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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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  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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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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