Re: [eigen] slow adjoint sparse dense product

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OK, it seems that this issue does not always occur and hardly depends
on the compiler version and whether you use complexes or simply
doubles... So sure this have to be fixed. These products will also be
parallelized. Of course if your solver is already parallel then you
don't care!


On Thu, Nov 10, 2011 at 1:21 PM, Sebastian Birk
<birk@xxxxxxxxxxxxxxxxxxxxx> wrote:
> Hi,
> I am working on iterative solvers for large sparse matrices and I am
> thinking about switching from uBLAS to Eigen. But the one thing that
> keeps me from changing the library is that the product of the adjoint of
> a sparse matrix with a vector is about half the speed of multiplying
> directly with the non-adjoint matrix. I attached a small simple test
> file that measures the time for an example matrix.
> I figured out that for the product y=Ax in class SparseTimeDenseProduct
> the case "if(Rhs::ColsAtCompileTime==1)" is chosen and the computation
> is quite fast.
> But for y=A^{H}x there is no optimized case that can be chosen. Is there
> a way to speed up the multiplication with an adjoint sparse matrix?
> Sebastian

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