Hardware-Based Nonlinear Filtering and Segmentation using High-Level Shading Languages
Proceedings of the 14th IEEE Visualization 2003 (VIS'03)
Compilers: Principles, Techniques, and Tools (2nd Edition)
Compilers: Principles, Techniques, and Tools (2nd Edition)
Open Source GIS: A GRASS GIS Approach
Open Source GIS: A GRASS GIS Approach
Parallel Image Processing Based on CUDA
CSSE '08 Proceedings of the 2008 International Conference on Computer Science and Software Engineering - Volume 03
Accelerating geoscience and engineering system simulations on graphics hardware
Computers & Geosciences
Parallel Banding Algorithm to compute exact distance transform with the GPU
Proceedings of the 2010 ACM SIGGRAPH symposium on Interactive 3D Graphics and Games
Natural neighbor interpolation based grid DEM construction using a GPU
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Indexing large-scale raster geospatial data using massively parallel GPGPU computing
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
GPU-based roofs' solar potential estimation using LiDAR data
Computers & Geosciences
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Batch processing of raster data performed by geographic information systems (GIS) is a time consuming procedure. Modern high performance GPUs are able to perform hundreds of arithmetical operations in parallel. These GPUs can help to reduce the computing time of such operations. In addition, most of the commonly used raster operations are I/O-bounded. Memory transfer between hard disk and RAM takes up more time than computations. The scope of this paper is to present an efficient two-level caching strategy for raster data and an acceleration of selected raster operations using the GPU, which were implemented as a plugin for the open source software GRASS. An example data flow based on a real world use-case will be presented and the obtainable and practically expectable speedup will be measured and discussed.