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Hardware Acceleration for Spatial Selections and Joins

Summary: GPU-accelerated refinement for spatial queries uses graphics hardware to speed up polygon/geometry comparisons, reducing CPU load in the refinement step. No pre-processing or index changes needed; works with both intersection and distance predicates, delivering notable end-to-end speedups by combining hardware and software. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3454
Venue
SIGMOD
Year
2003
Pagerank
9.1218781e-05
Overall Rank
2,278 | 84.16%
DOI
-

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Showing 4 of 4 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
2 R-Trees: A Dynamic Index Structure For Spatial Searching 1984 SIGMOD 0.0032169493
478 Multi-Step Processing of Spatial Joins 1994 SIGMOD 0.0002222104
2,703 A Raster Approximation for the Processing of Spatial Joins 1998 VLDB 8.2722965e-05
3,275 Quadtree and R-tree Indexes in Oracle Spatial: A Comparison using GIS Data 2002 SIGMOD 7.2897998e-05
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