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Before moving on to anything else, I wanted to share this soft repulsion test: The "particles", which, I want to remember, are mesh points, seek a position while avoiding any collisions with each other. It is based on the first test (TP Real-Time 3D flocking on GPU) in which however I used Thinking Particles and the dataset was not dynamic. Here 30 particles per frame are generated by the code, for a total of 15000 particles, the CUDA function takes care of calculating their position with respect to the others and generating a soft repulsion. Also calculate the reaction to the presence of a pivot. I tried to keep the code lightweight to show "clean" performance (as much as possible). In conclusion we can see how the GPU works in the same way also for still export (or any other case of creating a cache). I'm still working with Numpy (it will be totally replaced by CuPy in the future), experimenting with CUDA block synchronization and using shared memory.