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Soft Computing

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01.01.2014 | Methodologies and Application

Systolic neighborhood search on graphics processing units

verfasst von: Pablo Vidal, Francisco Luna, Enrique Alba

Erschienen in: Soft Computing | Ausgabe 1/2014

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Abstract

In this paper, we propose a parallel processing model based on systolic computing merged with concepts of evolutionary algorithms. The proposed model works over a Graphics Processing Unit using the structure of threads as cells that form a systolic mesh. Data passes through those cells, each one performing a simple computing operation. The systolic algorithm is implemented using NVIDIA’s compute unified device architecture. To investigate the behavior and performance of the proposed model we test it over a NP-complete problem. The study of systolic algorithms on GPU and the different versions of the proposal show that our canonical model is a competitive solver with efficacy and presents a good scalability behavior across different instance sizes.

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Titel: Systolic neighborhood search on graphics processing units
verfasst von: Pablo Vidal
Francisco Luna
Enrique Alba
Publikationsdatum: 01.01.2014
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 1/2014
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-013-1041-7

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