Building a scaleable geo-spatial DBMS: technology, implementation, and evaluation
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Multidimensional access methods
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Clone join and shadow join: two parallel spatial join algorithms
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Data Partitioning for Parallel Spatial Join Processing
Geoinformatica
Parallel Processing of Spatial Joins Using R-trees
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Guest editorial: high performance computing with geographical data
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IEEE Transactions on Knowledge and Data Engineering
ACM Transactions on Database Systems (TODS)
Data partitioning on chip multiprocessors
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Parallel Banding Algorithm to compute exact distance transform with the GPU
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Towards personal high-performance geospatial computing (HPC-G): perspectives and a case study
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A MapReduce approach to Gi*(d) spatial statistic
Proceedings of the ACM SIGSPATIAL International Workshop on High Performance and Distributed Geographic Information Systems
Indexing large-scale raster geospatial data using massively parallel GPGPU computing
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Accelerating CUDA graph algorithms at maximum warp
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Speeding up large-scale geospatial polygon rasterization on GPGPUs
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TerraNNI: natural neighbor interpolation on a 3D grid using a GPU
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Parallel quadtree coding of large-scale raster geospatial data on GPGPUs
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Efficient parallel kNN joins for large data in MapReduce
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Constructing natural neighbor interpolation based grid DEM using CUDA
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U2SOD-DB: a database system to manage large-scale ubiquitous urban sensing origin-destination data
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High-performance online spatial and temporal aggregations on multi-core CPUs and many-core GPUs
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U2STRA: high-performance data management of ubiquitous urban sensing trajectories on GPGPUs
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Robust and efficient polygon overlay on parallel stream processors
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
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We report the preliminary design and realization of a high-performance, general purposed, parallel GIS (CudaGIS), based on the General Purpose computing on Graphics Processing Units (GPGPU) technologies. Still under active developments, CudaGIS currently supports major types of geospatial data (point, polyline, polygon and raster) and provides modules for spatial indexing, spatial join and other types of geospatial operations on such geospatial data types. Experiments have demonstrated 10-40X on main-memory systems due to GPU accelerations and 1000-10000X speedups over serial CPU implementations and disk-resident systems by integrating additional performance boosting techniques, such as efficient in-memory data structures and algorithmic engineering.