On 02/07/2010 21:52, Dave Fugate wrote:
------------------------------------------------------------------------
*From:* users-boun...@lists.ironpython.com
[users-boun...@lists.ironpython.com] on behalf of Michael Foord
[fuzzy...@voidspace.org.uk]
*Sent:* Thursday, July 01, 2010 2:44 PM
*To:* Discussion of IronPython
*Subject:* Re: [IronPython] Better NumPy/SciPy Support for IronPython
On 01/07/2010 20:14, Dave Fugate wrote:
Enthought <http://www.enthought.com/>, a company specialized in
Python-based scientific computing solutions, announced
<http://www.enthought.com/media/SciPyNumPyDotNet.pdf> a
partnership with Microsoft several hours ago at the SciPy 2010
<https://conference.scipy.org/scipy2010/index.html> conference in
which they’re porting over the NumPy and SciPy
<http://www.scipy.org/> scientific software packages to
IronPython. A significant part of this effort involves
duplicating these packages’ C-based modules in .NET. Previously,
these libraries could only be consumed from IronPython very
slowly using a C to .NET bridge.
Is there any evidence (metrics) that using the Ironclad C to .NET
bridge is "very slow"? I can believe there are places where it is
slower but but I've never seen enthought (or any one else) show
metrics of this.
Michael
Hi Michael, I personally haven’t seen the performance reports on
IronClad, just word of mouth (e.g.,
http://www.johndcook.com/blog/2009/03/19/ironclad-ironpytho/).
Well that is William being typically self-effacing. :-) In practise most
of the examples I've seen have been pretty damn fast, and that article
points that out too. Going from "in pathological cases it’s worse" to
"only be consumed from IronPython very slowly" is quite a stretch.
Anyway, it's a serious point. It's a shame that the exciting news is
being promoted by knocking Ironclad instead of celebrating it. There is
another article that takes a similar tack, so I think this was part of
the presentation announcing it which is very disappointing.
All the best,
Michael
Dave
Not only will this porting effort drastically improve the
performance of Python’s top scientific packages under IronPython,
it’s fantastic for NumPy/SciPy in the sense that it enables an
entirely new community of (.NET) developers to utilize and
contribute to these libraries. Also, Enthought’s refactoring work
will make it easier to run these packages against all
implementations of Python, not just IronPython. It’s expected
that NumPy will be finished by September and SciPy before the end
of the year.
The IronPython Team
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