Multi-threaded parallel projection tetrahedral algorithm for unstructured volume rendering

Volume rendering methods have been extensively studied in recent years due to their effectiveness and expressiveness for unstructured grid data visualization. Although existing volume rendering methods have demonstrated great success, we observe that these methods have extensive interpolation and in...

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Vydáno v:Journal of visualization Ročník 24; číslo 2; s. 261 - 274
Hlavní autoři: Fan, Liang, Chen, Cheng, Zhao, Sirui, Zhang, Xiaorong, Wu, Yadong, Wang, Fang
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2021
Springer Nature B.V
Témata:
Algorithms
Arrays
Classical and Continuum Physics
Classification
Computer architecture
Computer Imaging
Decomposition
Efficiency
Engineering
Engineering Fluid Dynamics
Engineering Thermodynamics
Heat and Mass Transfer
Interpolation
Pattern Recognition and Graphics
Polygons
Projection
Regular Paper
Rendering
Run time (computers)
Scientific visualization
Unstructured data
Unstructured grids (mathematics)
Visibility
Vision
Visualization
Projection tetrahedral
Multi-threaded parallel
Unstructured grid
Volume rendering
ISSN:1343-8875, 1875-8975
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Popis
Shrnutí:Volume rendering methods have been extensively studied in recent years due to their effectiveness and expressiveness for unstructured grid data visualization. Although existing volume rendering methods have demonstrated great success, we observe that these methods have extensive interpolation and integral operations, which may adversely affect their efficiency and further prevent them being applied in interactive visualization. To boost efficiency and achieve interactive rendering rates, we propose a novel multi-threaded parallel projection tetrahedral algorithm based on multi-core architecture. By analyzing the parallelism of volume rendering methods, we find that the visibility sorting and classification/decomposition of projection polygons are the most time-consuming parts. To reduce the execution time of these two parts, we design corresponding parallel methods. In this manner, our method can dramatically improve efficiency and further enable user interactions for progressive unstructured grid analysis. The visibility sorting part includes partial sorting and global sorting: In partial sorting, we partition disordered tetrahedral depth array and obtain several loosely coupled subarrays, and in global sorting, we sort each subarray with multi-threads technique. In the classification/decomposition of projection polygons part, we normalize tetrahedral projection to ensure arbitrary tetrahedral produces the same number of triangles, and then store the produced vertex data into vertex array with offset computation that ensures correct order for the multi-threads runtime. The experimental results show that the proposed multi-threaded projection tetrahedral algorithm can achieve a speedup of 3.4X on a 20 cores CPU and outperforms the fastest VTK implementation at a speedup of 2.5X, which verifies the efficiency of our algorithm. Graphic Abstract
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ISSN:1343-8875
1875-8975
DOI:10.1007/s12650-020-00701-7