Date: 2026-03-31T05:46:14+00:00

Actual source code: itcreate.c

      1: /*
      2:      The basic KSP routines, Create, View etc. are here.
      3: */
      4: #include <petsc/private/kspimpl.h>

      6: /* Logging support */
      7: PetscClassId  KSP_CLASSID;
      8: PetscClassId  DMKSP_CLASSID;
      9: PetscClassId  KSPGUESS_CLASSID;
     10: PetscLogEvent KSP_GMRESOrthogonalization, KSP_SetUp, KSP_Solve, KSP_SolveTranspose, KSP_MatSolve, KSP_MatSolveTranspose;

     12: /*
     13:    Contains the list of registered KSP routines
     14: */
     15: PetscFunctionList KSPList              = NULL;
     16: PetscBool         KSPRegisterAllCalled = PETSC_FALSE;

     18: /*
     19:    Contains the list of registered KSP monitors
     20: */
     21: PetscFunctionList KSPMonitorList              = NULL;
     22: PetscFunctionList KSPMonitorCreateList        = NULL;
     23: PetscFunctionList KSPMonitorDestroyList       = NULL;
     24: PetscBool         KSPMonitorRegisterAllCalled = PETSC_FALSE;

     26: /*@
     27:   KSPLoad - Loads a `KSP` that has been stored in a `PETSCVIEWERBINARY`  with `KSPView()`.

     29:   Collective

     31:   Input Parameters:
     32: + newdm  - the newly loaded `KSP`, this needs to have been created with `KSPCreate()` or
     33:            some related function before a call to `KSPLoad()`.
     34: - viewer - binary file viewer, obtained from `PetscViewerBinaryOpen()`

     36:   Level: intermediate

     38:   Note:
     39:   The type is determined by the data in the file, any type set into the `KSP` before this call is ignored.

     41: .seealso: [](ch_ksp), `KSP`, `PetscViewerBinaryOpen()`, `KSPView()`, `MatLoad()`, `VecLoad()`
     42: @*/
     43: PetscErrorCode KSPLoad(KSP newdm, PetscViewer viewer)
     44: {
     45:   PetscBool isbinary;
     46:   PetscInt  classid;
     47:   char      type[256];
     48:   PC        pc;

     50:   PetscFunctionBegin;
     53:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
     54:   PetscCheck(isbinary, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Invalid viewer; open viewer with PetscViewerBinaryOpen()");

     56:   PetscCall(PetscViewerBinaryRead(viewer, &classid, 1, NULL, PETSC_INT));
     57:   PetscCheck(classid == KSP_FILE_CLASSID, PetscObjectComm((PetscObject)newdm), PETSC_ERR_ARG_WRONG, "Not KSP next in file");
     58:   PetscCall(PetscViewerBinaryRead(viewer, type, 256, NULL, PETSC_CHAR));
     59:   PetscCall(KSPSetType(newdm, type));
     60:   PetscTryTypeMethod(newdm, load, viewer);
     61:   PetscCall(KSPGetPC(newdm, &pc));
     62:   PetscCall(PCLoad(pc, viewer));
     63:   PetscFunctionReturn(PETSC_SUCCESS);
     64: }

     66: #include <petscdraw.h>
     67: #if defined(PETSC_HAVE_SAWS)
     68: #include <petscviewersaws.h>
     69: #endif
     70: /*@
     71:   KSPView - Prints the various parameters currently set in the `KSP` object. For example, the convergence tolerances and `KSPType`.
     72:   Also views the `PC` and `Mat` contained by the `KSP` with `PCView()` and `MatView()`.

     74:   Collective

     76:   Input Parameters:
     77: + ksp    - the Krylov space context
     78: - viewer - visualization context

     80:   Options Database Key:
     81: . -ksp_view - print the `KSP` data structure at the end of each `KSPSolve()` call

     83:   Level: beginner

     85:   Notes:
     86:   The available visualization contexts include
     87: +     `PETSC_VIEWER_STDOUT_SELF` - standard output (default)
     88: -     `PETSC_VIEWER_STDOUT_WORLD` - synchronized standard
     89:   output where only the first processor opens
     90:   the file.  All other processors send their
     91:   data to the first processor to print.

     93:   The available formats include
     94: +     `PETSC_VIEWER_DEFAULT` - standard output (default)
     95: -     `PETSC_VIEWER_ASCII_INFO_DETAIL` - more verbose output for `PCBJACOBI` and `PCASM`

     97:   The user can open an alternative visualization context with
     98:   `PetscViewerASCIIOpen()` - output to a specified file.

    100:   Use `KSPViewFromOptions()` to allow the user to select many different `PetscViewerType` and formats from the options database.

    102:   In the debugger you can do call `KSPView(ksp,0)` to display the `KSP`. (The same holds for any PETSc object viewer).

    104: .seealso: [](ch_ksp), `KSP`, `PetscViewer`, `PCView()`, `PetscViewerASCIIOpen()`, `KSPViewFromOptions()`
    105: @*/
    106: PetscErrorCode KSPView(KSP ksp, PetscViewer viewer)
    107: {
    108:   PetscBool isascii, isbinary, isdraw, isstring;
    109: #if defined(PETSC_HAVE_SAWS)
    110:   PetscBool issaws;
    111: #endif

    113:   PetscFunctionBegin;
    115:   if (!viewer) PetscCall(PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)ksp), &viewer));
    117:   PetscCheckSameComm(ksp, 1, viewer, 2);

    119:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &isascii));
    120:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
    121:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw));
    122:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERSTRING, &isstring));
    123: #if defined(PETSC_HAVE_SAWS)
    124:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERSAWS, &issaws));
    125: #endif
    126:   if (isascii) {
    127:     PetscCall(PetscObjectPrintClassNamePrefixType((PetscObject)ksp, viewer));
    128:     PetscCall(PetscViewerASCIIPushTab(viewer));
    129:     PetscTryTypeMethod(ksp, view, viewer);
    130:     PetscCall(PetscViewerASCIIPopTab(viewer));
    131:     if (ksp->guess_zero) {
    132:       PetscCall(PetscViewerASCIIPrintf(viewer, "  maximum iterations=%" PetscInt_FMT ", initial guess is zero\n", ksp->max_it));
    133:     } else {
    134:       PetscCall(PetscViewerASCIIPrintf(viewer, "  maximum iterations=%" PetscInt_FMT ", nonzero initial guess\n", ksp->max_it));
    135:     }
    136:     if (ksp->min_it) PetscCall(PetscViewerASCIIPrintf(viewer, "  minimum iterations=%" PetscInt_FMT "\n", ksp->min_it));
    137:     if (ksp->guess_knoll) PetscCall(PetscViewerASCIIPrintf(viewer, "  using preconditioner applied to right-hand side for initial guess\n"));
    138:     PetscCall(PetscViewerASCIIPrintf(viewer, "  tolerances: relative=%g, absolute=%g, divergence=%g\n", (double)ksp->rtol, (double)ksp->abstol, (double)ksp->divtol));
    139:     if (ksp->pc_side == PC_RIGHT) {
    140:       PetscCall(PetscViewerASCIIPrintf(viewer, "  right preconditioning\n"));
    141:     } else if (ksp->pc_side == PC_SYMMETRIC) {
    142:       PetscCall(PetscViewerASCIIPrintf(viewer, "  symmetric preconditioning\n"));
    143:     } else {
    144:       PetscCall(PetscViewerASCIIPrintf(viewer, "  left preconditioning\n"));
    145:     }
    146:     if (ksp->guess) {
    147:       PetscCall(PetscViewerASCIIPushTab(viewer));
    148:       PetscCall(KSPGuessView(ksp->guess, viewer));
    149:       PetscCall(PetscViewerASCIIPopTab(viewer));
    150:     }
    151:     if (ksp->dscale) PetscCall(PetscViewerASCIIPrintf(viewer, "  diagonally scaled system\n"));
    152:     if (ksp->converged == KSPConvergedSkip || ksp->normtype == KSP_NORM_NONE) PetscCall(PetscViewerASCIIPrintf(viewer, "  not checking for convergence\n"));
    153:     else PetscCall(PetscViewerASCIIPrintf(viewer, "  using %s norm type for convergence test\n", KSPNormTypes[ksp->normtype]));
    154:   } else if (isbinary) {
    155:     PetscInt    classid = KSP_FILE_CLASSID;
    156:     MPI_Comm    comm;
    157:     PetscMPIInt rank;
    158:     char        type[256];

    160:     PetscCall(PetscObjectGetComm((PetscObject)ksp, &comm));
    161:     PetscCallMPI(MPI_Comm_rank(comm, &rank));
    162:     if (rank == 0) {
    163:       PetscCall(PetscViewerBinaryWrite(viewer, &classid, 1, PETSC_INT));
    164:       PetscCall(PetscStrncpy(type, ((PetscObject)ksp)->type_name, 256));
    165:       PetscCall(PetscViewerBinaryWrite(viewer, type, 256, PETSC_CHAR));
    166:     }
    167:     PetscTryTypeMethod(ksp, view, viewer);
    168:   } else if (isstring) {
    169:     const char *type;
    170:     PetscCall(KSPGetType(ksp, &type));
    171:     PetscCall(PetscViewerStringSPrintf(viewer, " KSPType: %-7.7s", type));
    172:     PetscTryTypeMethod(ksp, view, viewer);
    173:   } else if (isdraw) {
    174:     PetscDraw draw;
    175:     char      str[36];
    176:     PetscReal x, y, bottom, h;
    177:     PetscBool flg;

    179:     PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw));
    180:     PetscCall(PetscDrawGetCurrentPoint(draw, &x, &y));
    181:     PetscCall(PetscObjectTypeCompare((PetscObject)ksp, KSPPREONLY, &flg));
    182:     if (!flg) {
    183:       PetscCall(PetscStrncpy(str, "KSP: ", sizeof(str)));
    184:       PetscCall(PetscStrlcat(str, ((PetscObject)ksp)->type_name, sizeof(str)));
    185:       PetscCall(PetscDrawStringBoxed(draw, x, y, PETSC_DRAW_RED, PETSC_DRAW_BLACK, str, NULL, &h));
    186:       bottom = y - h;
    187:     } else {
    188:       bottom = y;
    189:     }
    190:     PetscCall(PetscDrawPushCurrentPoint(draw, x, bottom));
    191: #if defined(PETSC_HAVE_SAWS)
    192:   } else if (issaws) {
    193:     PetscMPIInt rank;
    194:     const char *name;

    196:     PetscCall(PetscObjectGetName((PetscObject)ksp, &name));
    197:     PetscCallMPI(MPI_Comm_rank(PETSC_COMM_WORLD, &rank));
    198:     if (!((PetscObject)ksp)->amsmem && rank == 0) {
    199:       char dir[1024];

    201:       PetscCall(PetscObjectViewSAWs((PetscObject)ksp, viewer));
    202:       PetscCall(PetscSNPrintf(dir, 1024, "/PETSc/Objects/%s/its", name));
    203:       PetscCallSAWs(SAWs_Register, (dir, &ksp->its, 1, SAWs_READ, SAWs_INT));
    204:       if (!ksp->res_hist) PetscCall(KSPSetResidualHistory(ksp, NULL, PETSC_DECIDE, PETSC_TRUE));
    205:       PetscCall(PetscSNPrintf(dir, 1024, "/PETSc/Objects/%s/res_hist", name));
    206:       PetscCallSAWs(SAWs_Register, (dir, ksp->res_hist, 10, SAWs_READ, SAWs_DOUBLE));
    207:     }
    208: #endif
    209:   } else PetscTryTypeMethod(ksp, view, viewer);
    210:   if (ksp->pc) PetscCall(PCView(ksp->pc, viewer));
    211:   if (isdraw) {
    212:     PetscDraw draw;
    213:     PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw));
    214:     PetscCall(PetscDrawPopCurrentPoint(draw));
    215:   }
    216:   PetscFunctionReturn(PETSC_SUCCESS);
    217: }

    219: /*@
    220:   KSPViewFromOptions - View (print) a `KSP` object based on values in the options database. Also views the `PC` and `Mat` contained by the `KSP`
    221:   with `PCView()` and `MatView()`.

    223:   Collective

    225:   Input Parameters:
    226: + A    - Krylov solver context
    227: . obj  - Optional object that provides the options prefix used to query the options database
    228: - name - command line option

    230:   Level: intermediate

    232: .seealso: [](ch_ksp), `KSP`, `KSPView()`, `PetscObjectViewFromOptions()`, `KSPCreate()`
    233: @*/
    234: PetscErrorCode KSPViewFromOptions(KSP A, PetscObject obj, const char name[])
    235: {
    236:   PetscFunctionBegin;
    238:   PetscCall(PetscObjectViewFromOptions((PetscObject)A, obj, name));
    239:   PetscFunctionReturn(PETSC_SUCCESS);
    240: }

    242: /*@
    243:   KSPSetNormType - Sets the type of residual norm that is used for convergence testing in `KSPSolve()` for the given `KSP` context

    245:   Logically Collective

    247:   Input Parameters:
    248: + ksp      - Krylov solver context
    249: - normtype - one of
    250: .vb
    251:    KSP_NORM_NONE             - skips computing the norm, this should generally only be used if you are using
    252:                                the Krylov method as a smoother with a fixed small number of iterations.
    253:                                Implicitly sets `KSPConvergedSkip()` as the `KSP` convergence test.
    254:                                Note that certain algorithms such as `KSPGMRES` ALWAYS require the norm calculation,
    255:                                for these methods the norms are still computed, they are just not used in
    256:                                the convergence test.
    257:    KSP_NORM_PRECONDITIONED   - the default for left-preconditioned solves, uses the 2-norm
    258:                                of the preconditioned residual  $B^{-1}(b - A x)$.
    259:    KSP_NORM_UNPRECONDITIONED - uses the 2-norm of the true $b - Ax$ residual.
    260:    KSP_NORM_NATURAL          - uses the $A$ norm of the true $b - Ax$ residual; supported by `KSPCG`, `KSPCR`, `KSPCGNE`, `KSPCGS`
    261: .ve

    263:   Options Database Key:
    264: . -ksp_norm_type (none|preconditioned|unpreconditioned|natural) - set `KSP` norm type

    266:   Level: advanced

    268:   Notes:
    269:   The norm is always of the equations residual $\| b - A x^n \|$  (or an approximation to that norm), they are never a norm of the error in the equation.

    271:   Not all combinations of preconditioner side (see `KSPSetPCSide()`) and norm types are supported by all Krylov methods.
    272:   If only one is set, PETSc tries to automatically change the other to find a compatible pair.  If no such combination
    273:   is supported, PETSc will generate an error.

    275:   Developer Note:
    276:   Supported combinations of norm and preconditioner side are set using `KSPSetSupportedNorm()` for each `KSPType`.

    278: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSPConvergedSkip()`, `KSPSetCheckNormIteration()`, `KSPSetPCSide()`, `KSPGetPCSide()`, `KSPNormType`
    279: @*/
    280: PetscErrorCode KSPSetNormType(KSP ksp, KSPNormType normtype)
    281: {
    282:   PetscFunctionBegin;
    285:   ksp->normtype = ksp->normtype_set = normtype;
    286:   PetscFunctionReturn(PETSC_SUCCESS);
    287: }

    289: /*@
    290:   KSPSetCheckNormIteration - Sets the first iteration at which the norm of the residual will be
    291:   computed and used in the convergence test of `KSPSolve()` for the given `KSP` context

    293:   Logically Collective

    295:   Input Parameters:
    296: + ksp - Krylov solver context
    297: - it  - use -1 to check at all iterations

    299:   Level: advanced

    301:   Notes:
    302:   Currently only works with `KSPCG`, `KSPBCGS` and `KSPIBCGS`

    304:   Use `KSPSetNormType`(ksp,`KSP_NORM_NONE`) to never check the norm

    306:   On steps where the norm is not computed, the previous norm is still in the variable, so if you run with, for example,
    307:   `-ksp_monitor` the residual norm will appear to be unchanged for several iterations (though it is not really unchanged).

    309:   Certain methods such as `KSPGMRES` always compute the residual norm, this routine will not change that computation, but it will
    310:   prevent the computed norm from being checked.

    312: .seealso: [](ch_ksp), `KSP`, `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSPConvergedSkip()`, `KSPSetNormType()`, `KSPSetLagNorm()`
    313: @*/
    314: PetscErrorCode KSPSetCheckNormIteration(KSP ksp, PetscInt it)
    315: {
    316:   PetscFunctionBegin;
    319:   ksp->chknorm = it;
    320:   PetscFunctionReturn(PETSC_SUCCESS);
    321: }

    323: /*@
    324:   KSPSetLagNorm - Lags the residual norm calculation so that it is computed as part of the `MPI_Allreduce()` used for
    325:   computing the inner products needed for the next iteration.

    327:   Logically Collective

    329:   Input Parameters:
    330: + ksp - Krylov solver context
    331: - flg - `PETSC_TRUE` or `PETSC_FALSE`

    333:   Options Database Key:
    334: . -ksp_lag_norm - lag the calculated residual norm

    336:   Level: advanced

    338:   Notes:
    339:   Currently only works with `KSPIBCGS`.

    341:   This can reduce communication costs at the expense of doing
    342:   one additional iteration because the norm used in the convergence test of `KSPSolve()` is one iteration behind the actual
    343:   current residual norm (which has not yet been computed due to the lag).

    345:   Use `KSPSetNormType`(ksp,`KSP_NORM_NONE`) to never check the norm

    347:   If you lag the norm and run with, for example, `-ksp_monitor`, the residual norm reported will be the lagged one.

    349:   `KSPSetCheckNormIteration()` is an alternative way of avoiding the expense of computing the residual norm at each iteration.

    351: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSPConvergedSkip()`, `KSPSetNormType()`, `KSPSetCheckNormIteration()`
    352: @*/
    353: PetscErrorCode KSPSetLagNorm(KSP ksp, PetscBool flg)
    354: {
    355:   PetscFunctionBegin;
    358:   ksp->lagnorm = flg;
    359:   PetscFunctionReturn(PETSC_SUCCESS);
    360: }

    362: /*@
    363:   KSPSetSupportedNorm - Sets a norm and preconditioner side supported by a `KSPType`

    365:   Logically Collective

    367:   Input Parameters:
    368: + ksp      - Krylov method
    369: . normtype - supported norm type of the type `KSPNormType`
    370: . pcside   - preconditioner side, of the type `PCSide` that can be used with this `KSPNormType`
    371: - priority - positive integer preference for this combination; larger values have higher priority

    373:   Level: developer

    375:   Notes:
    376:   This function should be called from the implementation files `KSPCreate_XXX()` to declare
    377:   which norms and preconditioner sides are supported. Users should not call this
    378:   function.

    380:   This function can be called multiple times for each combination of `KSPNormType` and `PCSide`
    381:   the `KSPType` supports

    383: .seealso: [](ch_ksp), `KSP`, `KSPNormType`, `PCSide`, `KSPSetNormType()`, `KSPSetPCSide()`
    384: @*/
    385: PetscErrorCode KSPSetSupportedNorm(KSP ksp, KSPNormType normtype, PCSide pcside, PetscInt priority)
    386: {
    387:   PetscFunctionBegin;
    389:   ksp->normsupporttable[normtype][pcside] = priority;
    390:   PetscFunctionReturn(PETSC_SUCCESS);
    391: }

    393: static PetscErrorCode KSPNormSupportTableReset_Private(KSP ksp)
    394: {
    395:   PetscFunctionBegin;
    396:   PetscCall(PetscMemzero(ksp->normsupporttable, sizeof(ksp->normsupporttable)));
    397:   ksp->pc_side  = ksp->pc_side_set;
    398:   ksp->normtype = ksp->normtype_set;
    399:   PetscFunctionReturn(PETSC_SUCCESS);
    400: }

    402: PetscErrorCode KSPSetUpNorms_Private(KSP ksp, PetscBool errorifnotsupported, KSPNormType *normtype, PCSide *pcside)
    403: {
    404:   PetscInt i, j, best, ibest = 0, jbest = 0;

    406:   PetscFunctionBegin;
    407:   best = 0;
    408:   for (i = 0; i < KSP_NORM_MAX; i++) {
    409:     for (j = 0; j < PC_SIDE_MAX; j++) {
    410:       if ((ksp->normtype == KSP_NORM_DEFAULT || ksp->normtype == i) && (ksp->pc_side == PC_SIDE_DEFAULT || ksp->pc_side == j) && ksp->normsupporttable[i][j] > best) {
    411:         best  = ksp->normsupporttable[i][j];
    412:         ibest = i;
    413:         jbest = j;
    414:       }
    415:     }
    416:   }
    417:   if (best < 1 && errorifnotsupported) {
    418:     PetscCheck(ksp->normtype != KSP_NORM_DEFAULT || ksp->pc_side != PC_SIDE_DEFAULT, PetscObjectComm((PetscObject)ksp), PETSC_ERR_PLIB, "The %s KSP implementation did not call KSPSetSupportedNorm()", ((PetscObject)ksp)->type_name);
    419:     PetscCheck(ksp->normtype != KSP_NORM_DEFAULT, PetscObjectComm((PetscObject)ksp), PETSC_ERR_SUP, "KSP %s does not support preconditioner side %s", ((PetscObject)ksp)->type_name, PCSides[ksp->pc_side]);
    420:     PetscCheck(ksp->pc_side != PC_SIDE_DEFAULT, PetscObjectComm((PetscObject)ksp), PETSC_ERR_SUP, "KSP %s does not support norm type %s", ((PetscObject)ksp)->type_name, KSPNormTypes[ksp->normtype]);
    421:     SETERRQ(PetscObjectComm((PetscObject)ksp), PETSC_ERR_SUP, "KSP %s does not support norm type %s with preconditioner side %s", ((PetscObject)ksp)->type_name, KSPNormTypes[ksp->normtype], PCSides[ksp->pc_side]);
    422:   }
    423:   if (normtype) *normtype = (KSPNormType)ibest;
    424:   if (pcside) *pcside = (PCSide)jbest;
    425:   PetscFunctionReturn(PETSC_SUCCESS);
    426: }

    428: /*@
    429:   KSPGetNormType - Gets the `KSPNormType` that is used for convergence testing during `KSPSolve()` for this `KSP` context

    431:   Not Collective

    433:   Input Parameter:
    434: . ksp - Krylov solver context

    436:   Output Parameter:
    437: . normtype - the `KSPNormType` that is used for convergence testing

    439:   Level: advanced

    441: .seealso: [](ch_ksp), `KSPNormType`, `KSPSetNormType()`, `KSPConvergedSkip()`
    442: @*/
    443: PetscErrorCode KSPGetNormType(KSP ksp, KSPNormType *normtype)
    444: {
    445:   PetscFunctionBegin;
    447:   PetscAssertPointer(normtype, 2);
    448:   PetscCall(KSPSetUpNorms_Private(ksp, PETSC_TRUE, &ksp->normtype, &ksp->pc_side));
    449:   *normtype = ksp->normtype;
    450:   PetscFunctionReturn(PETSC_SUCCESS);
    451: }

    453: #if defined(PETSC_HAVE_SAWS)
    454: #include <petscviewersaws.h>
    455: #endif

    457: /*@
    458:   KSPSetOperators - Sets the matrix associated with the linear system
    459:   and a (possibly) different one from which the preconditioner will be built into the `KSP` context. The matrix will then be used during `KSPSolve()`

    461:   Collective

    463:   Input Parameters:
    464: + ksp  - the `KSP` context
    465: . Amat - the matrix that defines the linear system
    466: - Pmat - the matrix to be used in constructing the preconditioner, usually the same as `Amat`.

    468:   Level: beginner

    470:   Notes:
    471: .vb
    472:   KSPSetOperators(ksp, Amat, Pmat);
    473: .ve
    474:   is the same as
    475: .vb
    476:   KSPGetPC(ksp, &pc);
    477:   PCSetOperators(pc, Amat, Pmat);
    478: .ve
    479:   and is equivalent to
    480: .vb
    481:   PCCreate(PetscObjectComm((PetscObject)ksp), &pc);
    482:   PCSetOperators(pc, Amat, Pmat);
    483:   KSPSetPC(ksp, pc);
    484: .ve

    486:   If you know the operator `Amat` has a null space you can use `MatSetNullSpace()` and `MatSetTransposeNullSpace()` to supply the null
    487:   space to `Amat` and the `KSP` solvers will automatically use that null space as needed during the solution process.

    489:   All future calls to `KSPSetOperators()` must use the same size matrices, unless `KSPReset()` is called!

    491:   Passing a `NULL` for `Amat` or `Pmat` removes the matrix that is currently being used from the `KSP` context.

    493:   If you wish to replace either `Amat` or `Pmat` but leave the other one untouched then
    494:   first call `KSPGetOperators()` to get the one you wish to keep, call `PetscObjectReference()`
    495:   on it and then pass it back in your call to `KSPSetOperators()`.

    497:   Developer Notes:
    498:   If the operators have NOT been set with `KSPSetOperators()` then the operators
    499:   are created in the `PC` and returned to the user. In this case, if both operators
    500:   mat and pmat are requested, two DIFFERENT operators will be returned. If
    501:   only one is requested both operators in the `PC` will be the same (i.e. as
    502:   if one had called `KSPSetOperators()` with the same argument for both `Mat`s).
    503:   The user must set the sizes of the returned matrices and their type etc just
    504:   as if the user created them with `MatCreate()`. For example,

    506: .vb
    507:          KSPGetOperators(ksp/pc,&mat,NULL); is equivalent to
    508:            set size, type, etc of mat

    510:          MatCreate(comm,&mat);
    511:          KSP/PCSetOperators(ksp/pc,mat,mat);
    512:          PetscObjectDereference((PetscObject)mat);
    513:            set size, type, etc of mat

    515:      and

    517:          KSP/PCGetOperators(ksp/pc,&mat,&pmat); is equivalent to
    518:            set size, type, etc of mat and pmat

    520:          MatCreate(comm,&mat);
    521:          MatCreate(comm,&pmat);
    522:          KSP/PCSetOperators(ksp/pc,mat,pmat);
    523:          PetscObjectDereference((PetscObject)mat);
    524:          PetscObjectDereference((PetscObject)pmat);
    525:            set size, type, etc of mat and pmat
    526: .ve

    528:   The rationale for this support is so that when creating a `TS`, `SNES`, or `KSP` the hierarchy
    529:   of underlying objects (i.e. `SNES`, `KSP`, `PC`, `Mat`) and their lifespans can be completely
    530:   managed by the top most level object (i.e. the `TS`, `SNES`, or `KSP`). Another way to look
    531:   at this is when you create a `SNES` you do not NEED to create a `KSP` and attach it to
    532:   the `SNES` object (the `SNES` object manages it for you). Similarly when you create a `KSP`
    533:   you do not need to attach a `PC` to it (the `KSP` object manages the `PC` object for you).
    534:   Thus, why should YOU have to create the `Mat` and attach it to the `SNES`/`KSP`/`PC`, when
    535:   it can be created for you?

    537: .seealso: [](ch_ksp), `KSP`, `Mat`, `KSPSolve()`, `KSPGetPC()`, `PCGetOperators()`, `PCSetOperators()`, `KSPGetOperators()`, `KSPSetComputeOperators()`, `KSPSetComputeInitialGuess()`, `KSPSetComputeRHS()`
    538: @*/
    539: PetscErrorCode KSPSetOperators(KSP ksp, Mat Amat, Mat Pmat)
    540: {
    541:   PetscFunctionBegin;
    545:   if (Amat) PetscCheckSameComm(ksp, 1, Amat, 2);
    546:   if (Pmat) PetscCheckSameComm(ksp, 1, Pmat, 3);
    547:   if (!ksp->pc) PetscCall(KSPGetPC(ksp, &ksp->pc));
    548:   PetscCall(PCSetOperators(ksp->pc, Amat, Pmat));
    549:   if (ksp->setupstage == KSP_SETUP_NEWRHS) ksp->setupstage = KSP_SETUP_NEWMATRIX; /* so that next solve call will call PCSetUp() on new matrix */
    550:   PetscFunctionReturn(PETSC_SUCCESS);
    551: }

    553: /*@
    554:   KSPGetOperators - Gets the matrix associated with the linear system
    555:   and a (possibly) different one used to construct the preconditioner from the `KSP` context

    557:   Collective

    559:   Input Parameter:
    560: . ksp - the `KSP` context

    562:   Output Parameters:
    563: + Amat - the matrix that defines the linear system
    564: - Pmat - the matrix to be used in constructing the preconditioner, usually the same as `Amat`.

    566:   Level: intermediate

    568:   Notes:
    569:   If `KSPSetOperators()` has not been called then the `KSP` object will attempt to automatically create the matrix `Amat` and return it

    571:   Use `KSPGetOperatorsSet()` to determine if matrices have been provided.

    573:   DOES NOT increase the reference counts of the matrix, so you should NOT destroy them.

    575: .seealso: [](ch_ksp), `KSP`, `KSPSolve()`, `KSPGetPC()`, `PCSetOperators()`, `KSPSetOperators()`, `KSPGetOperatorsSet()`
    576: @*/
    577: PetscErrorCode KSPGetOperators(KSP ksp, Mat *Amat, Mat *Pmat)
    578: {
    579:   PetscFunctionBegin;
    581:   if (!ksp->pc) PetscCall(KSPGetPC(ksp, &ksp->pc));
    582:   PetscCall(PCGetOperators(ksp->pc, Amat, Pmat));
    583:   PetscFunctionReturn(PETSC_SUCCESS);
    584: }

    586: /*@
    587:   KSPGetOperatorsSet - Determines if the matrix associated with the linear system and
    588:   possibly a different one from which the preconditioner will be built have been set in the `KSP` with `KSPSetOperators()`

    590:   Not Collective, though the results on all processes will be the same

    592:   Input Parameter:
    593: . ksp - the `KSP` context

    595:   Output Parameters:
    596: + mat  - the matrix associated with the linear system was set
    597: - pmat - matrix from which the preconditioner will be built, usually the same as `mat` was set

    599:   Level: intermediate

    601:   Note:
    602:   This routine exists because if you call `KSPGetOperators()` on a `KSP` that does not yet have operators they are
    603:   automatically created in the call.

    605: .seealso: [](ch_ksp), `KSP`, `PCSetOperators()`, `KSPGetOperators()`, `KSPSetOperators()`, `PCGetOperators()`, `PCGetOperatorsSet()`
    606: @*/
    607: PetscErrorCode KSPGetOperatorsSet(KSP ksp, PetscBool *mat, PetscBool *pmat)
    608: {
    609:   PetscFunctionBegin;
    611:   if (!ksp->pc) PetscCall(KSPGetPC(ksp, &ksp->pc));
    612:   PetscCall(PCGetOperatorsSet(ksp->pc, mat, pmat));
    613:   PetscFunctionReturn(PETSC_SUCCESS);
    614: }

    616: /*@C
    617:   KSPSetPreSolve - Sets a function that is called at the beginning of each `KSPSolve()`. Used in conjunction with `KSPSetPostSolve()`.

    619:   Logically Collective

    621:   Input Parameters:
    622: + ksp      - the solver object
    623: . presolve - the function to call before the solve, see` KSPPSolveFn`
    624: - ctx      - an optional context needed by the function

    626:   Level: developer

    628:   Notes:
    629:   The function provided here `presolve` is used to modify the right hand side, and possibly the matrix, of the linear system to be solved.
    630:   The function provided with `KSPSetPostSolve()` then modifies the resulting solution of that linear system to obtain the correct solution
    631:   to the initial linear system.

    633:   The functions `PCPreSolve()` and `PCPostSolve()` provide a similar functionality and are used, for example with `PCEISENSTAT`.

    635: .seealso: [](ch_ksp), `KSPPSolveFn`, `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPSetPostSolve()`, `PCEISENSTAT`, `PCPreSolve()`, `PCPostSolve()`
    636: @*/
    637: PetscErrorCode KSPSetPreSolve(KSP ksp, KSPPSolveFn *presolve, PetscCtx ctx)
    638: {
    639:   PetscFunctionBegin;
    641:   ksp->presolve = presolve;
    642:   ksp->prectx   = ctx;
    643:   PetscFunctionReturn(PETSC_SUCCESS);
    644: }

    646: /*@C
    647:   KSPSetPostSolve - Sets a function that is called at the end of each `KSPSolve()` (whether it converges or not). Used in conjunction with `KSPSetPreSolve()`.

    649:   Logically Collective

    651:   Input Parameters:
    652: + ksp       - the solver object
    653: . postsolve - the function to call after the solve, see` KSPPSolveFn`
    654: - ctx       - an optional context needed by the function

    656:   Level: developer

    658: .seealso: [](ch_ksp), `KSPPSolveFn`, `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPSetPreSolve()`, `PCEISENSTAT`
    659: @*/
    660: PetscErrorCode KSPSetPostSolve(KSP ksp, KSPPSolveFn *postsolve, PetscCtx ctx)
    661: {
    662:   PetscFunctionBegin;
    664:   ksp->postsolve = postsolve;
    665:   ksp->postctx   = ctx;
    666:   PetscFunctionReturn(PETSC_SUCCESS);
    667: }

    669: /*@
    670:   KSPSetNestLevel - sets the amount of nesting the `KSP` has. That is the number of levels of `KSP` above this `KSP` in a linear solve.

    672:   Collective

    674:   Input Parameters:
    675: + ksp   - the `KSP`
    676: - level - the nest level

    678:   Level: developer

    680:   Note:
    681:   For example, the `KSP` in each block of a `KSPBJACOBI` has a level of 1, while the outer `KSP` has a level of 0.

    683: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPGMRES`, `KSPType`, `KSPGetNestLevel()`, `PCSetKSPNestLevel()`, `PCGetKSPNestLevel()`
    684: @*/
    685: PetscErrorCode KSPSetNestLevel(KSP ksp, PetscInt level)
    686: {
    687:   PetscFunctionBegin;
    690:   ksp->nestlevel = level;
    691:   PetscFunctionReturn(PETSC_SUCCESS);
    692: }

    694: /*@
    695:   KSPGetNestLevel - gets the amount of nesting the `KSP` has

    697:   Not Collective

    699:   Input Parameter:
    700: . ksp - the `KSP`

    702:   Output Parameter:
    703: . level - the nest level

    705:   Level: developer

    707: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPGMRES`, `KSPType`, `KSPSetNestLevel()`, `PCSetKSPNestLevel()`, `PCGetKSPNestLevel()`
    708: @*/
    709: PetscErrorCode KSPGetNestLevel(KSP ksp, PetscInt *level)
    710: {
    711:   PetscFunctionBegin;
    713:   PetscAssertPointer(level, 2);
    714:   *level = ksp->nestlevel;
    715:   PetscFunctionReturn(PETSC_SUCCESS);
    716: }

    718: /*@
    719:   KSPCreate - Creates the `KSP` context. This `KSP` context is used in PETSc to solve linear systems with `KSPSolve()`

    721:   Collective

    723:   Input Parameter:
    724: . comm - MPI communicator

    726:   Output Parameter:
    727: . inksp - location to put the `KSP` context

    729:   Level: beginner

    731:   Note:
    732:   The default `KSPType` is `KSPGMRES` with a restart of 30, using modified Gram-Schmidt orthogonalization. The `KSPType` may be
    733:   changed with `KSPSetType()`

    735: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPGMRES`, `KSPType`, `KSPSetType()`
    736: @*/
    737: PetscErrorCode KSPCreate(MPI_Comm comm, KSP *inksp)
    738: {
    739:   KSP      ksp;
    740:   PetscCtx ctx;

    742:   PetscFunctionBegin;
    743:   PetscAssertPointer(inksp, 2);
    744:   PetscCall(KSPInitializePackage());

    746:   PetscCall(PetscHeaderCreate(ksp, KSP_CLASSID, "KSP", "Krylov Method", "KSP", comm, KSPDestroy, KSPView));
    747:   ksp->default_max_it = ksp->max_it = 10000;
    748:   ksp->pc_side = ksp->pc_side_set = PC_SIDE_DEFAULT;

    750:   ksp->default_rtol = ksp->rtol = 1.e-5;
    751:   ksp->default_abstol = ksp->abstol = PetscDefined(USE_REAL_SINGLE) ? 1.e-25 : 1.e-50;
    752:   ksp->default_divtol = ksp->divtol = 1.e4;

    754:   ksp->chknorm  = -1;
    755:   ksp->normtype = ksp->normtype_set = KSP_NORM_DEFAULT;
    756:   ksp->rnorm                        = 0.0;
    757:   ksp->its                          = 0;
    758:   ksp->guess_zero                   = PETSC_TRUE;
    759:   ksp->calc_sings                   = PETSC_FALSE;
    760:   ksp->res_hist                     = NULL;
    761:   ksp->res_hist_alloc               = NULL;
    762:   ksp->res_hist_len                 = 0;
    763:   ksp->res_hist_max                 = 0;
    764:   ksp->res_hist_reset               = PETSC_TRUE;
    765:   ksp->err_hist                     = NULL;
    766:   ksp->err_hist_alloc               = NULL;
    767:   ksp->err_hist_len                 = 0;
    768:   ksp->err_hist_max                 = 0;
    769:   ksp->err_hist_reset               = PETSC_TRUE;
    770:   ksp->numbermonitors               = 0;
    771:   ksp->numberreasonviews            = 0;
    772:   ksp->setfromoptionscalled         = 0;
    773:   ksp->nmax                         = PETSC_DECIDE;

    775:   PetscCall(KSPConvergedDefaultCreate(&ctx));
    776:   PetscCall(KSPSetConvergenceTest(ksp, KSPConvergedDefault, ctx, KSPConvergedDefaultDestroy));
    777:   ksp->ops->buildsolution = KSPBuildSolutionDefault;
    778:   ksp->ops->buildresidual = KSPBuildResidualDefault;

    780:   ksp->vec_sol    = NULL;
    781:   ksp->vec_rhs    = NULL;
    782:   ksp->pc         = NULL;
    783:   ksp->data       = NULL;
    784:   ksp->nwork      = 0;
    785:   ksp->work       = NULL;
    786:   ksp->reason     = KSP_CONVERGED_ITERATING;
    787:   ksp->setupstage = KSP_SETUP_NEW;

    789:   PetscCall(KSPNormSupportTableReset_Private(ksp));

    791:   *inksp = ksp;
    792:   PetscFunctionReturn(PETSC_SUCCESS);
    793: }

    795: /*@
    796:   KSPSetType - Sets the algorithm/method to be used to solve the linear system with the given `KSP`

    798:   Logically Collective

    800:   Input Parameters:
    801: + ksp  - the Krylov space context
    802: - type - a known method

    804:   Options Database Key:
    805: . -ksp_type type - Sets the method; see `KSPType`

    807:   Level: intermediate

    809:   Notes:
    810:   See `KSPType` for available methods (for instance, `KSPCG` or `KSPGMRES`).

    812:   Normally, it is best to use the `KSPSetFromOptions()` command and
    813:   then set the `KSP` type from the options database rather than by using
    814:   this routine.  Using the options database provides the user with
    815:   maximum flexibility in evaluating the many different Krylov methods.
    816:   The `KSPSetType()` routine is provided for those situations where it
    817:   is necessary to set the iterative solver independently of the command
    818:   line or options database.  This might be the case, for example, when
    819:   the choice of iterative solver changes during the execution of the
    820:   program, and the user's application is taking responsibility for
    821:   choosing the appropriate method.  In other words, this routine is
    822:   not for beginners.

    824:   Developer Note:
    825:   `KSPRegister()` is used to add Krylov types to `KSPList` from which they are accessed by `KSPSetType()`.

    827: .seealso: [](ch_ksp), `PCSetType()`, `KSPType`, `KSPRegister()`, `KSPCreate()`, `KSP`
    828: @*/
    829: PetscErrorCode KSPSetType(KSP ksp, KSPType type)
    830: {
    831:   PetscBool match;
    832:   PetscErrorCode (*r)(KSP);

    834:   PetscFunctionBegin;
    836:   PetscAssertPointer(type, 2);

    838:   PetscCall(PetscObjectTypeCompare((PetscObject)ksp, type, &match));
    839:   if (match) PetscFunctionReturn(PETSC_SUCCESS);

    841:   PetscCall(PetscFunctionListFind(KSPList, type, &r));
    842:   PetscCheck(r, PetscObjectComm((PetscObject)ksp), PETSC_ERR_ARG_UNKNOWN_TYPE, "Unable to find requested KSP type %s", type);
    843:   /* Destroy the previous private KSP context */
    844:   PetscTryTypeMethod(ksp, destroy);

    846:   /* Reinitialize function pointers in KSPOps structure */
    847:   PetscCall(PetscMemzero(ksp->ops, sizeof(struct _KSPOps)));
    848:   ksp->ops->buildsolution = KSPBuildSolutionDefault;
    849:   ksp->ops->buildresidual = KSPBuildResidualDefault;
    850:   PetscCall(KSPNormSupportTableReset_Private(ksp));
    851:   ksp->converged_neg_curve = PETSC_FALSE; // restore default
    852:   ksp->setupnewmatrix      = PETSC_FALSE; // restore default (setup not called in case of new matrix)
    853:   /* Call the KSPCreate_XXX routine for this particular Krylov solver */
    854:   ksp->setupstage     = KSP_SETUP_NEW;
    855:   ksp->guess_not_read = PETSC_FALSE; // restore default
    856:   PetscCall((*r)(ksp));
    857:   PetscCall(PetscObjectChangeTypeName((PetscObject)ksp, type));
    858:   PetscFunctionReturn(PETSC_SUCCESS);
    859: }

    861: /*@
    862:   KSPGetType - Gets the `KSP` type as a string from the `KSP` object.

    864:   Not Collective

    866:   Input Parameter:
    867: . ksp - Krylov context

    869:   Output Parameter:
    870: . type - name of the `KSP` method

    872:   Level: intermediate

    874: .seealso: [](ch_ksp), `KSPType`, `KSP`, `KSPSetType()`
    875: @*/
    876: PetscErrorCode KSPGetType(KSP ksp, KSPType *type)
    877: {
    878:   PetscFunctionBegin;
    880:   PetscAssertPointer(type, 2);
    881:   *type = ((PetscObject)ksp)->type_name;
    882:   PetscFunctionReturn(PETSC_SUCCESS);
    883: }

    885: /*@C
    886:   KSPRegister -  Adds a method, `KSPType`, to the Krylov subspace solver package.

    888:   Not Collective, No Fortran Support

    890:   Input Parameters:
    891: + sname    - name of a new user-defined solver
    892: - function - routine to create method

    894:   Level: advanced

    896:   Note:
    897:   `KSPRegister()` may be called multiple times to add several user-defined solvers.

    899:   Example Usage:
    900: .vb
    901:    KSPRegister("my_solver", MySolverCreate);
    902: .ve

    904:   Then, your solver can be chosen with the procedural interface via
    905: .vb
    906:   KSPSetType(ksp, "my_solver")
    907: .ve
    908:   or at runtime via the option `-ksp_type my_solver`

    910: .seealso: [](ch_ksp), `KSP`, `KSPType`, `KSPSetType`, `KSPRegisterAll()`
    911: @*/
    912: PetscErrorCode KSPRegister(const char sname[], PetscErrorCode (*function)(KSP))
    913: {
    914:   PetscFunctionBegin;
    915:   PetscCall(KSPInitializePackage());
    916:   PetscCall(PetscFunctionListAdd(&KSPList, sname, function));
    917:   PetscFunctionReturn(PETSC_SUCCESS);
    918: }

    920: PetscErrorCode KSPMonitorMakeKey_Internal(const char name[], PetscViewerType vtype, PetscViewerFormat format, char key[])
    921: {
    922:   PetscFunctionBegin;
    923:   PetscCall(PetscStrncpy(key, name, PETSC_MAX_PATH_LEN));
    924:   PetscCall(PetscStrlcat(key, ":", PETSC_MAX_PATH_LEN));
    925:   PetscCall(PetscStrlcat(key, vtype, PETSC_MAX_PATH_LEN));
    926:   PetscCall(PetscStrlcat(key, ":", PETSC_MAX_PATH_LEN));
    927:   PetscCall(PetscStrlcat(key, PetscViewerFormats[format], PETSC_MAX_PATH_LEN));
    928:   PetscFunctionReturn(PETSC_SUCCESS);
    929: }

    931: /*@C
    932:   KSPMonitorRegister -  Registers a Krylov subspace solver monitor routine that may be accessed with `KSPMonitorSetFromOptions()`

    934:   Not Collective

    936:   Input Parameters:
    937: + name    - name of a new monitor type
    938: . vtype   - A `PetscViewerType` for the output
    939: . format  - A `PetscViewerFormat` for the output
    940: . monitor - Monitor routine, see `KSPMonitorRegisterFn`
    941: . create  - Creation routine, or `NULL`
    942: - destroy - Destruction routine, or `NULL`

    944:   Level: advanced

    946:   Notes:
    947:   `KSPMonitorRegister()` may be called multiple times to add several user-defined monitors.

    949:   The calling sequence for the given function matches the calling sequence used by `KSPMonitorFn` functions passed to `KSPMonitorSet()` with the additional
    950:   requirement that its final argument be a `PetscViewerAndFormat`.

    952:   Example Usage:
    953: .vb
    954:   KSPMonitorRegister("my_monitor", PETSCVIEWERASCII, PETSC_VIEWER_ASCII_INFO_DETAIL, MyMonitor, NULL, NULL);
    955: .ve

    957:   Then, your monitor can be chosen with the procedural interface via
    958: .vb
    959:   KSPMonitorSetFromOptions(ksp, "-ksp_monitor_my_monitor", "my_monitor", NULL)
    960: .ve
    961:   or at runtime via the option `-ksp_monitor_my_monitor`

    963: .seealso: [](ch_ksp), `KSP`, `KSPMonitorSet()`, `KSPMonitorRegisterAll()`, `KSPMonitorSetFromOptions()`
    964: @*/
    965: PetscErrorCode KSPMonitorRegister(const char name[], PetscViewerType vtype, PetscViewerFormat format, KSPMonitorRegisterFn *monitor, KSPMonitorRegisterCreateFn *create, KSPMonitorRegisterDestroyFn *destroy)
    966: {
    967:   char key[PETSC_MAX_PATH_LEN];

    969:   PetscFunctionBegin;
    970:   PetscCall(KSPInitializePackage());
    971:   PetscCall(KSPMonitorMakeKey_Internal(name, vtype, format, key));
    972:   PetscCall(PetscFunctionListAdd(&KSPMonitorList, key, monitor));
    973:   if (create) PetscCall(PetscFunctionListAdd(&KSPMonitorCreateList, key, create));
    974:   if (destroy) PetscCall(PetscFunctionListAdd(&KSPMonitorDestroyList, key, destroy));
    975:   PetscFunctionReturn(PETSC_SUCCESS);
    976: }