%0 Journal Article
	%A Silvina Caíno-Lores and  Jesús Carretero
	%D 2016
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 111, 2016
	%T A Survey on Data-Centric and Data-Aware Techniques for Large Scale Infrastructures
	%U https://publications.waset.org/pdf/10003998
	%V 111
	%X Large scale computing infrastructures have been widely
developed with the core objective of providing a suitable platform
for high-performance and high-throughput computing. These systems
are designed to support resource-intensive and complex applications,
which can be found in many scientific and industrial areas. Currently,
large scale data-intensive applications are hindered by the high
latencies that result from the access to vastly distributed data.
Recent works have suggested that improving data locality is key to
move towards exascale infrastructures efficiently, as solutions to this
problem aim to reduce the bandwidth consumed in data transfers, and
the overheads that arise from them. There are several techniques that
attempt to move computations closer to the data. In this survey we
analyse the different mechanisms that have been proposed to provide
data locality for large scale high-performance and high-throughput
systems. This survey intends to assist scientific computing community
in understanding the various technical aspects and strategies that
have been reported in recent literature regarding data locality. As a
result, we present an overview of locality-oriented techniques, which
are grouped in four main categories: application development, task
scheduling, in-memory computing and storage platforms. Finally, the
authors include a discussion on future research lines and synergies
among the former techniques.
	%P 517 - 523