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 iascii, 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, &iascii));
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 (iascii) {
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 l2 norm
257: of the preconditioned residual P^{-1}(b - A x).
258: KSP_NORM_UNPRECONDITIONED - uses the l2 norm of the true $b - Ax$ residual.
259: KSP_NORM_NATURAL - 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: .seealso: [](ch_ksp), `KSP`, `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSPConvergedSkip()`, `KSPSetNormType()`, `KSPSetLagNorm()`
309: @*/
310: PetscErrorCode KSPSetCheckNormIteration(KSP ksp, PetscInt it)
311: {
312: PetscFunctionBegin;
315: ksp->chknorm = it;
316: PetscFunctionReturn(PETSC_SUCCESS);
317: }
319: /*@
320: KSPSetLagNorm - Lags the residual norm calculation so that it is computed as part of the `MPI_Allreduce()` used for
321: computing the inner products needed for the next iteration.
323: Logically Collective
325: Input Parameters:
326: + ksp - Krylov solver context
327: - flg - `PETSC_TRUE` or `PETSC_FALSE`
329: Options Database Key:
330: . -ksp_lag_norm - lag the calculated residual norm
332: Level: advanced
334: Notes:
335: Currently only works with `KSPIBCGS`.
337: This can reduce communication costs at the expense of doing
338: one additional iteration because the norm used in the convergence test of `KSPSolve()` is one iteration behind the actual
339: current residual norm (which has not yet been computed due to the lag).
341: Use `KSPSetNormType`(ksp,`KSP_NORM_NONE`) to never check the norm
343: If you lag the norm and run with, for example, `-ksp_monitor`, the residual norm reported will be the lagged one.
345: `KSPSetCheckNormIteration()` is an alternative way of avoiding the expense of computing the residual norm at each iteration.
347: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSPConvergedSkip()`, `KSPSetNormType()`, `KSPSetCheckNormIteration()`
348: @*/
349: PetscErrorCode KSPSetLagNorm(KSP ksp, PetscBool flg)
350: {
351: PetscFunctionBegin;
354: ksp->lagnorm = flg;
355: PetscFunctionReturn(PETSC_SUCCESS);
356: }
358: /*@
359: KSPSetSupportedNorm - Sets a norm and preconditioner side supported by a `KSPType`
361: Logically Collective
363: Input Parameters:
364: + ksp - Krylov method
365: . normtype - supported norm type of the type `KSPNormType`
366: . pcside - preconditioner side, of the type `PCSide` that can be used with this `KSPNormType`
367: - priority - positive integer preference for this combination; larger values have higher priority
369: Level: developer
371: Notes:
372: This function should be called from the implementation files `KSPCreate_XXX()` to declare
373: which norms and preconditioner sides are supported. Users should not call this
374: function.
376: This function can be called multiple times for each combination of `KSPNormType` and `PCSide`
377: the `KSPType` supports
379: .seealso: [](ch_ksp), `KSP`, `KSPNormType`, `PCSide`, `KSPSetNormType()`, `KSPSetPCSide()`
380: @*/
381: PetscErrorCode KSPSetSupportedNorm(KSP ksp, KSPNormType normtype, PCSide pcside, PetscInt priority)
382: {
383: PetscFunctionBegin;
385: ksp->normsupporttable[normtype][pcside] = priority;
386: PetscFunctionReturn(PETSC_SUCCESS);
387: }
389: static PetscErrorCode KSPNormSupportTableReset_Private(KSP ksp)
390: {
391: PetscFunctionBegin;
392: PetscCall(PetscMemzero(ksp->normsupporttable, sizeof(ksp->normsupporttable)));
393: ksp->pc_side = ksp->pc_side_set;
394: ksp->normtype = ksp->normtype_set;
395: PetscFunctionReturn(PETSC_SUCCESS);
396: }
398: PetscErrorCode KSPSetUpNorms_Private(KSP ksp, PetscBool errorifnotsupported, KSPNormType *normtype, PCSide *pcside)
399: {
400: PetscInt i, j, best, ibest = 0, jbest = 0;
402: PetscFunctionBegin;
403: best = 0;
404: for (i = 0; i < KSP_NORM_MAX; i++) {
405: for (j = 0; j < PC_SIDE_MAX; j++) {
406: if ((ksp->normtype == KSP_NORM_DEFAULT || ksp->normtype == i) && (ksp->pc_side == PC_SIDE_DEFAULT || ksp->pc_side == j) && (ksp->normsupporttable[i][j] > best)) {
407: best = ksp->normsupporttable[i][j];
408: ibest = i;
409: jbest = j;
410: }
411: }
412: }
413: if (best < 1 && errorifnotsupported) {
414: 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);
415: 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]);
416: 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]);
417: 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]);
418: }
419: if (normtype) *normtype = (KSPNormType)ibest;
420: if (pcside) *pcside = (PCSide)jbest;
421: PetscFunctionReturn(PETSC_SUCCESS);
422: }
424: /*@
425: KSPGetNormType - Gets the `KSPNormType` that is used for convergence testing during `KSPSolve()` for this `KSP` context
427: Not Collective
429: Input Parameter:
430: . ksp - Krylov solver context
432: Output Parameter:
433: . normtype - the `KSPNormType` that is used for convergence testing
435: Level: advanced
437: .seealso: [](ch_ksp), `KSPNormType`, `KSPSetNormType()`, `KSPConvergedSkip()`
438: @*/
439: PetscErrorCode KSPGetNormType(KSP ksp, KSPNormType *normtype)
440: {
441: PetscFunctionBegin;
443: PetscAssertPointer(normtype, 2);
444: PetscCall(KSPSetUpNorms_Private(ksp, PETSC_TRUE, &ksp->normtype, &ksp->pc_side));
445: *normtype = ksp->normtype;
446: PetscFunctionReturn(PETSC_SUCCESS);
447: }
449: #if defined(PETSC_HAVE_SAWS)
450: #include <petscviewersaws.h>
451: #endif
453: /*@
454: KSPSetOperators - Sets the matrix associated with the linear system
455: and a (possibly) different one from which the preconditioner will be built into the `KSP` context. The matrix will then be used during `KSPSolve()`
457: Collective
459: Input Parameters:
460: + ksp - the `KSP` context
461: . Amat - the matrix that defines the linear system
462: - Pmat - the matrix to be used in constructing the preconditioner, usually the same as `Amat`.
464: Level: beginner
466: Notes:
467: If you know the operator `Amat` has a null space you can use `MatSetNullSpace()` and `MatSetTransposeNullSpace()` to supply the null
468: space to `Amat` and the `KSP` solvers will automatically use that null space as needed during the solution process.
470: All future calls to `KSPSetOperators()` must use the same size matrices, unless `KSPReset()` is called!
472: Passing a `NULL` for `Amat` or `Pmat` removes the matrix that is currently being used from the `KSP` context.
474: If you wish to replace either `Amat` or `Pmat` but leave the other one untouched then
475: first call `KSPGetOperators()` to get the one you wish to keep, call `PetscObjectReference()`
476: on it and then pass it back in your call to `KSPSetOperators()`.
478: Developer Notes:
479: If the operators have NOT been set with `KSPSetOperators()` then the operators
480: are created in the `PC` and returned to the user. In this case, if both operators
481: mat and pmat are requested, two DIFFERENT operators will be returned. If
482: only one is requested both operators in the `PC` will be the same (i.e. as
483: if one had called `KSPSetOperators()` with the same argument for both `Mat`s).
484: The user must set the sizes of the returned matrices and their type etc just
485: as if the user created them with `MatCreate()`. For example,
487: .vb
488: KSPGetOperators(ksp/pc,&mat,NULL); is equivalent to
489: set size, type, etc of mat
491: MatCreate(comm,&mat);
492: KSP/PCSetOperators(ksp/pc,mat,mat);
493: PetscObjectDereference((PetscObject)mat);
494: set size, type, etc of mat
496: and
498: KSP/PCGetOperators(ksp/pc,&mat,&pmat); is equivalent to
499: set size, type, etc of mat and pmat
501: MatCreate(comm,&mat);
502: MatCreate(comm,&pmat);
503: KSP/PCSetOperators(ksp/pc,mat,pmat);
504: PetscObjectDereference((PetscObject)mat);
505: PetscObjectDereference((PetscObject)pmat);
506: set size, type, etc of mat and pmat
507: .ve
509: The rationale for this support is so that when creating a `TS`, `SNES`, or `KSP` the hierarchy
510: of underlying objects (i.e. `SNES`, `KSP`, `PC`, `Mat`) and their lifespans can be completely
511: managed by the top most level object (i.e. the `TS`, `SNES`, or `KSP`). Another way to look
512: at this is when you create a `SNES` you do not NEED to create a `KSP` and attach it to
513: the `SNES` object (the `SNES` object manages it for you). Similarly when you create a `KSP`
514: you do not need to attach a `PC` to it (the `KSP` object manages the `PC` object for you).
515: Thus, why should YOU have to create the `Mat` and attach it to the `SNES`/`KSP`/`PC`, when
516: it can be created for you?
518: .seealso: [](ch_ksp), `KSP`, `Mat`, `KSPSolve()`, `KSPGetPC()`, `PCGetOperators()`, `PCSetOperators()`, `KSPGetOperators()`, `KSPSetComputeOperators()`, `KSPSetComputeInitialGuess()`, `KSPSetComputeRHS()`
519: @*/
520: PetscErrorCode KSPSetOperators(KSP ksp, Mat Amat, Mat Pmat)
521: {
522: PetscFunctionBegin;
526: if (Amat) PetscCheckSameComm(ksp, 1, Amat, 2);
527: if (Pmat) PetscCheckSameComm(ksp, 1, Pmat, 3);
528: if (!ksp->pc) PetscCall(KSPGetPC(ksp, &ksp->pc));
529: PetscCall(PCSetOperators(ksp->pc, Amat, Pmat));
530: if (ksp->setupstage == KSP_SETUP_NEWRHS) ksp->setupstage = KSP_SETUP_NEWMATRIX; /* so that next solve call will call PCSetUp() on new matrix */
531: PetscFunctionReturn(PETSC_SUCCESS);
532: }
534: /*@
535: KSPGetOperators - Gets the matrix associated with the linear system
536: and a (possibly) different one used to construct the preconditioner from the `KSP` context
538: Collective
540: Input Parameter:
541: . ksp - the `KSP` context
543: Output Parameters:
544: + Amat - the matrix that defines the linear system
545: - Pmat - the matrix to be used in constructing the preconditioner, usually the same as `Amat`.
547: Level: intermediate
549: Notes:
550: If `KSPSetOperators()` has not been called then the `KSP` object will attempt to automatically create the matrix `Amat` and return it
552: Use `KSPGetOperatorsSet()` to determine if matrices have been provided.
554: DOES NOT increase the reference counts of the matrix, so you should NOT destroy them.
556: .seealso: [](ch_ksp), `KSP`, `KSPSolve()`, `KSPGetPC()`, `PCSetOperators()`, `KSPSetOperators()`, `KSPGetOperatorsSet()`
557: @*/
558: PetscErrorCode KSPGetOperators(KSP ksp, Mat *Amat, Mat *Pmat)
559: {
560: PetscFunctionBegin;
562: if (!ksp->pc) PetscCall(KSPGetPC(ksp, &ksp->pc));
563: PetscCall(PCGetOperators(ksp->pc, Amat, Pmat));
564: PetscFunctionReturn(PETSC_SUCCESS);
565: }
567: /*@
568: KSPGetOperatorsSet - Determines if the matrix associated with the linear system and
569: possibly a different one from which the preconditioner will be built have been set in the `KSP` with `KSPSetOperators()`
571: Not Collective, though the results on all processes will be the same
573: Input Parameter:
574: . ksp - the `KSP` context
576: Output Parameters:
577: + mat - the matrix associated with the linear system was set
578: - pmat - matrix from which the preconditioner will be built, usually the same as `mat` was set
580: Level: intermediate
582: Note:
583: This routine exists because if you call `KSPGetOperators()` on a `KSP` that does not yet have operators they are
584: automatically created in the call.
586: .seealso: [](ch_ksp), `KSP`, `PCSetOperators()`, `KSPGetOperators()`, `KSPSetOperators()`, `PCGetOperators()`, `PCGetOperatorsSet()`
587: @*/
588: PetscErrorCode KSPGetOperatorsSet(KSP ksp, PetscBool *mat, PetscBool *pmat)
589: {
590: PetscFunctionBegin;
592: if (!ksp->pc) PetscCall(KSPGetPC(ksp, &ksp->pc));
593: PetscCall(PCGetOperatorsSet(ksp->pc, mat, pmat));
594: PetscFunctionReturn(PETSC_SUCCESS);
595: }
597: /*@C
598: KSPSetPreSolve - Sets a function that is called at the beginning of each `KSPSolve()`. Used in conjunction with `KSPSetPostSolve()`.
600: Logically Collective
602: Input Parameters:
603: + ksp - the solver object
604: . presolve - the function to call before the solve
605: - ctx - an optional context needed by the function
607: Calling sequence of `presolve`:
608: + ksp - the `KSP` context
609: . rhs - the right-hand side vector
610: . x - the solution vector
611: - ctx - optional user-provided context
613: Level: developer
615: Notes:
616: The function provided here `presolve` is used to modify the right hand side, and possibly the matrix, of the linear system to be solved.
617: The function provided with `KSPSetPostSolve()` then modifies the resulting solution of that linear system to obtain the correct solution
618: to the initial linear system.
620: The functions `PCPreSolve()` and `PCPostSolve()` provide a similar functionality and are used, for example with `PCEISENSTAT`.
622: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPSetPostSolve()`, `PCEISENSTAT`, `PCPreSolve()`, `PCPostSolve()`
623: @*/
624: PetscErrorCode KSPSetPreSolve(KSP ksp, PetscErrorCode (*presolve)(KSP ksp, Vec rhs, Vec x, void *ctx), void *ctx)
625: {
626: PetscFunctionBegin;
628: ksp->presolve = presolve;
629: ksp->prectx = ctx;
630: PetscFunctionReturn(PETSC_SUCCESS);
631: }
633: /*@C
634: KSPSetPostSolve - Sets a function that is called at the end of each `KSPSolve()` (whether it converges or not). Used in conjunction with `KSPSetPreSolve()`.
636: Logically Collective
638: Input Parameters:
639: + ksp - the solver object
640: . postsolve - the function to call after the solve
641: - ctx - an optional context needed by the function
643: Calling sequence of `postsolve`:
644: + ksp - the `KSP` context
645: . rhs - the right-hand side vector
646: . x - the solution vector
647: - ctx - optional user-provided context
649: Level: developer
651: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPSetPreSolve()`, `PCEISENSTAT`
652: @*/
653: PetscErrorCode KSPSetPostSolve(KSP ksp, PetscErrorCode (*postsolve)(KSP ksp, Vec rhs, Vec x, void *ctx), void *ctx)
654: {
655: PetscFunctionBegin;
657: ksp->postsolve = postsolve;
658: ksp->postctx = ctx;
659: PetscFunctionReturn(PETSC_SUCCESS);
660: }
662: /*@
663: KSPSetNestLevel - sets the amount of nesting the `KSP` has. That is the number of levels of `KSP` above this `KSP` in a linear solve.
665: Collective
667: Input Parameters:
668: + ksp - the `KSP`
669: - level - the nest level
671: Level: developer
673: Note:
674: For example, the `KSP` in each block of a `KSPBJACOBI` has a level of 1, while the outer `KSP` has a level of 0.
676: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPGMRES`, `KSPType`, `KSPGetNestLevel()`, `PCSetKSPNestLevel()`, `PCGetKSPNestLevel()`
677: @*/
678: PetscErrorCode KSPSetNestLevel(KSP ksp, PetscInt level)
679: {
680: PetscFunctionBegin;
683: ksp->nestlevel = level;
684: PetscFunctionReturn(PETSC_SUCCESS);
685: }
687: /*@
688: KSPGetNestLevel - gets the amount of nesting the `KSP` has
690: Not Collective
692: Input Parameter:
693: . ksp - the `KSP`
695: Output Parameter:
696: . level - the nest level
698: Level: developer
700: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPGMRES`, `KSPType`, `KSPSetNestLevel()`, `PCSetKSPNestLevel()`, `PCGetKSPNestLevel()`
701: @*/
702: PetscErrorCode KSPGetNestLevel(KSP ksp, PetscInt *level)
703: {
704: PetscFunctionBegin;
706: PetscAssertPointer(level, 2);
707: *level = ksp->nestlevel;
708: PetscFunctionReturn(PETSC_SUCCESS);
709: }
711: /*@
712: KSPCreate - Creates the `KSP` context. This `KSP` context is used in PETSc to solve linear systems with `KSPSolve()`
714: Collective
716: Input Parameter:
717: . comm - MPI communicator
719: Output Parameter:
720: . inksp - location to put the `KSP` context
722: Level: beginner
724: Note:
725: The default `KSPType` is `KSPGMRES` with a restart of 30, using modified Gram-Schmidt orthogonalization. The `KSPType` may be
726: changed with `KSPSetType()`
728: .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPGMRES`, `KSPType`, `KSPSetType()`
729: @*/
730: PetscErrorCode KSPCreate(MPI_Comm comm, KSP *inksp)
731: {
732: KSP ksp;
733: void *ctx;
735: PetscFunctionBegin;
736: PetscAssertPointer(inksp, 2);
737: PetscCall(KSPInitializePackage());
739: PetscCall(PetscHeaderCreate(ksp, KSP_CLASSID, "KSP", "Krylov Method", "KSP", comm, KSPDestroy, KSPView));
740: ksp->default_max_it = ksp->max_it = 10000;
741: ksp->pc_side = ksp->pc_side_set = PC_SIDE_DEFAULT;
743: ksp->default_rtol = ksp->rtol = 1.e-5;
744: ksp->default_abstol = ksp->abstol = PetscDefined(USE_REAL_SINGLE) ? 1.e-25 : 1.e-50;
745: ksp->default_divtol = ksp->divtol = 1.e4;
747: ksp->chknorm = -1;
748: ksp->normtype = ksp->normtype_set = KSP_NORM_DEFAULT;
749: ksp->rnorm = 0.0;
750: ksp->its = 0;
751: ksp->guess_zero = PETSC_TRUE;
752: ksp->calc_sings = PETSC_FALSE;
753: ksp->res_hist = NULL;
754: ksp->res_hist_alloc = NULL;
755: ksp->res_hist_len = 0;
756: ksp->res_hist_max = 0;
757: ksp->res_hist_reset = PETSC_TRUE;
758: ksp->err_hist = NULL;
759: ksp->err_hist_alloc = NULL;
760: ksp->err_hist_len = 0;
761: ksp->err_hist_max = 0;
762: ksp->err_hist_reset = PETSC_TRUE;
763: ksp->numbermonitors = 0;
764: ksp->numberreasonviews = 0;
765: ksp->setfromoptionscalled = 0;
766: ksp->nmax = PETSC_DECIDE;
768: PetscCall(KSPConvergedDefaultCreate(&ctx));
769: PetscCall(KSPSetConvergenceTest(ksp, KSPConvergedDefault, ctx, KSPConvergedDefaultDestroy));
770: ksp->ops->buildsolution = KSPBuildSolutionDefault;
771: ksp->ops->buildresidual = KSPBuildResidualDefault;
773: ksp->vec_sol = NULL;
774: ksp->vec_rhs = NULL;
775: ksp->pc = NULL;
776: ksp->data = NULL;
777: ksp->nwork = 0;
778: ksp->work = NULL;
779: ksp->reason = KSP_CONVERGED_ITERATING;
780: ksp->setupstage = KSP_SETUP_NEW;
782: PetscCall(KSPNormSupportTableReset_Private(ksp));
784: *inksp = ksp;
785: PetscFunctionReturn(PETSC_SUCCESS);
786: }
788: /*@
789: KSPSetType - Sets the algorithm/method to be used to solve the linear system with the given `KSP`
791: Logically Collective
793: Input Parameters:
794: + ksp - the Krylov space context
795: - type - a known method
797: Options Database Key:
798: . -ksp_type <method> - Sets the method; use `-help` for a list of available methods (for instance, cg or gmres)
800: Level: intermediate
802: Notes:
803: See `KSPType` for available methods (for instance, `KSPCG` or `KSPGMRES`).
805: Normally, it is best to use the `KSPSetFromOptions()` command and
806: then set the `KSP` type from the options database rather than by using
807: this routine. Using the options database provides the user with
808: maximum flexibility in evaluating the many different Krylov methods.
809: The `KSPSetType()` routine is provided for those situations where it
810: is necessary to set the iterative solver independently of the command
811: line or options database. This might be the case, for example, when
812: the choice of iterative solver changes during the execution of the
813: program, and the user's application is taking responsibility for
814: choosing the appropriate method. In other words, this routine is
815: not for beginners.
817: Developer Note:
818: `KSPRegister()` is used to add Krylov types to `KSPList` from which they are accessed by `KSPSetType()`.
820: .seealso: [](ch_ksp), `PCSetType()`, `KSPType`, `KSPRegister()`, `KSPCreate()`, `KSP`
821: @*/
822: PetscErrorCode KSPSetType(KSP ksp, KSPType type)
823: {
824: PetscBool match;
825: PetscErrorCode (*r)(KSP);
827: PetscFunctionBegin;
829: PetscAssertPointer(type, 2);
831: PetscCall(PetscObjectTypeCompare((PetscObject)ksp, type, &match));
832: if (match) PetscFunctionReturn(PETSC_SUCCESS);
834: PetscCall(PetscFunctionListFind(KSPList, type, &r));
835: PetscCheck(r, PetscObjectComm((PetscObject)ksp), PETSC_ERR_ARG_UNKNOWN_TYPE, "Unable to find requested KSP type %s", type);
836: /* Destroy the previous private KSP context */
837: PetscTryTypeMethod(ksp, destroy);
839: /* Reinitialize function pointers in KSPOps structure */
840: PetscCall(PetscMemzero(ksp->ops, sizeof(struct _KSPOps)));
841: ksp->ops->buildsolution = KSPBuildSolutionDefault;
842: ksp->ops->buildresidual = KSPBuildResidualDefault;
843: PetscCall(KSPNormSupportTableReset_Private(ksp));
844: ksp->converged_neg_curve = PETSC_FALSE; // restore default
845: ksp->setupnewmatrix = PETSC_FALSE; // restore default (setup not called in case of new matrix)
846: /* Call the KSPCreate_XXX routine for this particular Krylov solver */
847: ksp->setupstage = KSP_SETUP_NEW;
848: ksp->guess_not_read = PETSC_FALSE; // restore default
849: PetscCall((*r)(ksp));
850: PetscCall(PetscObjectChangeTypeName((PetscObject)ksp, type));
851: PetscFunctionReturn(PETSC_SUCCESS);
852: }
854: /*@
855: KSPGetType - Gets the `KSP` type as a string from the `KSP` object.
857: Not Collective
859: Input Parameter:
860: . ksp - Krylov context
862: Output Parameter:
863: . type - name of the `KSP` method
865: Level: intermediate
867: .seealso: [](ch_ksp), `KSPType`, `KSP`, `KSPSetType()`
868: @*/
869: PetscErrorCode KSPGetType(KSP ksp, KSPType *type)
870: {
871: PetscFunctionBegin;
873: PetscAssertPointer(type, 2);
874: *type = ((PetscObject)ksp)->type_name;
875: PetscFunctionReturn(PETSC_SUCCESS);
876: }
878: /*@C
879: KSPRegister - Adds a method, `KSPType`, to the Krylov subspace solver package.
881: Not Collective, No Fortran Support
883: Input Parameters:
884: + sname - name of a new user-defined solver
885: - function - routine to create method
887: Level: advanced
889: Note:
890: `KSPRegister()` may be called multiple times to add several user-defined solvers.
892: Example Usage:
893: .vb
894: KSPRegister("my_solver", MySolverCreate);
895: .ve
897: Then, your solver can be chosen with the procedural interface via
898: .vb
899: KSPSetType(ksp, "my_solver")
900: .ve
901: or at runtime via the option `-ksp_type my_solver`
903: .seealso: [](ch_ksp), `KSP`, `KSPType`, `KSPSetType`, `KSPRegisterAll()`
904: @*/
905: PetscErrorCode KSPRegister(const char sname[], PetscErrorCode (*function)(KSP))
906: {
907: PetscFunctionBegin;
908: PetscCall(KSPInitializePackage());
909: PetscCall(PetscFunctionListAdd(&KSPList, sname, function));
910: PetscFunctionReturn(PETSC_SUCCESS);
911: }
913: PetscErrorCode KSPMonitorMakeKey_Internal(const char name[], PetscViewerType vtype, PetscViewerFormat format, char key[])
914: {
915: PetscFunctionBegin;
916: PetscCall(PetscStrncpy(key, name, PETSC_MAX_PATH_LEN));
917: PetscCall(PetscStrlcat(key, ":", PETSC_MAX_PATH_LEN));
918: PetscCall(PetscStrlcat(key, vtype, PETSC_MAX_PATH_LEN));
919: PetscCall(PetscStrlcat(key, ":", PETSC_MAX_PATH_LEN));
920: PetscCall(PetscStrlcat(key, PetscViewerFormats[format], PETSC_MAX_PATH_LEN));
921: PetscFunctionReturn(PETSC_SUCCESS);
922: }
924: /*@C
925: KSPMonitorRegister - Registers a Krylov subspace solver monitor routine that may be accessed with `KSPMonitorSetFromOptions()`
927: Not Collective
929: Input Parameters:
930: + name - name of a new monitor routine
931: . vtype - A `PetscViewerType` for the output
932: . format - A `PetscViewerFormat` for the output
933: . monitor - Monitor routine
934: . create - Creation routine, or `NULL`
935: - destroy - Destruction routine, or `NULL`
937: Level: advanced
939: Note:
940: `KSPMonitorRegister()` may be called multiple times to add several user-defined monitors.
942: Example Usage:
943: .vb
944: KSPMonitorRegister("my_monitor", PETSCVIEWERASCII, PETSC_VIEWER_ASCII_INFO_DETAIL, MyMonitor, NULL, NULL);
945: .ve
947: Then, your monitor can be chosen with the procedural interface via
948: .vb
949: KSPMonitorSetFromOptions(ksp, "-ksp_monitor_my_monitor", "my_monitor", NULL)
950: .ve
951: or at runtime via the option `-ksp_monitor_my_monitor`
953: .seealso: [](ch_ksp), `KSP`, `KSPMonitorSet()`, `KSPMonitorRegisterAll()`, `KSPMonitorSetFromOptions()`
954: @*/
955: PetscErrorCode KSPMonitorRegister(const char name[], PetscViewerType vtype, PetscViewerFormat format, PetscErrorCode (*monitor)(KSP, PetscInt, PetscReal, PetscViewerAndFormat *), PetscErrorCode (*create)(PetscViewer, PetscViewerFormat, void *, PetscViewerAndFormat **), PetscErrorCode (*destroy)(PetscViewerAndFormat **))
956: {
957: char key[PETSC_MAX_PATH_LEN];
959: PetscFunctionBegin;
960: PetscCall(KSPInitializePackage());
961: PetscCall(KSPMonitorMakeKey_Internal(name, vtype, format, key));
962: PetscCall(PetscFunctionListAdd(&KSPMonitorList, key, monitor));
963: if (create) PetscCall(PetscFunctionListAdd(&KSPMonitorCreateList, key, create));
964: if (destroy) PetscCall(PetscFunctionListAdd(&KSPMonitorDestroyList, key, destroy));
965: PetscFunctionReturn(PETSC_SUCCESS);
966: }