>
> Benoit
>
>
>>
>> Marton
>>
>> 2010/3/5 Adolfo Rodríguez Tsouroukdissian <
dofo79@xxxxxxxxx>:
>>> Hello,
>>>
>>> I have a question on what the allocation policy of the eigen 3..x matrix
>>> decompositions will be, for this will strongly bias how I use eigen on
>>> different parts of my code.
>>>
>>> On the one hand, I know that the template parameters of the matrix to be
>>> decomposed (size, options, max size, ...) will be propagated to all the
>>> decomposition's members and temporaries [1], so if the input matrix is
>>> stack-allocated, so will be the internals of a decomposition. So far so
>>> good.
>>>
>>> On the other hand, I had the expectation that if heap-allocated matrices are
>>> used, all heap allocations of the decomposition algorithm would take place
>>> during the initialization phase, and none would be done in the computation
>>> phase (provided that the initialization and computation matrices have the
>>> same size in memory). This currently does not seem to be the case. For
>>> example,
>>>
>>> MatrixXd I(MatrixXd::Identity(16, 16));
>>> MatrixXd A(MatrixXd::Random(16, 16)); // Same size as I
>>>
>>> Eigen::FullPivLU<MatrixXd> lu(I); // Allocates 5 temps
>>> lu.compute(A); // Allocates 2 extra temps
>>>
>>> Eigen::JacobiSVD<MatrixXd> svd(I); // Allocates 4 temps
>>> svd.compute(A); // Allocates 1 extra temp
>>>
>>> I haven't checked where the extra allocations in compute() come from, but my
>>> question is, can and will they be prevented for 3.x? or is this an
>>> intentional design decision? (and if so, for what reasons).
>>>
>>> TIA,
>>>
>>> Adolfo
>>>
>>> [1]
>>>
http://listengine.tuxfamily..org/lists.tuxfamily.org/eigen/2010/03/msg00095.html
>>>
>>>
>>> --
>>> Adolfo Rodríguez Tsouroukdissian, Ph. D.
>>>
>>> Robotics engineer
>>> PAL ROBOTICS S.L
>>>
http://www.pal-robotics.com
>>> Tel. +34.93.414.53.47
>>> Fax.+34.93.209.11.09
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>>
>>
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