Interactive inspection of solids: cross-sections and interferences
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
Multi-step processing of spatial joins
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Computational geometry: algorithms and applications
Computational geometry: algorithms and applications
Fast computation of generalized Voronoi diagrams using graphics hardware
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
On local heuristics to speed up polygon-polygon intersection tests
Proceedings of the 7th ACM international symposium on Advances in geographic information systems
Fast and simple 2D geometric proximity queries using graphics hardware
I3D '01 Proceedings of the 2001 symposium on Interactive 3D graphics
Computational Geometry in C
Quadtree and R-tree indexes in oracle spatial: a comparison using GIS data
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
A Raster Approximation For Processing of Spatial Joins
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Efficient Processing of Large Spatial Queries Using Interior Approximations
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Evaluation of Buffer Queries in Spatial Databases
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Quick-CULLIDE: Fast Inter- and Intra-Object Collision Culling Using Graphics Hardware
VR '05 Proceedings of the 2005 IEEE Conference 2005 on Virtual Reality
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Spatial database operations are typically performed in two steps. In the filtering step, indexes and the minimum bounding rectangles (MBRs) of the objects are used to quickly determine a set of candidate objects. In the refinement step, the actual geometries of the objects are retrieved and compared to the query geometry or each other. Because of the complexity of the computational geometry algorithms involved, the CPU cost of the refinement step is usually the dominant cost of the operation for complex geometries such as polygons. Although many run-time and pre-processing-based heuristics have been proposed to alleviate this problem, the CPU cost still remains the bottleneck. In this paper, we propose a novel approach to address this problem using the efficient rendering and searching capabilities of modern graphics hardware. This approach does not require expensive pre-processing of the data or changes to existing storage and index structures, and is applicable to both intersection and distance predicates. We evaluate this approach by comparing the performance with leading software solutions. The results show that by combining hardware and software methods, the overall computational cost can be reduced substantially for both spatial selections and joins. We integrated this hardware/software co-processing technique into a popular database to evaluate its performance in the presence of indexes, pre-processing and other proprietary optimizations. Extensive experimentation with real-world data sets show that the hardware-accelerated technique not only outperforms the run-time software solutions but also performs as well if not better than pre-processing-assisted techniques.