Dag Sverre Seljebotn | 8 Mar 08:25 2011
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Re: correct way to compile cython project with icc?

On 03/06/2011 05:20 AM, Zak Stone wrote:
> Hello everyone,
>
> I would like to compile a Cython project with Intel's compiler icc to
> benchmark the resulting binary against one produced by gcc. It appears
> that calling "python setup.py build_ext" with CC="icc" is enough to
> switch the Cython compilation step to icc, but it is difficult to
> prevent distutils from passing the wrong flags to icc, and distutils
> insists on performing the linking step with gcc.
>
> It is possible to follow NumPy's lead and patch distutils to support
> icc -- that only requires a minor change to ccompiler.py and the
> addition of a file like intelccompiler.py -- but I'd rather not
> maintain a patch on my system-wide Python installation, and it appears
> that virtualenv doesn't make it easy to patch Python itself in an
> isolated local environment. It might be possible to use a modified
> local copy of distutils only as NumPy seems to, but then I would also
> have to modify Cython to interface with the modified copy of
> distutils, and the resulting toolchain would be rather fragile.
>
> Of course, there could be deeper problems still, considering that the
> system Python installation was compiled with gcc, as were NumPy and
> SciPy; I don't know whether gcc and icc play well together.
>
> Is the "right solution" to use icc to compile a completely separate
> installation of Python, NumPy, SciPy, and Cython and then to develop
> my project in that environment? If so, could anyone recommend tools to
> build and maintain such an environment? (pythonbrew appears to be a
> step in the right direction.) Or is there a simpler route? For
> example, the binary produced with CC="icc" in my current test case
> appears to run properly despite the various gcc confounds, but I don't
> know whether to trust it.

If you want this kind of flexibility I'd switch to a real build tool, 
such as 'waf'. Here's one example; it does more than you need since it 
also builds and links with Fortran code:

https://github.com/dagss/healpix4py/blob/9a730266a15ca8986165cfdc9077a8537ed595e9/wscript
https://github.com/dagss/healpix4py/blob/9a730266a15ca8986165cfdc9077a8537ed595e9/healpix/wscript

The downside is you can't that easily distribute your package in 
standard ways, but "bento" is here to help with that:

http://cournape.wordpress.com/2011/03/06/adding-a-distutils-compatibility-layer-to-bento/

(I didn't try this yet, as I don't need to easy_install my packages.) 
So, it's outside of the beaten path, but in the end it may be better 
than wasting your time with distutils.

Dag Sverre


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