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Landing sites detection using LiDAR data on manycore systems

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Abstract

Helicopters are widely used in emergency situations, where knowing if a geographical location is adequate for landing is a critical issue, and it is far from being a straightforward task. In this work, we present a method to detect and classify landing sites from LiDAR data in parallel on multi- and manycore systems using OpenMP. Load balancing was identified as the main cause of poor performance because the computational cost depends mainly on the input data. Results for a set of LiDAR point clouds that represent different real scenarios were used as case studies in this work. Balancing strategies for three different multi- and manycore systems were analyzed. The proposed load balancing techniques increase performance up to three times from the unbalanced case.

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Acknowledgments

This work has been partially supported by the Ministry of Economy and Competitiveness of Spain under project TIN2013-41129-P and Xunta de Galicia under projects GRC2014/008 and GRC GI-1638. It has been developed in the framework of the European network HiPEAC-2, the Spanish network CAPAP-H, the Galician network under the Consolidation Program of Competitive Research Units (TLIX Network ref. R2014/049). This work is also a result of a collaboration with INAER and the Laborate group of the University of Santiago de Compostela.

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Authors and Affiliations

  1. CiTIUS Centro Singular de Investigación en Tecnoloxías da Información, Universidade de Santiago de Compostela, Galicia, Spain

    Oscar G. Lorenzo, Jorge Martínez, David L. Vilariño, Tomás F. Pena, José C. Cabaleiro & Francisco F. Rivera

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  1. Oscar G. Lorenzo
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  2. Jorge Martínez
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  3. David L. Vilariño
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  4. Tomás F. Pena
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  5. José C. Cabaleiro
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  6. Francisco F. Rivera
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Corresponding author

Correspondence to Oscar G. Lorenzo.

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Lorenzo, O.G., Martínez, J., Vilariño, D.L. et al. Landing sites detection using LiDAR data on manycore systems. J Supercomput 73, 557–575 (2017). https://doi.org/10.1007/s11227-016-1912-7

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  • DOI: https://doi.org/10.1007/s11227-016-1912-7

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