Lyu, LuanRen, XiaohuaWu, EnhuaYang, Zhi-XinChen, RenjieRitschel, TobiasWhiting, Emily2024-10-132024-10-132024978-3-03868-250-9https://doi.org/10.2312/pg.20241299https://diglib.eg.org/handle/10.2312/pg20241299We propose a simple and efficient wavelet-based method to guide smoke simulation with specific velocity fields. This method primarily uses wavelets to combine low-resolution velocities with high-resolution details for smoke guiding. Due to the natural ability of wavelets to divide data into different frequency bands, we can merge low and high-resolution velocities by replacing wavelet coefficients. Compared to Fourier methods, the wavelet transform can use wavelets with shorter, compact supports, making the transformation faster and more adaptable to various boundary conditions. The method has a time complexity of O(n) and a memory complexity of n. Additionally, wavelets are compactly supported, which allows us to locally filter out or retain details by editing the wavelet coefficients. This enables us to locally edit smoke. Moreover, to accelerate the performance of wavelet transforms on GPUs, we propose a technique implemented in CUDA called in-kernel warp-level wavelet transform computation. This technique utilizes warp-level CUDA intrinsic functions to reduce data read times during computations, thus enhancing the efficiency of the wavelet transform. The experiments demonstrate that our proposed wavelet-based method achieves an approximate 5x speedup in 3D on GPUs compared to the Fourier methods, resulting in an overall improvement of around 40% in the smoke-guided simulation.Attribution 4.0 International LicenseCCS Concepts: Computing methodologies → Physical simulationComputing methodologies → Physical simulation10.2312/pg.2024129912 pages