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Hierarchical Line Integration
August 2011 (vol. 17 no. 8)
pp. 1148-1163
ASCII Text
x 
 
Marcel Hlawatsch, Filip Sadlo, Daniel Weiskopf, "Hierarchical Line Integration," IEEE Transactions on Visualization and Computer Graphics, vol. 17, no. 8, pp. 1148-1163, August, 2011.
 
 
BibTex
x
 
@article{ 10.1109/TVCG.2010.227,
author = {Marcel Hlawatsch and Filip Sadlo and Daniel Weiskopf},
title = {Hierarchical Line Integration},
journal ={IEEE Transactions on Visualization and Computer Graphics},
volume = {17},
number = {8},
issn = {1077-2626},
year = {2011},
pages = {1148-1163},
doi = {http://doi.ieeecomputersociety.org/10.1109/TVCG.2010.227},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Visualization and Computer Graphics
TI - Hierarchical Line Integration
IS - 8
SN - 1077-2626
SP1148
EP1163
EPD - 1148-1163
A1 - Marcel Hlawatsch,
A1 - Filip Sadlo,
A1 - Daniel Weiskopf,
PY - 2011
KW - Flow visualization
KW - integral curves
KW - hierarchical computation
KW - FTLE
KW - LIC
KW - GPU.
VL - 17
JA - IEEE Transactions on Visualization and Computer Graphics
ER -
 
Marcel Hlawatsch, University of Stuttgart, Stuttgart
Filip Sadlo, University of Stuttgart, Stuttgart
Daniel Weiskopf, University of Stuttgart, Stuttgart
This paper presents an acceleration scheme for the numerical computation of sets of trajectories in vector fields or iterated solutions in maps, possibly with simultaneous evaluation of quantities along the curves such as integrals or extrema. It addresses cases with a dense evaluation on the domain, where straightforward approaches are subject to redundant calculations. These are avoided by first calculating short solutions for the whole domain. From these, longer solutions are then constructed in a hierarchical manner until the designated length is achieved. While the computational complexity of the straightforward approach depends linearly on the length of the solutions, the computational cost with the proposed scheme grows only logarithmically with increasing length. Due to independence of subtasks and memory locality, our algorithm is suitable for parallel execution on many-core architectures like GPUs. The trade-offs of the method—lower accuracy and increased memory consumption—are analyzed, including error order as well as numerical error for discrete computation grids. The usefulness and flexibility of the scheme are demonstrated with two example applications: line integral convolution and the computation of the finite-time Lyapunov exponent. Finally, results and performance measurements of our GPU implementation are presented for both synthetic and simulated vector fields from computational fluid dynamics.

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Index Terms:
Flow visualization, integral curves, hierarchical computation, FTLE, LIC, GPU.
Citation:
Marcel Hlawatsch, Filip Sadlo, Daniel Weiskopf, "Hierarchical Line Integration," IEEE Transactions on Visualization and Computer Graphics, vol. 17, no. 8, pp. 1148-1163, Aug. 2011, doi:10.1109/TVCG.2010.227
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