GPU-based cloud performance for LiDAR data processing

R. Sugumaran, Dossay Oryspayev, P. Gray
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引用次数: 10

Abstract

Goal of this paper is to compare the timing/performance results of CPU and GPU on local and Cloud platform for processing massive Light Detecting and Ranging (LiDAR) topographic data. We have used locally various multi-core CPU technologies as well as GPU implementations on various graphics cards of nVidia which support CUDA, where as a cloud computing infrastructure we utilized various components of the Amazon Web Services (AWS). In order to study the performance, we have developed and implemented vertex decimation algorithm for data reduction of LiDAR point cloud. Our presentation will demonstrate the preliminary results by comparing the multi-core CPU and GPU based implementations of the code, as well as the comparison with cloud performance.
基于gpu的云性能激光雷达数据处理
本文的目的是比较CPU和GPU在本地和云平台上处理大量激光雷达(LiDAR)地形数据的时序/性能结果。我们在本地使用了各种多核CPU技术以及支持CUDA的nVidia各种显卡上的GPU实现,其中作为云计算基础设施,我们使用了亚马逊网络服务(AWS)的各种组件。为了研究其性能,我们开发并实现了用于激光雷达点云数据约简的顶点抽取算法。我们的演示将通过比较基于多核CPU和GPU的代码实现以及与云性能的比较来演示初步结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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