[petsc-users] Very slow SVD with SLEPC

[Matthew Knepley]

On Sun, Nov 15, 2020 at 2:18 PM Rakesh Halder <rhalder at umich.edu> wrote:

> Hi all,
>
> A program I'm writing involves calculating the SVD of a large, dense N by
> n matrix (N ~= 150,000, n ~=10,000). I've used the different SVD solvers
> available through SLEPc, including the cross product, lanczos, and method
> available through the LAPACK library. The cross product and lanczos methods
> take a very long time to compute the SVD (around 7-8 hours on one
> processor) while the solver using the LAPACK library runs out of memory. If
> I write this matrix to a file and solve the SVD using MATLAB or python
> (numPy) it takes around 10 minutes. I'm wondering if there's a much cheaper
> way to solve the SVD.
>

This seems suspicious, since I know numpy just calls LAPACK, and I am
fairly sure that Matlab does as well. Do the machines that you
are running on have different amounts of RAM?

  Thanks,

     Matt


> Thanks,
>
> Rakesh
>


-- 
What most experimenters take for granted before they begin their
experiments is infinitely more interesting than any results to which their
experiments lead.
-- Norbert Wiener

https://www.cse.buffalo.edu/~knepley/ <http://www.cse.buffalo.edu/~knepley/>
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