Symbolic factorization in Pardiso

Symbolic factorization in Pardiso

Hi All,

I use Pardiso to solve reactive transport problem. I tried to do symbolic factorization at first and then in the following newton iterations, only do numerical factorization and substitution.

For the simple problem, this works fine. But for the complex problem, things are quite different. The results are correct in the beginning, but after many iterations, the result is incorrect with large error. Then I tried to do symbolic factorization every step, it can generate correct results.

The structure of matrix (ia, ja) does not change for the whole simulation, only the coefficient (a) and right hand (b) changes. What's wrong with my setting?

The parameter for pardiso are as follows:
        iparm = 0
        iparm(1) = 1 ! no solver default
        iparm(2) = 3 ! fill-in reordering from METIS ,0-MIN DEGREE, 2-METIS, 3-OPENMP VERSION
        iparm(3) = 0 ! numbers of processors. Input the next call mkl_set_dynamic(0), mkl_set_num_threads(n);    
        iparm(4) = 61 ! 0-no iterative-direct algorithm; 10*L+K, K=1 CGS, K=2 CGS for symmetric, 1.0E-L: stopping criterion
        iparm(5) = 0 ! no user fill-in reducing permutation
        iparm(6) = 0 ! if == 0, the array of b is replaced with the solution x.
        iparm(7) = 0 ! Output, Number of iterative refinement steps performed
        iparm(8) = 9 ! numbers of iterative refinement steps, must be 0 if a solution is calculated with separate substitutions (phase = 331, 332, 333)
        iparm(9) = 0 ! not in use
        iparm(10) = 13 ! Default value 13, perturbe 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 ! Output, Peak memory on symbolic factorization.
        iparm(16) = 0 ! Output, Permanent memory on symbolic factorization. This value is only computed in phase 1.
        iparm(17) = 0 ! Output, Size of factors/Peak memory on numerical factorization and solution.
        iparm(18) = 0 ! Input/output. Report the number of non-zero elements in the factors. >= 0 Disable reporting.
        iparm(19) = 0 ! Input/output. Report number of floating point operations to factor matrix A. >= 0 Disable reporting.
        iparm(20) = 0 ! Output: Numbers of CG Iterations. >0 CGS succeeded, reports the number of completed iterations.
        iparm(24) = 1 ! Parallel factorization control, 0: classic algorithm, 1: two-level factorization algorithm, improve scalability on many threads.
        iparm(25) = 0 ! Parallel forward/backward solve control. 0: Use parallel algorithm for the solve step; 1: Use the sequential forward/backward solve.         
        iparm(27) = 0 !check matrix error, 0-without check, 1-check

        maxfct = 1        
        mnum = 1        
        nrhs = 1        
        error = 0 ! initialize error flag        
        msglvl = 0 ! print statistical information        
        mtype = 11 ! real unsymmetric

Thanks and regards,


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The topic is duplicate of, so I wrote my answer there.

With best regards,

Alexander Kalinkin

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