No, I am not calling MatMPIAIJSetPreallocation(... N,NULL);
Here is what I do:
PetscInt d_nz = 10;
PetscInt o_nz = 10;
ierr = MatCreate(PETSC_COMM_WORLD, &A); CHKERRQ(ierr);
ierr = MatSetType(A, MATMPIAIJ); CHKERRQ(ierr);
ierr = MatSetSizes(A, PETSC_DECIDE, PETSC_DECIDE, N, N); CHKERRQ(ierr);
ierr = MatMPIAIJSetPreallocation(A, d_nz, NULL, o_nz, NULL); CHKERRQ(ierr);
(Q1)
As I am setting the size of A to be N x N via
ierr = MatSetSizes(A, PETSC_DECIDE, PETSC_DECIDE, N, N); CHKERRQ(ierr);
and pre-allocation is done for ALL rows I would like to understand if the
‘inactive rows’ are NOT contributing to memory (while using ‘redistribute’)?
(Q2)
I tried solving using hypre within redistribute and system converges to a
solution. Is below correct way to use hypre within redistribute?
ierr = PetscOptionsSetValue(NULL,"-ksp_type", "preonly");
ierr = PetscOptionsSetValue(NULL,"-pc_type", "redistribute");
ierr = PetscOptionsSetValue(NULL,"-redistribute_ksp_type", "cg");
ierr = PetscOptionsSetValue(NULL,"-redistribute_pc_type", "hypre");
ierr = PetscOptionsSetValue(NULL,"-redistribute_pc_hypre_type",
"boomeramg");
Many thanks,
Karthik.
From: Barry Smith <[email protected]>
Date: Tuesday, 7 February 2023 at 19:52
To: Chockalingam, Karthikeyan (STFC,DL,HC) <[email protected]>
Cc: [email protected] <[email protected]>
Subject: Re: [petsc-users] Eliminating rows and columns which are zeros
On Feb 7, 2023, at 1:20 PM, Karthikeyan Chockalingam - STFC UKRI
<[email protected]> wrote:
Thank you Barry for your detailed response.
I would like to shed some light into what I try to accomplish using PETSc and
AMReX. Please see the attachment adaptive mesh image (and ignore the mesh-order
legend for now).
The number of elements on each level is a geometric progression.
N - Number elements on each level indexed by ‘n’
n - Adaptive mesh level index (starting from 1)
a - Number of elements on the base mesh = 16
r = 4 (each element is divided into four on the next higher level of refinement)
N = a r^(n-1)
The final solution u, is the super imposition of solutions from all levels
(here we have a total of 7 levels).
u = u^(1) + u^(2) + … + u^(7)
Hence I have seven system matrix and solution vector pairs, one for each level.
On each level the element index vary from 1 to N. But on each level NOT all
elements are ‘active’.
As you can see from the attached image not all elements are active (a lot of
white hollow spaces). So the ‘active’ indexes can be scatted anywhere between 1
to N = 65536 for n = 7.
(Q1) In my case, I can’t at the moment insert 1 on the diagonal because during
assembly I am using ADD_VALUES as a node can be common to many elements. So I
added 0.0 to ALL diagonals. After global assembly, I find that the linear
solver converges.
(Q2) After adding 0.0 to all diagonal. I able to solve using either
ierr = PetscOptionsSetValue(NULL,"-redistribute_pc_type", "jacobi");
CHKERRQ(ierr);
or
ierr = PetscOptionsSetValue(NULL," pc_type", "jacobi"); CHKERRQ(ierr);
I was able to solve using hypre as well.
Do I need to use -pc_type redistribute or not? Because I am able to solve
without it as well.
No you do not need redistribute, but for large problems with many empty rows
using a solver inside redistribute will be faster than just using that solver
directly on the much larger (mostly empty) system.
(Q3) I am sorry, if I sound like a broken record player. On each level I
request allocation for A[N][N]
Not sure what you mean by this? Call MatMPIAIJSetPreallocation(... N,NULL);
where N is the number of columns in the matrix?
If so, yes this causes a huge malloc() by PETSc when it allocates the matrix.
It is not scalable. Do you have a small upper bound on the number of nonzeros
in a row, say 9 or 27? Then use that instead of N, not perfect but much better
than N.
Barry
as the indexes can be scatted anywhere between 1 to N but most are ‘inactive
rows’. Is -pc_type redistribute the way to go for me to save on memory? Though
I request A[N][N] allocation, and not all rows are active - I wonder if I am
wasting a huge amount of memory?
Kind regards,
Karthik.
From: Barry Smith <[email protected]<mailto:[email protected]>>
Date: Monday, 6 February 2023 at 22:42
To: Chockalingam, Karthikeyan (STFC,DL,HC)
<[email protected]<mailto:[email protected]>>
Cc: [email protected]<mailto:[email protected]>
<[email protected]<mailto:[email protected]>>
Subject: Re: [petsc-users] Eliminating rows and columns which are zeros
Sorry was not clear MatZero*. I just meant MatZeroRows() or
MatZeroRowsColumns()
On Feb 6, 2023, at 4:45 PM, Karthikeyan Chockalingam - STFC UKRI
<[email protected]<mailto:[email protected]>>
wrote:
No problem. I don’t completely follow.
(Q1) I have used MATMPIAJI but not sure what is MatZero* (star) and what it
does? And its relevance to my problem.
(Q2) Since I am creating a MATMPIAJI system– what would be the best way to
insert 0.0 in to ALL diagonals (both active and inactive rows) to begin with?
Yes, just have each MPI process loop over its rows and put zero on the
diagonal (actually, you could put a 1 if you want). Then have your code use
AMReX to
put all its values in, I am assuming the code uses INSERT_VALUES so it will
always overwrite the value you put in initially (hence putting in 1 initially
will be fine; the advantage of 1 is if you do not use PCREDISTIBUTE the matrix
is fully defined and so any solver will work. If you know the inactive rows you
can just put the diagonal on those since AMReX will fill up the rest of the
rows, but it is harmless to put values on all diagonal entries. Do NOT call
MatAssemblyBegin/End between filling the diagonal entries and having AMReX put
in its values.
(Q3) If I have to insert 0.0 only into diagonals of “inactive” rows after I
have put values into the matrix would be an effort. Unless there is a straight
forward to do it in PETSc.
(Q4) For my problem do I need to use PCREDISTIBUTE or any linear solve would
eliminate those rows?
Well no solver will really make sense if you have "inactive" rows, that is
rows with nothing in them except PCREDISTIBUTE.
When PETSc was written we didn't understand having lots of completely empty
rows was a use case so much of the functionality does not work in that case.
Best,
Karthik.
From: Barry Smith <[email protected]<mailto:[email protected]>>
Date: Monday, 6 February 2023 at 20:18
To: Chockalingam, Karthikeyan (STFC,DL,HC)
<[email protected]<mailto:[email protected]>>
Cc: [email protected]<mailto:[email protected]>
<[email protected]<mailto:[email protected]>>
Subject: Re: [petsc-users] Eliminating rows and columns which are zeros
Sorry, I had a mistake in my thinking, PCREDISTRIBUTE supports completely
empty rows but MatZero* does not.
When you put values into the matrix you will need to insert a 0.0 on the
diagonal of each "inactive" row; all of this will be eliminated during the
linear solve process. It would be a major project to change the MatZero*
functions to handle empty rows.
Barry
On Feb 4, 2023, at 12:06 PM, Karthikeyan Chockalingam - STFC UKRI
<[email protected]<mailto:[email protected]>>
wrote:
Thank you very much for offering to debug.
I built PETSc along with AMReX, so I tried to extract the PETSc code alone
which would reproduce the same error on the smallest sized problem possible.
I have attached three files:
petsc_amrex_error_redistribute.txt – The error message from amrex/petsc
interface, but THE linear system solves and converges to a solution.
problem.c – A simple stand-alone petsc code, which produces almost the same
error message.
petsc_ error_redistribute.txt – The error message from problem.c but strangely
it does NOT solve – I am not sure why?
Please use problem.c to debug the issue.
Kind regards,
Karthik.
From: Barry Smith <[email protected]<mailto:[email protected]>>
Date: Saturday, 4 February 2023 at 00:22
To: Chockalingam, Karthikeyan (STFC,DL,HC)
<[email protected]<mailto:[email protected]>>
Cc: [email protected]<mailto:[email protected]>
<[email protected]<mailto:[email protected]>>
Subject: Re: [petsc-users] Eliminating rows and columns which are zeros
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
<[email protected]<mailto:[email protected]>>
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 <[email protected]<mailto:[email protected]>>
Date: Friday, 3 February 2023 at 18:51
To: Chockalingam, Karthikeyan (STFC,DL,HC)
<[email protected]<mailto:[email protected]>>
Cc: [email protected]<mailto:[email protected]>
<[email protected]<mailto:[email protected]>>
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
<[email protected]<mailto:[email protected]>>
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 <[email protected]<mailto:[email protected]>>
Date: Friday, 3 February 2023 at 17:41
To: Chockalingam, Karthikeyan (STFC,DL,HC)
<[email protected]<mailto:[email protected]>>
Cc: [email protected]<mailto:[email protected]>
<[email protected]<mailto:[email protected]>>
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
<[email protected]<mailto:[email protected]>>
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 <[email protected]<mailto:[email protected]>>
Date: Tuesday, 10 January 2023 at 18:50
To: Chockalingam, Karthikeyan (STFC,DL,HC)
<[email protected]<mailto:[email protected]>>
Cc: [email protected]<mailto:[email protected]>
<[email protected]<mailto:[email protected]>>
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
<[email protected]<mailto:[email protected]>>
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 <[email protected]<mailto:[email protected]>>
Date: Tuesday, 10 January 2023 at 16:04
To: Chockalingam, Karthikeyan (STFC,DL,HC)
<[email protected]<mailto:[email protected]>>
Cc: [email protected]<mailto:[email protected]>
<[email protected]<mailto:[email protected]>>
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 <[email protected]<mailto:[email protected]>> 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>
<petsc_error_redistribute.txt><petsc_amrex_error_redistribute.txt><problem.c>
<adaptive_mesh_level.png>
