# superlu_dist options

Fredrik Bengzon fredrik.bengzon at math.umu.se
Fri May 8 10:59:55 CDT 2009

```Hi,
Here is the output from the KSP and EPS objects, and the log summary.
/ Fredrik

#nodes=19345
#elements=81895
#nodes per element=4
Partitioning mesh with METIS 4.0
Element distribution (rank | #elements)
0 | 19771
1 | 20954
2 | 20611
3 | 20559
rank 1 has 257 ghost nodes
rank 0 has 127 ghost nodes
rank 2 has 143 ghost nodes
rank 3 has 270 ghost nodes
Calling 3D Navier-Lame Eigenvalue Solver
Assembling stiffness and mass matrix
Solving eigensystem with SLEPc
KSP Object:(st_)
type: preonly
maximum iterations=100000, initial guess is zero
tolerances:  relative=1e-08, absolute=1e-50, divergence=10000
left preconditioning
PC Object:(st_)
type: lu
LU: out-of-place factorization
matrix ordering: natural
LU: tolerance for zero pivot 1e-12
EPS Object:
problem type: generalized symmetric eigenvalue problem
method: krylovschur
extraction type: Rayleigh-Ritz
selected portion of the spectrum: largest eigenvalues in magnitude
number of eigenvalues (nev): 4
number of column vectors (ncv): 19
maximum dimension of projected problem (mpd): 19
maximum number of iterations: 6108
tolerance: 1e-05
dimension of user-provided deflation space: 0
IP Object:
orthogonalization method:   classical Gram-Schmidt
orthogonalization refinement:   if needed (eta: 0.707100)
ST Object:
type: sinvert
shift: 0
Matrices A and B have same nonzero pattern
Associated KSP object
------------------------------
KSP Object:(st_)
type: preonly
maximum iterations=100000, initial guess is zero
tolerances:  relative=1e-08, absolute=1e-50, divergence=10000
left preconditioning
PC Object:(st_)
type: lu
LU: out-of-place factorization
matrix ordering: natural
LU: tolerance for zero pivot 1e-12
LU: factor fill ratio needed 0
Factored matrix follows
Matrix Object:
type=mpiaij, rows=58035, cols=58035
package used to perform factorization: superlu_dist
total: nonzeros=0, allocated nonzeros=116070
SuperLU_DIST run parameters:
Process grid nprow 2 x npcol 2
Equilibrate matrix TRUE
Matrix input mode 1
Replace tiny pivots TRUE
Use iterative refinement FALSE
Processors in row 2 col partition 2
Row permutation LargeDiag
Column permutation PARMETIS
Parallel symbolic factorization TRUE
Repeated factorization SamePattern
linear system matrix = precond matrix:
Matrix Object:
type=mpiaij, rows=58035, cols=58035
total: nonzeros=2223621, allocated nonzeros=2233584
using I-node (on process 0) routines: found 4695 nodes,
limit used is 5
------------------------------
Number of iterations in the eigensolver: 1
Number of requested eigenvalues: 4
Stopping condition: tol=1e-05, maxit=6108
Number of converged eigenpairs: 8

Writing binary .vtu file /scratch/fredrik/output/mode-0.vtu
Writing binary .vtu file /scratch/fredrik/output/mode-1.vtu
Writing binary .vtu file /scratch/fredrik/output/mode-2.vtu
Writing binary .vtu file /scratch/fredrik/output/mode-3.vtu
Writing binary .vtu file /scratch/fredrik/output/mode-4.vtu
Writing binary .vtu file /scratch/fredrik/output/mode-5.vtu
Writing binary .vtu file /scratch/fredrik/output/mode-6.vtu
Writing binary .vtu file /scratch/fredrik/output/mode-7.vtu
************************************************************************************************************************
***             WIDEN YOUR WINDOW TO 120 CHARACTERS.  Use 'enscript -r
-fCourier9' to print this document            ***
************************************************************************************************************************

---------------------------------------------- PETSc Performance
Summary: ----------------------------------------------

/home/fredrik/Hakan/cmlfet/a.out on a linux-gnu named medusa1 with 4
processors, by fredrik Fri May  8 17:57:28 2009
Using Petsc Release Version 3.0.0, Patch 5, Mon Apr 13 09:15:37 CDT 2009

Max       Max/Min        Avg      Total
Time (sec):           5.429e+02      1.00001   5.429e+02
Objects:              1.380e+02      1.00000   1.380e+02
Flops:                1.053e+08      1.05695   1.028e+08  4.114e+08
Flops/sec:            1.939e+05      1.05696   1.894e+05  7.577e+05
Memory:               5.927e+07      1.03224              2.339e+08
MPI Messages:         2.880e+02      1.51579   2.535e+02  1.014e+03
MPI Message Lengths:  4.868e+07      1.08170   1.827e+05  1.853e+08
MPI Reductions:       1.122e+02      1.00000

Flop counting convention: 1 flop = 1 real number operation of type
e.g., VecAXPY() for real vectors of length N
--> 2N flops
and VecAXPY() for complex vectors of length
N --> 8N flops

Summary of Stages:   ----- Time ------  ----- Flops -----  --- Messages
---  -- Message Lengths --  -- Reductions --
Avg     %Total     Avg     %Total   counts
%Total     Avg         %Total   counts   %Total
0:      Main Stage: 5.4292e+02 100.0%  4.1136e+08 100.0%  1.014e+03
100.0%  1.827e+05      100.0%  3.600e+02  80.2%

------------------------------------------------------------------------------------------------------------------------
See the 'Profiling' chapter of the users' manual for details on
interpreting output.
Phase summary info:
Count: number of times phase was executed
Time and Flops: Max - maximum over all processors
Ratio - ratio of maximum to minimum over all processors
Mess: number of messages sent
Avg. len: average message length
Reduct: number of global reductions
Global: entire computation
Stage: stages of a computation. Set stages with PetscLogStagePush()
and PetscLogStagePop().
%T - percent time in this phase         %F - percent flops in this
phase
%M - percent messages in this phase     %L - percent message
lengths in this phase
%R - percent reductions in this phase
Total Mflop/s: 10e-6 * (sum of flops over all processors)/(max time
over all processors)
------------------------------------------------------------------------------------------------------------------------

##########################################################
#                                                        #
#                          WARNING!!!                    #
#                                                        #
#   This code was compiled with a debugging option,      #
#   To get timing results run config/configure.py        #
#   using --with-debugging=no, the performance will      #
#   be generally two or three times faster.              #
#                                                        #
##########################################################

Event                Count      Time (sec)
Flops                             --- Global ---  --- Stage ---   Total
Max Ratio  Max     Ratio   Max  Ratio  Mess   Avg len
Reduct  %T %F %M %L %R  %T %F %M %L %R Mflop/s
------------------------------------------------------------------------------------------------------------------------

--- Event Stage 0: Main Stage

STSetUp                1 1.0 1.0467e+01 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
8.0e+00  2  0  0  0  2   2  0  0  0  2     0
STApply               28 1.0 5.1775e+02 1.0 3.15e+07 1.1 1.7e+02 4.2e+03
2.8e+01 95 30 17  0  6  95 30 17  0  8     0
EPSSetUp               1 1.0 1.0482e+01 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
4.6e+01  2  0  0  0 10   2  0  0  0 13     0
EPSSolve               1 1.0 3.7193e+02 1.0 9.59e+07 1.1 3.5e+02 4.2e+03
9.7e+01 69 91 35  1 22  69 91 35  1 27     1
IPOrthogonalize       19 1.0 3.4406e-01 1.1 6.75e+07 1.1 2.3e+02 4.2e+03
7.6e+01  0 64 22  1 17   0 64 22  1 21   767
IPInnerProduct       153 1.0 3.1410e-01 1.0 5.63e+07 1.1 2.3e+02 4.2e+03
3.9e+01  0 53 23  1  9   0 53 23  1 11   700
IPApplyMatrix         39 1.0 2.4903e-01 1.1 4.38e+07 1.1 2.3e+02 4.2e+03
0.0e+00  0 42 23  1  0   0 42 23  1  0   687
UpdateVectors          1 1.0 4.2958e-03 1.2 4.51e+06 1.1 0.0e+00 0.0e+00
0.0e+00  0  4  0  0  0   0  4  0  0  0  4107
VecDot                 1 1.0 5.6815e-04 4.7 2.97e+04 1.1 0.0e+00 0.0e+00
1.0e+00  0  0  0  0  0   0  0  0  0  0   204
VecNorm                8 1.0 2.5260e-03 3.2 2.38e+05 1.1 0.0e+00 0.0e+00
8.0e+00  0  0  0  0  2   0  0  0  0  2   368
VecScale              27 1.0 5.9605e-04 1.1 4.01e+05 1.1 0.0e+00 0.0e+00
0.0e+00  0  0  0  0  0   0  0  0  0  0  2629
VecCopy               53 1.0 4.0610e-03 1.4 0.00e+00 0.0 0.0e+00 0.0e+00
0.0e+00  0  0  0  0  0   0  0  0  0  0     0
VecSet                77 1.0 6.2165e-03 1.1 0.00e+00 0.0 0.0e+00 0.0e+00
0.0e+00  0  0  0  0  0   0  0  0  0  0     0
VecAXPY               38 1.0 2.7709e-03 1.7 1.13e+06 1.1 0.0e+00 0.0e+00
0.0e+00  0  1  0  0  0   0  1  0  0  0  1592
VecMAXPY              38 1.0 2.5925e-02 1.1 1.13e+07 1.1 0.0e+00 0.0e+00
0.0e+00  0 11  0  0  0   0 11  0  0  0  1701
VecAssemblyBegin       5 1.0 9.0070e-03 2.3 0.00e+00 0.0 3.6e+01 2.1e+04
1.5e+01  0  0  4  0  3   0  0  4  0  4     0
VecAssemblyEnd         5 1.0 3.4809e-04 1.1 0.00e+00 0.0 0.0e+00 0.0e+00
0.0e+00  0  0  0  0  0   0  0  0  0  0     0
VecScatterBegin       73 1.0 8.5931e-03 1.5 0.00e+00 0.0 4.6e+02 8.9e+03
0.0e+00  0  0 45  2  0   0  0 45  2  0     0
VecScatterEnd         73 1.0 2.2542e-02 2.2 0.00e+00 0.0 0.0e+00 0.0e+00
0.0e+00  0  0  0  0  0   0  0  0  0  0     0
VecReduceArith        76 1.0 3.0838e-02 1.1 1.24e+07 1.1 0.0e+00 0.0e+00
0.0e+00  0 12  0  0  0   0 12  0  0  0  1573
VecReduceComm         38 1.0 4.8040e-02 2.0 0.00e+00 0.0 0.0e+00 0.0e+00
3.8e+01  0  0  0  0  8   0  0  0  0 11     0
VecNormalize           8 1.0 2.7280e-03 2.8 3.56e+05 1.1 0.0e+00 0.0e+00
8.0e+00  0  0  0  0  2   0  0  0  0  2   511
MatMult               67 1.0 4.1397e-01 1.1 7.53e+07 1.1 4.0e+02 4.2e+03
0.0e+00  0 71 40  1  0   0 71 40  1  0   710
MatSolve              28 1.0 5.1757e+02 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
0.0e+00 95  0  0  0  0  95  0  0  0  0     0
MatLUFactorSym         1 1.0 3.6097e-04 1.1 0.00e+00 0.0 0.0e+00 0.0e+00
0.0e+00  0  0  0  0  0   0  0  0  0  0     0
MatLUFactorNum         1 1.0 1.0464e+01 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
0.0e+00  2  0  0  0  0   2  0  0  0  0     0
MatAssemblyBegin       9 1.0 3.3842e-0146.7 0.00e+00 0.0 5.4e+01 6.0e+04
8.0e+00  0  0  5  2  2   0  0  5  2  2     0
MatAssemblyEnd         9 1.0 2.3042e-01 1.0 0.00e+00 0.0 3.6e+01 9.4e+02
3.1e+01  0  0  4  0  7   0  0  4  0  9     0
MatGetRow           5206 1.1 3.1164e-03 1.1 0.00e+00 0.0 0.0e+00 0.0e+00
0.0e+00  0  0  0  0  0   0  0  0  0  0     0
MatGetSubMatrice       5 1.0 8.7580e-01 1.2 0.00e+00 0.0 1.5e+02 1.1e+06
2.5e+01  0  0 15 88  6   0  0 15 88  7     0
MatZeroEntries         2 1.0 1.0233e-02 1.1 0.00e+00 0.0 0.0e+00 0.0e+00
0.0e+00  0  0  0  0  0   0  0  0  0  0     0
MatView                2 1.0 1.0149e-03 2.0 0.00e+00 0.0 0.0e+00 0.0e+00
2.0e+00  0  0  0  0  0   0  0  0  0  1     0
KSPSetup               1 1.0 2.8610e-06 1.5 0.00e+00 0.0 0.0e+00 0.0e+00
0.0e+00  0  0  0  0  0   0  0  0  0  0     0
KSPSolve              28 1.0 5.1758e+02 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
2.8e+01 95  0  0  0  6  95  0  0  0  8     0
PCSetUp                1 1.0 1.0467e+01 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
8.0e+00  2  0  0  0  2   2  0  0  0  2     0
PCApply               28 1.0 5.1757e+02 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
0.0e+00 95  0  0  0  0  95  0  0  0  0     0
------------------------------------------------------------------------------------------------------------------------

Memory usage is given in bytes:

Object Type          Creations   Destructions   Memory  Descendants' Mem.

--- Event Stage 0: Main Stage

Spectral Transform     1              1        536     0
Eigenproblem Solver     1              1        824     0
Inner product     1              1        428     0
Index Set    38             38    1796776     0
IS L to G Mapping     1              1      58700     0
Vec    65             65    5458584     0
Vec Scatter     9              9       7092     0
Application Order     1              1     155232     0
Matrix    17             16   17715680     0
Krylov Solver     1              1        832     0
Preconditioner     1              1        744     0
Viewer     2              2       1088     0
========================================================================================================================
Average time to get PetscTime(): 1.90735e-07
Average time for MPI_Barrier(): 5.9557e-05
Average time for zero size MPI_Send(): 2.97427e-05
#PETSc Option Table entries:
-log_summary
-mat_superlu_dist_parsymbfact
#End o PETSc Option Table entries
Compiled without FORTRAN kernels
Compiled with full precision matrices (default)
sizeof(short) 2 sizeof(int) 4 sizeof(long) 8 sizeof(void*) 8
sizeof(PetscScalar) 8
Configure run at: Wed May  6 15:14:39 2009
--with-mpi-dir=/usr/lib/mpich --with-shared=0
-----------------------------------------
Libraries compiled on Wed May  6 15:14:49 CEST 2009 on medusa1
Machine characteristics: Linux medusa1 2.6.18-6-amd64 #1 SMP Fri Dec 12
05:49:32 UTC 2008 x86_64 GNU/Linux
Using PETSc directory: /home/fredrik/Hakan/cmlfet/external/petsc-3.0.0-p5
Using PETSc arch: linux-gnu-c-debug
-----------------------------------------
Using C compiler: /usr/lib/mpich/bin/mpicc -Wall -Wwrite-strings
-Wno-strict-aliasing -g3
Using Fortran compiler: /usr/lib/mpich/bin/mpif77 -Wall
-Wno-unused-variable -g
-----------------------------------------
Using include paths:
-I/home/fredrik/Hakan/cmlfet/external/petsc-3.0.0-p5/linux-gnu-c-debug/include
-I/home/fredrik/Hakan/cmlfet/external/petsc-3.0.0-p5/include
-I/home/fredrik/Hakan/cmlfet/external/petsc-3.0.0-p5/linux-gnu-c-debug/include
-I/usr/lib/mpich/include
------------------------------------------
Using C linker: /usr/lib/mpich/bin/mpicc -Wall -Wwrite-strings
-Wno-strict-aliasing -g3
-Wno-unused-variable -g
Using libraries:
-Wl,-rpath,/home/fredrik/Hakan/cmlfet/external/petsc-3.0.0-p5/linux-gnu-c-debug/lib
-L/home/fredrik/Hakan/cmlfet/external/petsc-3.0.0-p5/linux-gnu-c-debug/lib
-lpetscts -lpetscsnes -lpetscksp -lpetscdm -lpetscmat -lpetscvec
-lpetsc        -lX11
-Wl,-rpath,/home/fredrik/Hakan/cmlfet/external/petsc-3.0.0-p5/linux-gnu-c-debug/lib
-L/home/fredrik/Hakan/cmlfet/external/petsc-3.0.0-p5/linux-gnu-c-debug/lib
-lsuperlu_dist_2.3 -llapack -lblas -lparmetis -lmetis -lm
-L/usr/lib/mpich/lib -L/usr/lib/gcc/x86_64-linux-gnu/4.1.2 -L/usr/lib64
-L/lib64 -ldl -lmpich -lpthread -lrt -lgcc_s -lg2c -lm
-L/usr/lib/gcc/x86_64-linux-gnu/3.4.6 -L/lib -lm -ldl -lmpich -lpthread
-lrt -lgcc_s -ldl
------------------------------------------

real    9m10.616s
user    0m23.921s
sys    0m6.944s

Satish Balay wrote:
> Just a note about scalability: its a function of the hardware as
> well.. For proper scalability studies - you'll need a true distributed
> system with fast network [not SMP nodes..]
>
> Satish
>
> On Fri, 8 May 2009, Fredrik Bengzon wrote:
>
>
>> Hong,
>> Thank you for the suggestions, but I have looked at the EPS and KSP objects
>> and I can not find anything wrong. The problem is that it takes longer to
>> solve with 4 cpus than with 2 so the scalability seems to be absent when using
>> superlu_dist. I have stored my mass and stiffness matrix in the mpiaij format
>> and just passed them on to slepc. When using the petsc iterative krylov
>> solvers i see 100% workload on all processors but when i switch to
>> superlu_dist only two cpus seem to do the whole work of LU factoring. I don't
>> want to use the krylov solver though since it might cause slepc not to
>> converge.
>> Regards,
>> Fredrik
>>
>> Hong Zhang wrote:
>>
>>> Run your code with '-eps_view -ksp_view' for checking
>>> which methods are used
>>> and '-log_summary' to see which operations dominate
>>> the computation.
>>>
>>> You can turn on parallel symbolic factorization
>>> with '-mat_superlu_dist_parsymbfact'.
>>>
>>> Unless you use large num of processors, symbolic factorization
>>> takes ignorable execution time. The numeric
>>> factorization usually dominates.
>>>
>>> Hong
>>>
>>> On Fri, 8 May 2009, Fredrik Bengzon wrote:
>>>
>>>
>>>> Hi Petsc team,
>>>> Sorry for posting questions not really concerning the petsc core, but when
>>>> I run superlu_dist from within slepc I notice that the load balance is
>>>> poor. It is just fine during assembly (I use Metis to partition my finite
>>>> element mesh) but when calling the slepc solver it dramatically changes. I
>>>> use superlu_dist as solver for the eigenvalue iteration. My question is:
>>>> can this have something to do with the fact that the option 'Parallel
>>>> symbolic factorization' is set to false? If so, can I change the options
>>>> to superlu_dist using MatSetOption for instance? Also, does this mean that
>>>> superlu_dist is not using parmetis to reorder the matrix?
>>>> Best Regards,
>>>> Fredrik Bengzon
>>>>
>>>>
>>>>
>>
>
>
>

```