Actual source code: factor.c
petsc-3.7.1 2016-05-15
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      2: #include <../src/ksp/pc/impls/factor/factor.h>  /*I "petscpc.h" I*/

      6: /*@
      7:     PCFactorSetUpMatSolverPackage - Can be called after KSPSetOperators() or PCSetOperators(), causes MatGetFactor() to be called so then one may
      8:        set the options for that particular factorization object.

     10:   Input Parameter:
     11: .  pc  - the preconditioner context

     13:   Notes: After you have called this function (which has to be after the KSPSetOperators() or PCSetOperators()) you can call PCFactorGetMatrix() and then set factor options on that matrix.

     15: .seealso: PCFactorSetMatSolverPackage(), PCFactorGetMatrix()

     17:   Level: intermediate

     19: @*/
     20: PetscErrorCode PCFactorSetUpMatSolverPackage(PC pc)
     21: {

     26:   PetscTryMethod(pc,"PCFactorSetUpMatSolverPackage_C",(PC),(pc));
     27:   return(0);
     28: }

     32: /*@
     33:    PCFactorSetZeroPivot - Sets the size at which smaller pivots are declared to be zero

     35:    Logically Collective on PC

     37:    Input Parameters:
     38: +  pc - the preconditioner context
     39: -  zero - all pivots smaller than this will be considered zero

     41:    Options Database Key:
     42: .  -pc_factor_zeropivot <zero> - Sets tolerance for what is considered a zero pivot

     44:    Level: intermediate

     46: .keywords: PC, set, factorization, direct, fill

     48: .seealso: PCFactorSetShiftType(), PCFactorSetShiftAmount()
     49: @*/
     50: PetscErrorCode  PCFactorSetZeroPivot(PC pc,PetscReal zero)
     51: {

     57:   PetscTryMethod(pc,"PCFactorSetZeroPivot_C",(PC,PetscReal),(pc,zero));
     58:   return(0);
     59: }

     63: /*@
     64:    PCFactorSetShiftType - adds a particular type of quantity to the diagonal of the matrix during
     65:      numerical factorization, thus the matrix has nonzero pivots

     67:    Logically Collective on PC

     69:    Input Parameters:
     70: +  pc - the preconditioner context
     71: -  shifttype - type of shift; one of MAT_SHIFT_NONE, MAT_SHIFT_NONZERO,  MAT_SHIFT_POSITIVE_DEFINITE, MAT_SHIFT_INBLOCKS

     73:    Options Database Key:
     74: .  -pc_factor_shift_type <shifttype> - Sets shift type or PETSC_DECIDE for the default; use '-help' for a list of available types

     76:    Level: intermediate

     78: .keywords: PC, set, factorization,

     80: .seealso: PCFactorSetZeroPivot(), PCFactorSetShiftAmount()
     81: @*/
     82: PetscErrorCode  PCFactorSetShiftType(PC pc,MatFactorShiftType shifttype)
     83: {

     89:   PetscTryMethod(pc,"PCFactorSetShiftType_C",(PC,MatFactorShiftType),(pc,shifttype));
     90:   return(0);
     91: }

     95: /*@
     96:    PCFactorSetShiftAmount - adds a quantity to the diagonal of the matrix during
     97:      numerical factorization, thus the matrix has nonzero pivots

     99:    Logically Collective on PC

    101:    Input Parameters:
    102: +  pc - the preconditioner context
    103: -  shiftamount - amount of shift

    105:    Options Database Key:
    106: .  -pc_factor_shift_amount <shiftamount> - Sets shift amount or PETSC_DECIDE for the default

    108:    Level: intermediate

    110: .keywords: PC, set, factorization,

    112: .seealso: PCFactorSetZeroPivot(), PCFactorSetShiftType()
    113: @*/
    114: PetscErrorCode  PCFactorSetShiftAmount(PC pc,PetscReal shiftamount)
    115: {

    121:   PetscTryMethod(pc,"PCFactorSetShiftAmount_C",(PC,PetscReal),(pc,shiftamount));
    122:   return(0);
    123: }

    127: /*
    128:    PCFactorSetDropTolerance - The preconditioner will use an ILU
    129:    based on a drop tolerance. (Under development)

    131:    Logically Collective on PC

    133:    Input Parameters:
    134: +  pc - the preconditioner context
    135: .  dt - the drop tolerance, try from 1.e-10 to .1
    136: .  dtcol - tolerance for column pivot, good values [0.1 to 0.01]
    137: -  maxrowcount - the max number of nonzeros allowed in a row, best value
    138:                  depends on the number of nonzeros in row of original matrix

    140:    Options Database Key:
    141: .  -pc_factor_drop_tolerance <dt,dtcol,maxrowcount> - Sets drop tolerance

    143:    Level: intermediate

    145:       There are NO default values for the 3 parameters, you must set them with reasonable values for your
    146:       matrix. We don't know how to compute reasonable values.

    148: .keywords: PC, levels, reordering, factorization, incomplete, ILU
    149: */
    150: PetscErrorCode  PCFactorSetDropTolerance(PC pc,PetscReal dt,PetscReal dtcol,PetscInt maxrowcount)
    151: {

    158:   PetscTryMethod(pc,"PCFactorSetDropTolerance_C",(PC,PetscReal,PetscReal,PetscInt),(pc,dt,dtcol,maxrowcount));
    159:   return(0);
    160: }

    164: /*@
    165:    PCFactorGetLevels - Gets the number of levels of fill to use.

    167:    Logically Collective on PC

    169:    Input Parameters:
    170: .  pc - the preconditioner context

    172:    Output Parameter:
    173: .  levels - number of levels of fill

    175:    Level: intermediate

    177: .keywords: PC, levels, fill, factorization, incomplete, ILU
    178: @*/
    179: PetscErrorCode  PCFactorGetLevels(PC pc,PetscInt *levels)
    180: {

    185:   PetscUseMethod(pc,"PCFactorGetLevels_C",(PC,PetscInt*),(pc,levels));
    186:   return(0);
    187: }

    191: /*@
    192:    PCFactorSetLevels - Sets the number of levels of fill to use.

    194:    Logically Collective on PC

    196:    Input Parameters:
    197: +  pc - the preconditioner context
    198: -  levels - number of levels of fill

    200:    Options Database Key:
    201: .  -pc_factor_levels <levels> - Sets fill level

    203:    Level: intermediate

    205: .keywords: PC, levels, fill, factorization, incomplete, ILU
    206: @*/
    207: PetscErrorCode  PCFactorSetLevels(PC pc,PetscInt levels)
    208: {

    213:   if (levels < 0) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_OUTOFRANGE,"negative levels");
    215:   PetscTryMethod(pc,"PCFactorSetLevels_C",(PC,PetscInt),(pc,levels));
    216:   return(0);
    217: }

    221: /*@
    222:    PCFactorSetAllowDiagonalFill - Causes all diagonal matrix entries to be
    223:    treated as level 0 fill even if there is no non-zero location.

    225:    Logically Collective on PC

    227:    Input Parameters:
    228: +  pc - the preconditioner context
    229: -  flg - PETSC_TRUE to turn on, PETSC_FALSE to turn off

    231:    Options Database Key:
    232: .  -pc_factor_diagonal_fill

    234:    Notes:
    235:    Does not apply with 0 fill.

    237:    Level: intermediate

    239: .keywords: PC, levels, fill, factorization, incomplete, ILU

    241: .seealso: PCFactorGetAllowDiagonalFill()

    243: @*/
    244: PetscErrorCode  PCFactorSetAllowDiagonalFill(PC pc,PetscBool flg)
    245: {

    250:   PetscTryMethod(pc,"PCFactorSetAllowDiagonalFill_C",(PC,PetscBool),(pc,flg));
    251:   return(0);
    252: }

    256: /*@
    257:    PCFactorGetAllowDiagonalFill - Determines if all diagonal matrix entries are
    258:        treated as level 0 fill even if there is no non-zero location.

    260:    Logically Collective on PC

    262:    Input Parameter:
    263: .  pc - the preconditioner context

    265:    Output Parameter:
    266: .   flg - PETSC_TRUE to turn on, PETSC_FALSE to turn off

    268:    Options Database Key:
    269: .  -pc_factor_diagonal_fill

    271:    Notes:
    272:    Does not apply with 0 fill.

    274:    Level: intermediate

    276: .keywords: PC, levels, fill, factorization, incomplete, ILU

    278: .seealso: PCFactorSetAllowDiagonalFill()

    280: @*/
    281: PetscErrorCode  PCFactorGetAllowDiagonalFill(PC pc,PetscBool *flg)
    282: {

    287:   PetscUseMethod(pc,"PCFactorGetAllowDiagonalFill_C",(PC,PetscBool*),(pc,flg));
    288:   return(0);
    289: }

    293: /*@
    294:    PCFactorReorderForNonzeroDiagonal - reorders rows/columns of matrix to remove zeros from diagonal

    296:    Logically Collective on PC

    298:    Input Parameters:
    299: +  pc - the preconditioner context
    300: -  tol - diagonal entries smaller than this in absolute value are considered zero

    302:    Options Database Key:
    303: .  -pc_factor_nonzeros_along_diagonal <tol>

    305:    Level: intermediate

    307: .keywords: PC, set, factorization, direct, fill

    309: .seealso: PCFactorSetFill(), PCFactorSetShiftNonzero(), PCFactorSetZeroPivot(), MatReorderForNonzeroDiagonal()
    310: @*/
    311: PetscErrorCode  PCFactorReorderForNonzeroDiagonal(PC pc,PetscReal rtol)
    312: {

    318:   PetscTryMethod(pc,"PCFactorReorderForNonzeroDiagonal_C",(PC,PetscReal),(pc,rtol));
    319:   return(0);
    320: }

    324: /*@C
    325:    PCFactorSetMatSolverPackage - sets the software that is used to perform the factorization

    327:    Logically Collective on PC

    329:    Input Parameters:
    330: +  pc - the preconditioner context
    331: -  stype - for example, superlu, superlu_dist

    333:    Options Database Key:
    334: .  -pc_factor_mat_solver_package <stype> - petsc, superlu, superlu_dist, mumps, cusparse

    336:    Level: intermediate

    338:    Note:
    339:      By default this will use the PETSc factorization if it exists

    342: .keywords: PC, set, factorization, direct, fill

    344: .seealso: MatGetFactor(), MatSolverPackage, PCFactorGetMatSolverPackage()

    346: @*/
    347: PetscErrorCode  PCFactorSetMatSolverPackage(PC pc,const MatSolverPackage stype)
    348: {

    353:   PetscTryMethod(pc,"PCFactorSetMatSolverPackage_C",(PC,const MatSolverPackage),(pc,stype));
    354:   return(0);
    355: }

    359: /*@C
    360:    PCFactorGetMatSolverPackage - gets the software that is used to perform the factorization

    362:    Not Collective

    364:    Input Parameter:
    365: .  pc - the preconditioner context

    367:    Output Parameter:
    368: .   stype - for example, superlu, superlu_dist (NULL if the PC does not have a solver package)

    370:    Level: intermediate

    373: .keywords: PC, set, factorization, direct, fill

    375: .seealso: MatGetFactor(), MatSolverPackage, PCFactorGetMatSolverPackage()

    377: @*/
    378: PetscErrorCode  PCFactorGetMatSolverPackage(PC pc,const MatSolverPackage *stype)
    379: {
    380:   PetscErrorCode ierr,(*f)(PC,const MatSolverPackage*);

    384:   PetscObjectQueryFunction((PetscObject)pc,"PCFactorGetMatSolverPackage_C",&f);
    385:   if (f) {
    386:     (*f)(pc,stype);
    387:   } else {
    388:     *stype = NULL;
    389:   }
    390:   return(0);
    391: }

    395: /*@
    396:    PCFactorSetFill - Indicate the amount of fill you expect in the factored matrix,
    397:    fill = number nonzeros in factor/number nonzeros in original matrix.

    399:    Not Collective, each process can expect a different amount of fill

    401:    Input Parameters:
    402: +  pc - the preconditioner context
    403: -  fill - amount of expected fill

    405:    Options Database Key:
    406: .  -pc_factor_fill <fill> - Sets fill amount

    408:    Level: intermediate

    410:    Note:
    411:    For sparse matrix factorizations it is difficult to predict how much
    412:    fill to expect. By running with the option -info PETSc will print the
    413:    actual amount of fill used; allowing you to set the value accurately for
    414:    future runs. Default PETSc uses a value of 5.0

    416:    This parameter has NOTHING to do with the levels-of-fill of ILU(). That is set with PCFactorSetLevels() or -pc_factor_levels.

    419: .keywords: PC, set, factorization, direct, fill

    421: @*/
    422: PetscErrorCode  PCFactorSetFill(PC pc,PetscReal fill)
    423: {

    428:   if (fill < 1.0) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_OUTOFRANGE,"Fill factor cannot be less then 1.0");
    429:   PetscTryMethod(pc,"PCFactorSetFill_C",(PC,PetscReal),(pc,fill));
    430:   return(0);
    431: }

    435: /*@
    436:    PCFactorSetUseInPlace - Tells the system to do an in-place factorization.
    437:    For dense matrices, this enables the solution of much larger problems.
    438:    For sparse matrices the factorization cannot be done truly in-place
    439:    so this does not save memory during the factorization, but after the matrix
    440:    is factored, the original unfactored matrix is freed, thus recovering that
    441:    space.

    443:    Logically Collective on PC

    445:    Input Parameters:
    446: +  pc - the preconditioner context
    447: -  flg - PETSC_TRUE to enable, PETSC_FALSE to disable

    449:    Options Database Key:
    450: .  -pc_factor_in_place <true,false>- Activate/deactivate in-place factorization

    452:    Notes:
    453:    PCFactorSetUseInplace() can only be used with the KSP method KSPPREONLY or when
    454:    a different matrix is provided for the multiply and the preconditioner in
    455:    a call to KSPSetOperators().
    456:    This is because the Krylov space methods require an application of the
    457:    matrix multiplication, which is not possible here because the matrix has
    458:    been factored in-place, replacing the original matrix.

    460:    Level: intermediate

    462: .keywords: PC, set, factorization, direct, inplace, in-place, LU

    464: .seealso: PCFactorGetUseInPlace()
    465: @*/
    466: PetscErrorCode  PCFactorSetUseInPlace(PC pc,PetscBool flg)
    467: {

    472:   PetscTryMethod(pc,"PCFactorSetUseInPlace_C",(PC,PetscBool),(pc,flg));
    473:   return(0);
    474: }

    478: /*@
    479:    PCFactorGetUseInPlace - Determines if an in-place factorization is being used.

    481:    Logically Collective on PC

    483:    Input Parameter:
    484: .  pc - the preconditioner context

    486:    Output Parameter:
    487: .  flg - PETSC_TRUE to enable, PETSC_FALSE to disable

    489:    Level: intermediate

    491: .keywords: PC, set, factorization, direct, inplace, in-place, LU

    493: .seealso: PCFactorSetUseInPlace()
    494: @*/
    495: PetscErrorCode  PCFactorGetUseInPlace(PC pc,PetscBool *flg)
    496: {

    501:   PetscUseMethod(pc,"PCFactorGetUseInPlace_C",(PC,PetscBool*),(pc,flg));
    502:   return(0);
    503: }

    507: /*@C
    508:     PCFactorSetMatOrderingType - Sets the ordering routine (to reduce fill) to
    509:     be used in the LU factorization.

    511:     Logically Collective on PC

    513:     Input Parameters:
    514: +   pc - the preconditioner context
    515: -   ordering - the matrix ordering name, for example, MATORDERINGND or MATORDERINGRCM

    517:     Options Database Key:
    518: .   -pc_factor_mat_ordering_type <nd,rcm,...> - Sets ordering routine

    520:     Level: intermediate

    522:     Notes: nested dissection is used by default

    524:     For Cholesky and ICC and the SBAIJ format reorderings are not available,
    525:     since only the upper triangular part of the matrix is stored. You can use the
    526:     SeqAIJ format in this case to get reorderings.

    528: @*/
    529: PetscErrorCode  PCFactorSetMatOrderingType(PC pc,MatOrderingType ordering)
    530: {

    535:   PetscTryMethod(pc,"PCFactorSetMatOrderingType_C",(PC,MatOrderingType),(pc,ordering));
    536:   return(0);
    537: }

    541: /*@
    542:     PCFactorSetColumnPivot - Determines when column pivoting is done during matrix factorization.
    543:       For PETSc dense matrices column pivoting is always done, for PETSc sparse matrices
    544:       it is never done. For the MATLAB and SuperLU factorization this is used.

    546:     Logically Collective on PC

    548:     Input Parameters:
    549: +   pc - the preconditioner context
    550: -   dtcol - 0.0 implies no pivoting, 1.0 complete pivoting (slower, requires more memory but more stable)

    552:     Options Database Key:
    553: .   -pc_factor_pivoting <dtcol>

    555:     Level: intermediate

    557: .seealso: PCILUSetMatOrdering(), PCFactorSetPivotInBlocks()
    558: @*/
    559: PetscErrorCode  PCFactorSetColumnPivot(PC pc,PetscReal dtcol)
    560: {

    566:   PetscTryMethod(pc,"PCFactorSetColumnPivot_C",(PC,PetscReal),(pc,dtcol));
    567:   return(0);
    568: }

    572: /*@
    573:     PCFactorSetPivotInBlocks - Determines if pivoting is done while factoring each block
    574:       with BAIJ or SBAIJ matrices

    576:     Logically Collective on PC

    578:     Input Parameters:
    579: +   pc - the preconditioner context
    580: -   pivot - PETSC_TRUE or PETSC_FALSE

    582:     Options Database Key:
    583: .   -pc_factor_pivot_in_blocks <true,false>

    585:     Level: intermediate

    587: .seealso: PCILUSetMatOrdering(), PCFactorSetColumnPivot()
    588: @*/
    589: PetscErrorCode  PCFactorSetPivotInBlocks(PC pc,PetscBool pivot)
    590: {

    596:   PetscTryMethod(pc,"PCFactorSetPivotInBlocks_C",(PC,PetscBool),(pc,pivot));
    597:   return(0);
    598: }

    602: /*@
    603:    PCFactorSetReuseFill - When matrices with same different nonzero structure are factored,
    604:    this causes later ones to use the fill ratio computed in the initial factorization.

    606:    Logically Collective on PC

    608:    Input Parameters:
    609: +  pc - the preconditioner context
    610: -  flag - PETSC_TRUE to reuse else PETSC_FALSE

    612:    Options Database Key:
    613: .  -pc_factor_reuse_fill - Activates PCFactorSetReuseFill()

    615:    Level: intermediate

    617: .keywords: PC, levels, reordering, factorization, incomplete, Cholesky

    619: .seealso: PCFactorSetReuseOrdering()
    620: @*/
    621: PetscErrorCode  PCFactorSetReuseFill(PC pc,PetscBool flag)
    622: {

    628:   PetscTryMethod(pc,"PCFactorSetReuseFill_C",(PC,PetscBool),(pc,flag));
    629:   return(0);
    630: }