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numpy-quaternion is a neat little C extension for Python that adds support for quaternions to NumPy. I haven't seen it use SIMD or GPGPU in a quick look through its source.
I suspect most C++ physics libraries like Box2D (https://github.com/erincatto/box2d) or Bullet3 (https://github.com/bulletphysics/bullet3) could really benefit a lot from SIMD.
I suspect most C++ physics libraries like Box2D (https://github.com/erincatto/box2d) or Bullet3 (https://github.com/bulletphysics/bullet3) could really benefit a lot from SIMD.
Currently I am part of a team working on an open source game (https://github.com/schombert/Project-Alice) that intends to lean heavily on vectorization for performance, since it is a strategy game that has to work with a decently large amount of data, by the standards of a game at least. We have things set up so that most of the data is stored in something like the struct of arrays pattern and we have some machinery in place for doing vectorized operations on it. But obviously we could benefit from a specialist. On the other hand, perhaps a game is not serious enough for your work, and there is a lot of things going on in a game that are probably irrelevant for your work.
The [hiring test](https://github.com/denniskb/hiring_test) I use for certain candidates.