Treffer: Geoscience visualization with GPU programming

Title:
Geoscience visualization with GPU programming
Source:
Visualization and data analysis 2005 (San Jose CA, 17-18 January 2005)SPIE proceedings series. :126-134
Publisher Information:
Bellingham WA: SPIE, 2005.
Publication Year:
2005
Physical Description:
print, 13 ref
Original Material:
INIST-CNRS
Subject Terms:
Electronics, Electronique, Optics, Optique, Physics, Physique, Telecommunications, Télécommunications, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Telecommunications et theorie de l'information, Telecommunications and information theory, Théorie de l'information, du signal et des communications, Information, signal and communications theory, Théorie du signal et des communications, Signal and communications theory, Signal, bruit, Signal, noise, Détection, estimation, filtrage, égalisation, prédiction, Detection, estimation, filtering, equalization, prediction, Traitement du signal, Signal processing, Traitement des images, Image processing, Algorithme, Algorithm, Algoritmo, Charge dynamique, Dynamic load, Carga dinámica, Dialogue homme machine, Man machine dialogue, Diálogo hombre máquina, Evaluation performance, Performance evaluation, Evaluación prestación, Implémentation, Implementation, Implementación, Infographie, Computer graphics, Gráfico computadora, Interface graphique, Graphical interface, Interfaz grafica, Interface programme application, Application program interfaces, Interface utilisateur, User interface, Interfase usuario, Langage JAVA, JAVA language, Lenguaje JAVA, Langage évolué, High level language, Lenguaje evolucionado, Ombrage, Shadowing, Umbría, Programmation, Programming, Programación, Qualité image, Image quality, Calidad imagen, Simulation, Simulación, Traitement image, Image processing, Procesamiento imagen, Unité centrale, Central unit, Unidad central, Visualisation donnée, Data visualization
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Landmark Graphics, 2101 CityWest Blvd, Houston, TX 77042-2827, United States
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Telecommunications and information theory
Accession Number:
edscal.17046422
Database:
PASCAL Archive

Weitere Informationen

In recent years, off-the-shelf graphics cards have provided the ability to program the graphics processing unit (GPU) as an alternative to using fixed function pipelines. We believe that this capability can enable a new paradigm in geoscience data visualization. In the past, the geoscience data preparation, interpretation, and simulation were all done by the central processing unit (CPU), and then the generated graphics primitives were fed into a GPU for visualization. This approach was dictated by the constraints imposed by the general-purpose graphics application programming interfaces (APIs). With GPU programming, this front-end processing can be done in the GPU and visualized immediately. After passing the geometry data into the GPU, parameters can be used to control these processes inside the GPU. The different algorithms associated with these processes can be applied at run time by loading a new shading program. To prove this concept, we designed and implemented Java-based shader classes, which operate on top of Cg, a high-level language for graphics programming. These shader classes load Cg shaders to provide a new method for visualizing and interacting with geoscience data. The results from this approach show better visual quality for seismic data display and dramatically improved performance for large 3D seismic data sets. For editing geological surfaces, tests demonstrate performance levels 10 times faster than the typical approach. This paper describes the use of these shaders and presents the results of shader application to geoscience data visualization.