Re: [boost] Back to Boost.SIMD - Some performances ...

Subject: Re: [boost] Back to Boost.SIMD - Some performances ...
From: Joel Falcou (joel.falcou_at_[hidden])
Date: 2009-03-26 16:21:26

> An efficient and well tested scalar math library as the by-product of 
> a generic SIMD vector library certainly wouldn't be useless, and I'd 
> guess that an SSE scalar implementation would look pretty similar to 
> the SSE vector implementation...
>
Well in fatc it does as the emulated vec<T,N> with N != cardinal<vector
T> use those. Boost.SIMD shouldmaybe renamed Boost.FastMath in fact

> I obviously wasn't. It's a bit unfortunate that there are so many 
> parallel development efforts in the area of template libraries for 
> linear algebra: ublas, mtl, eigen, nt2...
>
I know, so do I

> Have you thought about joining efforts with the Eigen guys? I'm no 
> expert in this area, but their benchmark numbers look pretty 
> compelling and the API seems to support fixed-size vectors in an 
> elegant way. There would probably be huge economies of scale if the 
> C++ community converged towards a single template matrix library.
Well, I largely prefer my API ;) but that's a domain rpeference. NT2
mimics exactly Matlab API and syntax wherever possible cause it was
aimed at a tool for physicist and automatism peopel to pass their matlab
demo onto a proper C++ paltform. Morevoer nt2 next version has a
extensive list of features that can be used as mark-up on matrix types.

Some exemples of divergence :
eigen2 sum of cube of column i is
r = m.cols(i).colwise().cube().sum()

NT2 sum of cube of column i is
r = sum0( cube( m(_,i) ) );

Compelx indexing is also supported :
Matlab : k(1,:, 1:2:10) = cos( m );
NT2 : k( 1, _, colon(1,2,10) ) = cos(m);

Mark-up settings :
want an upper-traingular matrix of flaot of maximum static_size of 50x50
with dynamic allocation and want to specify that all
loops involving it need to be blocked by a 3x3 pattern ?

matrix<float, settings( upper_triangular, 2D_(ofCapacity<50,50>),
cache(tiling<3,3>) )> m;

etc ...

I'm not against teaming-up but not sure which one is better than the
other. Moreover, I don't think eigen2 use proto as a base
while NT2 performs lots of pre-optimization using proto-transforms and
again that's something I don't want to lose.

Anyway, I'm not here to discuss NT2 as a whole, maybe we can continue
this elsewhere ;)

-- 
___________________________________________
Joel Falcou - Assistant Professor
PARALL Team - LRI - Universite Paris Sud XI
Tel : [phone]