever before, moving from small datasets to huge volumes of information. This data growth has forced researchers to look for new alternatives to process and store this data, since traditional techniques have been limited by the size and structure of the information. On the other hand, the power of parallel computing in new processors has gradually increased, from single processor architectures to multiple processor, cores and threads. This latter fact enabled the use of machine learning techniques to take advantage of parallel processing capabilities offered by new architectures on large volumes of data. The present paper reviews and proposes a classification, using as criteria, the hardware infrastructures used in works of machine learning parallel approaches applied to large volumes of data.
URI : http://www.dspace.uce.edu.ec/handle/25000/13653
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