Open Access
Using desktop graphics workstations for interactive remote exploration of large data sets
Lori A. Freitag,Raymond M. Loy +1 more
- 09 May 2000
TL;DR: This work describes the creation of reduced data sets using several different criteria including user-specified error bounds or a preset performance criterion, and presents performance results for the visualization of Rayleigh-Taylor instability and hairpin vortex data sets.
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Abstract: The interactive visualization and exploration of large scientific data sets is a challenging and difficult task; their size often far exceeds the performance and memory capacity of even the most powerful graphics workstations. To address this problem, we have created a technique that combines multiresolution data reduction methods with parallel computing to allow interactive exploration of large data sets while retaining full-resolution capability. We describe the creation of reduced data sets using several different criteria including user-specified error bounds or a preset performance criterion. We discuss the software architecture of the system with particular emphasis on the algorithms used to efficiently create a reduced data set and the software used to communicate between the remote data reduction server and the local graphics client. We present performance results for the visualization of Rayleigh-Taylor instability and hairpin vortex data sets.
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Citations
Visualization's role in analyzing computational fluid dynamics data
TL;DR: This work briefly discusses the growth of CFD and investigates why feature detection and visualization have become such a vital part of analyzing CFD simulation results.
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Wavelet-Based Volume Visualization
Jos B. T. M. Roerdink,Michel A. Westenberg +1 more
- 01 Jan 1999
TL;DR: In this article, a multiresolution visualization of large volume data sets based on wavelets is proposed, where a low resolution image is computed from a wavelet decomposition of the data, and this approximation can be successively refined.
5
Visualization's role in analyzing computational fluid dynamics data
TL;DR: This work briefly discusses the growth of CFD and investigates why feature detection and visualization have become such a vital part of analyzing CFD simulation results.
5
Distributed adaptive multivariate function visualization
TL;DR: The new function visualization method gives a view of the whole function while elaborating on important areas such as ridges and troughs, which are critical in many fields, including numerical integration.
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