[petsc-users] SLEPc with offline preconditioner

Ye Jianbo Bob yelpoo at gmail.com
Sat May 26 08:41:21 CDT 2012


Some additional test with different option
------------------------------------------------------------------
./ex11 -n 30 -eps_nev 5 -eps_target 0 -st_type sinvert -st_pc_type bjacobi
Fiedler vector of a 2-D regular mesh, N=900 (30x30 grid)

 Number of iterations of the method: 5
 Solution method: krylovschur

 Number of requested eigenvalues: 5
 Stopping condition: tol=1e-08, maxit=100
 Number of converged approximate eigenpairs: 5

           k          ||Ax-kx||/||kx||
   ----------------- ------------------
       0.457508           0.886784
       0.482412           0.930914
       0.492672           0.900046
       0.513074           0.880722
       0.526509           0.898048
------------------------------------------------------------------
bobye@:tutorials$ ./ex11 -n 30 -eps_nev 5 -st_type sinvert -st_shift
1e-9 -st_pc_type ilu
Fiedler vector of a 2-D regular mesh, N=900 (30x30 grid)

 Number of iterations of the method: 5
 Solution method: krylovschur

 Number of requested eigenvalues: 5
 Stopping condition: tol=1e-08, maxit=100
 Number of converged approximate eigenpairs: 5

           k          ||Ax-kx||/||kx||
   ----------------- ------------------
       0.457508           0.886784
       0.482412           0.930914
       0.492672           0.900046
       0.513074           0.880722
       0.526509           0.898048


On Sat, May 26, 2012 at 9:37 PM, Ye Jianbo Bob <yelpoo at gmail.com> wrote:
> Hi Jose, I found shift-and-invert does not work with an iterative pc
> solver. Say the examples given in source code
>
> /home/bobye/pub/slepc/slepc-3.2-p3/src/eps/examples/tutorials/ex11.c
> ------------------------------------------------------------------
> if I use the default setting, in fact I am not sure which pc it is
> used, even which is coefficient matrix. But it works well. However, in
> my cases, I am interested in how to reuse manipulation of A for
> different eigenvalues problem.
> bobye@:tutorials$ ./ex11 -n 30 -eps_nev 5
>
> Fiedler vector of a 2-D regular mesh, N=900 (30x30 grid)
>
>  Number of iterations of the method: 20
>  Solution method: krylovschur
>
>  Number of requested eigenvalues: 5
>  Stopping condition: tol=1e-08, maxit=100
>  Number of converged approximate eigenpairs: 7
>
>           k          ||Ax-kx||/||kx||
>   ----------------- ------------------
>       0.010956        1.60437e-09
>       0.021912        1.97096e-09
>       0.043705         5.3322e-10
>       0.054661        4.01148e-09
>       0.087410         8.7469e-10
>       0.097887         2.0693e-09
>       0.108843        3.46988e-09
> ------------------------------------------------------------------
> if I use direct pc
> bobye@:tutorials$ ./ex11 -n 30 -eps_nev 5 -st_type sinvert -st_pc_type lu
> It will report Detected zero pivot in LU factorization
> ------------------------------------------------------------------
> if I use direct pc with shift value
> bobye@:tutorials$ ./ex11 -n 30 -eps_nev 5 -st_type sinvert -st_shift
> 1e-9 -st_pc_type lu
>
> Fiedler vector of a 2-D regular mesh, N=900 (30x30 grid)
>
>  Number of iterations of the method: 1
>  Solution method: krylovschur
>
>  Number of requested eigenvalues: 5
>  Stopping condition: tol=1e-08, maxit=100
>  Number of converged approximate eigenpairs: 5
>
>           k          ||Ax-kx||/||kx||
>   ----------------- ------------------
>       0.010956        5.37411e-08
>       0.010956         5.3741e-08
>       0.021912        5.13947e-14
>       0.043705        1.95903e-11
>       0.054661        2.62529e-09
>
> ------------------------------------------------------------------
> if I use iterative pc with shift-and-invert, the result seems to be wrong.
> bobye@:tutorials$ ./ex11 -n 30 -eps_nev 5 -st_type sinvert -st_pc_type
> jacobi -st_ksp_rtol 1e-12
>
> Fiedler vector of a 2-D regular mesh, N=900 (30x30 grid)
>
>  Number of iterations of the method: 1
>  Solution method: krylovschur
>
>  Number of requested eigenvalues: 5
>  Stopping condition: tol=1e-08, maxit=100
>  Number of converged approximate eigenpairs: 12
>
>           k          ||Ax-kx||/||kx||
>   ----------------- ------------------
>       2.000000           0.707107
>       2.000000           0.707107
>       2.000000           0.707107
>       2.004191           0.704215
>       3.000000           0.579634
>       3.000000           0.578826
>       3.000000           0.580728
>       3.000000            0.57262
>       3.000000           0.597176
>       3.000000           0.562004
>       3.000000           0.587957
>       3.096958           0.710225
>
>
> -jianbo
>
> On Sat, May 26, 2012 at 5:47 PM, Jose E. Roman <jroman at dsic.upv.es> wrote:
>>
>> El 26/05/2012, a las 10:47, Ye Jianbo Bob escribió:
>>
>>> Hi, I have some problem when using SLEPc to compute eigenvalue
>>> problems. I do not know how to implement my idea properly. Let me
>>> explain in detail.
>>>
>>> I am interested in solving a set of eigenvalue problems (to find the
>>> smallest magnitude eigenvalues)
>>>
>>> A x = \lambda B_i x
>>> for i=1,2,3,...
>>>
>>> where A is the Laplacian of some regular grid, B_i is diagonal. It is
>>> known that A is semi-positive with a null vector [1,1,...,1].
>>>
>>> I found SLEPc provides EPSSetDeflationSpace to set deflation space
>>> when applies iterative eigen solver. But I am not sure what default
>>> precondition is used when I defined my problem by setting
>>> eps_smallest_magnitude through EPSSetWhichEigenpairs.
>>>
>>> It is possible to use shift-and-invert to explicitly address my
>>> problem. If the shift value is 0, zero pivot will be reported during
>>> LU precondition stage. But since my set of eigen problems has the
>>> exact the same A, I hope I could somehow do the precondition (direct
>>> solver) offline only associate with A and apply the iterative eigen
>>> solver online with set of different B_i.
>>>
>>> The very initiative is the direct solver applied in precondition stage
>>> is O(N^2) while the matrix-free eigen solver is O(N), thus I think
>>> this would improve the efficiency of my situation. Is there any way to
>>> realize it?
>>>
>>> Here is some rough idea:
>>> To prevent the zero pivot during LU, I would dampshift A with a small
>>> quantity A-\sigma I, and then compute its LU offline and store it. In
>>> online stage, I could build an ST shell that read LU computed in
>>> offline stage and solve. This is only an approximated approach,
>>> hopefully not degrading the performance.
>>>
>>> Thank you!
>>
>> You can use STSHELL to perform any customized spectral transformation. But in your case I don't think it is necessary. [1,1,...,1] is also an eigenvector of the matrix pair (A,B), so you can pass it through EPSSetDeflationSpace, then use shift-and-invert with zero target - in that case the internal KSP will have A as the coefficient matrix and KSPSetNullSpace will be invoked with the [1,1,...,1] vector. The only thing is that you have to use a KSP solver that supports nullspaces. I am not sure if PETSc's direct solvers (or external solvers) support it, so you may have to use an iterative solver (e.g., -st_ksp_type bcgs -st_pc_type bjacobi -st_ksp_rtol 1e-9).
>>
>> Jose
>>


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