[Numpy-discussion] Meta: too many numerical libraries doing the same thing?

[Rob]

I'm currently testing the SciPy Blitz++ features with FDTD.  Should have
some comparisons soon.  Right now my statements are compiling, but not
giving the right answers :(   I think they might have it fixed soon.  
Rob.



Chris Barker wrote:
> 
> Konrad Hinsen wrote:
> > Chris Barker <chrishbarker at home.net> writes:
> > > On another note, it looks like the blitz++ library might be a good basis
> > > for a general Numerical library (and NumPy 3)  as well. It does come
> > > with a flexible license. Any thoughts?
> 
> > I think the major question is whether we are willing to move to C++.
> > And if we want to keep up any pretentions for Numeric becoming part of
> > the Python core, this translates into whether Guido will accept C++
> > code in the Python core.
> 
> Actually, It's worse than that. Blitz++ makes heavy use of templates,
> and thus only works with compilers that support that well. The current
> Python core can compile under a very wide variety of compilers. I doubt
> that Guido would want to change that.
> 
> Personally, I'm torn. I would very much like to see NumPy arrays become
> part of the core Python, but don't want to have to compromise what it
> could be to do that. Another idea is to extend the SciPy project to
> become a complete Python distribution, that would clearly include
> Numeric. One download, and you have all you need.
> 
> > >From a more pragmatic point of view, I wonder what the implications
> > for efficiency would be. C++ used to be very different in their
> > optimization abilities, is that still the case? Even more
> > pragmatically, is blitz++ reasonably efficient with g++?
> 
> I know g++ is supported (and I think it is their primary development
> platform). From the web site:
> 
> Is there a way to soup up C++ so that we can keep the advanced language
> features but ditch the poor performance? This is the goal of the
> Blitz++ project: to develop techniques which will enable C++ to rival --
> and in some cases even exceed -- the speed of Fortran for numerical
> computing, while preserving an object-oriented interface. The Blitz++
> Numerical Library is being constructed as a testbed for these
> techniques.
> 
> Recent benchmarks show C++ encroaching steadily on Fortran's
> high-performance monopoly, and for some benchmarks, C++ is even faster
> than Fortran! These results are being obtained not through better
> optimizing compilers, preprocessors, or language extensions, but through
> the
> use of template techniques. By using templates cleverly, optimizations
> such as loop fusion, unrolling, tiling, and algorithm specialization can
> be
> performed automatically at compile time.
> 
> see: http://www.oonumerics.org/blitz/whatis.html for more info.
> 
> I havn't messed with it myself, but from the web page, it seems the
> answer is yes, C++ can produce high performance code.
> 
> --
> Christopher Barker,
> Ph.D.
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