EAN: 9783319069371

MACHINE LEARNING FOR ADAPTIVE MANY-CORE MACHINE...

The overwhelming data produced everyday and the increasing performance and cost requirements of
applications are transversal to a wide range of activities in society  from science to
industry. In particular  the magnitude and complexity of the tasks that Machine Learning (ML)
algorithms have to solve are driving the need to devise adaptive many-core machines that scale
well with the volume of data  or in other words  can handle Big Data. This book gives a concise
view on how to extend the applicability of well-known ML algorithms in Graphics Processing Unit
(GPU) with data scalability in mind. It presents a series of new techniques to enhance  scale
and distribute data in a Big Learning framework. It is not intended to be a comprehensive
survey of the state of the art of the whole field of machine learning for Big Data. Its purpose
is less ambitious and more practical: to explain and illustrate existing and novel GPU-based ML
algorithms  not viewed as a universal solution for the Big Data challenges but rather as part
of the answer  which may require the use of different strategies coupled together.

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