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From: Joerg Walter (jhr.walter_at_[hidden])
Date: 2003-02-17 15:48:16

Hi Johan,

you wrote:

> Thanks for all your info. I've run the tests with a Boost from CVS (from
> january 31st), compressed_matrix and axpy_prod, and the results give
> roughly the same speed as our implementation, and ca. 30% better memory
> efficiency. Great!

Kudos to the guys on Without them sparse
matrices would be as bad as in boost_1_29_0.

> The -DNDEBUG flag also seems critical, without it
> performance is terrible (quadratic).

Oh yes. That's my paranoia. Without -DNDEBUG defined ublas is in debug mode
and even double checks sparse matrix computations with a dense control
computation. You could customize this using the BOOST_UBLAS_TYPE_CHECK
preprocessor symbol.

> Alexei's proposed optimizations seem interesting. I tried the axpy_prod
> you provided, but it didn't give any significant change. I trust your
> figures however.

Yup. I didn't post the necessary dispatch logic. I'll later update Boost CVS
with my current version.

> I will propose that we start using ublas as soon as the linear complexity
> functions appear in the stable branch.
> I provide our benchmark below for reference (with the timing calls, and
> other dependencies stripped out):



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