在GPU上设置实时标记级别

Xing Mei, Philippe Decaudin, Bao-Gang Hu, Xiaopeng Zhang
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引用次数: 10

摘要

水平集方法已被广泛用于跟踪不同材料之间的动态界面,用于基于物理的模拟、几何建模、海洋建模和其他科学和工程应用。由于其固有的欧拉特性,基于水平集的界面演化存在数值扩散、尖锐特征缺失和质量损失等问题。虽然粒子水平集(PLS)和标记水平集(MLS)等有效的方法已经被提出来解决这些问题,但复杂的校正过程和高昂的计算成本严重限制了实时应用。在本文中,我们提供了标记水平集方法在最新图形硬件上的高效并行实现。采用不同计算技术的创新组合,将MLS方法的每一步都完全映射到GPU上。该方法依托GPL的并行性和灵活的可编程性,能够为大型2D示例和中等3D示例提供实时性能,比以往基于cpu的方法快得多。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-Time Marker Level Set on GPU
Level set methods have been extensively used to track the dynamical interfaces between different materials for physically based simulation, geometry modeling, oceanic modeling and other scientific and engineering applications. Due to the inherent Eulerian characteristics, interface evolution based on level set usually suffers from numerical diffusion, sharp feature missing and mass loss. Although some effective methods such as particle level set (PLS) and marker level set (MLS) have been proposed to tackle these difficulties, the complicated correction process and the high computational cost pose severe limitations for real-time applications. In this paper we provide an efficient parallel implementation of the marker level set method on latest graphics hardware. Each step of the MLS method is fully mapped on GPU with an innovative combination of different computation techniques. Relying on GPL's parallelism and flexible programmability, the method provides real-time performance for large size 2D examples and moderate 3D examples, which is significantly faster than previous CPU-based methods.
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