[petsc-users] Eliminating rows and columns which are zeros

Fri Feb 3 18:21:39 CST 2023

   If you can help me reproduce the problem with a simple code I can debug the problem and fix it.

  Barry

> On Feb 3, 2023, at 6:42 PM, Karthikeyan Chockalingam - STFC UKRI <karthikeyan.chockalingam at stfc.ac.uk> wrote:
> 
> I updated the main branch to the below commit but the same problem persists.
>  
> [0]PETSC ERROR: Petsc Development GIT revision: v3.18.4-529-g995ec06f92  GIT Date: 2023-02-03 18:41:48 +0000
>  
>  
> From: Barry Smith <bsmith at petsc.dev <mailto:bsmith at petsc.dev>>
> Date: Friday, 3 February 2023 at 18:51
> To: Chockalingam, Karthikeyan (STFC,DL,HC) <karthikeyan.chockalingam at stfc.ac.uk <mailto:karthikeyan.chockalingam at stfc.ac.uk>>
> Cc: petsc-users at mcs.anl.gov <mailto:petsc-users at mcs.anl.gov> <petsc-users at mcs.anl.gov <mailto:petsc-users at mcs.anl.gov>>
> Subject: Re: [petsc-users] Eliminating rows and columns which are zeros
> 
>  
>    If you switch to use the main branch of petsc https://petsc.org/release/install/download/#advanced-obtain-petsc-development-version-with-git you will not have the problem below (previously we required that a row exist before we zeroed it but now we allow the row to initially have no entries and still be zeroed.
>  
>   Barry
>  
>    
> On Feb 3, 2023, at 1:04 PM, Karthikeyan Chockalingam - STFC UKRI <karthikeyan.chockalingam at stfc.ac.uk <mailto:karthikeyan.chockalingam at stfc.ac.uk>> wrote:
>  
> Thank you. The entire error output was an attachment in my previous email. I am pasting here for your reference.
>  
>  
>  
> [1;31m[0]PETSC ERROR: --------------------- Error Message --------------------------------------------------------------
> [0;39m[0;49m[0]PETSC ERROR: Object is in wrong state
> [0]PETSC ERROR: Matrix is missing diagonal entry in row 0 (65792)
> [0]PETSC ERROR: WARNING! There are option(s) set that were not used! Could be the program crashed before they were used or a spelling mistake, etc!
> [0]PETSC ERROR: Option left: name:-options_left (no value)
> [0]PETSC ERROR: See https://petsc.org/release/faq/ for trouble shooting.
> [0]PETSC ERROR: Petsc Development GIT revision: v3.18.1-127-ga207d08eda  GIT Date: 2022-10-30 11:03:25 -0500
> [0]PETSC ERROR: /Users/karthikeyan.chockalingam/AMReX/amrFEM/build/Debug/amrFEM on a  named HC20210312 by karthikeyan.chockalingam Fri Feb  3 11:10:01 2023
> [0]PETSC ERROR: Configure options --with-debugging=0 --prefix=/Users/karthikeyan.chockalingam/AMReX/petsc --download-fblaslapack=yes --download-scalapack=yes --download-mumps=yes --with-hypre-dir=/Users/karthikeyan.chockalingam/AMReX/hypre/src/hypre
> [0]PETSC ERROR: #1 MatZeroRowsColumns_SeqAIJ() at /Users/karthikeyan.chockalingam/AMReX/SRC_PKG/petsc/src/mat/impls/aij/seq/aij.c:2218
> [0]PETSC ERROR: #2 MatZeroRowsColumns() at /Users/karthikeyan.chockalingam/AMReX/SRC_PKG/petsc/src/mat/interface/matrix.c:6085
> [0]PETSC ERROR: #3 MatZeroRowsColumns_MPIAIJ() at /Users/karthikeyan.chockalingam/AMReX/SRC_PKG/petsc/src/mat/impls/aij/mpi/mpiaij.c:879
> [0]PETSC ERROR: #4 MatZeroRowsColumns() at /Users/karthikeyan.chockalingam/AMReX/SRC_PKG/petsc/src/mat/interface/matrix.c:6085
> [0]PETSC ERROR: #5 MatZeroRowsColumnsIS() at /Users/karthikeyan.chockalingam/AMReX/SRC_PKG/petsc/src/mat/interface/matrix.c:6124
> [0]PETSC ERROR: #6 localAssembly() at /Users/karthikeyan.chockalingam/AMReX/amrFEM/src/FENodalPoisson.cpp:435
>     Residual norms for redistribute_ solve.
>     0 KSP preconditioned resid norm 5.182603110407e+00 true resid norm 1.382027496109e+01 ||r(i)||/||b|| 1.000000000000e+00
>     1 KSP preconditioned resid norm 1.862430383976e+00 true resid norm 4.966481023937e+00 ||r(i)||/||b|| 3.593619546588e-01
>     2 KSP preconditioned resid norm 2.132803507689e-01 true resid norm 5.687476020503e-01 ||r(i)||/||b|| 4.115313216645e-02
>     3 KSP preconditioned resid norm 5.499797533437e-02 true resid norm 1.466612675583e-01 ||r(i)||/||b|| 1.061203687852e-02
>     4 KSP preconditioned resid norm 2.829814271435e-02 true resid norm 7.546171390493e-02 ||r(i)||/||b|| 5.460217985345e-03
>     5 KSP preconditioned resid norm 7.431048995318e-03 true resid norm 1.981613065418e-02 ||r(i)||/||b|| 1.433844891652e-03
>     6 KSP preconditioned resid norm 3.182040728972e-03 true resid norm 8.485441943932e-03 ||r(i)||/||b|| 6.139850305312e-04
>     7 KSP preconditioned resid norm 1.030867020459e-03 true resid norm 2.748978721225e-03 ||r(i)||/||b|| 1.989091193167e-04
>     8 KSP preconditioned resid norm 4.469429300003e-04 true resid norm 1.191847813335e-03 ||r(i)||/||b|| 8.623908111021e-05
>     9 KSP preconditioned resid norm 1.237303313796e-04 true resid norm 3.299475503456e-04 ||r(i)||/||b|| 2.387416685085e-05
>    10 KSP preconditioned resid norm 5.822094326756e-05 true resid norm 1.552558487134e-04 ||r(i)||/||b|| 1.123391894522e-05
>    11 KSP preconditioned resid norm 1.735776150969e-05 true resid norm 4.628736402585e-05 ||r(i)||/||b|| 3.349236115503e-06
>   Linear redistribute_ solve converged due to CONVERGED_RTOL iterations 11
> KSP Object: (redistribute_) 1 MPI process
>   type: cg
>   maximum iterations=10000, initial guess is zero
>   tolerances:  relative=1e-05, absolute=1e-50, divergence=10000.
>   left preconditioning
>   using PRECONDITIONED norm type for convergence test
> PC Object: (redistribute_) 1 MPI process
>   type: jacobi
>     type DIAGONAL
>   linear system matrix = precond matrix:
>   Mat Object: 1 MPI process
>     type: mpiaij
>     rows=48896, cols=48896
>     total: nonzeros=307976, allocated nonzeros=307976
>     total number of mallocs used during MatSetValues calls=0
>       not using I-node (on process 0) routines
> End of program
>  solve time 0.564714744 seconds
> Starting max value is: 0
> Min value of level 0 is: 0
> Interpolated min value is: 741.978761
> Unused ParmParse Variables:
>   [TOP]::model.type(nvals = 1)  :: [3]
>   [TOP]::ref_ratio(nvals = 1)  :: [2]
>  
> AMReX (22.10-20-g3082028e4287) finalized
> #PETSc Option Table entries:
> -ksp_type preonly
> -options_left
> -pc_type redistribute
> -redistribute_ksp_converged_reason
> -redistribute_ksp_monitor_true_residual
> -redistribute_ksp_type cg
> -redistribute_ksp_view
> -redistribute_pc_type jacobi
> #End of PETSc Option Table entries
> There are no unused options.
> Program ended with exit code: 0
>  
>  
> Best,
> Karthik.
>  
> From: Barry Smith <bsmith at petsc.dev <mailto:bsmith at petsc.dev>>
> Date: Friday, 3 February 2023 at 17:41
> To: Chockalingam, Karthikeyan (STFC,DL,HC) <karthikeyan.chockalingam at stfc.ac.uk <mailto:karthikeyan.chockalingam at stfc.ac.uk>>
> Cc: petsc-users at mcs.anl.gov <mailto:petsc-users at mcs.anl.gov> <petsc-users at mcs.anl.gov <mailto:petsc-users at mcs.anl.gov>>
> Subject: Re: [petsc-users] Eliminating rows and columns which are zeros
> 
>  
>    We need all the error output for the errors you got below to understand why the errors are happening.
> 
> 
> 
> On Feb 3, 2023, at 11:41 AM, Karthikeyan Chockalingam - STFC UKRI <karthikeyan.chockalingam at stfc.ac.uk <mailto:karthikeyan.chockalingam at stfc.ac.uk>> wrote:
>  
> Hello Barry,
>  
> I would like to better understand pc_type redistribute usage. 
>  
> I am plan to use pc_type redistribute in the context of adaptive mesh refinement on a structured grid in 2D. My base mesh (level 0) is indexed from 0 to N-1 elements and refined mesh (level 1) is indexed from 0 to 4(N-1) elements. When I construct system matrix A on (level 1); I probably only use 20% of 4(N-1)  elements, however the indexes are scattered in the range of 0 to 4(N-1). That leaves 80% of the rows and columns of the system matrix A on (level 1) to be zero. From your earlier response, I believe this would be a use case for petsc_type redistribute.
>  
>   Indeed the linear solve will be more efficient if you use the redistribute solver. 
>  
>   But I don't understand your plan. With adaptive refinement I would just create the two matrices, one for the initial grid on which you solve the system, this will be a smaller matrix and then create a new larger matrix for the refined grid (and discard the previous matrix).
> 
> 
>  
>  
> Question (1)
>  
>  
> If N is really large, I would have to allocate memory of size 4(N-1) for the system matrix A on (level 1). How does pc_type redistribute help? Because, I did end up allocating memory for a large system, where most of the rows and columns are zeros. Is most of the allotted memory not wasted? Is this the correct usage?
>  
>   See above
> 
> 
>  
>  
> Question (2)
>  
>  
> I tried using pc_type redistribute for a two level system.
> I have attached the output only for  (level 1)
> The solution converges to right solution but still petsc outputs some error messages.
>  
> [0]PETSC ERROR: WARNING! There are option(s) set that were not used! Could be the program crashed before they were used or a spelling mistake, etc!
> [0]PETSC ERROR: Option left: name:-options_left (no value)
>  
> But the there were no unused options
>  
> #PETSc Option Table entries:
> -ksp_type preonly
> -options_left
> -pc_type redistribute
> -redistribute_ksp_converged_reason
> -redistribute_ksp_monitor_true_residual
> -redistribute_ksp_type cg
> -redistribute_ksp_view
> -redistribute_pc_type jacobi
> #End of PETSc Option Table entries
> There are no unused options.
> Program ended with exit code: 0
>  
> I cannot explain this
> 
> 
> 
> Question (2)
>  
> [0;39m[0;49m[0]PETSC ERROR: Object is in wrong state
> [0]PETSC ERROR: Matrix is missing diagonal entry in row 0 (65792)
>  
> What does this error message imply? Given I only use 20% of 4(N-1) indexes, I can imagine most of the diagonal entrees are zero. Is my understanding correct?
>  
>  
> Question (3)
> 
> 
> 
> [0]PETSC ERROR: #5 MatZeroRowsColumnsIS() at /Users/karthikeyan.chockalingam/AMReX/SRC_PKG/petsc/src/mat/interface/matrix.c:6124
>  
> I am using MatZeroRowsColumnsIS to set the homogenous Dirichelet boundary. I don’t follow why I get this error message as the linear system converges to the right solution.
>  
> Thank you for your help.
>  
> Kind regards,
> Karthik.
>  
>  
>  
> From: Barry Smith <bsmith at petsc.dev <mailto:bsmith at petsc.dev>>
> Date: Tuesday, 10 January 2023 at 18:50
> To: Chockalingam, Karthikeyan (STFC,DL,HC) <karthikeyan.chockalingam at stfc.ac.uk <mailto:karthikeyan.chockalingam at stfc.ac.uk>>
> Cc: petsc-users at mcs.anl.gov <mailto:petsc-users at mcs.anl.gov> <petsc-users at mcs.anl.gov <mailto:petsc-users at mcs.anl.gov>>
> Subject: Re: [petsc-users] Eliminating rows and columns which are zeros
> 
>  
>   Yes, after the solve the x will contain correct values for ALL the locations including the (zeroed out rows). You use case is exactly what redistribute it for.
>  
>   Barry
>  
> 
> 
> 
> 
> On Jan 10, 2023, at 11:25 AM, Karthikeyan Chockalingam - STFC UKRI <karthikeyan.chockalingam at stfc.ac.uk <mailto:karthikeyan.chockalingam at stfc.ac.uk>> wrote:
>  
> Thank you Barry. This is great!
>  
> I plan to solve using ‘-pc_type redistribute’ after applying the Dirichlet bc using
> MatZeroRowsColumnsIS(A, isout, 1, x, b); 
>  
> While I retrieve the solution data from x (after the solve) – can I index them using the original ordering (if I may say that)?
>  
> Kind regards,
> Karthik.
>  
> From: Barry Smith <bsmith at petsc.dev <mailto:bsmith at petsc.dev>>
> Date: Tuesday, 10 January 2023 at 16:04
> To: Chockalingam, Karthikeyan (STFC,DL,HC) <karthikeyan.chockalingam at stfc.ac.uk <mailto:karthikeyan.chockalingam at stfc.ac.uk>>
> Cc: petsc-users at mcs.anl.gov <mailto:petsc-users at mcs.anl.gov> <petsc-users at mcs.anl.gov <mailto:petsc-users at mcs.anl.gov>>
> Subject: Re: [petsc-users] Eliminating rows and columns which are zeros
> 
>  
> https://petsc.org/release/docs/manualpages/PC/PCREDISTRIBUTE/#pcredistribute   -pc_type redistribute
>  
>  
> It does everything for you. Note that if the right hand side for any of the "zero" rows is nonzero then the system is inconsistent and the system does not have a solution.
>  
> Barry
>  
> 
> 
> 
> 
> On Jan 10, 2023, at 10:30 AM, Karthikeyan Chockalingam - STFC UKRI via petsc-users <petsc-users at mcs.anl.gov <mailto:petsc-users at mcs.anl.gov>> wrote:
>  
> Hello,
>  
> I am assembling a MATIJ of size N, where a very large number of rows (and corresponding columns), are zeros. I would like to potentially eliminate them before the solve.
>  
> For instance say N=7
>  
> 0 0  0  0 0 0 0
> 0 1 -1  0 0 0 0
> 0 -1 2  0 0 0 -1
> 0 0  0  0 0 0 0
> 0 0  0  0 0 0 0
> 0 0  0  0 0 0 0
> 0 0  -1 0 0 0 1
>  
> I would like to reduce it to a 3x3
>  
> 1 -1 0
> -1 2 -1
> 0 -1 1
>  
> I do know the size N.
>  
> Q1) How do I do it?
> Q2) Is it better to eliminate them as it would save a lot of memory?
> Q3) At the moment, I don’t know which rows (and columns) have the zero entries but with some effort I probably can find them. Should I know which rows (and columns) I am eliminating?
>  
> Thank you.
>  
> Karthik.
> This email and any attachments are intended solely for the use of the named recipients. If you are not the intended recipient you must not use, disclose, copy or distribute this email or any of its attachments  and should notify the sender immediately and delete this email from your system. UK Research and Innovation (UKRI) has taken every reasonable precaution to minimise risk of this email or any attachments containing viruses or malware but the recipient should carry out its own virus and malware checks before opening the attachments. UKRI does not accept any liability for any losses or damages which the recipient may sustain due to presence of any viruses. 
> 
>  
> <petsc_redistribute.txt>

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