Parallel distributed viewshed analysis
Proceedings of the 6th ACM international symposium on Advances in geographic information systems
GPU Gems: Programming Techniques, Tips and Tricks for Real-Time Graphics
GPU Gems: Programming Techniques, Tips and Tricks for Real-Time Graphics
GPU Gems 2: Programming Techniques for High-Performance Graphics and General-Purpose Computation (Gpu Gems)
Debunking the 100X GPU vs. CPU myth: an evaluation of throughput computing on CPU and GPU
Proceedings of the 37th annual international symposium on Computer architecture
Programming Massively Parallel Processors: A Hands-on Approach
Programming Massively Parallel Processors: A Hands-on Approach
Parallel Viewshed Analysis on GPU Using CUDA
CSO '10 Proceedings of the 2010 Third International Joint Conference on Computational Science and Optimization - Volume 01
CUDA by Example: An Introduction to General-Purpose GPU Programming
CUDA by Example: An Introduction to General-Purpose GPU Programming
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In this paper, we present the graphics processing unit (GPU)-based parallel implementation of visibility calculation from multiple viewpoints on raster terrain grids. Two levels of parallelism are introduced in the GPU kernels — parallel traversal of visibility rays from a single viewpoint and parallel processing of viewpoints. The obtained visibility maps are combined in parallel using the selected logical operator. A comparison with multi-threaded CPU implementation is performed to establish the expected speed-ups of viewshed construction when the source and destination types are sets of scattered locations, paths, or regions. The results demonstrate that using the GPU, the acceleration of an order of magnitude can be achieved on average with both point sampling and bilinear filtering of the elevation map. Copyright © 2011 John Wiley & Sons, Ltd.