XSPH Fluid Plugin

1. XSPH Fluid Plugin F0703701 5070379014 潘哲融

2. Goals And Achievements Design a fluid plugin fit for both game and research。 Reach Real-time performance on average hardware。 Fully utilize Programmable Pipeline and Cuda on modern hardware。 No cpu participation，no gpu-cpu data transfer。 Convenient OGL/D3D integration。 No overhead integrating OGL/D3D。 Dynamic fluid/boundary addition/deletion。 Boundary throw mesh file voxelization。 Very fast voxelization schema utilizing GPU rasterization and Cuda。 On time vertex process in most cases。 Both CPU/GPU version fully optimized。 Stable Simulation by implementing various adjustment on simulation algorithm。 Lightening fast collision detection while still memory friendly。

3. Outline • The System Structure • Collision Detection Algorithm • Hardware Data Structure And Stream • Fluid Simulation • Voxelization Schema

4. Collision Detection • Limitation And Assumption: • Only limited world size。 • Not continuous collision detection。 • Naïve Implementation： • Use a grid and every particle put in it on one frame • √：fastest in distribution and search。 • ×：memory intensive O（n*m）where n is particle count and m is grid count。

5. Collision Detection • A Simple Improvement： • Use a linked-list to represent particles。 • √：Much more memory friendly。 • ×：Not Suitable For Simd Architecture Or Cuda Process。 • Our Method： • Memory consumption same as above。 • A little slower than first implementation。

6. Collision Detection • Our Method： • First tag particle 1~n。 • Calculate grid for every particle and the hash val。 • Perform Key-Value bucket radix-sort which is very fast on cuda。 • Find for each hash the particles in it。 • After simulation frame update，resort particle to 1~n • Only overhead is radix-sort，we have been confirmed that for one billion data，a GTX 480 can handle in less than a second。

7. Data Structure And Data Stream • Data are mainly particle attribute structure。 • We design the structure by the following principle： • Particle position as the first member so that the continuous memory space can be used as opengl vbo or d3d vertex stream。 • The whole structure and every member is 128bit aligned for cuda and sse。 • Every data memory has its gpu/cpu version and they work separatly unless user reset。

8. Data Structure And Data Stream • We consider the data stream in gpu case when voxelization is involved。 • On every frame in opengl case： • First voxel data is read from mesh。 • Voxelizer parse the mesh and voxel into gl texture。 • For every texture a PBO is created and mapped to cuda memory。 • Cuda output to another cuda memory as particle cache。 • The above memory cache is mapped to opengl vbo and rendered afterwards。

9. Fluid Simulation • Basic Algor On： • PDF - Predictive-Corrective Incompressible SPH • Implement Pressure Correction On： • Simulating Free Surface Flows with SPH • Implement Sound Correction On： • Load Balanced Parallel Simulation of Particle-Fluid DEM-SPH ... • Leapfrog Schema For Updation。

10. Voxelization Schema • Our Method： • Shader Based Skinned Mesh Updation。 • Shader Pass Voxelization Using Slicemap： • Fast Scene Voxelisation. • Cuda pass voxelization filling： • Every Cuda process manage a fragment in slice map。traversal throw every bit，for a bit inside the model，add a boundery particle in particle cache。 • Use Logic-Op to handle the case when start and end of a segment falls into the same grid。 • Watertight required in this schema。

11. THANK YOU！