文件列表:

SPHDemo2D_Ex1_CPU.m (3380, 2021-07-23)
SPHDemo2D_Ex1_GPU.m (3450, 2021-07-23)
SPHDemo2D_Ex2_NeighbourSearch_CPU.m (4516, 2021-07-23)
SPHDemo2D_UPTree_CPU.m (3291, 2021-07-23)
SPHDemo2D_UPTree_GPU.m (3319, 2021-07-23)
figures/ (0, 2021-07-23)
figures/sph_demo1a.gif (898939, 2021-07-23)
figures/sph_demo1b.gif (3788774, 2021-07-23)
figures/sph_demo1c.gif (3543266, 2021-07-23)
figures/sph_demo_up_tree.gif (1630736, 2021-07-23)
up_tree.m (369, 2021-07-23)
up_tree_logo.png (893, 2021-07-23)
write2gif.m (441, 2021-07-23)

[](https://www.mathworks.com/matlabcentral/fileexchange/96334-smoothed-particle-hydrodynamics) # smoothed-particle-hydrodynamics A MATLAB implementation of the smoothed particle hydrodynamics based on the Philip Mocz's paper, in both CPU and GPU. By using a GPU, we can speed up the computation to about 10 times. Here, I am using the NVidia Tesla K20m. It is probably the cheapest Tesla card in second-hand markets. ;-) A normal GPU also works. Please read Philip Mocz's paper here: https://pmocz.github.io/manuscripts/pmocz_sph.pdf Although the paper stated MATLAB implementation, I can only find the Python implementation in his Github repository: https://github.com/pmocz/sph-python These are some examples in this repository: Example 1: Free-falling Universitas Pertamina's logo  Example 2: Free-falling particles arranged in a grid formation  Example 3: More free-falling particles also arranged in a grid formation ;-)  Example 4: Waaayy more free-falling particles also arranged in a grid formation ;-) ;-)  Additional notes: SPHDemo2D_Ex2_NeighbourSearch_CPU.m uses a very simple neighbour search mechanism to reduce the execution time. We first sort all nodes based on their distances to the origin. Hence, the adjacent nodes are neighbours. Contact: manurunga@yadex.com

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