GPU Parallel Computation of Morse-Smale Complexes

被引:6
作者
Subhash, Varshini [1 ]
Pandey, Karran [1 ]
Natarajan, Vijay [1 ]
机构
[1] Indian Inst Sci, Dept Comp Sci & Automat, Bangalore, Karnataka, India
来源
2020 IEEE VISUALIZATION CONFERENCE - SHORT PAPERS (VIS 2020) | 2020年
关键词
Human-centered computing; Visualization; Visualization techniques; Computing methodologies; Parallel computing methodologies; Parallel algorithms; Shared memory algorithms;
D O I
10.1109/VIS47514.2020.00014
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
The Morse-Smale complex is a well studied topological structure that represents the gradient flow behavior of a scalar function. It supports multi-scale topological analysis and visualization of large scientific data. Its computation poses significant algorithmic challenges when considering large scale data and increased feature complexity. Several parallel algorithms have been proposed towards the fast computation of the 3D Morse-Smale complex. The non-trivial structure of the saddle-saddle connections are not amenable to parallel computation. This paper describes a fine grained parallel method for computing the Morse-Smale complex that is implemented on a GPU. The saddle-saddle reachability is first determined via a transformation into a sequence of vector operations followed by the path traversal, which is achieved via a sequence of matrix operations. Computational experiments show that the method achieves up to 7 x speedup over current shared memory implementations.
引用
收藏
页码:36 / 40
页数:5
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