13790

Parallel Unsteady Flow Line Integral Convolution for High-Performance Dense Visualization

Zi’ang Ding, Zhanping Liu, Yang Yu, Wei Chen
Department of Computer Science, Purdue University
IEEE VGTC Pacific Visualization Symposium (PacificVis 15), 2015

@article{ding2015parallel,

   title={Parallel Unsteady Flow Line Integral Convolution for High-Performance Dense Visualization},

   author={Ding, Zi’ang and Liu, Zhanping and Yu, Yang and Chen, Wei},

   year={2015}

}

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This paper presents an accurate parallel implementation of unsteady flow line integral convolution (UFLIC) for high-performance visualization of large time-varying flows. Our approach differs from previous implementations by using a novel value scattering+gathering mechanism to parallelize UFLIC and designing a pathline reuse strategy to reduce the computational cost of pathline integration. By exploiting the massive parallelism of modern graphical processing units (GPU), the proposed method allows for real-time dense visualization of unsteady flows with high spatial-temporal coherence.
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