Parallelized Topological Relaxation Algorithm
Parallelized Topological Relaxation Algorithm
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DOI：
10.1109/bigdata47090.2019.9006309
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发表时间：
2019-12
期刊：
影响因子：
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通讯作者：
Guangchen Ruan;Hui Zhang
中科院分区：
文献类型：
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作者：
Guangchen Ruan;Hui Zhang
数学可视化应用程序感兴趣的几何问题涉及改变结构，例如将一个结转换为等效结的移动。在本文中，我们将数学实体（曲线和曲面）描述为链接节点图，并利用能量驱动的松弛算法通过移动节点和面来优化其几何形状。此外，我们在松弛算法中设计和配置并行功能单元，以加速这些数学变形所需的计算。结果表明，通过提出的线程模型和并行化水平，我们可以实现显著的性能优化。
Geometric problems of interest to mathematical visualization applications involve changing structures, such as the moves that transform one knot into an equivalent knot. In this paper, we describe mathematical entities (curves and surfaces) as link-node graphs, and make use of energy-driven relaxation algorithms to optimize their geometric shapes by moving knots and surfaces to their simplified equivalence. Furthermore, we design and conFigure parallel functional units in the relaxation algorithms to accelerate the computation these mathematical deformations require. Results show that we can achieve significant performance optimization via the proposed threading model and level of parallelization.