We present a novel surface reconstruction pipeline that significantly improves reconstructing efficiency while preserves high-quality details for particle-based liquid simulation. Our surface reconstruction algorithm is a sort of completely parallel narrow band method. At the beginning of reconstruction, we develop a spatial hashing grid-based strategy to identify surface particles, which is much more precise and simpler than the smoothed color field. Consequently, those precise surface particles ensure accurate extraction of scalar field in the narrow band around surface without any redundancy, which brings great performance improvement for subsequent reconstruction stages. Furthermore, in order to obtain a better computation performance, we carefully analyze the potential race conditions and conditional branches of each reconstruction step between parallel threads and come up with a completely parallel reconstruction method combined with the exclusive prefix sum algorithm. Our method is pretty straightforward to implement. Experimental results demonstrate that our method runs up to dozen times faster than the state-of-the-art of narrow band-based fluid surface reconstruction, especially for large-scale particle-based fluid.

中文翻译：

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一种基于粒子的流体完全平行的表面重建方法

我们提出了一种新颖的表面重建管道，可显着提高重建效率，同时为基于粒子的液体模拟保留高质量的细节。我们的表面重建算法是一种完全并行的窄带方法。在重建开始时，我们开发了一种基于空间散列网格的策略来识别表面粒子，这比平滑的色域更精确和简单。因此，这些精确的表面粒子确保了表面周围窄带标量场的准确提取，没有任何冗余，这为后续重建阶段带来了极大的性能提升。此外，为了获得更好的计算性能，我们仔细分析了并行线程之间每个重构步骤的潜在竞争条件和条件分支，并结合专有前缀和算法提出了一种完全并行的重构方法。我们的方法很容易实现。实验结果表明，我们的方法比基于窄带的流体表面重建的最新技术运行速度高达数十倍，特别是对于大规模基于粒子的流体。