AParallel Local Reconnection Approach for Tetrahedral Mesh Improvement
Shang, Mengmeng, Chaoyan Zhu, Jianjun Chen, Zhoufang Xiao, Yao Zheng
Proceedings, 25th International Meshing Roundtable, Elsevier, Science Direct, September 26-30 2016
25th International Meshing Roundtable
Washington DC, U.S.A.
September 26-30, 2016
Mengmeng Shang, Zhejiang University, CN, firstname.lastname@example.org
Chaoyan Zhu, Zhejiang University, CN, email@example.com
Jianjun Chen, Zhejiang University, CN, firstname.lastname@example.org
Zhoufang Xiao, Zhejiang University, CN,
Yao Zheng, Zhejiang University, CN,
A multi-threaded parallel improvement algorithm is proposed for tetrahedral meshes. The sequential algorithm combines mesh smoothing operations and local reconnection operations; thus, different techniques are developed to parallelize both operations. The parallelization of mesh smoothing operations is based on an existing data decomposition technique, which colors the dual graph of the mesh to subdivide mesh points into a few independent sets. The parallelization of local reconnection operation is based on a new data decomposition technique, which defines a feature point in the interior of each local reconnection operation, and sorts the features points along a Hilbert curve. The decomposition of this Hilbert curve could result in a load-balanced distribution of local reconnection operations on active threads. This distribution features its ability to ensure that the regions of local operations concurrently executed in different threads are usually separated far away, such that the possibility of interference is reduced to a very low level. As a result, even if the interference happens, we could simply withdraw those local reconnection operations that cause interference, and it was observed that no obvious negative impact was introduced by this simple strategy. Finally, numerical experiments will be presented to verify the effectiveness and efficiency of the proposed algorithm.
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