|Re: [eigen] FLENS C++ expression template Library has excellent documentation|
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- To: eigen@xxxxxxxxxxxxxxxxxxx
- Subject: Re: [eigen] FLENS C++ expression template Library has excellent documentation
- From: Benoit Jacob <jacob.benoit.1@xxxxxxxxx>
- Date: Fri, 17 Apr 2009 15:49:20 -0400
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2009/4/17 Christian Mayer <mail@xxxxxxxxxxxxxxxxx>:
> (Disclaimer: I'm not knowing FLENS)
> FLENS and EIGEN have totally different use cases:
> - - EIGEN is a lib that gives you the best performance for small, fixed
> size matrices and vectors that's possible (e.g. those that are typical
> for 3D intensive applications)
> - - BLAS/LAPACK gives you the best performance (using the right
> implementation) for big, variable sized matrices and vectors (i.e. those
> used in numerical applications). FLENS is adding a modern, object
> orientated wrapper around this functionality.
> In this case both libs can peacefully coexist...
> As EIGEN is supporting variable sized matrices as well, both are
> starting to compete in exactly the same field of use. EIGEN has the
> advantage that the expression templates are the base and not something
> built on top, i.e. EIGEN can optimize "between" BLAS function calls.
That's an accurate summary :)
> FLENS has the advantage that it can use extremely optimized BLAS
> libraries (e.g. Intel MKL), something that EIGEN can't do (as it's cross
> platform) and won't do (as it doesn't have the funding that MKL has as a
> marketing platform for Intel...).
> => it would be interesting to see a benchmark of a non trivial numerical
> algorithm to see wich approach wins.
Our (updated) benchmarks on the wiki clearly show that as long as you
use only 1 thread, we have the same level of performance as Intel MKL
for many important operations, suggesting that we could have the same
level of performance for all operations given enough contributions.
This is made possible by 2 facts:
1) we have much more generic code so that it takes us far less effort
2) For the rest, when generic code doesn't cut it (e.g. matrix
product), Gael is an amazing coder :)
So, in which area does Intel MKL still have a long-term lead? I would
say parallelization. We haven't started that yet and it is probably a
very, very tough one. It's what I have in mind when I say that a
BLAS/LAPACK wrapper is still welcome.
> But as EIGEN could include a BLAS/LAPACK lib as well, there shouldn't be
> a way for FLENS to win...
> Perhaps it's best to convince the FLENS author to join effords?
It's hard to do without sounding offensive :) Also, adding a
BLAS/LAPACK wrapper to Eigen wouldn't be really difficult, so he would
feel that there doesnt survive much of FLENS in Eigen.
While we're discussing other libraries, I think that an interesting one is NT2:
I had a email conversation with its author, so here's what I know.
It's a c++ template library offering only very basic functionality,
and wrapping around LAPACK for advanced stuff. So in that respect, it
is similar to FLENS. The difference is that NT2 is extremely
aggressive on the expression-templates front. It is based on
Boost::proto which gives it a very high-up view of expression
templates, performing a lot of impressive global transformations on
expressions. He gets "for free" stuff that were hard to implement by
hand in Eigen such as the automatic introduction of temporaries where
appropriate. The downside is very long compilation times -- 3 seconds
for a trivial program and 10 seconds for a typical file, and remember
that this is only basic operations, since for the nontrivial stuff it
relies on LAPACK. Extrapolating, this suggest the order of magnitude
of 1 minute to compile any of our big linear algebra algorithms.
Another critique i'd formulate is that like Boost::ublas, it only
treats expr templates as an optimization that you can enable or
disable, so it doesn't leverage xpr templates to achieve a better API
like Eigen does.
Still, this got me thinking. Relying on Boost::proto is a no-go in
2009 as it makes compilation times awful. But what in 5 years? If
compilers improve enough until then, that could become very