[Numpy-discussion] NumPy 1.12.0 release

[Julian Taylor]

The version of gcc used will make a large difference in some places.
E.g. the AVX2 integer ufuncs require something around 4.5 to work and in
general the optimization level of gcc has improved greatly since the
clang competition showed up around that time. centos 5 has 4.1 which is
really ancient.
I though the wheels used newer gccs also on centos 5?

On 18.01.2017 08:27, Nathan Goldbaum wrote:
> I've seen reports on the anaconda mailing list of people seeing similar
> speed ups when they compile e.g. Numpy with a recent gcc. Anaconda has
> the same issue as manylinux in that they need to use versions of GCC
> available on CentOS 5.
> 
> Given the upcoming official EOL for CentOS5, it might make sense to
> think about making a pep for a CentOS 6-based manylinux2 docker image,
> which will allow compiling with a newer GCC.
> 
> On Tue, Jan 17, 2017 at 9:15 PM Jerome Kieffer <Jerome.Kieffer at esrf.fr
> <mailto:Jerome.Kieffer at esrf.fr>> wrote:
> 
>     On Tue, 17 Jan 2017 08:56:42 -0500
> 
>     Neal Becker <ndbecker2 at gmail.com <mailto:ndbecker2 at gmail.com>> wrote:
> 
> 
> 
>     > I've installed via pip3 on linux x86_64, which gives me a wheel.  My
> 
>     > question is, am I loosing significant performance choosing this
>     pre-built
> 
>     > binary vs. compiling myself?  For example, my processor might have
>     some more
> 
>     > features than the base version used to build wheels.
> 
> 
> 
>     Hi,
> 
> 
> 
>     I have done some benchmarking (%timeit) for my code running in a
> 
>     jupyter-notebook within a venv installed with pip+manylinux wheels
> 
>     versus ipython and debian packages (on the same computer).
> 
>     I noticed the debian installation was ~20% faster.
> 
> 
> 
>     I did not investigate further if those 20% came from the manylinux (I
> 
>     suspect) or from the notebook infrastructure.
> 
> 
> 
>     HTH,
> 
>     --
> 
>     Jérôme Kieffer
> 
> 
> 
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