Landing sites detection using LiDAR data on manycore systems

详细信息    查看全文

• 作者：Oscar G. Lorenzo ; Jorge Martínez ; David L. Vilariño…
• 关键词：LiDAR ; Landing zone detection ; Load balancing ; Xeon Phi
• 刊名：The Journal of Supercomputing
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：73
• 期：1
• 页码：557-575
• 全文大小：
• 刊物类别：Computer Science
• 刊物主题：Programming Languages, Compilers, Interpreters; Processor Architectures; Computer Science, general;
• 出版者：Springer US
• ISSN：1573-0484
• 卷排序：73

文摘

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.