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Abdolreza_A_

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05-08-2017
11:32 AM

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INTEL MKL ERROR : PARAMETER 5 WAS INCORRECT ON ENTRY TO MKL_DDIASM

Hello to all of my new firends.

I am writing a code for "Turbulent Negarively Bouyant Jet" in these days for my thesis in BSc.

I would like to use MKL_DDIASM for part of my code but when I RUN the code this message appeares and all of my RHS result (argument C) will be zero. The message is : INTEL MKL ERROR : PARAMETER 5 WAS INCORRECT ON ENTRY TO MKL_DDIASM

Then I tried to make a simple code to understand exactly what DDIASM do. I wrote 2 simple codes which I bring here. The first code works well but the secnod code doesn't. I notice that the second code have a general sparse matrix "A".

When I define MATDESCRA (1) = "G" then this message will apear : INTEL MKL ERROR : PARAMETER 5 WAS INCORRECT ON ENTRY TO MKL_DDIASM

my 1st answer : What's the problem with "G" for MATDESCRA (1) ????!!!

my 2nd answer : what should I do to solve the system of equations in my 2nd simple code to obtain correct answers for that with DDIASM? (How must I define MATDESCRA exactly?)

PROGRAM 2nd_simple_code IMPLICIT NONE CHARACTER(1) , DIMENSION ( 4 ) :: MATDESCRA REAL (8) , DIMENSION ( 3 , 3 ) :: A REAL (8) , DIMENSION ( 3 , 2 ) :: B , C REAL (8) , DIMENSION ( 3 , 3 ) :: VAL INTEGER I , J CHARACTER(1) TRANSA INTEGER :: M , N , LVAL , NDIAG , LDB , LDC REAL (8) :: ALPHA INTEGER , DIMENSION ( 3 ) :: IDIAG A = 0 B = 0 C = 0 VAL = 0 IDIAG = 0 A ( 1 , 1 ) = 1.0D0 A ( 2 , 2 ) = 1.0D0 A ( 3 , 3 ) = 1.0D0 A ( 2 , 1 ) = 2.0D0 A ( 1 , 3 ) = 5.0D0 B ( 1 , 1 ) = 16.0D0 B ( 1 , 2 ) = 34.0D0 B ( 2 , 1 ) = 4.0D0 B ( 2 , 2 ) = 13.0D0 B ( 3 , 1 ) = 3.0D0 B ( 3 , 2 ) = 6.0D0 VAL ( 2 , 1 ) = 2.0D0 VAL ( 1 , 2 ) = 1.0D0 VAL ( 2 , 2 ) = 1.0D0 VAL ( 3 , 2 ) = 1.0D0 VAL ( 1 , 3 ) = 5.0D0 M = 3 N = 2 LVAL = 3 NDIAG = 3 LDB = 3 LDC = 3 ALPHA = 1.0D0 TRANSA = "N" MATDESCRA (1) = 'G' MATDESCRA (2) = 'U' MATDESCRA (3) = 'U' MATDESCRA (4) = 'F' IDIAG (1) = -1 IDIAG (2) = 0 IDIAG (3) = 2 CALL MKL_DDIASM ( TRANSA , M , N , ALPHA , MATDESCRA , VAL , LVAL , IDIAG , NDIAG , B , LDB , C , LDC ) DO I = 1 , 3 WRITE ( * , * ) (C (I ,J), J = 1 , 2) END DO READ(*,*) END PROGRAM 2nd_simple_code

*****************************************************************************************************

PROGRAM 1st_simple_code IMPLICIT NONE CHARACTER(1) , DIMENSION ( 4 ) :: MATDESCRA REAL (8) , DIMENSION ( 3 , 3 ) :: A REAL (8) , DIMENSION ( 3 , 2 ) :: B , C REAL (8) , DIMENSION ( 3 , 1 ) :: VAL INTEGER I , J CHARACTER(1) TRANSA INTEGER :: M , N , LVAL , NDIAG , LDB , LDC REAL (8) :: ALPHA INTEGER , DIMENSION ( 1 ) :: IDIAG A = 0 B = 0 C = 0 A ( 1 , 1 ) = 1.0D0 A ( 2 , 2 ) = 1.0D0 A ( 3 , 3 ) = 1.0D0 B ( 1 , 1 ) = 1.0D0 B ( 1 , 2 ) = 4.0D0 B ( 2 , 1 ) = 2.0D0 B ( 2 , 2 ) = 5.0D0 B ( 3 , 1 ) = 3.0D0 B ( 3 , 2 ) = 6.0D0 VAL ( 1 , 1 ) = 1.0D0 VAL ( 2 , 1 ) = 1.0D0 VAL ( 3 , 1 ) = 1.0D0 M = 3 N = 2 LVAL = 3 NDIAG = 1 LDB = 3 LDC = 3 ALPHA = 1.0D0 TRANSA = "N" MATDESCRA (1) = 'D' MATDESCRA (2) = 'U' MATDESCRA (3) = 'U' MATDESCRA (4) = 'F' IDIAG (1) = 0 CALL MKL_DDIASM ( TRANSA , M , N , ALPHA , MATDESCRA , VAL , LVAL , IDIAG , NDIAG , B , LDB , C , LDC ) DO I = 1 , 3 WRITE ( * , * ) (C (I ,J), J = 1 , 2) END DO READ(*,*) END PROGRAM 1st_simple_code

**************************************************************

Thanks a lot dear friends.

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9 Replies

mecej4

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05-08-2017
05:41 PM

207 Views

The reference manual page for the routine in question says:

Ais a sparse upper or lower triangular matrix with unit or non-unit main diagonal

If you specify 'G' as the first element of MATDESCRA, you are in violation of this limitation, because G signifies "general", which includes non-triangular matrices. See the table https://software.intel.com/en-us/node/468532#TBL2-7 for a list of the permitted values.

Abdolreza_A_

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05-08-2017
08:05 PM

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mecej4

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05-08-2017
08:37 PM

207 Views

(name withheld) wrote:

My opinion : I should split "A" into 3 parts : L + D + U

Note that the L-D-U decomposition is A = L D U (the product), not L + D + U (the sum).

Have you analysed the structure of the equations that you obtained by discretizing the PDE and applying the boundary conditions? Is diagonal storage the best representation? If not, we do not need to be talking about SPBLAS routines.

Abdolreza_A_

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05-08-2017
09:55 PM

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mecej4

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05-09-2017
09:36 AM

207 Views

If your simultaneous equations cannot be represented by a triangular matrix, you cannot use MKL_DDIAS. Whether diagonal storage is convenient or not is of little significance if you do not have a solver that matches your problem requirements.

Secondly, and I repeat what I said in #4, L, D and U are factors whose product, not sum, equals A.

Abdolreza_A_

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05-09-2017
12:04 PM

207 Views

Ying_H_Intel

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05-09-2017
08:38 PM

207 Views

Hello

Welcome to MKL forum. If you want to solve one sparse equation, you may need to use the PARDISO interface.

You can find all example code in MKL install folder. For example : C:\Program Files (x86)\IntelSWTools\compilers_and_libraries_2017.2.187\windows\mkl\examples\examples_core_f.zip => unzip it \solverf\source\ pardiso_unsym_f.f. Which will solve sparse matrix and get the X.

And you can read MKL user guide and developer guide to find more information:

https://software.intel.com/en-us/articles/intel-math-kernel-library-documentation

Best Regards,

Ying

!===============================================================================

* Content : Intel(R) MKL PARDISO Fortran example

*

********************************************************************************

C----------------------------------------------------------------------

C Example program to show the use of the "PARDISO" routine

C for nonsymmetric linear systems

C---------------------------------------------------------------------

C This program can be downloaded from the following site:

C www.pardiso-project.org

C

C (C) Olaf Schenk, Department of Computer Science,

C University of Basel, Switzerland.

C Email: olaf.schenk@unibas.ch

C

C---------------------------------------------------------------------

PROGRAM pardiso_unsym

IMPLICIT NONE

include 'mkl_pardiso.fi'

C.. Internal solver memory pointer for 64-bit architectures

C.. INTEGER*8 pt(64)

C.. Internal solver memory pointer for 32-bit architectures

C.. INTEGER*4 pt(64)

C.. This is OK in both cases

TYPE(MKL_PARDISO_HANDLE) pt(64)

C.. All other variables

INTEGER maxfct, mnum, mtype, phase, n, nrhs, error, msglvl

INTEGER iparm(64)

INTEGER ia(6)

INTEGER ja(13)

REAL*8 a(13)

REAL*8 b(5)

REAL*8 x(5)

INTEGER i, idum(1)

REAL*8 ddum(1)

C.. Fill all arrays containing matrix data.

DATA n /5/, nrhs /1/, maxfct /1/, mnum /1/

DATA ia /1,4,6,9,12,14/

DATA ja

1 /1,2, 4,

2 1,2,

3 3,4,5,

4 1, 3,4,

5 2, 5/

DATA a

1 / 1.d0,-1.d0, -3.d0,

2 -2.d0, 5.d0,

3 4.d0, 6.d0, 4.d0,

4 -4.d0, 2.d0, 7.d0,

5 8.d0, -5.d0/

C..

C.. Setup PARDISO control parameter

C..

DO i = 1, 64

iparm(i) = 0

END DO

iparm(1) = 1 ! no solver default

iparm(2) = 2 ! fill-in reordering from METIS

iparm(3) = 1 ! numbers of processors

iparm(4) = 0 ! no iterative-direct algorithm

iparm(5) = 0 ! no user fill-in reducing permutation

iparm(6) = 0 ! =0 solution on the first n components of x

iparm(7) = 0 ! not in use

iparm(8) = 9 ! numbers of iterative refinement steps

iparm(9) = 0 ! not in use

iparm(10) = 13 ! perturb the pivot elements with 1E-13

iparm(11) = 1 ! use nonsymmetric permutation and scaling MPS

iparm(12) = 0 ! not in use

iparm(13) = 1 ! maximum weighted matching algorithm is switched-on (default for non-symmetric)

iparm(14) = 0 ! Output: number of perturbed pivots

iparm(15) = 0 ! not in use

iparm(16) = 0 ! not in use

iparm(17) = 0 ! not in use

iparm(18) = -1 ! Output: number of nonzeros in the factor LU

iparm(19) = -1 ! Output: Mflops for LU factorization

iparm(20) = 0 ! Output: Numbers of CG Iterations

error = 0 ! initialize error flag

msglvl = 1 ! print statistical information

mtype = 11 ! real unsymmetric

C.. Initialize the internal solver memory pointer. This is only

C necessary for the FIRST call of the PARDISO solver.

DO i = 1, 64

pt(i)%DUMMY = 0

END DO

C.. Reordering and Symbolic Factorization, This step also allocates

C all memory that is necessary for the factorization

phase = 11 ! only reordering and symbolic factorization

CALL pardiso (pt, maxfct, mnum, mtype, phase, n, a, ia, ja,

& idum, nrhs, iparm, msglvl, ddum, ddum, error)

WRITE(*,*) 'Reordering completed ... '

IF (error .NE. 0) THEN

WRITE(*,*) 'The following ERROR was detected: ', error

STOP 1

END IF

WRITE(*,*) 'Number of nonzeros in factors = ',iparm(18)

WRITE(*,*) 'Number of factorization MFLOPS = ',iparm(19)

C.. Factorization.

phase = 22 ! only factorization

CALL pardiso (pt, maxfct, mnum, mtype, phase, n, a, ia, ja,

& idum, nrhs, iparm, msglvl, ddum, ddum, error)

WRITE(*,*) 'Factorization completed ... '

IF (error .NE. 0) THEN

WRITE(*,*) 'The following ERROR was detected: ', error

STOP 1

END IF

C.. Back substitution and iterative refinement

iparm(8) = 2 ! max numbers of iterative refinement steps

phase = 33 ! only factorization

DO i = 1, n

b(i) = 1.0D0

END DO

CALL pardiso (pt, maxfct, mnum, mtype, phase, n, a, ia, ja,

& idum, nrhs, iparm, msglvl, b, x, error)

WRITE(*,*) 'Solve completed ... '

WRITE(*,*) 'The solution of the system is '

DO i = 1, n

WRITE(*,*) ' x(',i,') = ', x(i)

END DO

C.. Termination and release of memory

phase = -1 ! release internal memory

CALL pardiso (pt, maxfct, mnum, mtype, phase, n, ddum, idum,

& idum, idum, nrhs, iparm, msglvl, ddum, ddum, error)

END PROGRAM pardiso_unsym

Abdolreza_A_

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05-10-2017
09:02 AM

207 Views

Ying_H_Intel

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05-10-2017
05:56 PM

207 Views

Hello,

Right, you can use the code directly with your input sparse matrix ( ia, ja and a). and later, you may change the parameters of MKL function according to your needs and matrix type.

You may refer to MKL developer reference manual and MKL developer guide, which are basic docs for MKL usage and MKL functionality.

https://software.intel.com/en-us/articles/intel-math-kernel-library-documentation

Best Regards,

Ying

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