Re: [Numpy-discussion] NumPy in PyPy

[Papa, Florin]

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 has had an ASV test 
> suite for a while, see https://github.com/numpy/numpy/tree/master/benchmarks 
> for how to run it.
 
> Also, some projects have taken to utilizing the "airspeed velocity" utility 
> to track benchmarking stats for their projects. I know astropy utilizes it. 
> So, maybe their benchmarks might be a good starting point since they utilize 
> numpy heavily?

> Cheers!
> Ben Root

>> On Fri, Aug 5, 2016 at 3:42 AM, Papa, Florin  wrote:
>> 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 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, like GUPB for CPython, but we have not found such 
>> workloads for NumPy.
 
>> The approach of GUPB is interesting (the whole application part that is, the 
>> rest looks much more cumbersome than ASV benchmarks), but of course easier 
>> to create for Python than for Numpy. You'd need to find whole applications 
>> that spend most of their time in numpy but not in too small a set of numpy 
>> functions. Maybe benchmark suites of other projects aren't such a bad idea 
>> for that. Or spend a bit of time collecting relevant published ipython 
>> notebooks.
>> Ralf

Astropy definitely looks like a good candidate for a real life workload. Thank 
you also for the useful information on ASV.

Regards,
Florin
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Re: [Numpy-discussion] NumPy in PyPy

[Papa, Florin]

> 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 I've always assumed it's a non-starter.
> 
> Is there any hope?
> 
> 
> If you are curious:
> 
> https://github.com/NOAA-ORR-ERD/PyGnome
> 
> -CHB

Hi Christopher,

Thank you for the information, I will investigate whether we can use PyPy for 
this workload.

Regards,
Florin
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Re: [Numpy-discussion] NumPy in PyPy

[Chris Barker]

>
> 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,
>>>
>>
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 I've always assumed it's a
non-starter.

Is there any hope?


If you are curious:

https://github.com/NOAA-ORR-ERD/PyGnome

-CHB



-- 

Christopher Barker, Ph.D.
Oceanographer

Emergency Response Division
NOAA/NOS/OR&R(206) 526-6959   voice
7600 Sand Point Way NE   (206) 526-6329   fax
Seattle, WA  98115   (206) 526-6317   main reception

chris.bar...@noaa.gov
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Re: [Numpy-discussion] NumPy in PyPy

[Ralf Gommers]

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 has had an ASV
test suite for a while, see
https://github.com/numpy/numpy/tree/master/benchmarks for how to run it.


> Also, some projects have taken to utilizing the "airspeed velocity"
> utility to track benchmarking stats for their projects. I know astropy
> utilizes it. So, maybe their benchmarks might be a good starting point
> since they utilize numpy heavily?
>
> Cheers!
> Ben Root
>
>
> On Fri, Aug 5, 2016 at 3:42 AM, Papa, Florin 
> wrote:
>
>> 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 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, like GUPB for CPython, but we have not found
>> such workloads for NumPy.
>>
>
The approach of GUPB is interesting (the whole application part that is,
the rest looks much more cumbersome than ASV benchmarks), but of course
easier to create for Python than for Numpy. You'd need to find whole
applications that spend most of their time in numpy but not in too small a
set of numpy functions. Maybe benchmark suites of other projects aren't
such a bad idea for that. Or spend a bit of time collecting relevant
published ipython notebooks.

Ralf
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Re: [Numpy-discussion] NumPy in PyPy

[Benjamin Root]

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. I know astropy utilizes it.
So, maybe their benchmarks might be a good starting point since they
utilize numpy heavily?

Cheers!
Ben Root


On Fri, Aug 5, 2016 at 3:42 AM, Papa, Florin  wrote:

> 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 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, like GUPB for CPython, but we have not found
> such workloads for NumPy.
>
>
>
> Thank you,
>
> Florin
>
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Re: [Numpy-discussion] NumPy in PyPy ?

[xavier.gn...@gmail.com]

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. However, I'm using 
numexpr and  would like get to same about of vanilla numpy (and then 
with an option to use the GPU...)

Backward compatibility is key : We want to reuse our code during let say 
at least 5 to 10 years.
Matlab is ok in terms of backward compatibility. numpy should be (and 
not only numpy...scipy...matplotlib and so on).
It is ok to run an *automated* tool to correct the code if some breakage 
occurs...but it shall be reliable and automated.

go,scientific python,  go! :)

Cheers,
Xavier

> 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/2012/01/numpypy-status-update.html
>>
>> What's your opinion on such a numpy rewrite??
>>
>> Thanks,
>> Xavier
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>
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Re: [Numpy-discussion] NumPy in PyPy ?

[Travis Oliphant]

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/2012/01/numpypy-status-update.html
> 
> What's your opinion on such a numpy rewrite??
> 
> Thanks,
> Xavier
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