Hi, On Sun, Jul 23, 2017 at 5:07 PM, Ilhan Polat <ilhanpolat@gmail.com> wrote:
Ouch, that's from 2012 :( I'll add this thread as a reference to the wiki list.
On Sun, Jul 23, 2017 at 5:22 PM, Nathan Goldbaum <nathan12343@gmail.com> wrote:
See https://mail.scipy.org/pipermail/numpy-discussion/2012-August/063589.html and replies in that thread.
Quote from an Apple engineer in that thread:
"For API outside of POSIX, including GCD and technologies like Accelerate, we do not support usage on both sides of a fork(). For this reason among others, use of fork() without exec is discouraged in general in processes that use layers above POSIX."
On Sun, Jul 23, 2017 at 10:16 AM, Ilhan Polat <ilhanpolat@gmail.com> wrote:
That's probably because I know nothing about the issue, is there any reference I can read about?
But in general, please feel free populate new items in the wiki page.
On Sun, Jul 23, 2017 at 11:15 AM, Nathaniel Smith <njs@pobox.com> wrote:
I've been wishing we'd stop shipping Accelerate for years, because of how it breaks multiprocessing – that doesn't seem to be on your list yet.
On Sat, Jul 22, 2017 at 3:50 AM, Ilhan Polat <ilhanpolat@gmail.com> wrote:
A few months ago, I had the innocent intention to wrap LDLt decomposition routines of LAPACK into SciPy but then I am made aware that the minimum required version of LAPACK/BLAS was due to Accelerate framework. Since then I've been following the core SciPy team and others' discussion on this issue.
We have been exchanging opinions for quite a while now within various SciPy issues and PRs about the ever-increasing Accelerate-related issues and I've compiled a brief summary about the ongoing discussions to reduce the clutter.
First, I would like to kindly invite everyone to contribute and sharpen the cases presented here
https://github.com/scipy/scipy/wiki/Dropping-support-for-Accelerate
The reason I specifically wanted to post this also in NumPy mailing list is to probe for the situation from the NumPy-Accelerate perspective. Is there any NumPy specific problem that would indirectly effect SciPy should the support for Accelerate is dropped?
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I added some more discussion, and some links to previous discussion on the mailing list. I also pointed to this PR : https://github.com/MacPython/numpy-wheels/pull/1 - which builds OpenBLAS wheels for numpy. The same kind of thing would work fine for Scipy. Cheers, Matthew