Parallel Surface Reconstruction for Particle-Based Fluids

This paper presents a novel method that improves the efficiency of high-quality surface reconstructions for particle-based fluids using Marching Cubes. By constructing the scalar field only in a narrow band around the surface, the computational complexity and the memory consumption scale with the fluid surface instead of the volume. Furthermore, a parallel implementation of the method is proposed. The presented method works with various scalar field construction approaches. Experiments show that our method reconstructs high-quality surface meshes efficiently even on single-core CPUs. It scales nearly linearly on multi-core CPUs and runs up to fifty times faster on GPUs compared to the original scalar field construction approaches.