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_Orthogonalization, 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 PetscDefined(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 viewer_specification - Display the `KSP` at the end of each `KSPSolve()` call, see `PetscOptionsCreateViewer()` for the format of `viewer_specification`
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()`, `PetscOptionsCreateViewer()`
105: @*/
106: PetscErrorCode KSPView(KSP ksp, PetscViewer viewer)
107: {
108: PetscBool isascii, isbinary, isdraw, isstring;
109: #if PetscDefined(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 PetscDefined(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->converged == KSPConvergedSkip || ksp->normtype == KSP_NORM_NONE) PetscCall(PetscViewerASCIIPrintf(viewer, " not checking for convergence\n"));
152: else PetscCall(PetscViewerASCIIPrintf(viewer, " using %s norm type for convergence test\n", KSPNormTypes[ksp->normtype]));
153: } else if (isbinary) {
154: PetscInt classid = KSP_FILE_CLASSID;
155: MPI_Comm comm;
156: PetscMPIInt rank;
157: char type[256];
159: PetscCall(PetscObjectGetComm((PetscObject)ksp, &comm));
160: PetscCallMPI(MPI_Comm_rank(comm, &rank));
161: if (rank == 0) {
162: PetscCall(PetscViewerBinaryWrite(viewer, &classid, 1, PETSC_INT));
163: PetscCall(PetscStrncpy(type, ((PetscObject)ksp)->type_name, 256));
164: PetscCall(PetscViewerBinaryWrite(viewer, type, 256, PETSC_CHAR));
165: }
166: PetscTryTypeMethod(ksp, view, viewer);
167: } else if (isstring) {
168: const char *type;
169: PetscCall(KSPGetType(ksp, &type));
170: PetscCall(PetscViewerStringSPrintf(viewer, " KSPType: %-7.7s", type));
171: PetscTryTypeMethod(ksp, view, viewer);
172: } else if (isdraw) {
173: PetscDraw draw;
174: char str[36];
175: PetscReal x, y, bottom, h;
176: PetscBool flg;
178: PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw));
179: PetscCall(PetscDrawGetCurrentPoint(draw, &x, &y));
180: PetscCall(PetscObjectTypeCompare((PetscObject)ksp, KSPPREONLY, &flg));
181: if (!flg) {
182: PetscCall(PetscStrncpy(str, "KSP: ", sizeof(str)));
183: PetscCall(PetscStrlcat(str, ((PetscObject)ksp)->type_name, sizeof(str)));
184: PetscCall(PetscDrawStringBoxed(draw, x, y, PETSC_DRAW_RED, PETSC_DRAW_BLACK, str, NULL, &h));
185: bottom = y - h;
186: } else {
187: bottom = y;
188: }
189: PetscCall(PetscDrawPushCurrentPoint(draw, x, bottom));
190: #if PetscDefined(HAVE_SAWS)
191: } else if (issaws) {
192: PetscMPIInt rank;
193: const char *name;
195: PetscCall(PetscObjectGetName((PetscObject)ksp, &name));
196: PetscCallMPI(MPI_Comm_rank(PETSC_COMM_WORLD, &rank));
197: if (!((PetscObject)ksp)->amsmem && rank == 0) {
198: char dir[1024];
200: PetscCall(PetscObjectViewSAWs((PetscObject)ksp, viewer));
201: PetscCall(PetscSNPrintf(dir, 1024, "/PETSc/Objects/%s/its", name));
202: PetscCallSAWs(SAWs_Register, (dir, &ksp->its, 1, SAWs_READ, SAWs_INT));
203: if (!ksp->res_hist) PetscCall(KSPSetResidualHistory(ksp, NULL, PETSC_DECIDE, PETSC_TRUE));
204: PetscCall(PetscSNPrintf(dir, 1024, "/PETSc/Objects/%s/res_hist", name));
205: PetscCallSAWs(SAWs_Register, (dir, ksp->res_hist, 10, SAWs_READ, SAWs_DOUBLE));
206: }
207: #endif
208: } else PetscTryTypeMethod(ksp, view, viewer);
209: if (ksp->pc) PetscCall(PCView(ksp->pc, viewer));
210: if (isdraw) {
211: PetscDraw draw;
212: PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw));
213: PetscCall(PetscDrawPopCurrentPoint(draw));
214: }
215: PetscFunctionReturn(PETSC_SUCCESS);
216: }
218: /*@
219: KSPViewFromOptions - View (print) a `KSP` object based on values in the options database. Also views the `PC` and `Mat` contained by the `KSP`
220: with `PCView()` and `MatView()`.
222: Collective
224: Input Parameters:
225: + A - Krylov solver context
226: . obj - optional object that provides the options prefix used to query the options database, pass `NULL` to use the options prefix of `A`
227: - name - command line option
229: Options Database Key:
230: . -name viewer_specification - See `PetscOptionsCreateViewer()` for the values of `viewer_specification`
232: Level: intermediate
234: Note:
235: This checks the options database, creates the viewer on-the-fly, uses it and then destroys it. Hence it should not be called in heavily used routines,
236: rather `PetscOptionsCreateViewer()` should be used to construct the viewer once which can then be utilized in the heavily used routine.
238: .seealso: [](ch_ksp), `KSP`, `KSPView()`, `PetscObjectViewFromOptions()`, `KSPCreate()`, `PetscOptionsCreateViewer()`
239: @*/
240: PetscErrorCode KSPViewFromOptions(KSP A, PetscObject obj, const char name[])
241: {
242: PetscFunctionBegin;
244: PetscCall(PetscObjectViewFromOptions((PetscObject)A, obj, name));
245: PetscFunctionReturn(PETSC_SUCCESS);
246: }
248: /*@
249: KSPSetNormType - Sets the type of residual norm that is used for convergence testing in `KSPSolve()` for the given `KSP` context
251: Logically Collective
253: Input Parameters:
254: + ksp - Krylov solver context
255: - normtype - one of
256: .vb
257: KSP_NORM_NONE - skips computing the norm, this should generally only be used if you are using
258: the Krylov method as a smoother with a fixed small number of iterations.
259: Implicitly sets `KSPConvergedSkip()` as the `KSP` convergence test.
260: Note that certain algorithms such as `KSPGMRES` ALWAYS require the norm calculation,
261: for these methods the norms are still computed, they are just not used in
262: the convergence test.
263: KSP_NORM_PRECONDITIONED - the default for left-preconditioned solves, uses the 2-norm
264: of the preconditioned residual $B^{-1}(b - A x)$.
265: KSP_NORM_UNPRECONDITIONED - uses the 2-norm of the true $b - Ax$ residual.
266: KSP_NORM_NATURAL - uses the $A$ norm of the true $b - Ax$ residual; supported by `KSPCG`, `KSPCR`, `KSPCGNE`, `KSPCGS`
267: .ve
269: Options Database Key:
270: . -ksp_norm_type (none|preconditioned|unpreconditioned|natural) - set `KSP` norm type
272: Level: advanced
274: Notes:
275: 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.
277: Not all combinations of preconditioner side (see `KSPSetPCSide()`) and norm types are supported by all Krylov methods.
278: If only one is set, PETSc tries to automatically change the other to find a compatible pair. If no such combination
279: is supported, PETSc will generate an error.
281: Developer Note:
282: Supported combinations of norm and preconditioner side are set using `KSPSetSupportedNorm()` for each `KSPType`.
284: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSPConvergedSkip()`, `KSPSetCheckNormIteration()`, `KSPSetPCSide()`, `KSPGetPCSide()`, `KSPNormType`
285: @*/
286: PetscErrorCode KSPSetNormType(KSP ksp, KSPNormType normtype)
287: {
288: PetscFunctionBegin;
291: ksp->normtype = ksp->normtype_set = normtype;
292: PetscFunctionReturn(PETSC_SUCCESS);
293: }
295: /*@
296: KSPSetCheckNormIteration - Sets the first iteration at which the norm of the residual will be
297: computed and used in the convergence test of `KSPSolve()` for the given `KSP` context
299: Logically Collective
301: Input Parameters:
302: + ksp - Krylov solver context
303: - it - use -1 to check at all iterations
305: Level: advanced
307: Notes:
308: Currently only works with `KSPCG`, `KSPBCGS` and `KSPIBCGS`
310: Use `KSPSetNormType`(ksp,`KSP_NORM_NONE`) to never check the norm
312: On steps where the norm is not computed, the previous norm is still in the variable, so if you run with, for example,
313: `-ksp_monitor` the residual norm will appear to be unchanged for several iterations (though it is not really unchanged).
315: Certain methods such as `KSPGMRES` always compute the residual norm, this routine will not change that computation, but it will
316: prevent the computed norm from being checked.
318: .seealso: [](ch_ksp), `KSP`, `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSPConvergedSkip()`, `KSPSetNormType()`, `KSPSetLagNorm()`
319: @*/
320: PetscErrorCode KSPSetCheckNormIteration(KSP ksp, PetscInt it)
321: {
322: PetscFunctionBegin;
325: ksp->chknorm = it;
326: PetscFunctionReturn(PETSC_SUCCESS);
327: }
329: /*@
330: KSPSetLagNorm - Lags the residual norm calculation so that it is computed as part of the `MPI_Allreduce()` used for
331: computing the inner products needed for the next iteration.
333: Logically Collective
335: Input Parameters:
336: + ksp - Krylov solver context
337: - flg - `PETSC_TRUE` or `PETSC_FALSE`
339: Options Database Key:
340: . -ksp_lag_norm - lag the calculated residual norm
342: Level: advanced
344: Notes:
345: Currently only works with `KSPIBCGS`.
347: This can reduce communication costs at the expense of doing
348: one additional iteration because the norm used in the convergence test of `KSPSolve()` is one iteration behind the actual
349: current residual norm (which has not yet been computed due to the lag).
351: Use `KSPSetNormType`(ksp,`KSP_NORM_NONE`) to never check the norm
353: If you lag the norm and run with, for example, `-ksp_monitor`, the residual norm reported will be the lagged one.
355: `KSPSetCheckNormIteration()` is an alternative way of avoiding the expense of computing the residual norm at each iteration.
357: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSPConvergedSkip()`, `KSPSetNormType()`, `KSPSetCheckNormIteration()`
358: @*/
359: PetscErrorCode KSPSetLagNorm(KSP ksp, PetscBool flg)
360: {
361: PetscFunctionBegin;
364: ksp->lagnorm = flg;
365: PetscFunctionReturn(PETSC_SUCCESS);
366: }
368: /*@
369: KSPSetSupportedNorm - Sets a norm and preconditioner side supported by a `KSPType`
371: Logically Collective
373: Input Parameters:
374: + ksp - Krylov method
375: . normtype - supported norm type of the type `KSPNormType`
376: . pcside - preconditioner side, of the type `PCSide` that can be used with this `KSPNormType`
377: - priority - positive integer preference for this combination; larger values have higher priority
379: Level: developer
381: Notes:
382: This function should be called from the implementation files `KSPCreate_XXX()` to declare
383: which norms and preconditioner sides are supported. Users should not call this
384: function.
386: This function can be called multiple times for each combination of `KSPNormType` and `PCSide`
387: the `KSPType` supports
389: .seealso: [](ch_ksp), `KSP`, `KSPNormType`, `PCSide`, `KSPSetNormType()`, `KSPSetPCSide()`
390: @*/
391: PetscErrorCode KSPSetSupportedNorm(KSP ksp, KSPNormType normtype, PCSide pcside, PetscInt priority)
392: {
393: PetscFunctionBegin;
395: ksp->normsupporttable[normtype][pcside] = priority;
396: PetscFunctionReturn(PETSC_SUCCESS);
397: }
399: static PetscErrorCode KSPNormSupportTableReset_Private(KSP ksp)
400: {
401: PetscFunctionBegin;
402: PetscCall(PetscMemzero(ksp->normsupporttable, sizeof(ksp->normsupporttable)));
403: ksp->pc_side = ksp->pc_side_set;
404: ksp->normtype = ksp->normtype_set;
405: PetscFunctionReturn(PETSC_SUCCESS);
406: }
408: PetscErrorCode KSPSetUpNorms_Private(KSP ksp, PetscBool errorifnotsupported, KSPNormType *normtype, PCSide *pcside)
409: {
410: PetscInt i, j, best, ibest = 0, jbest = 0;
412: PetscFunctionBegin;
413: best = 0;
414: for (i = 0; i < KSP_NORM_MAX; i++) {
415: for (j = 0; j < PC_SIDE_MAX; j++) {
416: if ((ksp->normtype == KSP_NORM_DEFAULT || ksp->normtype == i) && (ksp->pc_side == PC_SIDE_DEFAULT || ksp->pc_side == j) && ksp->normsupporttable[i][j] > best) {
417: best = ksp->normsupporttable[i][j];
418: ibest = i;
419: jbest = j;
420: }
421: }
422: }
423: if (best < 1 && errorifnotsupported) {
424: 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);
425: 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]);
426: 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]);
427: 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]);
428: }
429: if (normtype) *normtype = (KSPNormType)ibest;
430: if (pcside) *pcside = (PCSide)jbest;
431: PetscFunctionReturn(PETSC_SUCCESS);
432: }
434: /*@
435: KSPGetNormType - Gets the `KSPNormType` that is used for convergence testing during `KSPSolve()` for this `KSP` context
437: Not Collective
439: Input Parameter:
440: . ksp - Krylov solver context
442: Output Parameter:
443: . normtype - the `KSPNormType` that is used for convergence testing
445: Level: advanced
447: .seealso: [](ch_ksp), `KSPNormType`, `KSPSetNormType()`, `KSPConvergedSkip()`
448: @*/
449: PetscErrorCode KSPGetNormType(KSP ksp, KSPNormType *normtype)
450: {
451: PetscFunctionBegin;
453: PetscAssertPointer(normtype, 2);
454: PetscCall(KSPSetUpNorms_Private(ksp, PETSC_TRUE, &ksp->normtype, &ksp->pc_side));
455: *normtype = ksp->normtype;
456: PetscFunctionReturn(PETSC_SUCCESS);
457: }
459: #if PetscDefined(HAVE_SAWS)
460: #include <petscviewersaws.h>
461: #endif
463: /*@
464: KSPSetOperators - Sets the matrix associated with the linear system
465: and a (possibly) different one from which the preconditioner will be built into the `KSP` context. The matrix will then be used during `KSPSolve()`
467: Collective
469: Input Parameters:
470: + ksp - the `KSP` context
471: . Amat - the matrix that defines the linear system
472: - Pmat - the matrix to be used in constructing the preconditioner, usually the same as `Amat`.
474: Level: beginner
476: Notes:
477: .vb
478: KSPSetOperators(ksp, Amat, Pmat);
479: .ve
480: is the same as
481: .vb
482: KSPGetPC(ksp, &pc);
483: PCSetOperators(pc, Amat, Pmat);
484: .ve
485: and is equivalent to
486: .vb
487: PCCreate(PetscObjectComm((PetscObject)ksp), &pc);
488: PCSetOperators(pc, Amat, Pmat);
489: KSPSetPC(ksp, pc);
490: .ve
492: If you know the operator `Amat` has a null space you can use `MatSetNullSpace()` and `MatSetTransposeNullSpace()` to supply the null
493: space to `Amat` and the `KSP` solvers will automatically use that null space as needed during the solution process.
495: All future calls to `KSPSetOperators()` must use the same size matrices, unless `KSPReset()` is called!
497: Passing a `NULL` for `Amat` or `Pmat` removes the matrix that is currently being used from the `KSP` context.
499: If you wish to replace either `Amat` or `Pmat` but leave the other one untouched then
500: first call `KSPGetOperators()` to get the one you wish to keep, call `PetscObjectReference()`
501: on it and then pass it back in your call to `KSPSetOperators()`.
503: Developer Notes:
504: If the operators have NOT been set with `KSPSetOperators()` then the operators
505: are created in the `PC` and returned to the user. In this case, if both operators
506: mat and pmat are requested, two DIFFERENT operators will be returned. If
507: only one is requested both operators in the `PC` will be the same (i.e. as
508: if one had called `KSPSetOperators()` with the same argument for both `Mat`s).
509: The user must set the sizes of the returned matrices and their type etc just
510: as if the user created them with `MatCreate()`. For example,
512: .vb
513: KSPGetOperators(ksp/pc,&mat,NULL); is equivalent to
514: set size, type, etc of mat
516: MatCreate(comm,&mat);
517: KSP/PCSetOperators(ksp/pc,mat,mat);
518: PetscObjectDereference((PetscObject)mat);
519: set size, type, etc of mat
521: and
523: KSP/PCGetOperators(ksp/pc,&mat,&pmat); is equivalent to
524: set size, type, etc of mat and pmat
526: MatCreate(comm,&mat);
527: MatCreate(comm,&pmat);
528: KSP/PCSetOperators(ksp/pc,mat,pmat);
529: PetscObjectDereference((PetscObject)mat);
530: PetscObjectDereference((PetscObject)pmat);
531: set size, type, etc of mat and pmat
532: .ve
534: The rationale for this support is so that when creating a `TS`, `SNES`, or `KSP` the hierarchy
535: of underlying objects (i.e. `SNES`, `KSP`, `PC`, `Mat`) and their lifespans can be completely
536: managed by the top most level object (i.e. the `TS`, `SNES`, or `KSP`). Another way to look
537: at this is when you create a `SNES` you do not NEED to create a `KSP` and attach it to
538: the `SNES` object (the `SNES` object manages it for you). Similarly when you create a `KSP`
539: you do not need to attach a `PC` to it (the `KSP` object manages the `PC` object for you).
540: Thus, why should YOU have to create the `Mat` and attach it to the `SNES`/`KSP`/`PC`, when
541: it can be created for you?
543: .seealso: [](ch_ksp), `KSP`, `Mat`, `KSPSolve()`, `KSPGetPC()`, `PCGetOperators()`, `PCSetOperators()`, `KSPGetOperators()`, `KSPSetComputeOperators()`, `KSPSetComputeInitialGuess()`, `KSPSetComputeRHS()`
544: @*/
545: PetscErrorCode KSPSetOperators(KSP ksp, Mat Amat, Mat Pmat)
546: {
547: PetscFunctionBegin;
551: if (Amat) PetscCheckSameComm(ksp, 1, Amat, 2);
552: if (Pmat) PetscCheckSameComm(ksp, 1, Pmat, 3);
553: if (!ksp->pc) PetscCall(KSPGetPC(ksp, &ksp->pc));
554: PetscCall(PCSetOperators(ksp->pc, Amat, Pmat));
555: if (ksp->setupstage == KSP_SETUP_NEWRHS) ksp->setupstage = KSP_SETUP_NEWMATRIX; /* so that next solve call will call PCSetUp() on new matrix */
556: PetscFunctionReturn(PETSC_SUCCESS);
557: }
559: /*@
560: KSPGetOperators - Gets the matrix associated with the linear system
561: and a (possibly) different one used to construct the preconditioner from the `KSP` context
563: Collective
565: Input Parameter:
566: . ksp - the `KSP` context
568: Output Parameters:
569: + Amat - the matrix that defines the linear system
570: - Pmat - the matrix to be used in constructing the preconditioner, usually the same as `Amat`.
572: Level: intermediate
574: Notes:
575: If `KSPSetOperators()` has not been called then the `KSP` object will attempt to automatically create the matrix `Amat` and return it
577: Use `KSPGetOperatorsSet()` to determine if matrices have been provided. After `KSPSolveTranspose()` or `KSPMatSolveTranspose()` with explicit transposition enabled by
578: `KSPSetUseExplicitTranspose()`, this function returns the explicitly transposed operators until a non-transpose solve restores their parent operators. These explicitly transposed
579: operators are owned by the `KSP` and may be destroyed by `KSPSetUseExplicitTranspose(ksp, PETSC_FALSE)`, by `KSPReset()`, or by a non-transpose solve after `KSPSetOperators()`
580: changes the operators.
582: DOES NOT increase the reference counts of the matrix, so you should NOT destroy them.
584: .seealso: [](ch_ksp), `KSP`, `KSPSolve()`, `KSPGetPC()`, `PCSetOperators()`, `KSPSetOperators()`, `KSPGetOperatorsSet()`, `KSPSetUseExplicitTranspose()`
585: @*/
586: PetscErrorCode KSPGetOperators(KSP ksp, Mat *Amat, Mat *Pmat)
587: {
588: PetscFunctionBegin;
590: if (!ksp->pc) PetscCall(KSPGetPC(ksp, &ksp->pc));
591: PetscCall(PCGetOperators(ksp->pc, Amat, Pmat));
592: PetscFunctionReturn(PETSC_SUCCESS);
593: }
595: /*@
596: KSPGetOperatorsSet - Determines if the matrix associated with the linear system and
597: possibly a different one from which the preconditioner will be built have been set in the `KSP` with `KSPSetOperators()`
599: Not Collective, though the results on all processes will be the same
601: Input Parameter:
602: . ksp - the `KSP` context
604: Output Parameters:
605: + mat - the matrix associated with the linear system was set
606: - pmat - matrix from which the preconditioner will be built, usually the same as `mat` was set
608: Level: intermediate
610: Note:
611: This routine exists because if you call `KSPGetOperators()` on a `KSP` that does not yet have operators they are
612: automatically created in the call.
614: .seealso: [](ch_ksp), `KSP`, `PCSetOperators()`, `KSPGetOperators()`, `KSPSetOperators()`, `PCGetOperators()`, `PCGetOperatorsSet()`
615: @*/
616: PetscErrorCode KSPGetOperatorsSet(KSP ksp, PetscBool *mat, PetscBool *pmat)
617: {
618: PetscFunctionBegin;
620: if (!ksp->pc) PetscCall(KSPGetPC(ksp, &ksp->pc));
621: PetscCall(PCGetOperatorsSet(ksp->pc, mat, pmat));
622: PetscFunctionReturn(PETSC_SUCCESS);
623: }
625: /*@
626: KSPSetPreSolve - Sets a function that is called at the beginning of each `KSPSolve()`. Used in conjunction with `KSPSetPostSolve()`.
628: Logically Collective
630: Input Parameters:
631: + ksp - the solver object
632: . presolve - the function to call before the solve, see` KSPPSolveFn`
633: - ctx - an optional context needed by the function
635: Level: developer
637: Notes:
638: The function provided here `presolve` is used to modify the right hand side, and possibly the matrix, of the linear system to be solved.
639: The function provided with `KSPSetPostSolve()` then modifies the resulting solution of that linear system to obtain the correct solution
640: to the initial linear system.
642: The functions `PCPreSolve()` and `PCPostSolve()` provide a similar functionality and are used, for example with `PCEISENSTAT`.
644: .seealso: [](ch_ksp), `KSPPSolveFn`, `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPSetPostSolve()`, `PCPreSolve()`, `PCPostSolve()`
645: @*/
646: PetscErrorCode KSPSetPreSolve(KSP ksp, KSPPSolveFn *presolve, PetscCtx ctx)
647: {
648: PetscFunctionBegin;
650: ksp->presolve = presolve;
651: ksp->prectx = ctx;
652: PetscFunctionReturn(PETSC_SUCCESS);
653: }
655: /*@
656: KSPSetPostSolve - Sets a function that is called at the end of each `KSPSolve()` (whether it converges or not). Used in conjunction with `KSPSetPreSolve()`.
658: Logically Collective
660: Input Parameters:
661: + ksp - the solver object
662: . postsolve - the function to call after the solve, see` KSPPSolveFn`
663: - ctx - an optional context needed by the function
665: Level: developer
667: .seealso: [](ch_ksp), `KSPPSolveFn`, `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPSetPreSolve()`, `KSPPostSolve()`
668: @*/
669: PetscErrorCode KSPSetPostSolve(KSP ksp, KSPPSolveFn *postsolve, PetscCtx ctx)
670: {
671: PetscFunctionBegin;
673: ksp->postsolve = postsolve;
674: ksp->postctx = ctx;
675: PetscFunctionReturn(PETSC_SUCCESS);
676: }
678: /*@
679: KSPPreSolve - Runs the KSP pre-solve callbacks. Used in conjunction with `KSPSetPreSolve()` or the Eisenstat-Walker method.
681: Collective
683: Input Parameters:
684: + ksp - the solver object
685: . rhs - the right-hand side vector
686: - sol - the solution vector
688: Level: developer
690: Note:
691: `KSPPreSolve()` is typically used within `KSPSolve()`, so most users would not generally call this routine themselves.
693: .seealso: [](ch_ksp), `KSPSolve()`, `KSP`, `KSPSetPreSolve()`, `KSPPostSolve()`, `SNESKSPSetUseEW()`
694: @*/
695: PetscErrorCode KSPPreSolve(KSP ksp, Vec rhs, Vec sol)
696: {
697: PetscFunctionBegin;
701: if (ksp->presolve_ew) PetscCall((*ksp->presolve_ew)(ksp, rhs, sol, ksp->prectx_ew));
702: if (ksp->presolve) PetscCall((*ksp->presolve)(ksp, rhs, sol, ksp->prectx));
703: PetscFunctionReturn(PETSC_SUCCESS);
704: }
706: /*@
707: KSPPostSolve - Runs the KSP post-solve callbacks. Used in conjunction with `KSPSetPostSolve()` or the Eisenstat-Walker method.
709: Collective
711: Input Parameters:
712: + ksp - the solver object
713: . rhs - the right-hand side vector
714: - sol - the solution vector
716: Level: developer
718: Note:
719: `KSPPostSolve()` is typically used within `KSPSolve()`, so most users would not generally call this routine themselves.
721: .seealso: [](ch_ksp), `KSPSolve()`, `KSP`, `KSPSetPostSolve()`, `KSPPreSolve()`, `SNESKSPSetUseEW()`
722: @*/
723: PetscErrorCode KSPPostSolve(KSP ksp, Vec rhs, Vec sol)
724: {
725: PetscFunctionBegin;
729: if (ksp->postsolve_ew) PetscCall((*ksp->postsolve_ew)(ksp, rhs, sol, ksp->postctx_ew));
730: if (ksp->postsolve) PetscCall((*ksp->postsolve)(ksp, rhs, sol, ksp->postctx));
731: PetscFunctionReturn(PETSC_SUCCESS);
732: }
734: /*@
735: KSPSetNestLevel - sets the amount of nesting the `KSP` has. That is the number of levels of `KSP` above this `KSP` in a linear solve.
737: Collective
739: Input Parameters:
740: + ksp - the `KSP`
741: - level - the nest level
743: Level: developer
745: Note:
746: For example, the `KSP` in each block of a `KSPBJACOBI` has a level of 1, while the outer `KSP` has a level of 0.
748: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPGMRES`, `KSPType`, `KSPGetNestLevel()`, `PCSetKSPNestLevel()`, `PCGetKSPNestLevel()`
749: @*/
750: PetscErrorCode KSPSetNestLevel(KSP ksp, PetscInt level)
751: {
752: PetscFunctionBegin;
755: ksp->nestlevel = level;
756: PetscFunctionReturn(PETSC_SUCCESS);
757: }
759: /*@
760: KSPGetNestLevel - gets the amount of nesting the `KSP` has
762: Not Collective
764: Input Parameter:
765: . ksp - the `KSP`
767: Output Parameter:
768: . level - the nest level
770: Level: developer
772: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPGMRES`, `KSPType`, `KSPSetNestLevel()`, `PCSetKSPNestLevel()`, `PCGetKSPNestLevel()`
773: @*/
774: PetscErrorCode KSPGetNestLevel(KSP ksp, PetscInt *level)
775: {
776: PetscFunctionBegin;
778: PetscAssertPointer(level, 2);
779: *level = ksp->nestlevel;
780: PetscFunctionReturn(PETSC_SUCCESS);
781: }
783: /*@
784: KSPCreate - Creates the `KSP` context. This `KSP` context is used in PETSc to solve linear systems with `KSPSolve()`
786: Collective
788: Input Parameter:
789: . comm - MPI communicator
791: Output Parameter:
792: . inksp - location to put the `KSP` context
794: Level: beginner
796: Note:
797: The default `KSPType` is `KSPGMRES` with a restart of 30, using modified Gram-Schmidt orthogonalization. The `KSPType` may be
798: changed with `KSPSetType()`
800: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPGMRES`, `KSPType`, `KSPSetType()`
801: @*/
802: PetscErrorCode KSPCreate(MPI_Comm comm, KSP *inksp)
803: {
804: KSP ksp;
805: PetscCtx ctx;
807: PetscFunctionBegin;
808: PetscAssertPointer(inksp, 2);
809: PetscCall(KSPInitializePackage());
811: PetscCall(PetscHeaderCreate(ksp, KSP_CLASSID, "KSP", "Krylov Method", "KSP", comm, KSPDestroy, KSPView));
812: ksp->default_max_it = ksp->max_it = 10000;
813: ksp->pc_side = ksp->pc_side_set = PC_SIDE_DEFAULT;
815: ksp->default_rtol = ksp->rtol = 1.e-5;
816: ksp->default_abstol = ksp->abstol = PetscDefined(USE_REAL_SINGLE) ? 1.e-25 : 1.e-50;
817: ksp->default_divtol = ksp->divtol = 1.e4;
819: ksp->normtype = ksp->normtype_set = KSP_NORM_DEFAULT;
821: ksp->chknorm = -1;
822: ksp->guess_zero = PETSC_TRUE;
823: ksp->res_hist_reset = PETSC_TRUE;
824: ksp->err_hist_reset = PETSC_TRUE;
825: ksp->nmax = PETSC_DECIDE;
826: ksp->orthog = KSPOrthogonalizationClassicalGramSchmidt;
827: ksp->cgstype = KSP_ORTHOGONALIZATION_CGS_REFINE_NEVER;
828: ksp->reason = KSP_CONVERGED_ITERATING;
829: ksp->setupstage = KSP_SETUP_NEW;
831: PetscCall(MatStateInvalidate(ksp->amatstate));
833: PetscCall(KSPConvergedDefaultCreate(&ctx));
834: PetscCall(KSPSetConvergenceTest(ksp, KSPConvergedDefault, ctx, KSPConvergedDefaultDestroy));
835: ksp->ops->buildsolution = KSPBuildSolutionDefault;
836: ksp->ops->buildresidual = KSPBuildResidualDefault;
838: PetscCall(KSPNormSupportTableReset_Private(ksp));
840: *inksp = ksp;
841: PetscFunctionReturn(PETSC_SUCCESS);
842: }
844: /*@
845: KSPSetType - Sets the algorithm/method to be used to solve the linear system with the given `KSP`
847: Logically Collective
849: Input Parameters:
850: + ksp - the Krylov space context
851: - type - a known method
853: Options Database Key:
854: . -ksp_type type - Sets the method; see `KSPType`
856: Level: intermediate
858: Notes:
859: See `KSPType` for available methods (for instance, `KSPCG` or `KSPGMRES`).
861: Normally, it is best to use the `KSPSetFromOptions()` command and
862: then set the `KSP` type from the options database rather than by using
863: this routine. Using the options database provides the user with
864: maximum flexibility in evaluating the many different Krylov methods.
865: The `KSPSetType()` routine is provided for those situations where it
866: is necessary to set the iterative solver independently of the command
867: line or options database. This might be the case, for example, when
868: the choice of iterative solver changes during the execution of the
869: program, and the user's application is taking responsibility for
870: choosing the appropriate method. In other words, this routine is
871: not for beginners.
873: Developer Note:
874: `KSPRegister()` is used to add Krylov types to `KSPList` from which they are accessed by `KSPSetType()`.
876: .seealso: [](ch_ksp), `PCSetType()`, `KSPType`, `KSPRegister()`, `KSPCreate()`, `KSP`
877: @*/
878: PetscErrorCode KSPSetType(KSP ksp, KSPType type)
879: {
880: PetscBool match;
881: PetscErrorCode (*r)(KSP);
883: PetscFunctionBegin;
885: PetscAssertPointer(type, 2);
887: PetscCall(PetscObjectTypeCompare((PetscObject)ksp, type, &match));
888: if (match) PetscFunctionReturn(PETSC_SUCCESS);
890: PetscCall(PetscFunctionListFind(KSPList, type, &r));
891: PetscCheck(r, PetscObjectComm((PetscObject)ksp), PETSC_ERR_ARG_UNKNOWN_TYPE, "Unable to find requested KSP type %s", type);
892: /* Destroy the previous private KSP context */
893: PetscTryTypeMethod(ksp, destroy);
895: /* Reinitialize function pointers in KSPOps structure */
896: PetscCall(PetscMemzero(ksp->ops, sizeof(struct _KSPOps)));
897: ksp->ops->buildsolution = KSPBuildSolutionDefault;
898: ksp->ops->buildresidual = KSPBuildResidualDefault;
899: PetscCall(KSPNormSupportTableReset_Private(ksp));
900: ksp->converged_neg_curve = PETSC_FALSE; // restore default
901: ksp->setupnewmatrix = PETSC_FALSE; // restore default (setup not called in case of new matrix)
902: /* Call the KSPCreate_XXX routine for this particular Krylov solver */
903: ksp->setupstage = KSP_SETUP_NEW;
904: ksp->guess_not_read = PETSC_FALSE; // restore default
905: PetscCall((*r)(ksp));
906: PetscCall(PetscObjectChangeTypeName((PetscObject)ksp, type));
907: PetscFunctionReturn(PETSC_SUCCESS);
908: }
910: /*@
911: KSPGetType - Gets the `KSP` type as a string from the `KSP` object.
913: Not Collective
915: Input Parameter:
916: . ksp - Krylov context
918: Output Parameter:
919: . type - name of the `KSP` method
921: Level: intermediate
923: Note:
924: `type` should not be retained for later use as it will be an invalid pointer if the `KSPType` of `ksp` is changed.
926: .seealso: [](ch_ksp), `KSPType`, `KSP`, `KSPSetType()`, `PetscObjectTypeCompare()`, `PetscObjectTypeCompareAny()`
927: @*/
928: PetscErrorCode KSPGetType(KSP ksp, KSPType *type)
929: {
930: PetscFunctionBegin;
932: PetscAssertPointer(type, 2);
933: *type = ((PetscObject)ksp)->type_name;
934: PetscFunctionReturn(PETSC_SUCCESS);
935: }
937: /*@
938: KSPRegister - Adds a method, `KSPType`, to the Krylov subspace solver package.
940: Not Collective, No Fortran Support
942: Input Parameters:
943: + sname - name of a new user-defined solver
944: - function - routine to create method
946: Level: advanced
948: Note:
949: `KSPRegister()` may be called multiple times to add several user-defined solvers.
951: Example Usage:
952: .vb
953: KSPRegister("my_solver", MySolverCreate);
954: .ve
956: Then, your solver can be chosen with the procedural interface via
957: .vb
958: KSPSetType(ksp, "my_solver")
959: .ve
960: or at runtime via the option `-ksp_type my_solver`
962: .seealso: [](ch_ksp), `KSP`, `KSPType`, `KSPSetType`, `KSPRegisterAll()`
963: @*/
964: PetscErrorCode KSPRegister(const char sname[], PetscErrorCode (*function)(KSP))
965: {
966: PetscFunctionBegin;
967: PetscCall(KSPInitializePackage());
968: PetscCall(PetscFunctionListAdd(&KSPList, sname, function));
969: PetscFunctionReturn(PETSC_SUCCESS);
970: }
972: PetscErrorCode KSPMonitorMakeKey_Internal(const char name[], PetscViewerType vtype, PetscViewerFormat format, char key[])
973: {
974: PetscFunctionBegin;
975: PetscCall(PetscStrncpy(key, name, PETSC_MAX_PATH_LEN));
976: PetscCall(PetscStrlcat(key, ":", PETSC_MAX_PATH_LEN));
977: PetscCall(PetscStrlcat(key, vtype, PETSC_MAX_PATH_LEN));
978: PetscCall(PetscStrlcat(key, ":", PETSC_MAX_PATH_LEN));
979: PetscCall(PetscStrlcat(key, PetscViewerFormats[format], PETSC_MAX_PATH_LEN));
980: PetscFunctionReturn(PETSC_SUCCESS);
981: }
983: /*@
984: KSPMonitorRegister - Registers a Krylov subspace solver monitor routine that may be accessed with `KSPMonitorSetFromOptions()`
986: Not Collective
988: Input Parameters:
989: + name - name of a new monitor type
990: . vtype - A `PetscViewerType` for the output
991: . format - A `PetscViewerFormat` for the output
992: . monitor - Monitor routine, see `KSPMonitorRegisterFn`
993: . create - Creation routine, or `NULL`
994: - destroy - Destruction routine, or `NULL`
996: Level: advanced
998: Notes:
999: `KSPMonitorRegister()` may be called multiple times to add several user-defined monitors.
1001: The calling sequence for the given function matches the calling sequence used by `KSPMonitorFn` functions passed to `KSPMonitorSet()` with the additional
1002: requirement that its final argument be a `PetscViewerAndFormat`.
1004: Example Usage:
1005: .vb
1006: KSPMonitorRegister("my_monitor", PETSCVIEWERASCII, PETSC_VIEWER_ASCII_INFO_DETAIL, MyMonitor, NULL, NULL);
1007: .ve
1009: Then, your monitor can be chosen with the procedural interface via
1010: .vb
1011: KSPMonitorSetFromOptions(ksp, "-ksp_monitor_my_monitor", "my_monitor", NULL)
1012: .ve
1013: or at runtime via the option `-ksp_monitor_my_monitor`
1015: .seealso: [](ch_ksp), `KSP`, `KSPMonitorSet()`, `KSPMonitorRegisterAll()`, `KSPMonitorSetFromOptions()`
1016: @*/
1017: PetscErrorCode KSPMonitorRegister(const char name[], PetscViewerType vtype, PetscViewerFormat format, KSPMonitorRegisterFn *monitor, KSPMonitorRegisterCreateFn *create, KSPMonitorRegisterDestroyFn *destroy)
1018: {
1019: char key[PETSC_MAX_PATH_LEN];
1021: PetscFunctionBegin;
1022: PetscCall(KSPInitializePackage());
1023: PetscCall(KSPMonitorMakeKey_Internal(name, vtype, format, key));
1024: PetscCall(PetscFunctionListAdd(&KSPMonitorList, key, monitor));
1025: if (create) PetscCall(PetscFunctionListAdd(&KSPMonitorCreateList, key, create));
1026: if (destroy) PetscCall(PetscFunctionListAdd(&KSPMonitorDestroyList, key, destroy));
1027: PetscFunctionReturn(PETSC_SUCCESS);
1028: }