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 <bsm...@petsc.dev>
Date: Friday, 3 February 2023 at 17:41
To: Chockalingam, Karthikeyan (STFC,DL,HC) <karthikeyan.chockalin...@stfc.ac.uk>
Cc: petsc-users@mcs.anl.gov <petsc-users@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.chockalin...@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 <bsm...@petsc.dev<mailto:bsm...@petsc.dev>>
Date: Tuesday, 10 January 2023 at 18:50
To: Chockalingam, Karthikeyan (STFC,DL,HC) 
<karthikeyan.chockalin...@stfc.ac.uk<mailto:karthikeyan.chockalin...@stfc.ac.uk>>
Cc: petsc-users@mcs.anl.gov<mailto:petsc-users@mcs.anl.gov> 
<petsc-users@mcs.anl.gov<mailto:petsc-users@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.chockalin...@stfc.ac.uk<mailto:karthikeyan.chockalin...@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 <bsm...@petsc.dev<mailto:bsm...@petsc.dev>>
Date: Tuesday, 10 January 2023 at 16:04
To: Chockalingam, Karthikeyan (STFC,DL,HC) 
<karthikeyan.chockalin...@stfc.ac.uk<mailto:karthikeyan.chockalin...@stfc.ac.uk>>
Cc: petsc-users@mcs.anl.gov<mailto:petsc-users@mcs.anl.gov> 
<petsc-users@mcs.anl.gov<mailto:petsc-users@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@mcs.anl.gov<mailto:petsc-users@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.

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<petsc_redistribute.txt>

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