On 07/04/15 02:41, Nathaniel Smith wrote:
> Sure, but in some cases accelerate reduces speed by a factor of infinity
> by hanging, and OpenBLAS may or may not give wrong answers (but
> quickly!) since apparently they don't do regression tests, so we have to
> pick our poison.
OpenBLAS is safer on
On 07/04/15 02:19, Matthew Brett wrote:
> ATLAS compiled with gcc also gives us some more license complication:
>
> http://numpy-discussion.10968.n7.nabble.com/Copyright-status-of-NumPy-binaries-on-Windows-OS-X-tp38793p38824.html
Ok, then I have a question regarding OpenBLAS:
Do we use the f2c'd
On Apr 6, 2015 5:13 PM, "Sturla Molden" wrote:
>
> On 07/04/15 01:49, Nathaniel Smith wrote:
>
> > Any opinions, objections?
>
> Accelerate does not break multiprocessing, quite the opposite. The bug
> is in multiprocessing and has been fixed in Python 3.4.
I disagree, but it hardly matters: you
On 07/04/15 02:13, Sturla Molden wrote:
> Most of the test failures with OpenBLAS and Carl Kleffner's toolchain on
> Windows are due to differences between Microsoft and MinGW runtime
> libraries
... and also differences in FPU precision.
Sturla
___
Hi,
On Mon, Apr 6, 2015 at 5:13 PM, Sturla Molden wrote:
> On 07/04/15 01:49, Nathaniel Smith wrote:
>
>> Any opinions, objections?
>
> Accelerate does not break multiprocessing, quite the opposite. The bug
> is in multiprocessing and has been fixed in Python 3.4.
>
> My vote would nevertheless b
On 07/04/15 01:49, Nathaniel Smith wrote:
> Any opinions, objections?
Accelerate does not break multiprocessing, quite the opposite. The bug
is in multiprocessing and has been fixed in Python 3.4.
My vote would nevertheless be for OpenBLAS if we can use it without
producing test failures in Nu
Hi all,
Starting with 1.9.1, the official numpy OS X wheels (the ones you get by
doing "pip install numpy") have been built to use Apple's Accelerate
library for linear algebra. This is fast, but it breaks multiprocessing in
obscure ways (e.g. see this user report:
https://github.com/numpy/numpy/i
