Computer graphics (2nd ed.): C version
Computer graphics (2nd ed.): C version
Hardware acceleration for spatial selections and joins
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Foundations of Multidimensional and Metric Data Structures (The Morgan Kaufmann Series in Computer Graphics and Geometric Modeling)
Spatial indexing in microsoft SQL server 2008
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Real-time KD-tree construction on graphics hardware
ACM SIGGRAPH Asia 2008 papers
A Fast Similarity Join Algorithm Using Graphics Processing Units
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Designing efficient sorting algorithms for manycore GPUs
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
Density-based clustering using graphics processors
Proceedings of the 18th ACM conference on Information and knowledge management
Programming Massively Parallel Processors: A Hands-on Approach
Programming Massively Parallel Processors: A Hands-on Approach
Revisiting sorting for GPGPU stream architectures
Proceedings of the 19th international conference on Parallel architectures and compilation techniques
Fast parallel surface and solid voxelization on GPUs
ACM SIGGRAPH Asia 2010 papers
Indexing large-scale raster geospatial data using massively parallel GPGPU computing
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Memory-Scalable GPU Spatial Hierarchy Construction
IEEE Transactions on Visualization and Computer Graphics
Data-Parallel Octrees for Surface Reconstruction
IEEE Transactions on Visualization and Computer Graphics
GPU Computing Gems Emerald Edition
GPU Computing Gems Emerald Edition
High-performance software rasterization on GPUs
Proceedings of the ACM SIGGRAPH Symposium on High Performance Graphics
VoxelPipe: a programmable pipeline for 3D voxelization
Proceedings of the ACM SIGGRAPH Symposium on High Performance Graphics
CudaGIS: report on the design and realization of a massive data parallel GIS on GPUs
Proceedings of the Third ACM SIGSPATIAL International Workshop on GeoStreaming
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This study targets at speeding up polygon rasterization in large-scale geospatial datasets by utilizing massively parallel General Purpose Graphics Processing Units (GPGPU) computing for efficient spatial indexing and analysis based on a dynamically integrated vector-raster data model. As the first step, we have designed and implemented a parallelization schema for moderately large polygons using the Compute Unified Device Architecture (CUDA). Experiment results on 41,768 real world geospatial polygons with vertex numbers between 64 and 1024, which are selected among a total of 717,057 polygons with 1,199,799 rings in the experiment dataset, show that our implementation can speed up the computation of intersection points among polygon edges and scan lines by more than 20 times on a Nvidia C2050 GPU card when compared to a serial CPU implementation. Extending the design and implementation to support polygons with arbitrarily large numbers of vertices by extensively using efficient sorting is discussed. The paper also reports the design and implementation of a profile quadtree to better understand the data and the distributions of its parallel computing tasks, in addition to help select polygon groups for experiments.