Gesellschaft für Informatik e.V.

Lecture Notes in Informatics


Informatik 2014 P-232, 1767-1780 (2014).

Gesellschaft für Informatik, Bonn
2014


Copyright © Gesellschaft für Informatik, Bonn

Contents

Pattern-guided big data processing on hybrid parallel architectures

Fahad Khalid , Frank Feinbube and Andreas Polze

Abstract


The advent of hybrid CPU-GPU architectures has significantly increased the number of raw FLOP/s. However, it is not obvious how these can be put to use when processing Big Data. In this paper, we present an approach for designing Big Data simulations for hybrid architectures, which is based on a hierarchal application of design patterns in parallel programming. We provide a detailed account of the step by step approach that results in efficient utilization of processing and memory resources, while simultaneously improving developer productivity. Finally, we present our vision of automated tools that will further simplify the development of efficient parallel implementations for Big Data processing on hybrid architectures.


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Gesellschaft für Informatik, Bonn
ISBN 978-3-88579-626-8


Last changed 18.11.2014 21:18:14