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A comment on Faster Python calculations with Numba. Parent comment

Re:Faster Python calculations with Numba by johndough on Saturday February 19, 2022 @05:53AM (#30396112)
In theory, a compiler toolchain is not required since Numba already comes with LLVM, i.e. for JIT compilation, no additional compiler is necessary.

In the past, that was also possible for AOT compilation [1], but that technique broke during some update and it seems like there is no one left who knows how to fix this.

[1] https://stackoverflow.com/a/42198101

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Re:Faster Python calculations with Numba by woadwarrior01 on Saturday February 19, 2022 @07:28AM (#30396628)
Jax also has experimental support for persisting its JIT cache on the filesystem in the ‘jax.experimental.compilation_cache’ module.
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Re:Faster Python calculations with Numba by VHRanger on Saturday February 19, 2022 @11:27AM (#30398268)
How does jax compare to numba?
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Re:Faster Python calculations with Numba by woadwarrior01 on Saturday February 19, 2022 @02:58PM (#30400000)
numba is more general. Any change to the shapes of arrays triggers a JIT recompilation in jax, numba is a bit more forgiving. jax has autodiff that numba doesn't. Also, JAX supports TPUs, which numba doesn't support (yet).
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