Actual source code: petscksp.h
1: /*
2: Defines the interface functions for the Krylov subspace accelerators.
3: */
4: #pragma once
6: #include <petscpc.h>
8: /* SUBMANSEC = KSP */
10: PETSC_EXTERN PetscErrorCode KSPInitializePackage(void);
11: PETSC_EXTERN PetscErrorCode KSPFinalizePackage(void);
13: /*S
14: KSP - Abstract PETSc object that manages the linear solves in PETSc (even those such as direct factorization-based solvers that
15: do not use Krylov accelerators).
17: Level: beginner
19: Notes:
20: When a direct solver is used, but no Krylov solver is used, the `KSP` object is still used but with a
21: `KSPType` of `KSPPREONLY` (or equivalently `KSPNONE`), meaning that only application of the preconditioner is used as the linear solver.
23: Use `KSPSetType()` or the options database key `-ksp_type` to set the specific Krylov solver algorithm to use with a given `KSP` object
25: The `PC` object is used to control preconditioners in PETSc.
27: `KSP` can also be used to solve some least squares problems (over or under-determined linear systems), using, for example, `KSPLSQR`, see `PETSCREGRESSORLINEAR`
28: for additional methods that can be used to solve least squares problems and other linear regressions).
30: .seealso: [](doc_linsolve), [](ch_ksp), `KSPCreate()`, `KSPSetType()`, `KSPType`, `SNES`, `TS`, `PC`, `KSP`, `KSPDestroy()`, `KSPCG`, `KSPGMRES`
31: S*/
32: typedef struct _p_KSP *KSP;
34: /*J
35: KSPType - String with the name of a PETSc Krylov method. These are all the Krylov solvers that PETSc provides.
37: Level: beginner
39: .seealso: [](doc_linsolve), [](ch_ksp), `KSPSetType()`, `KSP`, `KSPRegister()`, `KSPCreate()`, `KSPSetFromOptions()`
40: J*/
41: typedef const char *KSPType;
42: #define KSPRICHARDSON "richardson"
43: #define KSPCHEBYSHEV "chebyshev"
44: #define KSPCG "cg"
45: #define KSPGROPPCG "groppcg"
46: #define KSPPIPECG "pipecg"
47: #define KSPPIPECGRR "pipecgrr"
48: #define KSPPIPELCG "pipelcg"
49: #define KSPPIPEPRCG "pipeprcg"
50: #define KSPPIPECG2 "pipecg2"
51: #define KSPCGNE "cgne"
52: #define KSPNASH "nash"
53: #define KSPSTCG "stcg"
54: #define KSPGLTR "gltr"
55: #define KSPCGNASH PETSC_DEPRECATED_MACRO(3, 11, 0, "KSPNASH", ) "nash"
56: #define KSPCGSTCG PETSC_DEPRECATED_MACRO(3, 11, 0, "KSPSTCG", ) "stcg"
57: #define KSPCGGLTR PETSC_DEPRECATED_MACRO(3, 11, 0, "KSPSGLTR", ) "gltr"
58: #define KSPFCG "fcg"
59: #define KSPPIPEFCG "pipefcg"
60: #define KSPGMRES "gmres"
61: #define KSPPIPEFGMRES "pipefgmres"
62: #define KSPFGMRES "fgmres"
63: #define KSPLGMRES "lgmres"
64: #define KSPDGMRES "dgmres"
65: #define KSPPGMRES "pgmres"
66: #define KSPTCQMR "tcqmr"
67: #define KSPBCGS "bcgs"
68: #define KSPIBCGS "ibcgs"
69: #define KSPQMRCGS "qmrcgs"
70: #define KSPFBCGS "fbcgs"
71: #define KSPFBCGSR "fbcgsr"
72: #define KSPBCGSL "bcgsl"
73: #define KSPPIPEBCGS "pipebcgs"
74: #define KSPCGS "cgs"
75: #define KSPTFQMR "tfqmr"
76: #define KSPCR "cr"
77: #define KSPPIPECR "pipecr"
78: #define KSPLSQR "lsqr"
79: #define KSPPREONLY "preonly"
80: #define KSPNONE "none"
81: #define KSPQCG "qcg"
82: #define KSPBICG "bicg"
83: #define KSPMINRES "minres"
84: #define KSPSYMMLQ "symmlq"
85: #define KSPLCD "lcd"
86: #define KSPPYTHON "python"
87: #define KSPGCR "gcr"
88: #define KSPPIPEGCR "pipegcr"
89: #define KSPTSIRM "tsirm"
90: #define KSPCGLS "cgls"
91: #define KSPFETIDP "fetidp"
92: #define KSPHPDDM "hpddm"
93: #define KSPIDR "idr"
94: #define KSPEKSM "eksm"
96: /* Logging support */
97: PETSC_EXTERN PetscClassId KSP_CLASSID;
98: PETSC_EXTERN PetscClassId KSPGUESS_CLASSID;
99: PETSC_EXTERN PetscClassId DMKSP_CLASSID;
101: PETSC_EXTERN PetscErrorCode KSPCreate(MPI_Comm, KSP *);
102: PETSC_EXTERN PetscErrorCode KSPSetType(KSP, KSPType);
103: PETSC_EXTERN PetscErrorCode KSPGetType(KSP, KSPType *);
104: PETSC_EXTERN PetscErrorCode KSPSetUp(KSP);
105: PETSC_EXTERN PetscErrorCode KSPSetUpOnBlocks(KSP);
106: PETSC_EXTERN PetscErrorCode KSPSolve(KSP, Vec, Vec);
107: PETSC_EXTERN PetscErrorCode KSPSolveTranspose(KSP, Vec, Vec);
108: PETSC_EXTERN PetscErrorCode KSPSetUseExplicitTranspose(KSP, PetscBool);
109: PETSC_EXTERN PetscErrorCode KSPMatSolve(KSP, Mat, Mat);
110: PETSC_EXTERN PetscErrorCode KSPMatSolveTranspose(KSP, Mat, Mat);
111: PETSC_EXTERN PetscErrorCode KSPSetMatSolveBatchSize(KSP, PetscInt);
112: PETSC_DEPRECATED_FUNCTION(3, 15, 0, "KSPSetMatSolveBatchSize()", ) static inline PetscErrorCode KSPSetMatSolveBlockSize(KSP ksp, PetscInt n)
113: {
114: return KSPSetMatSolveBatchSize(ksp, n);
115: }
116: PETSC_EXTERN PetscErrorCode KSPGetMatSolveBatchSize(KSP, PetscInt *);
117: PETSC_DEPRECATED_FUNCTION(3, 15, 0, "KSPGetMatSolveBatchSize()", ) static inline PetscErrorCode KSPGetMatSolveBlockSize(KSP ksp, PetscInt *n)
118: {
119: return KSPGetMatSolveBatchSize(ksp, n);
120: }
121: PETSC_EXTERN PetscErrorCode KSPReset(KSP);
122: PETSC_EXTERN PetscErrorCode KSPResetViewers(KSP);
123: PETSC_EXTERN PetscErrorCode KSPDestroy(KSP *);
124: PETSC_EXTERN PetscErrorCode KSPSetReusePreconditioner(KSP, PetscBool);
125: PETSC_EXTERN PetscErrorCode KSPGetReusePreconditioner(KSP, PetscBool *);
126: PETSC_EXTERN PetscErrorCode KSPSetSkipPCSetFromOptions(KSP, PetscBool);
127: PETSC_EXTERN PetscErrorCode KSPCheckSolve(KSP, PC, Vec);
128: PETSC_EXTERN PetscErrorCode KSPCheckMatSolve(KSP, PC, Mat);
130: PETSC_EXTERN PetscFunctionList KSPList;
131: PETSC_EXTERN PetscFunctionList KSPGuessList;
132: PETSC_EXTERN PetscFunctionList KSPMonitorList;
133: PETSC_EXTERN PetscFunctionList KSPMonitorCreateList;
134: PETSC_EXTERN PetscFunctionList KSPMonitorDestroyList;
135: PETSC_EXTERN PetscErrorCode KSPRegister(const char[], PetscErrorCode (*)(KSP));
137: /*S
138: KSPMonitorRegisterFn - A function prototype for functions provided to `KSPMonitorRegister()`
140: Calling Sequence:
141: + ksp - iterative solver obtained from `KSPCreate()`
142: . it - iteration number
143: . rnorm - (estimated) 2-norm of (preconditioned) residual
144: - ctx - `PetscViewerAndFormat` object
146: Level: beginner
148: Note:
149: This is a `KSPMonitorFn` specialized for a context of `PetscViewerAndFormat`
151: .seealso: [](ch_snes), `KSP`, `KSPMonitorSet()`, `KSPMonitorRegister()`, `KSPMonitorFn`, `KSPMonitorRegisterCreateFn`, `KSPMonitorRegisterDestroyFn`
152: S*/
153: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPMonitorRegisterFn(KSP ksp, PetscInt it, PetscReal rnorm, PetscViewerAndFormat *ctx);
155: /*S
156: KSPMonitorRegisterCreateFn - A function prototype for functions that do the creation when provided to `KSPMonitorRegister()`
158: Calling Sequence:
159: + viewer - the viewer to be used with the `KSPMonitorRegisterFn`
160: . format - the format of the viewer
161: . ctx - a context for the monitor
162: - result - a `PetscViewerAndFormat` object
164: Level: beginner
166: .seealso: [](ch_snes), `KSPMonitorRegisterFn`, `KSP`, `KSPMonitorSet()`, `KSPMonitorRegister()`, `KSPMonitorFn`, `KSPMonitorRegisterDestroyFn`
167: S*/
168: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPMonitorRegisterCreateFn(PetscViewer viewer, PetscViewerFormat format, PetscCtx ctx, PetscViewerAndFormat **result);
170: /*S
171: KSPMonitorRegisterDestroyFn - A function prototype for functions that do the after use destruction when provided to `KSPMonitorRegister()`
173: Calling Sequence:
174: . vf - a `PetscViewerAndFormat` object to be destroyed, including any context
176: Level: beginner
178: .seealso: [](ch_snes), `KSPMonitorRegisterFn`, `KSP`, `KSPMonitorSet()`, `KSPMonitorRegister()`, `KSPMonitorFn`, `KSPMonitorRegisterCreateFn`
179: S*/
180: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPMonitorRegisterDestroyFn(PetscViewerAndFormat **result);
182: PETSC_EXTERN PetscErrorCode KSPMonitorRegister(const char[], PetscViewerType, PetscViewerFormat, KSPMonitorRegisterFn *, KSPMonitorRegisterCreateFn *, KSPMonitorRegisterDestroyFn *);
184: PETSC_EXTERN PetscErrorCode KSPSetPCSide(KSP, PCSide);
185: PETSC_EXTERN PetscErrorCode KSPGetPCSide(KSP, PCSide *);
186: PETSC_EXTERN PetscErrorCode KSPSetTolerances(KSP, PetscReal, PetscReal, PetscReal, PetscInt);
187: PETSC_EXTERN PetscErrorCode KSPGetTolerances(KSP, PetscReal *, PetscReal *, PetscReal *, PetscInt *);
188: PETSC_EXTERN PetscErrorCode KSPSetMinimumIterations(KSP, PetscInt);
189: PETSC_EXTERN PetscErrorCode KSPGetMinimumIterations(KSP, PetscInt *);
190: PETSC_EXTERN PetscErrorCode KSPSetInitialGuessNonzero(KSP, PetscBool);
191: PETSC_EXTERN PetscErrorCode KSPGetInitialGuessNonzero(KSP, PetscBool *);
192: PETSC_EXTERN PetscErrorCode KSPSetErrorIfNotConverged(KSP, PetscBool);
193: PETSC_EXTERN PetscErrorCode KSPGetErrorIfNotConverged(KSP, PetscBool *);
194: PETSC_EXTERN PetscErrorCode KSPSetComputeEigenvalues(KSP, PetscBool);
195: PETSC_EXTERN PetscErrorCode KSPSetComputeRitz(KSP, PetscBool);
196: PETSC_EXTERN PetscErrorCode KSPGetComputeEigenvalues(KSP, PetscBool *);
197: PETSC_EXTERN PetscErrorCode KSPSetComputeSingularValues(KSP, PetscBool);
198: PETSC_EXTERN PetscErrorCode KSPGetComputeSingularValues(KSP, PetscBool *);
199: PETSC_EXTERN PetscErrorCode KSPGetRhs(KSP, Vec *);
200: PETSC_EXTERN PetscErrorCode KSPGetSolution(KSP, Vec *);
201: PETSC_EXTERN PetscErrorCode KSPGetResidualNorm(KSP, PetscReal *);
202: PETSC_EXTERN PetscErrorCode KSPGetIterationNumber(KSP, PetscInt *);
203: PETSC_EXTERN PetscErrorCode KSPGetTotalIterations(KSP, PetscInt *);
204: PETSC_EXTERN PetscErrorCode KSPCreateVecs(KSP, PetscInt, Vec **, PetscInt, Vec **);
205: PETSC_DEPRECATED_FUNCTION(3, 6, 0, "KSPCreateVecs()", ) static inline PetscErrorCode KSPGetVecs(KSP ksp, PetscInt n, Vec **x, PetscInt m, Vec **y)
206: {
207: return KSPCreateVecs(ksp, n, x, m, y);
208: }
210: /*S
211: KSPPSolveFn - A function prototype for functions provided to `KSPSetPreSolve()` and `KSPSetPostSolve()`
213: Calling Sequence:
214: + ksp - the `KSP` context
215: . rhs - the right-hand side vector
216: . x - the solution vector
217: - ctx - optional context that was provided with `KSPSetPreSolve()` or `KSPSetPostSolve()`
219: Level: intermediate
221: .seealso: [](ch_snes), `KSP`, `KSPSetPreSolve()`, `KSPSetPostSolve()`, `PCShellPSolveFn`
222: S*/
223: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPPSolveFn(KSP ksp, Vec rhs, Vec x, PetscCtx ctx);
225: PETSC_EXTERN PetscErrorCode KSPSetPreSolve(KSP, KSPPSolveFn *, PetscCtx);
226: PETSC_EXTERN PetscErrorCode KSPSetPostSolve(KSP, KSPPSolveFn *, PetscCtx);
227: PETSC_EXTERN PetscErrorCode KSPPreSolve(KSP, Vec, Vec);
228: PETSC_EXTERN PetscErrorCode KSPPostSolve(KSP, Vec, Vec);
230: PETSC_EXTERN PetscErrorCode KSPSetPC(KSP, PC);
231: PETSC_EXTERN PetscErrorCode KSPGetPC(KSP, PC *);
232: PETSC_EXTERN PetscErrorCode KSPSetNestLevel(KSP, PetscInt);
233: PETSC_EXTERN PetscErrorCode KSPGetNestLevel(KSP, PetscInt *);
235: /*S
236: KSPMonitorFn - A function prototype for functions provided to `KSPMonitorSet()`
238: Calling Sequence:
239: + ksp - iterative solver obtained from `KSPCreate()`
240: . it - iteration number
241: . rnorm - (estimated) 2-norm of (preconditioned) residual
242: - ctx - optional monitoring context, as provided with `KSPMonitorSet()`
244: Level: beginner
246: .seealso: [](ch_snes), `KSP`, `KSPMonitorSet()`
247: S*/
248: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPMonitorFn(KSP ksp, PetscInt it, PetscReal rnorm, PetscCtx ctx);
250: PETSC_EXTERN PetscErrorCode KSPMonitor(KSP, PetscInt, PetscReal);
251: PETSC_EXTERN PetscErrorCode KSPMonitorSet(KSP, KSPMonitorFn *, PetscCtx, PetscCtxDestroyFn *);
252: PETSC_EXTERN PetscErrorCode KSPMonitorCancel(KSP);
253: PETSC_EXTERN PetscErrorCode KSPGetMonitorContext(KSP, PetscCtxRt);
254: PETSC_EXTERN PetscErrorCode KSPGetResidualHistory(KSP, const PetscReal *[], PetscInt *);
255: PETSC_EXTERN PetscErrorCode KSPSetResidualHistory(KSP, PetscReal[], PetscCount, PetscBool);
256: PETSC_EXTERN PetscErrorCode KSPGetErrorHistory(KSP, const PetscReal *[], PetscInt *);
257: PETSC_EXTERN PetscErrorCode KSPSetErrorHistory(KSP, PetscReal[], PetscCount, PetscBool);
259: PETSC_EXTERN PetscErrorCode KSPBuildSolutionDefault(KSP, Vec, Vec *);
260: PETSC_EXTERN PetscErrorCode KSPBuildSolutionFlexibleDefault(KSP, Vec, Vec *);
261: PETSC_EXTERN PetscErrorCode KSPBuildResidualDefault(KSP, Vec, Vec, Vec *);
262: PETSC_EXTERN PetscErrorCode KSPDestroyDefault(KSP);
263: PETSC_EXTERN PetscErrorCode KSPSetWorkVecs(KSP, PetscInt);
265: PETSC_EXTERN PetscErrorCode PCKSPGetKSP(PC, KSP *);
266: PETSC_EXTERN PetscErrorCode PCKSPSetKSP(PC, KSP);
267: PETSC_EXTERN PetscErrorCode PCBJacobiGetSubKSP(PC, PetscInt *, PetscInt *, KSP *[]);
268: PETSC_EXTERN PetscErrorCode PCASMGetSubKSP(PC, PetscInt *, PetscInt *, KSP *[]);
269: PETSC_EXTERN PetscErrorCode PCGASMGetSubKSP(PC, PetscInt *, PetscInt *, KSP *[]);
270: PETSC_EXTERN PetscErrorCode PCPatchGetSubKSP(PC, PetscInt *, KSP *[]);
271: PETSC_EXTERN PetscErrorCode PCFieldSplitGetSubKSP(PC, PetscInt *, KSP *[]);
272: PETSC_EXTERN PetscErrorCode PCFieldSplitSchurGetSubKSP(PC, PetscInt *, KSP *[]);
273: PETSC_EXTERN PetscErrorCode PCMGGetSmoother(PC, PetscInt, KSP *);
274: PETSC_EXTERN PetscErrorCode PCMGGetSmootherDown(PC, PetscInt, KSP *);
275: PETSC_EXTERN PetscErrorCode PCMGGetSmootherUp(PC, PetscInt, KSP *);
276: PETSC_EXTERN PetscErrorCode PCMGGetCoarseSolve(PC, KSP *);
277: PETSC_EXTERN PetscErrorCode PCGalerkinGetKSP(PC, KSP *);
278: PETSC_EXTERN PetscErrorCode PCDeflationGetCoarseKSP(PC, KSP *);
280: /*S
281: PCMGCoarseSpaceConstructorFn - A function prototype for functions registered with `PCMGRegisterCoarseSpaceConstructor()`
283: Calling Sequence:
284: + pc - The `PC` object
285: . l - The multigrid level, 0 is the coarse level
286: . dm - The `DM` for this level
287: . smooth - The level smoother
288: . Nc - The size of the coarse space
289: . initGuess - Basis for an initial guess for the space
290: - coarseSp - A basis for the computed coarse space
292: Level: beginner
294: .seealso: [](ch_ksp), `PCMGRegisterCoarseSpaceConstructor()`, `PCMGGetCoarseSpaceConstructor()`
295: S*/
296: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode PCMGCoarseSpaceConstructorFn(PC pc, PetscInt l, DM dm, KSP smooth, PetscInt Nc, Mat initGuess, Mat *coarseSp);
298: PETSC_EXTERN PetscFunctionList PCMGCoarseList;
299: PETSC_EXTERN PetscErrorCode PCMGRegisterCoarseSpaceConstructor(const char[], PCMGCoarseSpaceConstructorFn *);
300: PETSC_EXTERN PetscErrorCode PCMGGetCoarseSpaceConstructor(const char[], PCMGCoarseSpaceConstructorFn **);
302: PETSC_EXTERN PetscErrorCode KSPBuildSolution(KSP, Vec, Vec *);
303: PETSC_EXTERN PetscErrorCode KSPBuildResidual(KSP, Vec, Vec, Vec *);
305: /*E
306: KSPChebyshevKind - Which kind of Chebyshev polynomial to use with `KSPCHEBYSHEV`
308: Values:
309: + `KSP_CHEBYSHEV_FIRST` - "classic" first-kind Chebyshev polynomial
310: . `KSP_CHEBYSHEV_FOURTH` - fourth-kind Chebyshev polynomial
311: - `KSP_CHEBYSHEV_OPT_FOURTH` - optimized fourth-kind Chebyshev polynomial
313: Level: intermediate
315: .seealso: [](ch_ksp), `KSPCHEBYSHEV`, `KSPChebyshevSetKind()`, `KSPChebyshevGetKind()`
316: E*/
317: typedef enum {
318: KSP_CHEBYSHEV_FIRST,
319: KSP_CHEBYSHEV_FOURTH,
320: KSP_CHEBYSHEV_OPT_FOURTH
321: } KSPChebyshevKind;
323: PETSC_EXTERN PetscErrorCode KSPRichardsonSetScale(KSP, PetscReal);
324: PETSC_EXTERN PetscErrorCode KSPRichardsonSetSelfScale(KSP, PetscBool);
325: PETSC_EXTERN PetscErrorCode KSPChebyshevSetEigenvalues(KSP, PetscReal, PetscReal);
326: PETSC_EXTERN PetscErrorCode KSPChebyshevEstEigSet(KSP, PetscReal, PetscReal, PetscReal, PetscReal);
327: PETSC_EXTERN PetscErrorCode KSPChebyshevEstEigSetUseNoisy(KSP, PetscBool);
328: PETSC_EXTERN PetscErrorCode KSPChebyshevSetKind(KSP, KSPChebyshevKind);
329: PETSC_EXTERN PetscErrorCode KSPChebyshevGetKind(KSP, KSPChebyshevKind *);
330: PETSC_EXTERN PetscErrorCode KSPChebyshevEstEigGetKSP(KSP, KSP *);
331: PETSC_EXTERN PetscErrorCode KSPComputeExtremeSingularValues(KSP, PetscReal *, PetscReal *);
332: PETSC_EXTERN PetscErrorCode KSPComputeEigenvalues(KSP, PetscInt, PetscReal[], PetscReal[], PetscInt *);
333: PETSC_EXTERN PetscErrorCode KSPComputeEigenvaluesExplicitly(KSP, PetscInt, PetscReal[], PetscReal[]);
334: PETSC_EXTERN PetscErrorCode KSPComputeRitz(KSP, PetscBool, PetscBool, PetscInt *, Vec[], PetscReal[], PetscReal[]);
336: /*E
337: KSPFCDTruncationType - Define how stored directions are used to orthogonalize in flexible conjugate directions (FCD) methods
339: Values:
340: + `KSP_FCD_TRUNC_TYPE_STANDARD` - uses all (up to `mmax`) stored directions
341: - `KSP_FCD_TRUNC_TYPE_NOTAY` - uses the last `max(1,mod(i,mmax))` stored directions at iteration i = 0, 1, ...
343: Level: intermediate
345: Note:
346: Function such as `KSPFCGSetMmax()`, `KSPPIPEGCRSetNMax()`, `KSPPIPEGCRSetNMax()`, and `KSPPIPEFCGSetNMax()` may be
347: used to provide `nmax` or they may be provided with the option database.
349: .seealso: [](ch_ksp), `KSP`, `KSPFCG`, `KSPPIPEFCG`, `KSPPIPEGCR`, `KSPFCGSetTruncationType()`, `KSPFCGGetTruncationType()`,
350: `KSPPIPEGCRSetTruncationType()`, `KSPPIPEGCRGetTruncationType()`,
351: `KSPFCGSetMmax()`, `KSPPIPEGCRSetNMax()`, `KSPPIPEGCRGetNMax()`, `KSPPIPEFCGGetNMax()`
352: E*/
353: typedef enum {
354: KSP_FCD_TRUNC_TYPE_STANDARD,
355: KSP_FCD_TRUNC_TYPE_NOTAY
356: } KSPFCDTruncationType;
357: PETSC_EXTERN const char *const KSPFCDTruncationTypes[];
359: PETSC_EXTERN PetscErrorCode KSPFCGSetMmax(KSP, PetscInt);
360: PETSC_EXTERN PetscErrorCode KSPFCGGetMmax(KSP, PetscInt *);
361: PETSC_EXTERN PetscErrorCode KSPFCGSetNprealloc(KSP, PetscInt);
362: PETSC_EXTERN PetscErrorCode KSPFCGGetNprealloc(KSP, PetscInt *);
363: PETSC_EXTERN PetscErrorCode KSPFCGSetTruncationType(KSP, KSPFCDTruncationType);
364: PETSC_EXTERN PetscErrorCode KSPFCGGetTruncationType(KSP, KSPFCDTruncationType *);
366: PETSC_EXTERN PetscErrorCode KSPPIPEFCGSetMmax(KSP, PetscInt);
367: PETSC_EXTERN PetscErrorCode KSPPIPEFCGGetMmax(KSP, PetscInt *);
368: PETSC_EXTERN PetscErrorCode KSPPIPEFCGSetNprealloc(KSP, PetscInt);
369: PETSC_EXTERN PetscErrorCode KSPPIPEFCGGetNprealloc(KSP, PetscInt *);
370: PETSC_EXTERN PetscErrorCode KSPPIPEFCGSetTruncationType(KSP, KSPFCDTruncationType);
371: PETSC_EXTERN PetscErrorCode KSPPIPEFCGGetTruncationType(KSP, KSPFCDTruncationType *);
373: PETSC_EXTERN PetscErrorCode KSPPIPEGCRSetMmax(KSP, PetscInt);
374: PETSC_EXTERN PetscErrorCode KSPPIPEGCRGetMmax(KSP, PetscInt *);
375: PETSC_EXTERN PetscErrorCode KSPPIPEGCRSetNprealloc(KSP, PetscInt);
376: PETSC_EXTERN PetscErrorCode KSPPIPEGCRGetNprealloc(KSP, PetscInt *);
377: PETSC_EXTERN PetscErrorCode KSPPIPEGCRSetTruncationType(KSP, KSPFCDTruncationType);
378: PETSC_EXTERN PetscErrorCode KSPPIPEGCRGetTruncationType(KSP, KSPFCDTruncationType *);
379: PETSC_EXTERN PetscErrorCode KSPPIPEGCRSetUnrollW(KSP, PetscBool);
380: PETSC_EXTERN PetscErrorCode KSPPIPEGCRGetUnrollW(KSP, PetscBool *);
382: /*S
383: KSPFlexibleModifyPCFn - A prototype of a function used to modify the preconditioner during the use of flexible `KSP` methods, such as `KSPFGMRES`
385: Calling Sequence:
386: + ksp - the `KSP` context being used.
387: . total_its - the total number of iterations that have occurred.
388: . local_its - the number of iterations since last restart if applicable
389: . res_norm - the current residual norm
390: - ctx - optional context variable set with `KSPFlexibleSetModifyPC()`
392: Level: beginner
394: .seealso: [](ch_ksp), `KSP`, `KSPFlexibleSetModifyPC()`
395: S*/
396: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPFlexibleModifyPCFn(KSP ksp, PetscInt total_its, PetscInt local_its, PetscReal res_norm, PetscCtx ctx);
398: PETSC_EXTERN PetscErrorCode KSPFlexibleSetModifyPC(KSP, KSPFlexibleModifyPCFn *, PetscCtx, PetscCtxDestroyFn *);
400: PETSC_DEPRECATED_FUNCTION(3, 25, 0, "KSPFlexibleSetModifyPC()", ) static inline PetscErrorCode KSPPIPEGCRSetModifyPC(KSP ksp, KSPFlexibleModifyPCFn *fun, PetscCtx ctx, PetscCtxDestroyFn *dfun)
401: {
402: return KSPFlexibleSetModifyPC(ksp, fun, ctx, dfun);
403: }
405: PETSC_EXTERN PetscErrorCode KSPGMRESSetRestart(KSP, PetscInt);
406: PETSC_EXTERN PetscErrorCode KSPGMRESGetRestart(KSP, PetscInt *);
407: PETSC_EXTERN PetscErrorCode KSPGMRESSetHapTol(KSP, PetscReal);
408: PETSC_EXTERN PetscErrorCode KSPGMRESSetBreakdownTolerance(KSP, PetscReal);
410: PETSC_EXTERN PetscErrorCode KSPGMRESSetVectorAllocationSize(KSP, PetscInt);
411: PETSC_EXTERN PetscErrorCode KSPGMRESSetPreAllocateVectors(KSP);
413: PETSC_EXTERN PetscErrorCode KSPLGMRESSetAugDim(KSP, PetscInt);
414: PETSC_EXTERN PetscErrorCode KSPLGMRESSetConstant(KSP);
416: PETSC_EXTERN PetscErrorCode KSPPIPEFGMRESSetShift(KSP, PetscScalar);
418: PETSC_EXTERN PetscErrorCode KSPGCRSetRestart(KSP, PetscInt);
419: PETSC_EXTERN PetscErrorCode KSPGCRGetRestart(KSP, PetscInt *);
421: PETSC_EXTERN PetscErrorCode KSPIDRSetS(KSP, PetscInt);
422: PETSC_EXTERN PetscErrorCode KSPIDRGetS(KSP, PetscInt *);
423: PETSC_EXTERN PetscErrorCode KSPIDRSetCosine(KSP, PetscReal);
424: PETSC_EXTERN PetscErrorCode KSPIDRGetCosine(KSP, PetscReal *);
425: PETSC_EXTERN PetscErrorCode KSPIDRSetRandom(KSP, PetscRandom);
426: PETSC_EXTERN PetscErrorCode KSPIDRGetRandom(KSP, PetscRandom *);
428: PETSC_EXTERN PetscErrorCode KSPEKSMSetHapTol(KSP, PetscReal);
429: PETSC_EXTERN PetscErrorCode KSPEKSMGetHapTol(KSP, PetscReal *);
430: PETSC_EXTERN PetscErrorCode KSPEKSMSetKSP(KSP, KSP, KSP);
431: PETSC_EXTERN PetscErrorCode KSPEKSMGetKSP(KSP, KSP *, KSP *);
432: PETSC_EXTERN PetscErrorCode KSPEKSMSetShift(KSP, PetscScalar);
433: PETSC_EXTERN PetscErrorCode KSPEKSMGetShift(KSP, PetscScalar *);
435: PETSC_DEPRECATED_FUNCTION(3, 25, 0, "KSPFlexibleSetModifyPC()", ) static inline PetscErrorCode KSPGCRSetModifyPC(KSP ksp, KSPFlexibleModifyPCFn *fun, PetscCtx ctx, PetscCtxDestroyFn *dfun)
436: {
437: return KSPFlexibleSetModifyPC(ksp, fun, ctx, dfun);
438: }
440: PETSC_EXTERN PetscErrorCode KSPMINRESSetRadius(KSP, PetscReal);
441: PETSC_EXTERN PetscErrorCode KSPMINRESGetUseQLP(KSP, PetscBool *);
442: PETSC_EXTERN PetscErrorCode KSPMINRESSetUseQLP(KSP, PetscBool);
444: PETSC_EXTERN PetscErrorCode KSPFETIDPGetInnerBDDC(KSP, PC *);
445: PETSC_EXTERN PetscErrorCode KSPFETIDPSetInnerBDDC(KSP, PC);
446: PETSC_EXTERN PetscErrorCode KSPFETIDPGetInnerKSP(KSP, KSP *);
447: PETSC_EXTERN PetscErrorCode KSPFETIDPSetPressureOperator(KSP, Mat);
449: PETSC_EXTERN PetscErrorCode KSPHPDDMSetDeflationMat(KSP, Mat);
450: PETSC_EXTERN PetscErrorCode KSPHPDDMGetDeflationMat(KSP, Mat *);
451: #if PetscDefined(HAVE_HPDDM)
452: PETSC_DEPRECATED_FUNCTION(3, 18, 0, "KSPHPDDMSetDeflationMat()", ) static inline PetscErrorCode KSPHPDDMSetDeflationSpace(KSP ksp, Mat U)
453: {
454: return KSPHPDDMSetDeflationMat(ksp, U);
455: }
456: PETSC_DEPRECATED_FUNCTION(3, 18, 0, "KSPHPDDMGetDeflationMat()", ) static inline PetscErrorCode KSPHPDDMGetDeflationSpace(KSP ksp, Mat *U)
457: {
458: return KSPHPDDMGetDeflationMat(ksp, U);
459: }
460: #endif
461: PETSC_DEPRECATED_FUNCTION(3, 14, 0, "KSPMatSolve()", ) static inline PetscErrorCode KSPHPDDMMatSolve(KSP ksp, Mat B, Mat X)
462: {
463: return KSPMatSolve(ksp, B, X);
464: }
465: /*E
466: KSPHPDDMType - Type of Krylov method used by `KSPHPDDM`
468: Values:
469: + `KSP_HPDDM_TYPE_GMRES` (default) - Generalized Minimal Residual method
470: . `KSP_HPDDM_TYPE_BGMRES` - block GMRES
471: . `KSP_HPDDM_TYPE_CG` - Conjugate Gradient
472: . `KSP_HPDDM_TYPE_BCG` - block CG
473: . `KSP_HPDDM_TYPE_GCRODR` - Generalized Conjugate Residual method with inner Orthogonalization and Deflated Restarting
474: . `KSP_HPDDM_TYPE_BGCRODR` - block GCRODR
475: . `KSP_HPDDM_TYPE_BFBCG` - breakdown-free BCG
476: - `KSP_HPDDM_TYPE_PREONLY` - apply the preconditioner only
478: Level: intermediate
480: .seealso: [](ch_ksp), `KSPHPDDM`, `KSPHPDDMSetType()`
481: E*/
482: typedef enum {
483: KSP_HPDDM_TYPE_GMRES = 0,
484: KSP_HPDDM_TYPE_BGMRES = 1,
485: KSP_HPDDM_TYPE_CG = 2,
486: KSP_HPDDM_TYPE_BCG = 3,
487: KSP_HPDDM_TYPE_GCRODR = 4,
488: KSP_HPDDM_TYPE_BGCRODR = 5,
489: KSP_HPDDM_TYPE_BFBCG = 6,
490: KSP_HPDDM_TYPE_PREONLY = 7
491: } KSPHPDDMType;
492: PETSC_EXTERN const char *const KSPHPDDMTypes[];
494: PETSC_EXTERN PetscErrorCode KSPHPDDMSetType(KSP, KSPHPDDMType);
495: PETSC_EXTERN PetscErrorCode KSPHPDDMGetType(KSP, KSPHPDDMType *);
497: /*S
498: KSPOrthogonalizationFn - A function prototype for functions provided to `KSPOrthogonalizationSet()`
500: Calling Sequence:
501: + ksp - the `KSP` context
502: . V - array of previously computed orthonormal vectors
503: . n - number of vectors
504: . x - vector to be orthogonalized (may be `NULL`)
505: - h - computed orthogonalization coefficients
507: Level: intermediate
509: Note:
510: If no `x` is given, then the vector to be orthogonalized is assumed to be located at `V[n]`.
512: .seealso: [](ch_ksp), `KSP`, `KSPOrthogonalizationSet()`
513: S*/
514: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPOrthogonalizationFn(KSP ksp, Vec V[], PetscInt n, Vec x, PetscScalar h[]);
516: PETSC_EXTERN PetscErrorCode KSPOrthogonalizationSet(KSP, KSPOrthogonalizationFn *);
517: PETSC_EXTERN PetscErrorCode KSPOrthogonalizationGet(KSP, KSPOrthogonalizationFn **);
518: PETSC_EXTERN KSPOrthogonalizationFn KSPOrthogonalizationClassicalGramSchmidt;
519: PETSC_EXTERN KSPOrthogonalizationFn KSPOrthogonalizationModifiedGramSchmidt;
521: #define KSP_GMRES_CGS_REFINE_NEVER_DEPRECATED KSP_GMRES_CGS_REFINE_NEVER PETSC_DEPRECATED_ENUM(3, 26, 0, "KSP_ORTHOGONALIZATION_CGS_REFINE_NEVER", )
522: #define KSP_GMRES_CGS_REFINE_IFNEEDED_DEPRECATED KSP_GMRES_CGS_REFINE_IFNEEDED PETSC_DEPRECATED_ENUM(3, 26, 0, "KSP_ORTHOGONALIZATION_CGS_REFINE_IFNEEDED", )
523: #define KSP_GMRES_CGS_REFINE_ALWAYS_DEPRECATED KSP_GMRES_CGS_REFINE_ALWAYS PETSC_DEPRECATED_ENUM(3, 26, 0, "KSP_ORTHOGONALIZATION_CGS_REFINE_ALWAYS", )
524: /*E
525: KSPOrthogonalizationCGSRefinementType - How the classical (unmodified) Gram-Schmidt is performed in the GMRES solvers
527: Values:
528: + `KSP_ORTHOGONALIZATION_CGS_REFINE_NEVER` - one step of classical Gram-Schmidt
529: . `KSP_ORTHOGONALIZATION_CGS_REFINE_IFNEEDED` - a second step is performed if the first step does not satisfy some criteria
530: - `KSP_ORTHOGONALIZATION_CGS_REFINE_ALWAYS` - always perform two steps
532: Level: advanced
534: .seealso: [](ch_ksp), `KSP`, `KSPGMRES`, `KSPOrthogonalizationClassicalGramSchmidt()`, `KSPOrthogonalizationSet()`,
535: `KSPOrthogonalizationGet()`,
536: `KSPOrthogonalizationSetCGSRefinementType()`, `KSPOrthogonalizationGetCGSRefinementType()`, `KSPOrthogonalizationModifiedGramSchmidt()`
537: E*/
538: typedef enum {
539: KSP_ORTHOGONALIZATION_CGS_REFINE_NEVER = 0,
540: KSP_ORTHOGONALIZATION_CGS_REFINE_IFNEEDED = 1,
541: KSP_ORTHOGONALIZATION_CGS_REFINE_ALWAYS = 2,
542: KSP_GMRES_CGS_REFINE_NEVER_DEPRECATED = 0,
543: KSP_GMRES_CGS_REFINE_IFNEEDED_DEPRECATED = 1,
544: KSP_GMRES_CGS_REFINE_ALWAYS_DEPRECATED = 2
545: } KSPOrthogonalizationCGSRefinementType;
546: PETSC_EXTERN const char *const KSPOrthogonalizationCGSRefinementTypes[];
548: /*MC
549: KSP_ORTHOGONALIZATION_CGS_REFINE_NEVER - Do the classical (unmodified) Gram-Schmidt process
551: Level: advanced
553: Note:
554: Possibly unstable, but the fastest to compute
556: .seealso: [](ch_ksp), `KSPGMRES`, `KSPOrthogonalizationCGSRefinementType`, `KSPOrthogonalizationClassicalGramSchmidt()`, `KSPOrthogonalizationSet()`,
557: `KSP`, `KSPOrthogonalizationGet()`,
558: `KSPOrthogonalizationSetCGSRefinementType()`, `KSPOrthogonalizationGetCGSRefinementType()`, `KSP_ORTHOGONALIZATION_CGS_REFINE_IFNEEDED`, `KSP_ORTHOGONALIZATION_CGS_REFINE_ALWAYS`,
559: `KSPOrthogonalizationModifiedGramSchmidt()`
560: M*/
562: /*MC
563: KSP_ORTHOGONALIZATION_CGS_REFINE_IFNEEDED - Do the classical (unmodified) Gram-Schmidt process and one step of
564: iterative refinement if an estimate of the orthogonality of the resulting vectors indicates
565: poor orthogonality.
567: Level: advanced
569: Note:
570: This is slower than `KSP_ORTHOGONALIZATION_CGS_REFINE_NEVER` because it requires an extra norm computation to
571: estimate the orthogonality but is more stable.
573: .seealso: [](ch_ksp), `KSPGMRES`, `KSPOrthogonalizationCGSRefinementType`, `KSPOrthogonalizationClassicalGramSchmidt()`, `KSPOrthogonalizationSet()`,
574: `KSP`, `KSPOrthogonalizationGet()`,
575: `KSPOrthogonalizationSetCGSRefinementType()`, `KSPOrthogonalizationGetCGSRefinementType()`, `KSP_ORTHOGONALIZATION_CGS_REFINE_NEVER`, `KSP_ORTHOGONALIZATION_CGS_REFINE_ALWAYS`,
576: `KSPOrthogonalizationModifiedGramSchmidt()`
577: M*/
579: /*MC
580: KSP_ORTHOGONALIZATION_CGS_REFINE_ALWAYS - Do two steps of the classical (unmodified) Gram-Schmidt process.
582: Level: advanced
584: Notes:
585: This is roughly twice the cost of `KSP_ORTHOGONALIZATION_CGS_REFINE_NEVER` because it performs the process twice
586: but it saves the extra norm calculation needed by `KSP_ORTHOGONALIZATION_CGS_REFINE_IFNEEDED`.
588: You should only use this if you absolutely know that the iterative refinement is needed.
590: .seealso: [](ch_ksp), `KSPGMRES`, `KSPOrthogonalizationCGSRefinementType`, `KSPOrthogonalizationClassicalGramSchmidt()`, `KSPOrthogonalizationSet()`,
591: `KSP`, `KSPOrthogonalizationGet()`,
592: `KSPOrthogonalizationSetCGSRefinementType()`, `KSPOrthogonalizationGetCGSRefinementType()`, `KSP_ORTHOGONALIZATION_CGS_REFINE_IFNEEDED`, `KSP_ORTHOGONALIZATION_CGS_REFINE_ALWAYS`,
593: `KSPOrthogonalizationModifiedGramSchmidt()`
594: M*/
596: PETSC_EXTERN PetscErrorCode KSPOrthogonalizationSetCGSRefinementType(KSP, KSPOrthogonalizationCGSRefinementType);
597: PETSC_EXTERN PetscErrorCode KSPOrthogonalizationGetCGSRefinementType(KSP, KSPOrthogonalizationCGSRefinementType *);
599: PETSC_DEPRECATED_FUNCTION(3, 26, 0, "KSPOrthogonalizationModifiedGramSchmidt()", ) static inline PetscErrorCode KSPGMRESModifiedGramSchmidtOrthogonalization(KSP ksp, PETSC_UNUSED PetscInt it)
600: {
601: SETERRQ(PetscObjectComm((PetscObject)ksp), PETSC_ERR_SUP, "Use KSPOrthogonalizationModifiedGramSchmidt()");
602: }
603: PETSC_DEPRECATED_FUNCTION(3, 26, 0, "KSPOrthogonalizationClassicalGramSchmidt()", ) static inline PetscErrorCode KSPGMRESClassicalGramSchmidtOrthogonalization(KSP ksp, PETSC_UNUSED PetscInt it)
604: {
605: SETERRQ(PetscObjectComm((PetscObject)ksp), PETSC_ERR_SUP, "Use KSPOrthogonalizationClassicalGramSchmidt()");
606: }
607: PETSC_DEPRECATED_FUNCTION(3, 26, 0, "KSPOrthogonalizationSet()", ) static inline PetscErrorCode KSPGMRESSetOrthogonalization(KSP ksp, PETSC_UNUSED PetscErrorCode (*orthog)(KSP, PetscInt))
608: {
609: SETERRQ(PetscObjectComm((PetscObject)ksp), PETSC_ERR_SUP, "Use KSPOrthogonalizationSet()");
610: }
611: PETSC_DEPRECATED_FUNCTION(3, 26, 0, "KSPOrthogonalizationGet()", ) static inline PetscErrorCode KSPGMRESGetOrthogonalization(KSP ksp, PETSC_UNUSED PetscErrorCode (**orthog)(KSP, PetscInt))
612: {
613: SETERRQ(PetscObjectComm((PetscObject)ksp), PETSC_ERR_SUP, "Use KSPOrthogonalizationGet()");
614: }
615: PETSC_DEPRECATED_TYPEDEF(3, 26, 0, "KSPOrthogonalizationCGSRefinementType", ) typedef KSPOrthogonalizationCGSRefinementType KSPGMRESCGSRefinementType;
616: PETSC_DEPRECATED_FUNCTION(3, 26, 0, "KSPOrthogonalizationSetCGSRefinementType()", )
617: static inline PetscErrorCode KSPGMRESSetCGSRefinementType(KSP ksp, KSPOrthogonalizationCGSRefinementType type)
618: {
619: return KSPOrthogonalizationSetCGSRefinementType(ksp, type);
620: }
621: PETSC_DEPRECATED_FUNCTION(3, 26, 0, "KSPOrthogonalizationGetCGSRefinementType()", )
622: static inline PetscErrorCode KSPGMRESGetCGSRefinementType(KSP ksp, KSPOrthogonalizationCGSRefinementType *type)
623: {
624: return KSPOrthogonalizationGetCGSRefinementType(ksp, type);
625: }
627: PETSC_EXTERN KSPFlexibleModifyPCFn KSPFlexibleModifyPCNoChange;
628: PETSC_EXTERN KSPFlexibleModifyPCFn KSPFlexibleModifyPCKSP;
630: PETSC_DEPRECATED_FUNCTION(3, 25, 0, "KSPFlexibleModifyPCNoChange()", ) static inline PetscErrorCode KSPFGMRESModifyPCNoChange(KSP ksp, PetscInt total_its, PetscInt loc_its, PetscReal res_norm, PetscCtx ctx)
631: {
632: return KSPFlexibleModifyPCNoChange(ksp, total_its, loc_its, res_norm, ctx);
633: }
635: PETSC_DEPRECATED_FUNCTION(3, 25, 0, "KSPFlexibleModifyPCKSP()", ) static inline PetscErrorCode KSPFGMRESModifyPCKSP(KSP ksp, PetscInt total_its, PetscInt loc_its, PetscReal res_norm, PetscCtx ctx)
636: {
637: return KSPFlexibleModifyPCKSP(ksp, total_its, loc_its, res_norm, ctx);
638: }
640: PETSC_EXTERN PetscErrorCode KSPQCGSetTrustRegionRadius(KSP, PetscReal);
641: PETSC_EXTERN PetscErrorCode KSPQCGGetQuadratic(KSP, PetscReal *);
642: PETSC_EXTERN PetscErrorCode KSPQCGGetTrialStepNorm(KSP, PetscReal *);
644: PETSC_EXTERN PetscErrorCode KSPBCGSLSetXRes(KSP, PetscReal);
645: PETSC_EXTERN PetscErrorCode KSPBCGSLSetPol(KSP, PetscBool);
646: PETSC_EXTERN PetscErrorCode KSPBCGSLSetEll(KSP, PetscInt);
647: PETSC_EXTERN PetscErrorCode KSPBCGSLSetUsePseudoinverse(KSP, PetscBool);
649: PETSC_EXTERN PetscErrorCode KSPSetFromOptions(KSP);
650: PETSC_EXTERN PetscErrorCode KSPResetFromOptions(KSP);
652: PETSC_EXTERN PetscErrorCode KSPMonitorSetFromOptions(KSP, const char[], const char[], PetscCtx);
653: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorResidual;
654: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorResidualView;
655: PETSC_DEPRECATED_FUNCTION(3, 23, 0, "KSPMonitorResidualDraw()", ) static inline PetscErrorCode KSPMonitorResidualDraw(KSP ksp, PetscInt n, PetscReal rnorm, PetscViewerAndFormat *vf)
656: {
657: return KSPMonitorResidualView(ksp, n, rnorm, vf);
658: }
659: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorResidualDrawLG;
660: PETSC_EXTERN PetscErrorCode KSPMonitorResidualDrawLGCreate(PetscViewer, PetscViewerFormat, PetscCtx, PetscViewerAndFormat **);
661: PETSC_DEPRECATED_FUNCTION(3, 26, 0, "KSPMonitorResidual()", ) static inline PetscErrorCode KSPMonitorResidualShort(KSP ksp, PetscInt n, PetscReal rnorm, PetscViewerAndFormat *vf)
662: {
663: return KSPMonitorResidual(ksp, n, rnorm, vf);
664: }
665: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorResidualRange;
666: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorTrueResidual;
667: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorTrueResidualView;
668: PETSC_DEPRECATED_FUNCTION(3, 23, 0, "KSPMonitorTrueResidualDraw()", ) static inline PetscErrorCode KSPMonitorTrueResidualDraw(KSP ksp, PetscInt n, PetscReal rnorm, PetscViewerAndFormat *vf)
669: {
670: return KSPMonitorTrueResidualView(ksp, n, rnorm, vf);
671: }
672: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorTrueResidualDrawLG;
673: PETSC_EXTERN PetscErrorCode KSPMonitorTrueResidualDrawLGCreate(PetscViewer, PetscViewerFormat, PetscCtx, PetscViewerAndFormat **);
674: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorTrueResidualMax;
675: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorError;
676: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorErrorDraw;
677: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorErrorDrawLG;
678: PETSC_EXTERN PetscErrorCode KSPMonitorErrorDrawLGCreate(PetscViewer, PetscViewerFormat, PetscCtx, PetscViewerAndFormat **);
679: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorSolution;
680: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorSolutionDraw;
681: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorSolutionDrawLG;
682: PETSC_EXTERN PetscErrorCode KSPMonitorSolutionDrawLGCreate(PetscViewer, PetscViewerFormat, PetscCtx, PetscViewerAndFormat **);
683: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorSingularValue;
684: PETSC_EXTERN PetscErrorCode KSPMonitorSingularValueCreate(PetscViewer, PetscViewerFormat, PetscCtx, PetscViewerAndFormat **);
685: PETSC_DEPRECATED_FUNCTION(3, 15, 0, "KSPMonitorResidual()", ) static inline PetscErrorCode KSPMonitorDefault(KSP ksp, PetscInt n, PetscReal rnorm, PetscViewerAndFormat *vf)
686: {
687: return KSPMonitorResidual(ksp, n, rnorm, vf);
688: }
689: PETSC_DEPRECATED_FUNCTION(3, 15, 0, "KSPMonitorTrueResidual()", ) static inline PetscErrorCode KSPMonitorTrueResidualNorm(KSP ksp, PetscInt n, PetscReal rnorm, PetscViewerAndFormat *vf)
690: {
691: return KSPMonitorTrueResidual(ksp, n, rnorm, vf);
692: }
693: PETSC_DEPRECATED_FUNCTION(3, 15, 0, "KSPMonitorTrueResidualMax()", ) static inline PetscErrorCode KSPMonitorTrueResidualMaxNorm(KSP ksp, PetscInt n, PetscReal rnorm, PetscViewerAndFormat *vf)
694: {
695: return KSPMonitorTrueResidualMax(ksp, n, rnorm, vf);
696: }
698: PETSC_EXTERN PetscErrorCode KSPGMRESMonitorKrylov(KSP, PetscInt, PetscReal, void *);
699: PETSC_EXTERN PetscErrorCode KSPMonitorDynamicTolerance(KSP, PetscInt, PetscReal, PetscCtx);
700: PETSC_EXTERN PetscErrorCode KSPMonitorDynamicToleranceDestroy(PetscCtxRt);
701: PETSC_EXTERN PetscErrorCode KSPMonitorDynamicToleranceCreate(void *);
702: PETSC_EXTERN PetscErrorCode KSPMonitorDynamicToleranceSetCoefficient(void *, PetscReal);
703: PETSC_EXTERN PetscErrorCode KSPMonitorSAWs(KSP, PetscInt, PetscReal, void *);
704: PETSC_EXTERN PetscErrorCode KSPMonitorSAWsCreate(KSP, void **);
705: PETSC_EXTERN PetscErrorCode KSPMonitorSAWsDestroy(PetscCtxRt);
707: PETSC_EXTERN PetscErrorCode KSPUnwindPreconditioner(KSP, Vec, Vec);
708: PETSC_EXTERN PetscErrorCode KSPInitialResidual(KSP, Vec, Vec, Vec, Vec, Vec);
710: PETSC_EXTERN PetscErrorCode KSPSetOperators(KSP, Mat, Mat);
711: PETSC_EXTERN PetscErrorCode KSPGetOperators(KSP, Mat *, Mat *);
712: PETSC_EXTERN PetscErrorCode KSPGetOperatorsSet(KSP, PetscBool *, PetscBool *);
713: PETSC_EXTERN PetscErrorCode KSPSetOptionsPrefix(KSP, const char[]);
714: PETSC_EXTERN PetscErrorCode KSPAppendOptionsPrefix(KSP, const char[]);
715: PETSC_EXTERN PetscErrorCode KSPGetOptionsPrefix(KSP, const char *[]);
717: /*S
718: KSPConvergedReasonViewFn - A prototype of a function used with `KSPConvergedReasonViewSet()`
720: Calling Sequence:
721: + ksp - the `KSP` object whose `KSPConvergedReason` is to be viewed
722: - ctx - context used by the function, set with `KSPConvergedReasonViewSet()`
724: Level: beginner
726: .seealso: [](ch_ksp), `KSP`, `KSPConvergedReasonView()`, `KSPConvergedReasonViewSet()`, `KSPConvergedReasonViewFromOptions()`, `KSPView()`
727: S*/
728: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPConvergedReasonViewFn(KSP ksp, PetscCtx ctx);
730: PETSC_EXTERN PetscErrorCode KSPView(KSP, PetscViewer);
731: PETSC_EXTERN PetscErrorCode KSPLoad(KSP, PetscViewer);
732: PETSC_EXTERN PetscErrorCode KSPViewFromOptions(KSP, PetscObject, const char[]);
733: PETSC_EXTERN PetscErrorCode KSPConvergedReasonView(KSP, PetscViewer);
734: PETSC_EXTERN PetscErrorCode KSPConvergedReasonViewSet(KSP, KSPConvergedReasonViewFn *, void *, PetscCtxDestroyFn *);
735: PETSC_EXTERN PetscErrorCode KSPConvergedReasonViewFromOptions(KSP);
736: PETSC_EXTERN PetscErrorCode KSPConvergedReasonViewCancel(KSP);
737: PETSC_EXTERN PetscErrorCode KSPConvergedRateView(KSP, PetscViewer);
739: PETSC_DEPRECATED_FUNCTION(3, 14, 0, "KSPConvergedReasonView()", ) static inline PetscErrorCode KSPReasonView(KSP ksp, PetscViewer v)
740: {
741: return KSPConvergedReasonView(ksp, v);
742: }
743: PETSC_DEPRECATED_FUNCTION(3, 14, 0, "KSPConvergedReasonViewFromOptions()", ) static inline PetscErrorCode KSPReasonViewFromOptions(KSP ksp)
744: {
745: return KSPConvergedReasonViewFromOptions(ksp);
746: }
748: #define KSP_FILE_CLASSID 1211223
750: PETSC_EXTERN PetscErrorCode KSPLSQRSetExactMatNorm(KSP, PetscBool);
751: PETSC_EXTERN PetscErrorCode KSPLSQRSetComputeStandardErrorVec(KSP, PetscBool);
752: PETSC_EXTERN PetscErrorCode KSPLSQRGetStandardErrorVec(KSP, Vec *);
753: PETSC_EXTERN PetscErrorCode KSPLSQRGetNorms(KSP, PetscReal *, PetscReal *);
754: PETSC_EXTERN KSPMonitorRegisterFn KSPLSQRMonitorResidual;
755: PETSC_EXTERN KSPMonitorRegisterFn KSPLSQRMonitorResidualDrawLG;
756: PETSC_EXTERN PetscErrorCode KSPLSQRMonitorResidualDrawLGCreate(PetscViewer, PetscViewerFormat, void *, PetscViewerAndFormat **);
758: PETSC_EXTERN PetscErrorCode PCRedundantGetKSP(PC, KSP *);
759: PETSC_EXTERN PetscErrorCode PCRedistributeGetKSP(PC, KSP *);
760: PETSC_EXTERN PetscErrorCode PCTelescopeGetKSP(PC, KSP *);
761: PETSC_EXTERN PetscErrorCode PCMPIGetKSP(PC, KSP *);
763: /*E
764: KSPNormType - Norm calculated by the `KSP` and used in the Krylov convergence
765: test routines.
767: Values:
768: + `KSP_NORM_DEFAULT` - use the default for the current `KSPType`
769: . `KSP_NORM_NONE` - use no norm calculation
770: . `KSP_NORM_PRECONDITIONED` - use the preconditioned residual norm
771: . `KSP_NORM_UNPRECONDITIONED` - use the unpreconditioned residual norm
772: - `KSP_NORM_NATURAL` - use an approximation of the natural norm (the norm induced by the linear operator) of the error
774: Level: advanced
776: Note:
777: Each solver only supports a subset of these and some may support different ones
778: depending on whether left or right preconditioning is used, see `KSPSetPCSide()`
780: .seealso: [](ch_ksp), `KSP`, `PCSide`, `KSPSolve()`, `KSPGetConvergedReason()`, `KSPSetNormType()`,
781: `KSPSetConvergenceTest()`, `KSPSetPCSide()`, `KSP_NORM_DEFAULT`, `KSP_NORM_NONE`, `KSP_NORM_PRECONDITIONED`, `KSP_NORM_UNPRECONDITIONED`, `KSP_NORM_NATURAL`
782: E*/
783: typedef enum {
784: KSP_NORM_DEFAULT = -1,
785: KSP_NORM_NONE = 0,
786: KSP_NORM_PRECONDITIONED = 1,
787: KSP_NORM_UNPRECONDITIONED = 2,
788: KSP_NORM_NATURAL = 3
789: } KSPNormType;
790: #define KSP_NORM_MAX (KSP_NORM_NATURAL + 1)
791: PETSC_EXTERN const char *const *const KSPNormTypes;
793: /*MC
794: KSP_NORM_NONE - Do not compute a norm during the Krylov process. This will
795: possibly save some computation but means the convergence test cannot
796: be based on a norm of a residual etc.
798: Level: advanced
800: Note:
801: Some Krylov methods need to compute a residual norm (such as `KPSGMRES`) and then this option is ignored
803: .seealso: [](ch_ksp), `KSPNormType`, `KSP`, `KSPSetNormType()`, `KSP_NORM_PRECONDITIONED`, `KSP_NORM_UNPRECONDITIONED`, `KSP_NORM_NATURAL`
804: M*/
806: /*MC
807: KSP_NORM_PRECONDITIONED - Compute the norm of the preconditioned residual $B(b - Ax)$, if left preconditioning, and pass that to the
808: convergence test routine.
810: Level: advanced
812: .seealso: [](ch_ksp), `KSPNormType`, `KSP`, `KSPSetNormType()`, `KSP_NORM_NONE`, `KSP_NORM_UNPRECONDITIONED`, `KSP_NORM_NATURAL`, `KSPSetConvergenceTest()`
813: M*/
815: /*MC
816: KSP_NORM_UNPRECONDITIONED - Compute the norm of the true residual $(b - Ax)$ and pass that to the
817: convergence test routine.
819: Level: advanced
821: .seealso: [](ch_ksp), `KSPNormType`, `KSP`, `KSPSetNormType()`, `KSP_NORM_NONE`, `KSP_NORM_PRECONDITIONED`, `KSP_NORM_NATURAL`, `KSPSetConvergenceTest()`
822: M*/
824: /*MC
825: KSP_NORM_NATURAL - Computes $((b - Ax)^TB(b - Ax))^{1/2}$ and passes that to the
826: convergence test routine.
828: Level: advanced
830: Notes:
831: This is supported by the conjugate gradient-type methods `KSPCG`, `KSPCR`, `KSPCGNE`, `KSPCGS`, `KSPFCG`, `KSPPIPEFCG`, `KSPPIPELCG`, `KSPPIPEGCR`,
832: `KSPPIPECGRR`, `KSPPIPECG`, `KSPPIPECG2`, `KSPPIPEPRCG`, `KSPGROPPCG`, `KSPGLTR`, and `KSPNASH`.
834: `KSPFETIDP` and `KSPPREONLY` accept this setting for compatibility but do not use it directly.
835: For `KSPFETIDP`, configure the norm type on the inner `KSP` returned by `KSPFETIDPGetInnerKSP()`.
837: Since $(b - Ax)^TB(b - Ax) = e^TA^TBAe \approx e^TAe$, where $e$ is the error and $A$ is the discretization of the differential
838: operator arising from the weak formulation of the governing equations, the code is approximating the norm that operator induces on the error.
839: For many problems, the underlying norm is $H^1$, often
840: called the energy norm.
842: Since the application of $B$ to $(b - Ax)$ is already computed in the conjugate gradient and related routines, the use of `KSP_NORM_NATURAL` does not require
843: any additional operations over using other `KSPNormType`s.
845: .seealso: [](ch_ksp), `KSPNormType`, `KSP`, `KSPSetNormType()`, `KSP_NORM_NONE`, `KSP_NORM_PRECONDITIONED`, `KSP_NORM_UNPRECONDITIONED`, `KSPSetConvergenceTest()`
846: M*/
848: PETSC_EXTERN PetscErrorCode KSPSetNormType(KSP, KSPNormType);
849: PETSC_EXTERN PetscErrorCode KSPGetNormType(KSP, KSPNormType *);
850: PETSC_EXTERN PetscErrorCode KSPSetSupportedNorm(KSP, KSPNormType, PCSide, PetscInt);
851: PETSC_EXTERN PetscErrorCode KSPSetCheckNormIteration(KSP, PetscInt);
852: PETSC_EXTERN PetscErrorCode KSPSetLagNorm(KSP, PetscBool);
854: #define KSP_CONVERGED_CG_NEG_CURVE_DEPRECATED KSP_CONVERGED_CG_NEG_CURVE PETSC_DEPRECATED_ENUM(3, 19, 0, "KSP_CONVERGED_NEG_CURVE", )
855: #define KSP_CONVERGED_CG_CONSTRAINED_DEPRECATED KSP_CONVERGED_CG_CONSTRAINED PETSC_DEPRECATED_ENUM(3, 19, 0, "KSP_CONVERGED_STEP_LENGTH", )
856: #define KSP_CONVERGED_RTOL_NORMAL_DEPRECATED KSP_CONVERGED_RTOL_NORMAL PETSC_DEPRECATED_ENUM(3, 24, 0, "KSP_CONVERGED_RTOL_NORMAL_EQUATIONS", )
857: #define KSP_CONVERGED_ATOL_NORMAL_DEPRECATED KSP_CONVERGED_ATOL_NORMAL PETSC_DEPRECATED_ENUM(3, 24, 0, "KSP_CONVERGED_ATOL_NORMAL_EQUATIONS", )
858: /*E
859: KSPConvergedReason - reason a Krylov method was determined to have converged or diverged
861: Values:
862: + `KSP_CONVERGED_RTOL_NORMAL_EQUATIONS` - requested decrease in the residual of the normal equations, for `KSPLSQR`
863: . `KSP_CONVERGED_ATOL_NORMAL_EQUATIONS` - requested absolute value in the residual of the normal equations, for `KSPLSQR`
864: . `KSP_CONVERGED_RTOL` - requested decrease in the residual
865: . `KSP_CONVERGED_ATOL` - requested absolute value in the residual
866: . `KSP_CONVERGED_ITS` - requested number of iterations
867: . `KSP_CONVERGED_NEG_CURVE` - see note below
868: . `KSP_CONVERGED_STEP_LENGTH` - see note below
869: . `KSP_CONVERGED_HAPPY_BREAKDOWN` - happy breakdown (meaning early convergence of the `KSPType` occurred).
870: . `KSP_CONVERGED_USER` - the user has indicated convergence for an arbitrary reason
871: . `KSP_DIVERGED_NULL` - breakdown when solving the Hessenberg system within `KSPGMRES`
872: . `KSP_DIVERGED_ITS` - requested number of iterations
873: . `KSP_DIVERGED_DTOL` - large increase in the residual norm indicating the solution is diverging
874: . `KSP_DIVERGED_BREAKDOWN` - breakdown in the Krylov method
875: . `KSP_DIVERGED_BREAKDOWN_BICG` - breakdown in the `KSPBCGS` Krylov method
876: . `KSP_DIVERGED_NONSYMMETRIC` - the operator or preonditioner was not symmetric for a `KSPType` that requires symmetry
877: . `KSP_DIVERGED_INDEFINITE_PC` - the preconditioner was indefinite for a `KSPType` that requires it be definite, such as `KSPCG`
878: . `KSP_DIVERGED_NANORINF` - a not a number of infinity was detected in a vector during the computation
879: . `KSP_DIVERGED_INDEFINITE_MAT` - the operator was indefinite for a `KSPType` that requires it be definite, such as `KSPCG`
880: . `KSP_DIVERGED_PC_FAILED` - the action of the preconditioner failed for some reason
881: . `KSP_DIVERGED_USER` - the user has indicated divergence for an arbitrary reason
882: - `KSP_DIVERGED_INNER_SOLVE_FAILED` - the inner `KSPSolve()` failed for some reason
884: Level: beginner
886: Note:
887: The values `KSP_CONVERGED_NEG_CURVE`, and `KSP_CONVERGED_STEP_LENGTH` are returned only by `KSPCG`, `KSPMINRES` and by
888: the special `KSPNASH`, `KSPSTCG`, and `KSPGLTR` solvers which are used by the `SNESNEWTONTR` (trust region) solver.
890: Developer Note:
891: The string versions of these are `KSPConvergedReasons`; if you change
892: any of the values here also change them that array of names.
894: .seealso: [](ch_ksp), `KSP`, `KSPSolve()`, `KSPGetConvergedReason()`, `KSPSetTolerances()`, `KSPConvergedReasonView()`
895: E*/
896: typedef enum { /* converged */
897: KSP_CONVERGED_RTOL_NORMAL_DEPRECATED = 1,
898: KSP_CONVERGED_RTOL_NORMAL_EQUATIONS = 1,
899: KSP_CONVERGED_ATOL_NORMAL_DEPRECATED = 9,
900: KSP_CONVERGED_ATOL_NORMAL_EQUATIONS = 9,
901: KSP_CONVERGED_RTOL = 2,
902: KSP_CONVERGED_ATOL = 3,
903: KSP_CONVERGED_ITS = 4,
904: KSP_CONVERGED_NEG_CURVE = 5,
905: KSP_CONVERGED_CG_NEG_CURVE_DEPRECATED = 5,
906: KSP_CONVERGED_CG_CONSTRAINED_DEPRECATED = 6,
907: KSP_CONVERGED_STEP_LENGTH = 6,
908: KSP_CONVERGED_HAPPY_BREAKDOWN = 7,
909: KSP_CONVERGED_USER = 8,
910: /* diverged */
911: KSP_DIVERGED_NULL = -2,
912: KSP_DIVERGED_ITS = -3,
913: KSP_DIVERGED_DTOL = -4,
914: KSP_DIVERGED_BREAKDOWN = -5,
915: KSP_DIVERGED_BREAKDOWN_BICG = -6,
916: KSP_DIVERGED_NONSYMMETRIC = -7,
917: KSP_DIVERGED_INDEFINITE_PC = -8,
918: KSP_DIVERGED_NANORINF = -9,
919: KSP_DIVERGED_INDEFINITE_MAT = -10,
920: KSP_DIVERGED_PC_FAILED = -11,
921: KSP_DIVERGED_PCSETUP_FAILED_DEPRECATED = -11,
922: KSP_DIVERGED_USER = -12,
923: KSP_DIVERGED_INNER_SOLVE_FAILED = -13,
925: KSP_CONVERGED_ITERATING = 0
926: } KSPConvergedReason;
927: PETSC_EXTERN const char *const *KSPConvergedReasons;
929: /*MC
930: KSP_CONVERGED_RTOL - $\|r\| \le rtol \|b\|$ or $rtol \|b - A x_0\|$ if `KSPConvergedDefaultSetUIRNorm()` was called
932: Level: beginner
934: Notes:
935: See `KSPNormType` and `KSPSetNormType()` for possible norms that may be used. By default
936: for left preconditioning it is the 2-norm of the preconditioned residual, and the
937: 2-norm of the residual for right preconditioning
939: See also `KSP_CONVERGED_ATOL` which may apply before this tolerance.
941: .seealso: [](ch_ksp), `KSPNormType`, `KSP_CONVERGED_ATOL`, `KSP_DIVERGED_DTOL`, `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
942: M*/
944: /*MC
945: KSP_CONVERGED_ATOL - $\|r\| \le atol$
947: Level: beginner
949: Notes:
950: See `KSPNormType` and `KSPSetNormType()` for possible norms that may be used. By default
951: for left preconditioning it is the 2-norm of the preconditioned residual, and the
952: 2-norm of the residual for right preconditioning
954: See also `KSP_CONVERGED_RTOL` which may apply before this tolerance.
956: .seealso: [](ch_ksp), `KSPNormType`, `KSP_CONVERGED_RTOL`, `KSP_DIVERGED_DTOL`, `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
957: M*/
959: /*MC
960: KSP_DIVERGED_DTOL - $\|r\| \ge dtol \|b\|$
962: Level: beginner
964: Note:
965: See `KSPNormType` and `KSPSetNormType()` for possible norms that may be used. By default
966: for left preconditioning it is the 2-norm of the preconditioned residual, and the
967: 2-norm of the residual for right preconditioning
969: .seealso: [](ch_ksp), `KSPNormType`, `KSP_CONVERGED_ATOL`, `KSP_CONVERGED_RTOL`, `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
970: M*/
972: /*MC
973: KSP_DIVERGED_ITS - Ran out of iterations before any convergence criteria was
974: reached
976: Level: beginner
978: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
979: M*/
981: /*MC
982: KSP_CONVERGED_ITS - Used by the `KSPPREONLY` solver after the single iteration of
983: the preconditioner is applied. Also used when the `KSPConvergedSkip()` convergence
984: test routine is set in `KSP`.
986: Level: beginner
988: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
989: M*/
991: /*MC
992: KSP_DIVERGED_BREAKDOWN - A breakdown in the Krylov method was detected so the
993: method could not continue to enlarge the Krylov space. Could be due to a singular matrix or
994: preconditioner. In `KSPHPDDM`, this is also returned when some search directions within a block
995: are collinear.
997: Level: beginner
999: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
1000: M*/
1002: /*MC
1003: KSP_DIVERGED_BREAKDOWN_BICG - A breakdown in the `KSPBICG` method was detected so the
1004: method could not continue to enlarge the Krylov space.
1006: Level: beginner
1008: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
1009: M*/
1011: /*MC
1012: KSP_DIVERGED_NONSYMMETRIC - It appears the operator or preconditioner is not
1013: symmetric and this Krylov method (`KSPCG`, `KSPMINRES`, `KSPCR`) requires symmetry
1015: Level: beginner
1017: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
1018: M*/
1020: /*MC
1021: KSP_DIVERGED_INDEFINITE_PC - It appears the preconditioner is indefinite (has both
1022: positive and negative eigenvalues) and this Krylov method (`KSPCG`) requires it to
1023: be symmetric positive definite (SPD).
1025: Level: beginner
1027: Note:
1028: This can happen with the `PCICC` preconditioner, use the options database option `-pc_factor_shift_positive_definite` to force
1029: the `PCICC` preconditioner to generate a positive definite preconditioner
1031: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
1032: M*/
1034: /*MC
1035: KSP_DIVERGED_PC_FAILED - It was not possible to build or use the requested preconditioner. This is usually due to a
1036: zero pivot in a factorization. It can also result from a failure in a subpreconditioner inside a nested preconditioner
1037: such as `PCFIELDSPLIT`.
1039: Level: beginner
1041: Note:
1042: Run with `-ksp_error_if_not_converged` to stop the program when the error is detected and print an error message with details.
1044: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
1045: M*/
1047: /*MC
1048: KSP_DIVERGED_USER - The user has indicated divergence for an arbitrary reason.
1050: Level: beginner
1052: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
1053: M*/
1055: /*MC
1056: KSP_DIVERGED_INNER_SOLVE_FAILED - It was not possible to solve an inner linear system in solvers such as `KSPEKSM`.
1058: Level: beginner
1060: Note:
1061: Run with `-ksp_error_if_not_converged` to stop the program when the error is detected and print an error message with details.
1063: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
1064: M*/
1066: /*MC
1067: KSP_CONVERGED_ITERATING - This flag is returned if `KSPGetConvergedReason()` is called
1068: while `KSPSolve()` is still running.
1070: Level: beginner
1072: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
1073: M*/
1075: /*S
1076: KSPConvergenceTestFn - A prototype of a function used with `KSPSetConvergenceTest()`
1078: Calling Sequence:
1079: + ksp - iterative solver obtained from `KSPCreate()`
1080: . it - iteration number
1081: . rnorm - (estimated) 2-norm of (preconditioned) residual
1082: . reason - the reason why it has converged or diverged
1083: - ctx - optional convergence context, as set by `KSPSetConvergenceTest()`
1085: Level: beginner
1087: .seealso: [](ch_ksp), `KSP`, `KSPSetConvergenceTest()`, `KSPGetConvergenceTest()`
1088: S*/
1089: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPConvergenceTestFn(KSP ksp, PetscInt it, PetscReal rnorm, KSPConvergedReason *reason, PetscCtx ctx);
1091: PETSC_EXTERN PetscErrorCode KSPSetConvergenceTest(KSP, KSPConvergenceTestFn *, void *, PetscCtxDestroyFn *);
1092: PETSC_EXTERN PetscErrorCode KSPGetConvergenceTest(KSP, KSPConvergenceTestFn **, PetscCtxRt, PetscCtxDestroyFn **);
1093: PETSC_EXTERN PetscErrorCode KSPGetAndClearConvergenceTest(KSP, KSPConvergenceTestFn **, PetscCtxRt, PetscCtxDestroyFn **);
1094: PETSC_EXTERN PetscErrorCode KSPGetConvergenceContext(KSP, PetscCtxRt);
1095: PETSC_EXTERN KSPConvergenceTestFn KSPConvergedDefault;
1096: PETSC_EXTERN KSPConvergenceTestFn KSPLSQRConvergedDefault;
1097: PETSC_EXTERN PetscCtxDestroyFn KSPConvergedDefaultDestroy;
1098: PETSC_EXTERN PetscErrorCode KSPConvergedDefaultCreate(void **);
1099: PETSC_EXTERN PetscErrorCode KSPConvergedDefaultSetUIRNorm(KSP);
1100: PETSC_EXTERN PetscErrorCode KSPConvergedDefaultSetUMIRNorm(KSP);
1101: PETSC_EXTERN PetscErrorCode KSPConvergedDefaultSetConvergedMaxits(KSP, PetscBool);
1102: PETSC_EXTERN PetscErrorCode KSPConvergedSkip(KSP, PetscInt, PetscReal, KSPConvergedReason *, void *);
1103: PETSC_EXTERN PetscErrorCode KSPGetConvergedReason(KSP, KSPConvergedReason *);
1104: PETSC_EXTERN PetscErrorCode KSPGetConvergedReasonString(KSP, const char *[]);
1105: PETSC_EXTERN PetscErrorCode KSPComputeConvergenceRate(KSP, PetscReal *, PetscReal *, PetscReal *, PetscReal *);
1106: PETSC_EXTERN PetscErrorCode KSPSetConvergedNegativeCurvature(KSP, PetscBool);
1107: PETSC_EXTERN PetscErrorCode KSPGetConvergedNegativeCurvature(KSP, PetscBool *);
1109: PETSC_DEPRECATED_FUNCTION(3, 5, 0, "KSPConvergedDefault()", ) static inline void KSPDefaultConverged(void)
1110: { /* never called */
1111: }
1112: #define KSPDefaultConverged (KSPDefaultConverged, KSPConvergedDefault)
1113: PETSC_DEPRECATED_FUNCTION(3, 5, 0, "KSPConvergedDefaultDestroy()", ) static inline void KSPDefaultConvergedDestroy(void)
1114: { /* never called */
1115: }
1116: #define KSPDefaultConvergedDestroy (KSPDefaultConvergedDestroy, KSPConvergedDefaultDestroy)
1117: PETSC_DEPRECATED_FUNCTION(3, 5, 0, "KSPConvergedDefaultCreate()", ) static inline void KSPDefaultConvergedCreate(void)
1118: { /* never called */
1119: }
1120: #define KSPDefaultConvergedCreate (KSPDefaultConvergedCreate, KSPConvergedDefaultCreate)
1121: PETSC_DEPRECATED_FUNCTION(3, 5, 0, "KSPConvergedDefaultSetUIRNorm()", ) static inline void KSPDefaultConvergedSetUIRNorm(void)
1122: { /* never called */
1123: }
1124: #define KSPDefaultConvergedSetUIRNorm (KSPDefaultConvergedSetUIRNorm, KSPConvergedDefaultSetUIRNorm)
1125: PETSC_DEPRECATED_FUNCTION(3, 5, 0, "KSPConvergedDefaultSetUMIRNorm()", ) static inline void KSPDefaultConvergedSetUMIRNorm(void)
1126: { /* never called */
1127: }
1128: #define KSPDefaultConvergedSetUMIRNorm (KSPDefaultConvergedSetUMIRNorm, KSPConvergedDefaultSetUMIRNorm)
1129: PETSC_DEPRECATED_FUNCTION(3, 5, 0, "KSPConvergedSkip()", ) static inline void KSPSkipConverged(void)
1130: { /* never called */
1131: }
1132: #define KSPSkipConverged (KSPSkipConverged, KSPConvergedSkip)
1134: PETSC_EXTERN PetscErrorCode KSPComputeOperator(KSP, MatType, Mat *);
1135: PETSC_DEPRECATED_FUNCTION(3, 12, 0, "KSPComputeOperator()", ) static inline PetscErrorCode KSPComputeExplicitOperator(KSP A, Mat *B)
1136: {
1137: return KSPComputeOperator(A, PETSC_NULLPTR, B);
1138: }
1140: /*E
1141: KSPCGType - Determines what type of `KSPCG` to use
1143: Values:
1144: + `KSP_CG_SYMMETRIC` - the matrix is complex symmetric
1145: - `KSP_CG_HERMITIAN` - the matrix is complex Hermitian
1147: Level: beginner
1149: .seealso: [](ch_ksp), `KSPCG`, `KSP`, `KSPCGSetType()`
1150: E*/
1151: typedef enum {
1152: KSP_CG_SYMMETRIC = 0,
1153: KSP_CG_HERMITIAN = 1
1154: } KSPCGType;
1155: PETSC_EXTERN const char *const KSPCGTypes[];
1157: PETSC_EXTERN PetscErrorCode KSPCGSetType(KSP, KSPCGType);
1158: PETSC_EXTERN PetscErrorCode KSPCGUseSingleReduction(KSP, PetscBool);
1160: /*E
1161: KSPCGTRNormType - Norm used for the trust-region constraint in `KSPCG`, `KSPSTCG`, `KSPNASH`, and `KSPGLTR`
1163: Values:
1164: + `KSP_CG_TR_NORM_PRECONDITIONED` - use $\sqrt{x^H M x}$, where the preconditioner applies $M^{-1}$
1165: - `KSP_CG_TR_NORM_UNPRECONDITIONED` - use the Euclidean norm $\sqrt{x^H x}$ (default)
1167: Level: advanced
1169: Note:
1170: These norms measure the solution vector $x$. The residual norm used for convergence is selected independently with `KSPSetNormType()`.
1172: .seealso: [](ch_ksp), `KSP`, `KSPCGSetTRNormType()`, `KSPCGGetTRNormType()`, `KSPCGGetTRSolutionNorm()`, `KSPCGSetRadius()`, `KSPNormType`
1173: E*/
1174: typedef enum {
1175: KSP_CG_TR_NORM_PRECONDITIONED,
1176: KSP_CG_TR_NORM_UNPRECONDITIONED
1177: } KSPCGTRNormType;
1178: PETSC_EXTERN const char *const KSPCGTRNormTypes[];
1180: PETSC_EXTERN PetscErrorCode KSPCGSetTRNormType(KSP, KSPCGTRNormType);
1181: PETSC_EXTERN PetscErrorCode KSPCGGetTRNormType(KSP, KSPCGTRNormType *);
1182: PETSC_EXTERN PetscErrorCode KSPCGSetRadius(KSP, PetscReal);
1183: PETSC_EXTERN PetscErrorCode KSPCGSetObjectiveTarget(KSP, PetscReal);
1184: PETSC_EXTERN PetscErrorCode KSPCGGetTRSolutionNorm(KSP, PetscReal *);
1185: PETSC_DEPRECATED_FUNCTION(3, 27, 0, "KSPCGGetTRSolutionNorm()", ) static inline PetscErrorCode KSPCGGetNormD(KSP ksp, PetscReal *norm)
1186: {
1187: return KSPCGGetTRSolutionNorm(ksp, norm);
1188: }
1189: PETSC_EXTERN PetscErrorCode KSPCGGetObjFcn(KSP, PetscReal *);
1191: PETSC_EXTERN PetscErrorCode KSPGLTRGetMinEig(KSP, PetscReal *);
1192: PETSC_EXTERN PetscErrorCode KSPGLTRGetLambda(KSP, PetscReal *);
1193: PETSC_DEPRECATED_FUNCTION(3, 12, 0, "KSPGLTRGetMinEig()", ) static inline PetscErrorCode KSPCGGLTRGetMinEig(KSP ksp, PetscReal *x)
1194: {
1195: return KSPGLTRGetMinEig(ksp, x);
1196: }
1197: PETSC_DEPRECATED_FUNCTION(3, 12, 0, "KSPGLTRGetLambda()", ) static inline PetscErrorCode KSPCGGLTRGetLambda(KSP ksp, PetscReal *x)
1198: {
1199: return KSPGLTRGetLambda(ksp, x);
1200: }
1202: PETSC_EXTERN PetscErrorCode KSPPythonSetType(KSP, const char[]);
1203: PETSC_EXTERN PetscErrorCode KSPPythonGetType(KSP, const char *[]);
1205: PETSC_EXTERN PetscErrorCode PCPreSolve(PC, KSP);
1206: PETSC_EXTERN PetscErrorCode PCPostSolve(PC, KSP);
1208: PETSC_EXTERN PetscErrorCode KSPMonitorLGRange(KSP, PetscInt, PetscReal, void *);
1210: /*S
1211: PCShellPSolveFn - A function prototype for functions provided to `PCShellSetPreSolve()` and `PCShellSetPostSolve()`
1213: Calling Sequence:
1214: + pc - the preconditioner `PC` context
1215: . ksp - the `KSP` context
1216: . xin - input vector
1217: - xout - output vector
1219: Level: intermediate
1221: .seealso: [](ch_snes), `KSPPSolveFn`, `KSP`, `PCShellSetPreSolve()`, `PCShellSetPostSolve()`
1222: S*/
1223: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode PCShellPSolveFn(PC pc, KSP ksp, Vec xim, Vec xout);
1225: PETSC_EXTERN PetscErrorCode PCShellSetPreSolve(PC, PCShellPSolveFn *);
1226: PETSC_EXTERN PetscErrorCode PCShellSetPostSolve(PC, PCShellPSolveFn *);
1228: /*S
1229: KSPGuess - Abstract PETSc object that manages all initial guess generation methods for Krylov methods.
1231: Level: intermediate
1233: Note:
1234: These methods generate initial guesses based on a series of previous, related, linear solves. For example,
1235: in implicit time-stepping with `TS`.
1237: .seealso: [](ch_ksp), `KSPCreate()`, `KSPGuessSetType()`, `KSPGuessType`
1238: S*/
1239: typedef struct _p_KSPGuess *KSPGuess;
1241: /*J
1242: KSPGuessType - String with the name of a PETSc initial guess approach for Krylov methods.
1244: Values:
1245: + `KSPGUESSFISCHER` - methodology developed by Paul Fischer
1246: - `KSPGUESSPOD` - methodology based on proper orthogonal decomposition (POD)
1248: Options Database Key:
1249: . -ksp_guess_type (fischer|pod) - set the type
1251: Level: intermediate
1253: .seealso: [](ch_ksp), `KSP`, `KSPGuess`, `KSPGuessSetType()`
1254: J*/
1255: typedef const char *KSPGuessType;
1256: #define KSPGUESSFISCHER "fischer"
1257: #define KSPGUESSPOD "pod"
1259: PETSC_EXTERN PetscErrorCode KSPGuessRegister(const char[], PetscErrorCode (*)(KSPGuess));
1260: PETSC_EXTERN PetscErrorCode KSPSetGuess(KSP, KSPGuess);
1261: PETSC_EXTERN PetscErrorCode KSPGetGuess(KSP, KSPGuess *);
1262: PETSC_EXTERN PetscErrorCode KSPGuessView(KSPGuess, PetscViewer);
1263: PETSC_EXTERN PetscErrorCode KSPGuessDestroy(KSPGuess *);
1264: PETSC_EXTERN PetscErrorCode KSPGuessCreate(MPI_Comm, KSPGuess *);
1265: PETSC_EXTERN PetscErrorCode KSPGuessSetType(KSPGuess, KSPGuessType);
1266: PETSC_EXTERN PetscErrorCode KSPGuessGetType(KSPGuess, KSPGuessType *);
1267: PETSC_EXTERN PetscErrorCode KSPGuessSetTolerance(KSPGuess, PetscReal);
1268: PETSC_EXTERN PetscErrorCode KSPGuessSetUp(KSPGuess);
1269: PETSC_EXTERN PetscErrorCode KSPGuessUpdate(KSPGuess, Vec, Vec);
1270: PETSC_EXTERN PetscErrorCode KSPGuessFormGuess(KSPGuess, Vec, Vec);
1271: PETSC_EXTERN PetscErrorCode KSPGuessSetFromOptions(KSPGuess);
1272: PETSC_EXTERN PetscErrorCode KSPGuessFischerSetModel(KSPGuess, PetscInt, PetscInt);
1273: PETSC_EXTERN PetscErrorCode KSPSetUseFischerGuess(KSP, PetscInt, PetscInt);
1274: PETSC_EXTERN PetscErrorCode KSPSetInitialGuessKnoll(KSP, PetscBool);
1275: PETSC_EXTERN PetscErrorCode KSPGetInitialGuessKnoll(KSP, PetscBool *);
1277: /*E
1278: MatSchurComplementAinvType - Determines how to approximate the inverse of the (0,0) block in Schur complement matrix assembly routines
1280: Values:
1281: + `MAT_SCHUR_COMPLEMENT_AINV_DIAG` - invert the diagonal of `A00`
1282: . `MAT_SCHUR_COMPLEMENT_AINV_LUMP` - invert the diagonal matrix containing the row sums of `A00` (mass lumping)
1283: . `MAT_SCHUR_COMPLEMENT_AINV_BLOCK_DIAG` - invert the block diagonal of the matrix, where the blocks are determined by the block size of the matrix
1284: - `MAT_SCHUR_COMPLEMENT_AINV_FULL` - invert the full matrix `A00`
1286: Level: intermediate
1288: Note:
1289: In the documentation this inverse type is indicated with $inv(DIAGFORM(A00))$.
1291: .seealso: `MatSchurComplementGetAinvType()`, `MatSchurComplementSetAinvType()`, `MatSchurComplementGetPmat()`, `MatGetSchurComplement()`,
1292: `MatCreateSchurComplementPmat()`, `MatCreateSchurComplement()`
1293: E*/
1294: typedef enum {
1295: MAT_SCHUR_COMPLEMENT_AINV_DIAG,
1296: MAT_SCHUR_COMPLEMENT_AINV_LUMP,
1297: MAT_SCHUR_COMPLEMENT_AINV_BLOCK_DIAG,
1298: MAT_SCHUR_COMPLEMENT_AINV_FULL
1299: } MatSchurComplementAinvType;
1300: PETSC_EXTERN const char *const MatSchurComplementAinvTypes[];
1302: PETSC_EXTERN PetscErrorCode MatCreateSchurComplement(Mat, Mat, Mat, Mat, Mat, Mat *);
1303: PETSC_EXTERN PetscErrorCode MatSchurComplementGetKSP(Mat, KSP *);
1304: PETSC_EXTERN PetscErrorCode MatSchurComplementSetKSP(Mat, KSP);
1305: PETSC_EXTERN PetscErrorCode MatSchurComplementSetSubMatrices(Mat, Mat, Mat, Mat, Mat, Mat);
1306: PETSC_EXTERN PetscErrorCode MatSchurComplementUpdateSubMatrices(Mat, Mat, Mat, Mat, Mat, Mat);
1307: PETSC_EXTERN PetscErrorCode MatSchurComplementGetSubMatrices(Mat, Mat *, Mat *, Mat *, Mat *, Mat *);
1308: PETSC_EXTERN PetscErrorCode MatSchurComplementSetAinvType(Mat, MatSchurComplementAinvType);
1309: PETSC_EXTERN PetscErrorCode MatSchurComplementGetAinvType(Mat, MatSchurComplementAinvType *);
1310: PETSC_EXTERN PetscErrorCode MatSchurComplementGetPmat(Mat, MatReuse, Mat *);
1311: PETSC_EXTERN PetscErrorCode MatSchurComplementComputeExplicitOperator(Mat, Mat *);
1312: PETSC_EXTERN PetscErrorCode MatGetSchurComplement(Mat, IS, IS, IS, IS, MatReuse, Mat *, MatSchurComplementAinvType, MatReuse, Mat *);
1313: PETSC_EXTERN PetscErrorCode MatCreateSchurComplementPmat(Mat, Mat, Mat, Mat, MatSchurComplementAinvType, MatReuse, Mat *);
1315: PETSC_EXTERN PetscErrorCode MatCreateLMVMDFP(MPI_Comm, PetscInt, PetscInt, Mat *);
1316: PETSC_EXTERN PetscErrorCode MatCreateLMVMBFGS(MPI_Comm, PetscInt, PetscInt, Mat *);
1317: PETSC_EXTERN PetscErrorCode MatCreateLMVMDBFGS(MPI_Comm, PetscInt, PetscInt, Mat *);
1318: PETSC_EXTERN PetscErrorCode MatCreateLMVMDDFP(MPI_Comm, PetscInt, PetscInt, Mat *);
1319: PETSC_EXTERN PetscErrorCode MatCreateLMVMDQN(MPI_Comm, PetscInt, PetscInt, Mat *);
1320: PETSC_EXTERN PetscErrorCode MatCreateLMVMSR1(MPI_Comm, PetscInt, PetscInt, Mat *);
1321: PETSC_EXTERN PetscErrorCode MatCreateLMVMBroyden(MPI_Comm, PetscInt, PetscInt, Mat *);
1322: PETSC_EXTERN PetscErrorCode MatCreateLMVMBadBroyden(MPI_Comm, PetscInt, PetscInt, Mat *);
1323: PETSC_EXTERN PetscErrorCode MatCreateLMVMSymBroyden(MPI_Comm, PetscInt, PetscInt, Mat *);
1324: PETSC_EXTERN PetscErrorCode MatCreateLMVMSymBadBroyden(MPI_Comm, PetscInt, PetscInt, Mat *);
1325: PETSC_EXTERN PetscErrorCode MatCreateLMVMDiagBroyden(MPI_Comm, PetscInt, PetscInt, Mat *);
1327: PETSC_EXTERN PetscErrorCode MatLMVMUpdate(Mat, Vec, Vec);
1328: PETSC_EXTERN PetscErrorCode MatLMVMIsAllocated(Mat, PetscBool *);
1329: PETSC_EXTERN PetscErrorCode MatLMVMAllocate(Mat, Vec, Vec);
1330: PETSC_EXTERN PetscErrorCode MatLMVMReset(Mat, PetscBool);
1331: PETSC_EXTERN PetscErrorCode MatLMVMResetShift(Mat);
1332: PETSC_EXTERN PetscErrorCode MatLMVMClearJ0(Mat);
1333: PETSC_EXTERN PetscErrorCode MatLMVMSetJ0(Mat, Mat);
1334: PETSC_EXTERN PetscErrorCode MatLMVMSetJ0Scale(Mat, PetscReal);
1335: PETSC_EXTERN PetscErrorCode MatLMVMSetJ0Diag(Mat, Vec);
1336: PETSC_EXTERN PetscErrorCode MatLMVMSetJ0PC(Mat, PC);
1337: PETSC_EXTERN PetscErrorCode MatLMVMSetJ0KSP(Mat, KSP);
1338: PETSC_EXTERN PetscErrorCode MatLMVMApplyJ0Fwd(Mat, Vec, Vec);
1339: PETSC_EXTERN PetscErrorCode MatLMVMApplyJ0Inv(Mat, Vec, Vec);
1340: PETSC_EXTERN PetscErrorCode MatLMVMGetLastUpdate(Mat, Vec *, Vec *);
1341: PETSC_EXTERN PetscErrorCode MatLMVMGetJ0(Mat, Mat *);
1342: PETSC_EXTERN PetscErrorCode MatLMVMGetJ0PC(Mat, PC *);
1343: PETSC_EXTERN PetscErrorCode MatLMVMGetJ0KSP(Mat, KSP *);
1344: PETSC_EXTERN PetscErrorCode MatLMVMSetHistorySize(Mat, PetscInt);
1345: PETSC_EXTERN PetscErrorCode MatLMVMGetHistorySize(Mat, PetscInt *);
1346: PETSC_EXTERN PetscErrorCode MatLMVMGetUpdateCount(Mat, PetscInt *);
1347: PETSC_EXTERN PetscErrorCode MatLMVMGetRejectCount(Mat, PetscInt *);
1348: PETSC_EXTERN PetscErrorCode MatLMVMSymBroydenSetDelta(Mat, PetscScalar);
1350: /*E
1351: MatLMVMMultAlgorithm - The type of algorithm used for matrix-vector products and solves used internally by a `MatLMVM` matrix
1353: Values:
1354: + `MAT_LMVM_MULT_RECURSIVE` - Use recursive formulas for products and solves
1355: . `MAT_LMVM_MULT_DENSE` - Use dense formulas for products and solves when possible
1356: - `MAT_LMVM_MULT_COMPACT_DENSE` - The same as `MATLMVM_MULT_DENSE`, but go further and ensure products and solves are computed in compact low-rank update form
1358: Level: advanced
1360: Options Database Keys:
1361: . -mat_lmvm_mult_algorithm (recursive|dense|compact_dense) - the algorithm to use for multiplication
1363: .seealso: [](ch_matrices), `MATLMVM`, `MatLMVMSetMultAlgorithm()`, `MatLMVMGetMultAlgorithm()`
1364: E*/
1365: typedef enum {
1366: MAT_LMVM_MULT_RECURSIVE,
1367: MAT_LMVM_MULT_DENSE,
1368: MAT_LMVM_MULT_COMPACT_DENSE,
1369: } MatLMVMMultAlgorithm;
1371: PETSC_EXTERN const char *const MatLMVMMultAlgorithms[];
1373: PETSC_EXTERN PetscErrorCode MatLMVMSetMultAlgorithm(Mat, MatLMVMMultAlgorithm);
1374: PETSC_EXTERN PetscErrorCode MatLMVMGetMultAlgorithm(Mat, MatLMVMMultAlgorithm *);
1376: /*E
1377: MatLMVMSymBroydenScaleType - Rescaling type for the initial Hessian of a symmetric Broyden matrix.
1379: Values:
1380: + `MAT_LMVM_SYMBROYDEN_SCALE_NONE` - no rescaling
1381: . `MAT_LMVM_SYMBROYDEN_SCALE_SCALAR` - scalar rescaling
1382: . `MAT_LMVM_SYMBROYDEN_SCALE_DIAGONAL` - diagonal rescaling
1383: . `MAT_LMVM_SYMBROYDEN_SCALE_USER` - same as `MAT_LMVM_SYMBROYDN_SCALE_NONE`
1384: - `MAT_LMVM_SYMBROYDEN_SCALE_DECIDE` - let PETSc decide rescaling
1386: Level: intermediate
1388: .seealso: [](ch_matrices), `MATLMVM`, `MatLMVMSymBroydenSetScaleType()`
1389: E*/
1390: typedef enum {
1391: MAT_LMVM_SYMBROYDEN_SCALE_NONE = 0,
1392: MAT_LMVM_SYMBROYDEN_SCALE_SCALAR = 1,
1393: MAT_LMVM_SYMBROYDEN_SCALE_DIAGONAL = 2,
1394: MAT_LMVM_SYMBROYDEN_SCALE_USER = 3,
1395: MAT_LMVM_SYMBROYDEN_SCALE_DECIDE = 4
1396: } MatLMVMSymBroydenScaleType;
1397: PETSC_EXTERN const char *const MatLMVMSymBroydenScaleTypes[];
1399: PETSC_EXTERN PetscErrorCode MatLMVMSymBroydenSetScaleType(Mat, MatLMVMSymBroydenScaleType);
1400: PETSC_EXTERN PetscErrorCode MatLMVMSymBroydenGetPhi(Mat, PetscReal *);
1401: PETSC_EXTERN PetscErrorCode MatLMVMSymBroydenSetPhi(Mat, PetscReal);
1402: PETSC_EXTERN PetscErrorCode MatLMVMSymBadBroydenGetPsi(Mat, PetscReal *);
1403: PETSC_EXTERN PetscErrorCode MatLMVMSymBadBroydenSetPsi(Mat, PetscReal);
1405: /*E
1406: MatLMVMDenseType - Memory storage strategy for dense variants of `MATLMVM`.
1408: Values:
1409: + `MAT_LMVM_DENSE_REORDER` - reorders memory to minimize kernel launch
1410: - `MAT_LMVM_DENSE_INPLACE` - computes inplace to minimize memory movement
1412: Level: intermediate
1414: .seealso: [](ch_matrices), `MatLMVM`, `MatLMVMDenseSetType()`
1415: E*/
1416: typedef enum {
1417: MAT_LMVM_DENSE_REORDER,
1418: MAT_LMVM_DENSE_INPLACE
1419: } MatLMVMDenseType;
1420: PETSC_EXTERN const char *const MatLMVMDenseTypes[];
1422: PETSC_EXTERN PetscErrorCode MatLMVMDenseSetType(Mat, MatLMVMDenseType);
1424: PETSC_EXTERN PetscErrorCode KSPSetDM(KSP, DM);
1426: /*E
1427: KSPDMActive - Indicates if the `DM` attached to the `KSP` should be used to compute the operator, the right-hand side, or the initial guess
1429: Values:
1430: + `KSP_DMACTIVE_OPERATOR` - compute the operator
1431: . `KSP_DMACTIVE_RHS` - compute the right-hand side
1432: . `KSP_DMACTIVE_INITIAL_GUESS` - compute the initial guess
1433: - `KSP_DMACTIVE_ALL` - compute all of them
1435: Level: intermediate
1437: .seealso: [](ch_ksp), `KSP`, `KSPSetDMActive()`, `KSPSetDM()`
1438: E*/
1439: typedef enum {
1440: KSP_DMACTIVE_OPERATOR = 1,
1441: KSP_DMACTIVE_RHS = 2,
1442: KSP_DMACTIVE_INITIAL_GUESS = 4,
1443: KSP_DMACTIVE_ALL = 1 + 2 + 4
1444: } KSPDMActive;
1445: PETSC_EXTERN PetscErrorCode KSPSetDMActive(KSP, KSPDMActive, PetscBool);
1447: PETSC_EXTERN PetscErrorCode KSPGetDM(KSP, DM *);
1448: PETSC_EXTERN PetscErrorCode KSPSetApplicationContext(KSP, PetscCtx);
1449: PETSC_EXTERN PetscErrorCode KSPGetApplicationContext(KSP, PetscCtxRt);
1451: /*S
1452: KSPComputeRHSFn - A prototype of a `KSP` evaluation function that would be passed to `KSPSetComputeRHS()`
1454: Calling Sequence:
1455: + ksp - `ksp` context
1456: . b - output vector
1457: - ctx - [optional] user-defined function context
1459: Level: beginner
1461: .seealso: [](ch_ksp), `KSP`, `KSPSetComputeRHS()`, `SNESGetFunction()`, `KSPComputeInitialGuessFn`, `KSPComputeOperatorsFn`
1462: S*/
1463: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPComputeRHSFn(KSP ksp, Vec b, PetscCtx ctx);
1465: PETSC_EXTERN PetscErrorCode KSPSetComputeRHS(KSP, KSPComputeRHSFn *, void *);
1467: /*S
1468: KSPComputeOperatorsFn - A prototype of a `KSP` evaluation function that would be passed to `KSPSetComputeOperators()`
1470: Calling Sequence:
1471: + ksp - `KSP` context
1472: . A - the operator that defines the linear system
1473: . P - an operator from which to build the preconditioner (often the same as `A`)
1474: - ctx - [optional] user-defined function context
1476: Level: beginner
1478: .seealso: [](ch_ksp), `KSP`, `KSPSetComputeRHS()`, `SNESGetFunction()`, `KSPComputeRHSFn`, `KSPComputeInitialGuessFn`
1479: S*/
1480: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPComputeOperatorsFn(KSP ksp, Mat A, Mat P, PetscCtx ctx);
1482: PETSC_EXTERN PetscErrorCode KSPSetComputeOperators(KSP, KSPComputeOperatorsFn, void *);
1484: /*S
1485: KSPCreateOperatorsFn - A prototype of a `KSP` operator creation function that would be passed to `DMKSPSetCreateOperators()`
1487: Calling Sequence:
1488: + ksp - `KSP` context
1489: . A - the created operator that defines the linear system
1490: . P - the created operator from which to build the preconditioner, often the same as `A`
1491: - ctx - [optional] user-defined function context
1493: Level: developer
1495: Notes:
1496: The returned matrices are owned by the caller, similar to `DMCreateMatrix()`.
1498: `A` and `P` may be the same object. In such a case, users do not need to increase the reference count of `A`. If `P` is not returned, then we assume it is the same of `A`.
1500: .seealso: [](ch_ksp), `DMKSPSetCreateOperators()`, `DMKSPGetCreateOperators()`, `KSPComputeOperatorsFn`, `KSPSetOperators()`
1501: S*/
1502: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPCreateOperatorsFn(KSP ksp, Mat *A, Mat *P, PetscCtx ctx);
1504: /*S
1505: KSPComputeInitialGuessFn - A prototype of a `KSP` evaluation function that would be passed to `KSPSetComputeInitialGuess()`
1507: Calling Sequence:
1508: + ksp - `ksp` context
1509: . x - output vector
1510: - ctx - [optional] user-defined function context
1512: Level: beginner
1514: .seealso: [](ch_ksp), `KSP`, `KSPSetComputeInitialGuess()`, `SNESGetFunction()`, `KSPComputeRHSFn`, `KSPComputeOperatorsFn`
1515: S*/
1516: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPComputeInitialGuessFn(KSP ksp, Vec x, PetscCtx ctx);
1518: PETSC_EXTERN PetscErrorCode KSPSetComputeInitialGuess(KSP, KSPComputeInitialGuessFn *, void *);
1519: PETSC_EXTERN PetscErrorCode DMKSPSetComputeOperators(DM, KSPComputeOperatorsFn *, void *);
1520: PETSC_EXTERN PetscErrorCode DMKSPGetComputeOperators(DM, KSPComputeOperatorsFn **, void *);
1521: PETSC_EXTERN PetscErrorCode DMKSPSetCreateOperators(DM, KSPCreateOperatorsFn *, void *);
1522: PETSC_EXTERN PetscErrorCode DMKSPGetCreateOperators(DM, KSPCreateOperatorsFn **, void *);
1523: PETSC_EXTERN PetscErrorCode DMKSPSetComputeRHS(DM, KSPComputeRHSFn *, void *);
1524: PETSC_EXTERN PetscErrorCode DMKSPGetComputeRHS(DM, KSPComputeRHSFn **, void *);
1525: PETSC_EXTERN PetscErrorCode DMKSPSetComputeInitialGuess(DM, KSPComputeInitialGuessFn *, void *);
1526: PETSC_EXTERN PetscErrorCode DMKSPGetComputeInitialGuess(DM, KSPComputeInitialGuessFn **, void *);
1528: PETSC_EXTERN PetscErrorCode DMGlobalToLocalSolve(DM, Vec, Vec);
1529: PETSC_EXTERN PetscErrorCode DMSwarmProjectFields(DM, DM, PetscInt, const char *[], Vec[], ScatterMode);
1530: PETSC_EXTERN PetscErrorCode DMSwarmProjectGradientFields(DM, DM, PetscInt, const char *[], Vec[], ScatterMode);
1532: PETSC_EXTERN PetscErrorCode DMAdaptInterpolator(DM, DM, Mat, KSP, Mat, Mat, Mat *, void *);
1533: PETSC_EXTERN PetscErrorCode DMCheckInterpolator(DM, Mat, Mat, Mat, PetscReal);
1535: PETSC_EXTERN PetscErrorCode PCBJKOKKOSSetKSP(PC, KSP);
1536: PETSC_EXTERN PetscErrorCode PCBJKOKKOSGetKSP(PC, KSP *);
1538: PETSC_EXTERN PetscErrorCode DMCopyDMKSP(DM, DM);
1540: #include <petscdstypes.h>
1541: PETSC_EXTERN PetscErrorCode DMProjectField(DM, PetscReal, Vec, PetscPointFn **, InsertMode, Vec);