On Sat, Aug 6, 2016 at 9:20 AM, Benjamin Root wrote:
> Don't know if it is what you are looking for, but NumPy has a built-in suite
> of benchmarks:
> http://docs.scipy.org/doc/numpy/reference/generated/numpy.testing.Tester.bench.html
> That's the very old (now unused) benchmark runner. Numpy
> We have a numpy -- heavy app. bu tit, like many others, I'm sure, also
> relies heavily on Cython-wrapped C++ code, as well as pure Cython extensions.
>
> As well as many other packages that are also wrappers around C libs, Cython
> -optimized, etc.
>
> I've never tried to run it under PyPy
>
> On Fri, Aug 5, 2016 at 3:42 AM, Papa, Florin
>> wrote:
>>
>>> Does anyone have knowledge of real life workloads that use NumPy and
>>> cannot be run using PyPy?
>>>
>>>
>>>
>>> We are also interested in creating a repository with relevant benchmarks
>>> for real world usage of NumPy,
>>>
>>
W
On Sat, Aug 6, 2016 at 9:20 AM, Benjamin Root wrote:
> Don't know if it is what you are looking for, but NumPy has a built-in
> suite of benchmarks: http://docs.scipy.org/doc/numpy/reference/generated/
> numpy.testing.Tester.bench.html
>
That's the very old (now unused) benchmark runner. Numpy h
Don't know if it is what you are looking for, but NumPy has a built-in
suite of benchmarks:
http://docs.scipy.org/doc/numpy/reference/generated/numpy.testing.Tester.bench.html
Also, some projects have taken to utilizing the "airspeed velocity" utility
to track benchmarking stats for their projects
Hi,
This is Florin Papa from the Dynamic Scripting Languages Optimizations team in
Intel Corporation.
Our team is working on optimizing the PyPy interpreter and part of this work is
to find and fix incompatibilities between NumPy and PyPy. Does anyone have
knowledge of real life workloads that
I'm trying to promote the usage of python and scientific python modules
at work.
I fully agree with the fact that numpy is only the entrance point to
scientific python.
Without at least scipy and matplotlib, it is hopeless to forget about
matlab.
Speed : In my usecases, numpy is decently fast.
I have written up a summary of my views here:
http://technicaldiscovery.blogspot.com/2011/10/thoughts-on-porting-numpy-to-pypy.html
-Travis
On Feb 19, 2012, at 9:45 AM, xavier.gn...@gmail.com wrote:
> Hi,
>
> I'm trying to understand what's going on with :
> http://morepypy.blogspot.com/2012
Hi,
I'm trying to understand what's going on with :
http://morepypy.blogspot.com/2012/01/numpypy-status-update.html
What's your opinion on such a numpy rewrite??
Thanks,
Xavier
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