全速前进：使用GPU加速3D空间数据库
Full Speed Ahead: 3D Spatial Database Acceleration with GPUs
摘要：
许多行业依靠视觉洞察来支持其业务中的决策过程。在采矿中，对钻头和地质形状（以3D几何图形表示）的分析是帮助地质学家寻找新矿床的重要工具。在设计新飞机时，航空学通过空气动力学的数值模拟来操纵高分辨率的几何形状。通常，这些行业需要可扩展的数据库来计算空间关系和测量，以便可以无延迟地进行决策。然而，正如我们在这项研究中所展示的那样，大多数数据库系统要么缺乏对处理3D几何图形的支持，要么在处理大量数据时表现不佳。本文提出了一种可插拔的空间数据库加速引擎，通过GPU卸载，可以将空间操作的性能提高3000倍以上。我们专注于我们的PostgreSQL数据库系统的插件的设计和评估。
英文摘要：
Many industries rely on visual insights to support decision- making processes in their businesses. In mining, the analysis of drills and geological shapes, represented as 3D geometries, is an important tool to assist geologists on the search for new ore deposits. Aeronautics manipulate high-resolution geometries when designing a new aircraft aided by the numerical simulation of aerodynamics. In common, these industries require scalable databases that compute spatial relationships and measurements so that decision making can be conducted without lags. However, as we show in this study, most database systems either lack support for handling 3D geometries or show poor performance when given a sheer volume of data to work with. This paper presents a pluggable acceleration engine for spatial database systems that can improve the performance of spatial operations by more than 3000x through GPU offloading. We focus on the design and evaluation of our plug-in for the PostgreSQL database system.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
