3D Terrain Real-time Rendering Method Based on CUDA-OpenGL Interoperability

ABSTRACT In the field of geographic information, fast surface modelling techniques are important. Usually, mesh model is used to describe the terrain. However, the large data of mesh model are a bottleneck of real-time rendering. Compared with the CPU, GPU has more execution units and memory units, which greatly improves its computing capacity and memory bandwidth. Meanwhile, in the field of image rendering, OpenGL has always played an important role. Since CUDA (compute unified device architecture) and OpenGL both run on GPU and share data through common memory, this paper gives a three-dimensional terrain real-time rendering method based on CUDA–OpenGL interoperability. First, we use CUDA C kernel function to calculate the vertex coordinates and normal vectors, then we pass the data to OpenGL buffer, and render it. In this paper, we use share memory and register, overlap strategy, the expansion of concurrency and the reasonable block size. The experimental results show that this algorithm can improve the computing speed greatly, with the speedup to 212.3x, meeting the needs of real-time rendering.

[1]  Zhang Changchun,et al.  PAR Model SAR Image Interpolation Algorithm on GPU with CUDA , 2014 .

[2]  Yunsong Li,et al.  A GPU-Accelerated Wavelet Decompression System With SPIHT and Reed-Solomon Decoding for Satellite Images , 2011, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[3]  Jesús Mateo Lázaro,et al.  3D-geological structures with digital elevation models using GPU programming , 2014, Comput. Geosci..

[4]  Valerio Pascucci,et al.  Terrain Simplification Simplified: A General Framework for View-Dependent Out-of-Core Visualization , 2002, IEEE Trans. Vis. Comput. Graph..

[5]  Javier Reguera-Salgado,et al.  Real time orthorectification of high resolution airborne pushbroom imagery , 2011, Remote Sensing.

[6]  Guoying Yue,et al.  Visualization of large scale geologically related data in virtual 3D scenes with OpenGL , 2007, Other Conferences.

[7]  Anand Paul.  High Performance Adaptive Deblocking Filter for H.264/AVC , 2013 .

[8]  Melin Huang,et al.  Further Improvement on GPU-Based Parallel Implementation of WRF 5-Layer Thermal Diffusion Scheme , 2013, 2013 International Conference on Parallel and Distributed Systems.

[9]  D. Semmens,et al.  A GIS application for assessing, mapping, and quantifying the social values of ecosystem services , 2011 .

[10]  Gwanggil Jeon,et al.  GPU-Parallel Implementation of the Edge-Directed Adaptive Intra-Field Deinterlacing Method , 2014, Journal of Display Technology.

[11]  Damodar Lamsal,et al.  Digital terrain modelling using Corona and ALOS PRISM data to investigate the distal part of Imja Glacier, Khumbu Himal, Nepal , 2011 .

[12]  M. Garland,et al.  Fast Polygonal Approximation of Terrains and Height Fields , 1998 .

[13]  C. Petit,et al.  Techniques for quantifying the accuracy of gridded elevation models and for mapping uncertainty in digital terrain analysis , 2011 .

[14]  K. Bharanitharan,et al.  Algorithm and Architecture for Adaptive Motion Estimation in Video Processing , 2013 .

[15]  Bormin Huang,et al.  Development of a GPU-based high-performance radiative transfer model for the Infrared Atmospheric Sounding Interferometer (IASI) , 2011, J. Comput. Phys..

[16]  Julio Martín-Herrero,et al.  High performance GCP-based Particle Swarm Optimization of orthorectification of airborne pushbroom imagery , 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.

[17]  Qing Zhu,et al.  Three-dimensional TIN algorithm for digital terrain modeling , 2008 .

[18]  Jeffrey Scott Vitter,et al.  Efficient Flow Computation on Massive Grid Terrain Datasets , 2003, GeoInformatica.

[19]  Chao Yang,et al.  An efficient simplification and real-time rendering algorithm for large-scale terrain , 2010, Int. J. Comput. Appl. Technol..

[20]  W. Long,et al.  Simulation of annual biogeochemical cycles of nutrient balance, phytoplankton bloom(s), and DO in Puget Sound using an unstructured grid model , 2012, Ocean Dynamics.

[21]  Hongxia Wang,et al.  Realistic Real-Time Rendering of 3D Terrain Scenes Based on OpenGL , 2009, 2009 First International Conference on Information Science and Engineering.

[22]  Fabio Daolio,et al.  Evaluation of parallel particle swarm optimization algorithms within the CUDA™ architecture , 2011, Inf. Sci..

[23]  Guray Yilmaz,et al.  Development of a GPU Accelerated Terrain Referenced UAV Localization and Navigation Algorithm , 2013, J. Intell. Robotic Syst..

[24]  Xianfeng Li,et al.  A new large-scale terrain real-time simplification algorithm based on Delaunay triangulation , 2007, Other Conferences.

[25]  Zhiming Cui,et al.  A New Quadtree-based Terrain LOD Algorithm , 2010, J. Softw..

[26]  Jian Wang,et al.  Efficient Data-Parallel Algorithm for Elevation Color Generation in Terrain Rendering , 2012 .

[27]  Stephan Olariu,et al.  A 3d-localization and terrain modeling technique for wireless sensor networks , 2009, FOWANC '09.

[28]  Alexander Zipf,et al.  Generating web-based 3D City Models from OpenStreetMap: The current situation in Germany , 2010, Comput. Environ. Urban Syst..

[29]  N. Nedjah,et al.  Parallel GPU-based implementation of high dimension Particle Swarm Optimizations , 2013, 2013 IEEE 4th Latin American Symposium on Circuits and Systems (LASCAS).

[30]  Jay C. Bell,et al.  Digital elevation model resolution: effects on terrain attribute calculation and quantitative soil-landscape modeling , 2001 .

[31]  María Calvino-Cancela,et al.  GPU Geocorrection for Airborne Pushbroom Imagers , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[32]  Markus Metz,et al.  GRASS GIS: A multi-purpose open source GIS , 2012, Environ. Model. Softw..

[33]  Qiming Zhou,et al.  Generalization of DEM for terrain analysis using a compound method , 2011 .