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Erschienen in:
Behavioral Emulation for Scalable Design-Space Exploration of Algorithms and Architectures Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

Work Distribution of Data-Parallel Applications on Heterogeneous Systems

verfasst von : Suejb Memeti, Sabri Pllana

Erschienen in: High Performance Computing

Verlag: Springer International Publishing

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Abstract

Heterogeneous computing systems offer high peak performance and energy efficiency, and utilizing this potential is essential to achieve extreme-scale performance. However, optimal sharing of the work among processing elements in heterogeneous systems is not straightforward. In this paper, we propose an approach that uses combinatorial optimization to search for optimal system configuration in a given parameter space. The optimization goal is to determine the number of threads, thread affinities, and workload partitioning, such that the overall execution time is minimized. For combinatorial optimization we use the Simulated Annealing. We evaluate our approach with a DNA sequence analysis application on a heterogeneous platform that comprises two Intel Xeon E5 processors and an Intel Xeon Phi 7120P co-processor. The obtained results demonstrate that using the near-optimal system configuration, determined by our algorithm based on the simulated annealing, application performance is improved.

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Vorheriges Kapitel The EPiGRAM Project: Preparing Parallel Programming Models for Exascale
Nächstes Kapitel Reducing Manipulation Overhead of Remote Data-Structure by Controlling Remote Memory Access Order
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Metadaten
Titel
Work Distribution of Data-Parallel Applications on Heterogeneous Systems
verfasst von
Suejb Memeti
Sabri Pllana
Copyright-Jahr
2016
Buch
High Performance Computing

Print ISBN: 978-3-319-46078-9

Electronic ISBN: 978-3-319-46079-6

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-46079-6_6

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