[petsc-users] Slepc: Computing first 4 smallest eigenvalues and eigenvectors of a large graph Laplacian

Sat Mar 25 23:08:18 CDT 2017

Send all the output in the error message:

[0]PETSC ERROR: --------------------- Error Message
--------------------------------------------------------------
[0]PETSC ERROR: Object is in wrong state
[0]PETSC ERROR: Must call EPSSolve() first: Parameter #1
[0]PETSC ERROR: See http://www.mcs.anl.gov/petsc/documentation/faq.html for
trouble shooting.
[0]PETSC ERROR: Petsc Release Version 3.7.5, Jan, 01, 2017
[0]PETSC ERROR: ./RunPart on a arch-linux2-c-debug named
research-5.ece.iastate.edu by bodhi91 Sat Mar 25 22:33:56 2017
[0]PETSC ERROR: Configure options --with-cc=gcc --with-css=g++
-with-fc=gfortran --download-fblaslapack --download-mpich
[0]PETSC ERROR: #10468 EPSComputeError() line 643 in
/tmp/Bodhi/slepc-3.7.3/src/eps/interface/epssolve.c
         0.000000     2.0795e-317

Send the output from -log_view:
         I have attached the .txt file: "Log Summary".txt

Ok. Since it only stores half the matrix it requires less memory and
because of the way it does the MatMult and MatSolve it can be a tiny bit
faster.
        I do get a little improvement in speed, but nothing significant.

Thanks,
Bodhi

On Sat, Mar 25, 2017 at 10:56 PM, Barry Smith <bsmith at mcs.anl.gov> wrote:

>
> > On Mar 25, 2017, at 10:48 PM, Bodhisatta Pramanik <bodhi91 at iastate.edu>
> wrote:
> >
> > Try     -st_pc_type gamg:
> >
> > Doing this with the existing eigensolver,linear solver : ./RunPart
> -eps_type jd -eps_nev 3 -st_ksp_type cg -st_ksp_rtol 0.001 -eps_tol 0.001
> -st_pc_type gamg -eps_smallest_real        results in the following issues:-
> > PETSC ERROR: Object is in wrong state
> > PETSC ERROR: Must call EPSSolve() first: Parameter #1
>
>    I cannot explain this. A different preconditioner with nothing else
> changed shouldn't cause any problem like this. Send all the output in the
> error message.
> >
> > Try -st_pc_type sor
> >
> > Doing this again with the existing eigensolver,linear solver returns me
> the eigenvalues but it takes more time. (106 seconds) for a Laplacian
> matrix of 200K size. The bjacobi was giving me the same eigenvalues but in
> 60 seconds.
>
>    Ok, this is reasonable.
>
> >
> >
> > Run with -log_view to see where the computation is taking the most time:
>
>    Send the output from -log_view
> >
> > EPSSolve and KSPSolve take the most time to finish computation.
> >
> > Since the matrix is symmetric are you using the sbaij format instead of
> AIJ?
> >
> > I am using the sbaij format but with block size 1. I guess that is
> equivalent to the AIJ format itself.
>
>    Ok. Since it only stores half the matrix it requires less memory and
> because of the way it does the MatMult and MatSolve it can be a tiny bit
> faster.
>
>    Barry
>
> >
> >
> > Thanks,
> > Bodhi
> >
> >
> >
> >
> > On Sat, Mar 25, 2017 at 10:22 PM, Barry Smith <bsmith at mcs.anl.gov>
> wrote:
> >
> > > On Mar 25, 2017, at 8:52 PM, Bodhisatta Pramanik <bodhi91 at iastate.edu>
> wrote:
> > >
> > > Hi,
> > >
> > > I apologize for the slepc question. I could not find any user lists so
> I'm hoping someone on here might be able to offer some guidance.
> > >
> > > Problem Definition:
> > > I am working on a graph partitioning problem. I have the laplacian of
> a large graph(500,000 nodes) and am interested in extracting its global
> information in order to find good partitioning. An approach is to compute
> the first few(4-5) eigenvalues and use that information to formulate the
> partition algorithm.
> > >
> > > I am leveraging the EPS solvers of the Slepc library. It appears that
> the Jacobi-davidson eigen solver gives me the eigenvalues in the shortest
> period of time compared to others (Krylov-Schur, Rayleigh quotient,
> Lanczos, etc). I use this eigensolver with the conjugate gradient linear
> solver and the block-jacobi preconditioner. So this is what I am basically
> passing through the command line:
> > >
> > > ./RunPart -eps_type jd -eps_nev 4 -st_ksp_type cg -st_ksp_rtol 0.001
> -eps_tol 0.001 -st_pc_type bjacobi -eps_smallest_real
> >
> >   Try     -st_pc_type gamg
> >
> >    One one process default bjacobi results in ILU which is not a great
> preconditioner.
> >
> >   Also try -st_pc_type sor
> >
> > >
> > > Question:
> > > The time it takes to compute the first 4-5 eigenvectors of a matrix of
> size (200k) is near about 60 seconds. CPU config: Intel Xeon 2GHz. I am
> using a single processor to run my code. Is there any way I can gain major
> speedup than what I am getting?
> >
> >   Run with -log_view to see where the computation is taking the most
> time.
> >
> > >
> > > Is it possible to obtain the eigenvalues inside 10-15 seconds of such
> huge matrices even if I do not use multiple processor??
> > >
> > > Can someone provide me with some valuable guidance??
> >
> >    Since the matrix is symmetric are you using the sbaij format instead
> of AIJ?
> >
> > >
> > > Thanks,
> > > Bodhi
> >
> >
> >
> >
> > --
> > Bodhisatta Pramanik,
> > Graduate Student,
> > Department of Electrical and Computer Engineering,
> > 301 Durham,
> > Iowa State University,
> > Ames,Iowa 50011,
> > bodhi91 at iastate.edu
> > 515-735-6300
>
>

-- 
*Bodhisatta Pramanik,*
*Graduate Student,*
*Department of Electrical and Computer Engineering,*
*301 Durham,*
*Iowa State University,*
*Ames,Iowa 50011,*
bodhi91 at iastate.edu
*515-735-6300*
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