Large-scale 3D geospatial processing made possible

Abstract

Several industries rely on accurate and efficient processing of 3D spatial queries over increasingly large datasets for decision optimization and exploration purposes. Examples include clinical diagnosis supported by 3D imaging of human tissues, numerical simulation of aerodynamics during the design of aircraft and vehicles, and the search for profitable deposits of minerals, oil and gas guided by 3D maps extrapolated from dense collections of rock samples. Despite the clear demand for spatial data processing in 3D space, existing systems supporting these organizations are scarce and scale poorly with data volume. This paper presents a GPU-based acceleration engine for SQL database management systems that can serve spatial queries orders of magnitude faster than solutions based on traditional software stacks.