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: 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 defined(PETSC_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
227: - name - command line option
229: Level: intermediate
231: .seealso: [](ch_ksp), `KSP`, `KSPView()`, `PetscObjectViewFromOptions()`, `KSPCreate()`
232: @*/
233: PetscErrorCode KSPViewFromOptions(KSP A, PetscObject obj, const char name[])
234: {
235: PetscFunctionBegin;
237: PetscCall(PetscObjectViewFromOptions((PetscObject)A, obj, name));
238: PetscFunctionReturn(PETSC_SUCCESS);
239: }
241: /*@
242: KSPSetNormType - Sets the type of residual norm that is used for convergence testing in `KSPSolve()` for the given `KSP` context
244: Logically Collective
246: Input Parameters:
247: + ksp - Krylov solver context
248: - normtype - one of
249: .vb
250: KSP_NORM_NONE - skips computing the norm, this should generally only be used if you are using
251: the Krylov method as a smoother with a fixed small number of iterations.
252: Implicitly sets `KSPConvergedSkip()` as the `KSP` convergence test.
253: Note that certain algorithms such as `KSPGMRES` ALWAYS require the norm calculation,
254: for these methods the norms are still computed, they are just not used in
255: the convergence test.
256: KSP_NORM_PRECONDITIONED - the default for left-preconditioned solves, uses the 2-norm
257: of the preconditioned residual $B^{-1}(b - A x)$.
258: KSP_NORM_UNPRECONDITIONED - uses the 2-norm of the true $b - Ax$ residual.
259: KSP_NORM_NATURAL - uses the $A$ norm of the true $b - Ax$ residual; supported by `KSPCG`, `KSPCR`, `KSPCGNE`, `KSPCGS`
260: .ve
262: Options Database Key:
263: . -ksp_norm_type <none,preconditioned,unpreconditioned,natural> - set `KSP` norm type
265: Level: advanced
267: Notes:
268: 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.
270: Not all combinations of preconditioner side (see `KSPSetPCSide()`) and norm types are supported by all Krylov methods.
271: If only one is set, PETSc tries to automatically change the other to find a compatible pair. If no such combination
272: is supported, PETSc will generate an error.
274: Developer Note:
275: Supported combinations of norm and preconditioner side are set using `KSPSetSupportedNorm()` for each `KSPType`.
277: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSPConvergedSkip()`, `KSPSetCheckNormIteration()`, `KSPSetPCSide()`, `KSPGetPCSide()`, `KSPNormType`
278: @*/
279: PetscErrorCode KSPSetNormType(KSP ksp, KSPNormType normtype)
280: {
281: PetscFunctionBegin;
284: ksp->normtype = ksp->normtype_set = normtype;
285: PetscFunctionReturn(PETSC_SUCCESS);
286: }
288: /*@
289: KSPSetCheckNormIteration - Sets the first iteration at which the norm of the residual will be
290: computed and used in the convergence test of `KSPSolve()` for the given `KSP` context
292: Logically Collective
294: Input Parameters:
295: + ksp - Krylov solver context
296: - it - use -1 to check at all iterations
298: Level: advanced
300: Notes:
301: Currently only works with `KSPCG`, `KSPBCGS` and `KSPIBCGS`
303: Use `KSPSetNormType`(ksp,`KSP_NORM_NONE`) to never check the norm
305: On steps where the norm is not computed, the previous norm is still in the variable, so if you run with, for example,
306: `-ksp_monitor` the residual norm will appear to be unchanged for several iterations (though it is not really unchanged).
308: Certain methods such as `KSPGMRES` always compute the residual norm, this routine will not change that computation, but it will
309: prevent the computed norm from being checked.
311: .seealso: [](ch_ksp), `KSP`, `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSPConvergedSkip()`, `KSPSetNormType()`, `KSPSetLagNorm()`
312: @*/
313: PetscErrorCode KSPSetCheckNormIteration(KSP ksp, PetscInt it)
314: {
315: PetscFunctionBegin;
318: ksp->chknorm = it;
319: PetscFunctionReturn(PETSC_SUCCESS);
320: }
322: /*@
323: KSPSetLagNorm - Lags the residual norm calculation so that it is computed as part of the `MPI_Allreduce()` used for
324: computing the inner products needed for the next iteration.
326: Logically Collective
328: Input Parameters:
329: + ksp - Krylov solver context
330: - flg - `PETSC_TRUE` or `PETSC_FALSE`
332: Options Database Key:
333: . -ksp_lag_norm - lag the calculated residual norm
335: Level: advanced
337: Notes:
338: Currently only works with `KSPIBCGS`.
340: This can reduce communication costs at the expense of doing
341: one additional iteration because the norm used in the convergence test of `KSPSolve()` is one iteration behind the actual
342: current residual norm (which has not yet been computed due to the lag).
344: Use `KSPSetNormType`(ksp,`KSP_NORM_NONE`) to never check the norm
346: If you lag the norm and run with, for example, `-ksp_monitor`, the residual norm reported will be the lagged one.
348: `KSPSetCheckNormIteration()` is an alternative way of avoiding the expense of computing the residual norm at each iteration.
350: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSPConvergedSkip()`, `KSPSetNormType()`, `KSPSetCheckNormIteration()`
351: @*/
352: PetscErrorCode KSPSetLagNorm(KSP ksp, PetscBool flg)
353: {
354: PetscFunctionBegin;
357: ksp->lagnorm = flg;
358: PetscFunctionReturn(PETSC_SUCCESS);
359: }
361: /*@
362: KSPSetSupportedNorm - Sets a norm and preconditioner side supported by a `KSPType`
364: Logically Collective
366: Input Parameters:
367: + ksp - Krylov method
368: . normtype - supported norm type of the type `KSPNormType`
369: . pcside - preconditioner side, of the type `PCSide` that can be used with this `KSPNormType`
370: - priority - positive integer preference for this combination; larger values have higher priority
372: Level: developer
374: Notes:
375: This function should be called from the implementation files `KSPCreate_XXX()` to declare
376: which norms and preconditioner sides are supported. Users should not call this
377: function.
379: This function can be called multiple times for each combination of `KSPNormType` and `PCSide`
380: the `KSPType` supports
382: .seealso: [](ch_ksp), `KSP`, `KSPNormType`, `PCSide`, `KSPSetNormType()`, `KSPSetPCSide()`
383: @*/
384: PetscErrorCode KSPSetSupportedNorm(KSP ksp, KSPNormType normtype, PCSide pcside, PetscInt priority)
385: {
386: PetscFunctionBegin;
388: ksp->normsupporttable[normtype][pcside] = priority;
389: PetscFunctionReturn(PETSC_SUCCESS);
390: }
392: static PetscErrorCode KSPNormSupportTableReset_Private(KSP ksp)
393: {
394: PetscFunctionBegin;
395: PetscCall(PetscMemzero(ksp->normsupporttable, sizeof(ksp->normsupporttable)));
396: ksp->pc_side = ksp->pc_side_set;
397: ksp->normtype = ksp->normtype_set;
398: PetscFunctionReturn(PETSC_SUCCESS);
399: }
401: PetscErrorCode KSPSetUpNorms_Private(KSP ksp, PetscBool errorifnotsupported, KSPNormType *normtype, PCSide *pcside)
402: {
403: PetscInt i, j, best, ibest = 0, jbest = 0;
405: PetscFunctionBegin;
406: best = 0;
407: for (i = 0; i < KSP_NORM_MAX; i++) {
408: for (j = 0; j < PC_SIDE_MAX; j++) {
409: if ((ksp->normtype == KSP_NORM_DEFAULT || ksp->normtype == i) && (ksp->pc_side == PC_SIDE_DEFAULT || ksp->pc_side == j) && ksp->normsupporttable[i][j] > best) {
410: best = ksp->normsupporttable[i][j];
411: ibest = i;
412: jbest = j;
413: }
414: }
415: }
416: if (best < 1 && errorifnotsupported) {
417: 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);
418: 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]);
419: 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]);
420: 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]);
421: }
422: if (normtype) *normtype = (KSPNormType)ibest;
423: if (pcside) *pcside = (PCSide)jbest;
424: PetscFunctionReturn(PETSC_SUCCESS);
425: }
427: /*@
428: KSPGetNormType - Gets the `KSPNormType` that is used for convergence testing during `KSPSolve()` for this `KSP` context
430: Not Collective
432: Input Parameter:
433: . ksp - Krylov solver context
435: Output Parameter:
436: . normtype - the `KSPNormType` that is used for convergence testing
438: Level: advanced
440: .seealso: [](ch_ksp), `KSPNormType`, `KSPSetNormType()`, `KSPConvergedSkip()`
441: @*/
442: PetscErrorCode KSPGetNormType(KSP ksp, KSPNormType *normtype)
443: {
444: PetscFunctionBegin;
446: PetscAssertPointer(normtype, 2);
447: PetscCall(KSPSetUpNorms_Private(ksp, PETSC_TRUE, &ksp->normtype, &ksp->pc_side));
448: *normtype = ksp->normtype;
449: PetscFunctionReturn(PETSC_SUCCESS);
450: }
452: #if defined(PETSC_HAVE_SAWS)
453: #include <petscviewersaws.h>
454: #endif
456: /*@
457: KSPSetOperators - Sets the matrix associated with the linear system
458: and a (possibly) different one from which the preconditioner will be built into the `KSP` context. The matrix will then be used during `KSPSolve()`
460: Collective
462: Input Parameters:
463: + ksp - the `KSP` context
464: . Amat - the matrix that defines the linear system
465: - Pmat - the matrix to be used in constructing the preconditioner, usually the same as `Amat`.
467: Level: beginner
469: Notes:
470: If you know the operator `Amat` has a null space you can use `MatSetNullSpace()` and `MatSetTransposeNullSpace()` to supply the null
471: space to `Amat` and the `KSP` solvers will automatically use that null space as needed during the solution process.
473: All future calls to `KSPSetOperators()` must use the same size matrices, unless `KSPReset()` is called!
475: Passing a `NULL` for `Amat` or `Pmat` removes the matrix that is currently being used from the `KSP` context.
477: If you wish to replace either `Amat` or `Pmat` but leave the other one untouched then
478: first call `KSPGetOperators()` to get the one you wish to keep, call `PetscObjectReference()`
479: on it and then pass it back in your call to `KSPSetOperators()`.
481: Developer Notes:
482: If the operators have NOT been set with `KSPSetOperators()` then the operators
483: are created in the `PC` and returned to the user. In this case, if both operators
484: mat and pmat are requested, two DIFFERENT operators will be returned. If
485: only one is requested both operators in the `PC` will be the same (i.e. as
486: if one had called `KSPSetOperators()` with the same argument for both `Mat`s).
487: The user must set the sizes of the returned matrices and their type etc just
488: as if the user created them with `MatCreate()`. For example,
490: .vb
491: KSPGetOperators(ksp/pc,&mat,NULL); is equivalent to
492: set size, type, etc of mat
494: MatCreate(comm,&mat);
495: KSP/PCSetOperators(ksp/pc,mat,mat);
496: PetscObjectDereference((PetscObject)mat);
497: set size, type, etc of mat
499: and
501: KSP/PCGetOperators(ksp/pc,&mat,&pmat); is equivalent to
502: set size, type, etc of mat and pmat
504: MatCreate(comm,&mat);
505: MatCreate(comm,&pmat);
506: KSP/PCSetOperators(ksp/pc,mat,pmat);
507: PetscObjectDereference((PetscObject)mat);
508: PetscObjectDereference((PetscObject)pmat);
509: set size, type, etc of mat and pmat
510: .ve
512: The rationale for this support is so that when creating a `TS`, `SNES`, or `KSP` the hierarchy
513: of underlying objects (i.e. `SNES`, `KSP`, `PC`, `Mat`) and their lifespans can be completely
514: managed by the top most level object (i.e. the `TS`, `SNES`, or `KSP`). Another way to look
515: at this is when you create a `SNES` you do not NEED to create a `KSP` and attach it to
516: the `SNES` object (the `SNES` object manages it for you). Similarly when you create a `KSP`
517: you do not need to attach a `PC` to it (the `KSP` object manages the `PC` object for you).
518: Thus, why should YOU have to create the `Mat` and attach it to the `SNES`/`KSP`/`PC`, when
519: it can be created for you?
521: .seealso: [](ch_ksp), `KSP`, `Mat`, `KSPSolve()`, `KSPGetPC()`, `PCGetOperators()`, `PCSetOperators()`, `KSPGetOperators()`, `KSPSetComputeOperators()`, `KSPSetComputeInitialGuess()`, `KSPSetComputeRHS()`
522: @*/
523: PetscErrorCode KSPSetOperators(KSP ksp, Mat Amat, Mat Pmat)
524: {
525: PetscFunctionBegin;
529: if (Amat) PetscCheckSameComm(ksp, 1, Amat, 2);
530: if (Pmat) PetscCheckSameComm(ksp, 1, Pmat, 3);
531: if (!ksp->pc) PetscCall(KSPGetPC(ksp, &ksp->pc));
532: PetscCall(PCSetOperators(ksp->pc, Amat, Pmat));
533: if (ksp->setupstage == KSP_SETUP_NEWRHS) ksp->setupstage = KSP_SETUP_NEWMATRIX; /* so that next solve call will call PCSetUp() on new matrix */
534: PetscFunctionReturn(PETSC_SUCCESS);
535: }
537: /*@
538: KSPGetOperators - Gets the matrix associated with the linear system
539: and a (possibly) different one used to construct the preconditioner from the `KSP` context
541: Collective
543: Input Parameter:
544: . ksp - the `KSP` context
546: Output Parameters:
547: + Amat - the matrix that defines the linear system
548: - Pmat - the matrix to be used in constructing the preconditioner, usually the same as `Amat`.
550: Level: intermediate
552: Notes:
553: If `KSPSetOperators()` has not been called then the `KSP` object will attempt to automatically create the matrix `Amat` and return it
555: Use `KSPGetOperatorsSet()` to determine if matrices have been provided.
557: DOES NOT increase the reference counts of the matrix, so you should NOT destroy them.
559: .seealso: [](ch_ksp), `KSP`, `KSPSolve()`, `KSPGetPC()`, `PCSetOperators()`, `KSPSetOperators()`, `KSPGetOperatorsSet()`
560: @*/
561: PetscErrorCode KSPGetOperators(KSP ksp, Mat *Amat, Mat *Pmat)
562: {
563: PetscFunctionBegin;
565: if (!ksp->pc) PetscCall(KSPGetPC(ksp, &ksp->pc));
566: PetscCall(PCGetOperators(ksp->pc, Amat, Pmat));
567: PetscFunctionReturn(PETSC_SUCCESS);
568: }
570: /*@
571: KSPGetOperatorsSet - Determines if the matrix associated with the linear system and
572: possibly a different one from which the preconditioner will be built have been set in the `KSP` with `KSPSetOperators()`
574: Not Collective, though the results on all processes will be the same
576: Input Parameter:
577: . ksp - the `KSP` context
579: Output Parameters:
580: + mat - the matrix associated with the linear system was set
581: - pmat - matrix from which the preconditioner will be built, usually the same as `mat` was set
583: Level: intermediate
585: Note:
586: This routine exists because if you call `KSPGetOperators()` on a `KSP` that does not yet have operators they are
587: automatically created in the call.
589: .seealso: [](ch_ksp), `KSP`, `PCSetOperators()`, `KSPGetOperators()`, `KSPSetOperators()`, `PCGetOperators()`, `PCGetOperatorsSet()`
590: @*/
591: PetscErrorCode KSPGetOperatorsSet(KSP ksp, PetscBool *mat, PetscBool *pmat)
592: {
593: PetscFunctionBegin;
595: if (!ksp->pc) PetscCall(KSPGetPC(ksp, &ksp->pc));
596: PetscCall(PCGetOperatorsSet(ksp->pc, mat, pmat));
597: PetscFunctionReturn(PETSC_SUCCESS);
598: }
600: /*@C
601: KSPSetPreSolve - Sets a function that is called at the beginning of each `KSPSolve()`. Used in conjunction with `KSPSetPostSolve()`.
603: Logically Collective
605: Input Parameters:
606: + ksp - the solver object
607: . presolve - the function to call before the solve, see` KSPPSolveFn`
608: - ctx - an optional context needed by the function
610: Level: developer
612: Notes:
613: The function provided here `presolve` is used to modify the right hand side, and possibly the matrix, of the linear system to be solved.
614: The function provided with `KSPSetPostSolve()` then modifies the resulting solution of that linear system to obtain the correct solution
615: to the initial linear system.
617: The functions `PCPreSolve()` and `PCPostSolve()` provide a similar functionality and are used, for example with `PCEISENSTAT`.
619: .seealso: [](ch_ksp), `KSPPSolveFn`, `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPSetPostSolve()`, `PCEISENSTAT`, `PCPreSolve()`, `PCPostSolve()`
620: @*/
621: PetscErrorCode KSPSetPreSolve(KSP ksp, KSPPSolveFn *presolve, void *ctx)
622: {
623: PetscFunctionBegin;
625: ksp->presolve = presolve;
626: ksp->prectx = ctx;
627: PetscFunctionReturn(PETSC_SUCCESS);
628: }
630: /*@C
631: KSPSetPostSolve - Sets a function that is called at the end of each `KSPSolve()` (whether it converges or not). Used in conjunction with `KSPSetPreSolve()`.
633: Logically Collective
635: Input Parameters:
636: + ksp - the solver object
637: . postsolve - the function to call after the solve, see` KSPPSolveFn`
638: - ctx - an optional context needed by the function
640: Level: developer
642: .seealso: [](ch_ksp), `KSPPSolveFn`, `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPSetPreSolve()`, `PCEISENSTAT`
643: @*/
644: PetscErrorCode KSPSetPostSolve(KSP ksp, KSPPSolveFn *postsolve, void *ctx)
645: {
646: PetscFunctionBegin;
648: ksp->postsolve = postsolve;
649: ksp->postctx = ctx;
650: PetscFunctionReturn(PETSC_SUCCESS);
651: }
653: /*@
654: KSPSetNestLevel - sets the amount of nesting the `KSP` has. That is the number of levels of `KSP` above this `KSP` in a linear solve.
656: Collective
658: Input Parameters:
659: + ksp - the `KSP`
660: - level - the nest level
662: Level: developer
664: Note:
665: For example, the `KSP` in each block of a `KSPBJACOBI` has a level of 1, while the outer `KSP` has a level of 0.
667: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPGMRES`, `KSPType`, `KSPGetNestLevel()`, `PCSetKSPNestLevel()`, `PCGetKSPNestLevel()`
668: @*/
669: PetscErrorCode KSPSetNestLevel(KSP ksp, PetscInt level)
670: {
671: PetscFunctionBegin;
674: ksp->nestlevel = level;
675: PetscFunctionReturn(PETSC_SUCCESS);
676: }
678: /*@
679: KSPGetNestLevel - gets the amount of nesting the `KSP` has
681: Not Collective
683: Input Parameter:
684: . ksp - the `KSP`
686: Output Parameter:
687: . level - the nest level
689: Level: developer
691: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPGMRES`, `KSPType`, `KSPSetNestLevel()`, `PCSetKSPNestLevel()`, `PCGetKSPNestLevel()`
692: @*/
693: PetscErrorCode KSPGetNestLevel(KSP ksp, PetscInt *level)
694: {
695: PetscFunctionBegin;
697: PetscAssertPointer(level, 2);
698: *level = ksp->nestlevel;
699: PetscFunctionReturn(PETSC_SUCCESS);
700: }
702: /*@
703: KSPCreate - Creates the `KSP` context. This `KSP` context is used in PETSc to solve linear systems with `KSPSolve()`
705: Collective
707: Input Parameter:
708: . comm - MPI communicator
710: Output Parameter:
711: . inksp - location to put the `KSP` context
713: Level: beginner
715: Note:
716: The default `KSPType` is `KSPGMRES` with a restart of 30, using modified Gram-Schmidt orthogonalization. The `KSPType` may be
717: changed with `KSPSetType()`
719: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPGMRES`, `KSPType`, `KSPSetType()`
720: @*/
721: PetscErrorCode KSPCreate(MPI_Comm comm, KSP *inksp)
722: {
723: KSP ksp;
724: void *ctx;
726: PetscFunctionBegin;
727: PetscAssertPointer(inksp, 2);
728: PetscCall(KSPInitializePackage());
730: PetscCall(PetscHeaderCreate(ksp, KSP_CLASSID, "KSP", "Krylov Method", "KSP", comm, KSPDestroy, KSPView));
731: ksp->default_max_it = ksp->max_it = 10000;
732: ksp->pc_side = ksp->pc_side_set = PC_SIDE_DEFAULT;
734: ksp->default_rtol = ksp->rtol = 1.e-5;
735: ksp->default_abstol = ksp->abstol = PetscDefined(USE_REAL_SINGLE) ? 1.e-25 : 1.e-50;
736: ksp->default_divtol = ksp->divtol = 1.e4;
738: ksp->chknorm = -1;
739: ksp->normtype = ksp->normtype_set = KSP_NORM_DEFAULT;
740: ksp->rnorm = 0.0;
741: ksp->its = 0;
742: ksp->guess_zero = PETSC_TRUE;
743: ksp->calc_sings = PETSC_FALSE;
744: ksp->res_hist = NULL;
745: ksp->res_hist_alloc = NULL;
746: ksp->res_hist_len = 0;
747: ksp->res_hist_max = 0;
748: ksp->res_hist_reset = PETSC_TRUE;
749: ksp->err_hist = NULL;
750: ksp->err_hist_alloc = NULL;
751: ksp->err_hist_len = 0;
752: ksp->err_hist_max = 0;
753: ksp->err_hist_reset = PETSC_TRUE;
754: ksp->numbermonitors = 0;
755: ksp->numberreasonviews = 0;
756: ksp->setfromoptionscalled = 0;
757: ksp->nmax = PETSC_DECIDE;
759: PetscCall(KSPConvergedDefaultCreate(&ctx));
760: PetscCall(KSPSetConvergenceTest(ksp, KSPConvergedDefault, ctx, KSPConvergedDefaultDestroy));
761: ksp->ops->buildsolution = KSPBuildSolutionDefault;
762: ksp->ops->buildresidual = KSPBuildResidualDefault;
764: ksp->vec_sol = NULL;
765: ksp->vec_rhs = NULL;
766: ksp->pc = NULL;
767: ksp->data = NULL;
768: ksp->nwork = 0;
769: ksp->work = NULL;
770: ksp->reason = KSP_CONVERGED_ITERATING;
771: ksp->setupstage = KSP_SETUP_NEW;
773: PetscCall(KSPNormSupportTableReset_Private(ksp));
775: *inksp = ksp;
776: PetscFunctionReturn(PETSC_SUCCESS);
777: }
779: /*@
780: KSPSetType - Sets the algorithm/method to be used to solve the linear system with the given `KSP`
782: Logically Collective
784: Input Parameters:
785: + ksp - the Krylov space context
786: - type - a known method
788: Options Database Key:
789: . -ksp_type <method> - Sets the method; see `KSPGType` or use `-help` for a list of available methods (for instance, cg or gmres)
791: Level: intermediate
793: Notes:
794: See `KSPType` for available methods (for instance, `KSPCG` or `KSPGMRES`).
796: Normally, it is best to use the `KSPSetFromOptions()` command and
797: then set the `KSP` type from the options database rather than by using
798: this routine. Using the options database provides the user with
799: maximum flexibility in evaluating the many different Krylov methods.
800: The `KSPSetType()` routine is provided for those situations where it
801: is necessary to set the iterative solver independently of the command
802: line or options database. This might be the case, for example, when
803: the choice of iterative solver changes during the execution of the
804: program, and the user's application is taking responsibility for
805: choosing the appropriate method. In other words, this routine is
806: not for beginners.
808: Developer Note:
809: `KSPRegister()` is used to add Krylov types to `KSPList` from which they are accessed by `KSPSetType()`.
811: .seealso: [](ch_ksp), `PCSetType()`, `KSPType`, `KSPRegister()`, `KSPCreate()`, `KSP`
812: @*/
813: PetscErrorCode KSPSetType(KSP ksp, KSPType type)
814: {
815: PetscBool match;
816: PetscErrorCode (*r)(KSP);
818: PetscFunctionBegin;
820: PetscAssertPointer(type, 2);
822: PetscCall(PetscObjectTypeCompare((PetscObject)ksp, type, &match));
823: if (match) PetscFunctionReturn(PETSC_SUCCESS);
825: PetscCall(PetscFunctionListFind(KSPList, type, &r));
826: PetscCheck(r, PetscObjectComm((PetscObject)ksp), PETSC_ERR_ARG_UNKNOWN_TYPE, "Unable to find requested KSP type %s", type);
827: /* Destroy the previous private KSP context */
828: PetscTryTypeMethod(ksp, destroy);
830: /* Reinitialize function pointers in KSPOps structure */
831: PetscCall(PetscMemzero(ksp->ops, sizeof(struct _KSPOps)));
832: ksp->ops->buildsolution = KSPBuildSolutionDefault;
833: ksp->ops->buildresidual = KSPBuildResidualDefault;
834: PetscCall(KSPNormSupportTableReset_Private(ksp));
835: ksp->converged_neg_curve = PETSC_FALSE; // restore default
836: ksp->setupnewmatrix = PETSC_FALSE; // restore default (setup not called in case of new matrix)
837: /* Call the KSPCreate_XXX routine for this particular Krylov solver */
838: ksp->setupstage = KSP_SETUP_NEW;
839: ksp->guess_not_read = PETSC_FALSE; // restore default
840: PetscCall((*r)(ksp));
841: PetscCall(PetscObjectChangeTypeName((PetscObject)ksp, type));
842: PetscFunctionReturn(PETSC_SUCCESS);
843: }
845: /*@
846: KSPGetType - Gets the `KSP` type as a string from the `KSP` object.
848: Not Collective
850: Input Parameter:
851: . ksp - Krylov context
853: Output Parameter:
854: . type - name of the `KSP` method
856: Level: intermediate
858: .seealso: [](ch_ksp), `KSPType`, `KSP`, `KSPSetType()`
859: @*/
860: PetscErrorCode KSPGetType(KSP ksp, KSPType *type)
861: {
862: PetscFunctionBegin;
864: PetscAssertPointer(type, 2);
865: *type = ((PetscObject)ksp)->type_name;
866: PetscFunctionReturn(PETSC_SUCCESS);
867: }
869: /*@C
870: KSPRegister - Adds a method, `KSPType`, to the Krylov subspace solver package.
872: Not Collective, No Fortran Support
874: Input Parameters:
875: + sname - name of a new user-defined solver
876: - function - routine to create method
878: Level: advanced
880: Note:
881: `KSPRegister()` may be called multiple times to add several user-defined solvers.
883: Example Usage:
884: .vb
885: KSPRegister("my_solver", MySolverCreate);
886: .ve
888: Then, your solver can be chosen with the procedural interface via
889: .vb
890: KSPSetType(ksp, "my_solver")
891: .ve
892: or at runtime via the option `-ksp_type my_solver`
894: .seealso: [](ch_ksp), `KSP`, `KSPType`, `KSPSetType`, `KSPRegisterAll()`
895: @*/
896: PetscErrorCode KSPRegister(const char sname[], PetscErrorCode (*function)(KSP))
897: {
898: PetscFunctionBegin;
899: PetscCall(KSPInitializePackage());
900: PetscCall(PetscFunctionListAdd(&KSPList, sname, function));
901: PetscFunctionReturn(PETSC_SUCCESS);
902: }
904: PetscErrorCode KSPMonitorMakeKey_Internal(const char name[], PetscViewerType vtype, PetscViewerFormat format, char key[])
905: {
906: PetscFunctionBegin;
907: PetscCall(PetscStrncpy(key, name, PETSC_MAX_PATH_LEN));
908: PetscCall(PetscStrlcat(key, ":", PETSC_MAX_PATH_LEN));
909: PetscCall(PetscStrlcat(key, vtype, PETSC_MAX_PATH_LEN));
910: PetscCall(PetscStrlcat(key, ":", PETSC_MAX_PATH_LEN));
911: PetscCall(PetscStrlcat(key, PetscViewerFormats[format], PETSC_MAX_PATH_LEN));
912: PetscFunctionReturn(PETSC_SUCCESS);
913: }
915: /*@C
916: KSPMonitorRegister - Registers a Krylov subspace solver monitor routine that may be accessed with `KSPMonitorSetFromOptions()`
918: Not Collective
920: Input Parameters:
921: + name - name of a new monitor type
922: . vtype - A `PetscViewerType` for the output
923: . format - A `PetscViewerFormat` for the output
924: . monitor - Monitor routine, see `KSPMonitorRegisterFn`
925: . create - Creation routine, or `NULL`
926: - destroy - Destruction routine, or `NULL`
928: Level: advanced
930: Notes:
931: `KSPMonitorRegister()` may be called multiple times to add several user-defined monitors.
933: The calling sequence for the given function matches the calling sequence used by `KSPMonitorFn` functions passed to `KSPMonitorSet()` with the additional
934: requirement that its final argument be a `PetscViewerAndFormat`.
936: Example Usage:
937: .vb
938: KSPMonitorRegister("my_monitor", PETSCVIEWERASCII, PETSC_VIEWER_ASCII_INFO_DETAIL, MyMonitor, NULL, NULL);
939: .ve
941: Then, your monitor can be chosen with the procedural interface via
942: .vb
943: KSPMonitorSetFromOptions(ksp, "-ksp_monitor_my_monitor", "my_monitor", NULL)
944: .ve
945: or at runtime via the option `-ksp_monitor_my_monitor`
947: .seealso: [](ch_ksp), `KSP`, `KSPMonitorSet()`, `KSPMonitorRegisterAll()`, `KSPMonitorSetFromOptions()`
948: @*/
949: PetscErrorCode KSPMonitorRegister(const char name[], PetscViewerType vtype, PetscViewerFormat format, KSPMonitorRegisterFn *monitor, KSPMonitorRegisterCreateFn *create, KSPMonitorRegisterDestroyFn *destroy)
950: {
951: char key[PETSC_MAX_PATH_LEN];
953: PetscFunctionBegin;
954: PetscCall(KSPInitializePackage());
955: PetscCall(KSPMonitorMakeKey_Internal(name, vtype, format, key));
956: PetscCall(PetscFunctionListAdd(&KSPMonitorList, key, monitor));
957: if (create) PetscCall(PetscFunctionListAdd(&KSPMonitorCreateList, key, create));
958: if (destroy) PetscCall(PetscFunctionListAdd(&KSPMonitorDestroyList, key, destroy));
959: PetscFunctionReturn(PETSC_SUCCESS);
960: }