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Possibility to speed up further with JAX? #2
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Thanks for the suggestion! |
Yup, that makes sense. |
So this means that multiprocessing is also complicated to implement? I've seen it done here: https://github.com/NMVHS/PyTracer |
Multiprocessing works on CPU cores so it doesn't have these GPU limitations. What happens it's that my raytracer already uses multiple cores because lot of Numpy methods uses multithreading so it cannot be made faster using multiprocessing. About the PyTracer project I already have talked with the author and made some tests. It's also a cool project. |
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Have you seen Google's JAX project?
https://github.com/google/jax
Do you think it might feasible to speed this up further with that?
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