[issue18835] Add aligned memory variants to the suite of PyMem functions/macros
Antoine Pitrou
report at bugs.python.org
Tue Oct 31 11:01:12 EDT 2017
Antoine Pitrou <pitrou at free.fr> added the comment:
Le 31/10/2017 à 15:55, Nathaniel Smith a écrit :
>
> 1) numpy hasn't actually come to a decision about whether to use aligned allocation at all, or under what circumstances.
This isn't the Numpy bug tracker, but I can't help but mention that if
Numpy grew a facility for users to override the memory allocators it
invokes to allocate array data, Numpy may not have to come to a decision
about this at all... ;-) And it would also help specialized
accelerators, which may want to direct Numpy arrays to e.g. memory
that's cheaply shared with the GPU.
(see https://github.com/numpy/numpy/pull/5470)
> I wasn't making a criticism of your API; "it's not you, it's us" :-). But this is a complicated and subtle area that's not really part of CPython's core competency, and coming at a time when people are fretting about how to shrink the C APIs surface area. E.g. I can think of more interesting ways for the PyPy folks to spend their time than implementing an aligned_alloc wrapper...
The same argument can be made for any part of the stdlib or core
language that PyPy has to reproduce. Besides, I don't think
implementing an aligned_alloc wrapper is very difficult. The hard part
is getting an agreement over the exposed APIs, and that's CPython's job,
not PyPy ;-)
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