Full Speed Ahead: 3D Spatial Database Acceleration with GPUs
August 28, 2018 Β· Declared Dead Β· π ADMS@VLDB
"No code URL or promise found in abstract"
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Authors
Lucas C. Villa Real, Bruno Silva
arXiv ID
1808.09571
Category
cs.DC: Distributed Computing
Citations
4
Venue
ADMS@VLDB
Last Checked
5 months ago
Abstract
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.
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