[eigen] Allocation policy of eigen decompositions

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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).



[1] http://listengine.tuxfamily.org/lists.tuxfamily.org/eigen/2010/03/msg00095.html

Adolfo Rodríguez Tsouroukdissian, Ph. D.

Robotics engineer
Tel. +34.93.414.53.47
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