Hi Matthieu,
I considered Eigen, but have already invested a lot of time/effort with ublas.
The main issue with Eigen is that it did not provide (at least at first sight) with
any handling of the allocator.uBLAS does so through the unbounded_array
input and this is very useful in overwriting allocation functionality.
Also, I am really looking for wrapping LAPACK, since I don’t believe in rewriting code
that is mature, works very well and has been optimized over a long period
of time ( as happens with mkl ) and covers a plethora of numerical algorithms (as LAPACK does).
But, there should be an answer within the uBLAS confines, right?
Thank you for your help,
Petros
From: Matthieu Brucher
Sent: Saturday, October 22, 2011 1:43 PM
To: boost-users@lists.boost.org
Subject: Re: [Boost-users] ublas speed and multi-core processors
Hi,
You may want to try Eigen instead.
Matthieu Brucher
2011/10/22 petros
Hi,
Is there any way to use ublas taking advantage of the multi-core facility of current processors?
Even naive “strategies”, like breaking the number of rows of a targeted matrix expression across
different threads would improve performance significantly, even if not optimally.
It would be nice to be able to use the matrix expression templates to perform operations in a multi-threaded
way.
Is there any provision for this?
Thank you for your help,
Petros
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