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"
94: /* Logging support */
95: PETSC_EXTERN PetscClassId KSP_CLASSID;
96: PETSC_EXTERN PetscClassId KSPGUESS_CLASSID;
97: PETSC_EXTERN PetscClassId DMKSP_CLASSID;
99: PETSC_EXTERN PetscErrorCode KSPCreate(MPI_Comm, KSP *);
100: PETSC_EXTERN PetscErrorCode KSPSetType(KSP, KSPType);
101: PETSC_EXTERN PetscErrorCode KSPGetType(KSP, KSPType *);
102: PETSC_EXTERN PetscErrorCode KSPSetUp(KSP);
103: PETSC_EXTERN PetscErrorCode KSPSetUpOnBlocks(KSP);
104: PETSC_EXTERN PetscErrorCode KSPSolve(KSP, Vec, Vec);
105: PETSC_EXTERN PetscErrorCode KSPSolveTranspose(KSP, Vec, Vec);
106: PETSC_EXTERN PetscErrorCode KSPSetUseExplicitTranspose(KSP, PetscBool);
107: PETSC_EXTERN PetscErrorCode KSPMatSolve(KSP, Mat, Mat);
108: PETSC_EXTERN PetscErrorCode KSPMatSolveTranspose(KSP, Mat, Mat);
109: PETSC_EXTERN PetscErrorCode KSPSetMatSolveBatchSize(KSP, PetscInt);
110: PETSC_DEPRECATED_FUNCTION(3, 15, 0, "KSPSetMatSolveBatchSize()", ) static inline PetscErrorCode KSPSetMatSolveBlockSize(KSP ksp, PetscInt n)
111: {
112: return KSPSetMatSolveBatchSize(ksp, n);
113: }
114: PETSC_EXTERN PetscErrorCode KSPGetMatSolveBatchSize(KSP, PetscInt *);
115: PETSC_DEPRECATED_FUNCTION(3, 15, 0, "KSPGetMatSolveBatchSize()", ) static inline PetscErrorCode KSPGetMatSolveBlockSize(KSP ksp, PetscInt *n)
116: {
117: return KSPGetMatSolveBatchSize(ksp, n);
118: }
119: PETSC_EXTERN PetscErrorCode KSPReset(KSP);
120: PETSC_EXTERN PetscErrorCode KSPResetViewers(KSP);
121: PETSC_EXTERN PetscErrorCode KSPDestroy(KSP *);
122: PETSC_EXTERN PetscErrorCode KSPSetReusePreconditioner(KSP, PetscBool);
123: PETSC_EXTERN PetscErrorCode KSPGetReusePreconditioner(KSP, PetscBool *);
124: PETSC_EXTERN PetscErrorCode KSPSetSkipPCSetFromOptions(KSP, PetscBool);
125: PETSC_EXTERN PetscErrorCode KSPCheckSolve(KSP, PC, Vec);
127: PETSC_EXTERN PetscFunctionList KSPList;
128: PETSC_EXTERN PetscFunctionList KSPGuessList;
129: PETSC_EXTERN PetscFunctionList KSPMonitorList;
130: PETSC_EXTERN PetscFunctionList KSPMonitorCreateList;
131: PETSC_EXTERN PetscFunctionList KSPMonitorDestroyList;
132: PETSC_EXTERN PetscErrorCode KSPRegister(const char[], PetscErrorCode (*)(KSP));
134: /*S
135: KSPMonitorRegisterFn - A function prototype for functions provided to `KSPMonitorRegister()`
137: Calling Sequence:
138: + ksp - iterative solver obtained from `KSPCreate()`
139: . it - iteration number
140: . rnorm - (estimated) 2-norm of (preconditioned) residual
141: - ctx - `PetscViewerAndFormat` object
143: Level: beginner
145: Note:
146: This is a `KSPMonitorFn` specialized for a context of `PetscViewerAndFormat`
148: .seealso: [](ch_snes), `KSP`, `KSPMonitorSet()`, `KSPMonitorRegister()`, `KSPMonitorFn`, `KSPMonitorRegisterCreateFn`, `KSPMonitorRegisterDestroyFn`
149: S*/
150: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPMonitorRegisterFn(KSP ksp, PetscInt it, PetscReal rnorm, PetscViewerAndFormat *ctx);
152: /*S
153: KSPMonitorRegisterCreateFn - A function prototype for functions that do the creation when provided to `KSPMonitorRegister()`
155: Calling Sequence:
156: + viewer - the viewer to be used with the `KSPMonitorRegisterFn`
157: . format - the format of the viewer
158: . ctx - a context for the monitor
159: - result - a `PetscViewerAndFormat` object
161: Level: beginner
163: .seealso: [](ch_snes), `KSPMonitorRegisterFn`, `KSP`, `KSPMonitorSet()`, `KSPMonitorRegister()`, `KSPMonitorFn`, `KSPMonitorRegisterDestroyFn`
164: S*/
165: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPMonitorRegisterCreateFn(PetscViewer viewer, PetscViewerFormat format, void *ctx, PetscViewerAndFormat **result);
167: /*S
168: KSPMonitorRegisterDestroyFn - A function prototype for functions that do the after use destruction when provided to `KSPMonitorRegister()`
170: Calling Sequence:
171: . vf - a `PetscViewerAndFormat` object to be destroyed, including any context
173: Level: beginner
175: .seealso: [](ch_snes), `KSPMonitorRegisterFn`, `KSP`, `KSPMonitorSet()`, `KSPMonitorRegister()`, `KSPMonitorFn`, `KSPMonitorRegisterCreateFn`
176: S*/
177: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPMonitorRegisterDestroyFn(PetscViewerAndFormat **result);
179: PETSC_EXTERN PetscErrorCode KSPMonitorRegister(const char[], PetscViewerType, PetscViewerFormat, KSPMonitorRegisterFn *, KSPMonitorRegisterCreateFn *, KSPMonitorRegisterDestroyFn *);
181: PETSC_EXTERN PetscErrorCode KSPSetPCSide(KSP, PCSide);
182: PETSC_EXTERN PetscErrorCode KSPGetPCSide(KSP, PCSide *);
183: PETSC_EXTERN PetscErrorCode KSPSetTolerances(KSP, PetscReal, PetscReal, PetscReal, PetscInt);
184: PETSC_EXTERN PetscErrorCode KSPGetTolerances(KSP, PetscReal *, PetscReal *, PetscReal *, PetscInt *);
185: PETSC_EXTERN PetscErrorCode KSPSetMinimumIterations(KSP, PetscInt);
186: PETSC_EXTERN PetscErrorCode KSPGetMinimumIterations(KSP, PetscInt *);
187: PETSC_EXTERN PetscErrorCode KSPSetInitialGuessNonzero(KSP, PetscBool);
188: PETSC_EXTERN PetscErrorCode KSPGetInitialGuessNonzero(KSP, PetscBool *);
189: PETSC_EXTERN PetscErrorCode KSPSetErrorIfNotConverged(KSP, PetscBool);
190: PETSC_EXTERN PetscErrorCode KSPGetErrorIfNotConverged(KSP, PetscBool *);
191: PETSC_EXTERN PetscErrorCode KSPSetComputeEigenvalues(KSP, PetscBool);
192: PETSC_EXTERN PetscErrorCode KSPSetComputeRitz(KSP, PetscBool);
193: PETSC_EXTERN PetscErrorCode KSPGetComputeEigenvalues(KSP, PetscBool *);
194: PETSC_EXTERN PetscErrorCode KSPSetComputeSingularValues(KSP, PetscBool);
195: PETSC_EXTERN PetscErrorCode KSPGetComputeSingularValues(KSP, PetscBool *);
196: PETSC_EXTERN PetscErrorCode KSPGetRhs(KSP, Vec *);
197: PETSC_EXTERN PetscErrorCode KSPGetSolution(KSP, Vec *);
198: PETSC_EXTERN PetscErrorCode KSPGetResidualNorm(KSP, PetscReal *);
199: PETSC_EXTERN PetscErrorCode KSPGetIterationNumber(KSP, PetscInt *);
200: PETSC_EXTERN PetscErrorCode KSPGetTotalIterations(KSP, PetscInt *);
201: PETSC_EXTERN PetscErrorCode KSPCreateVecs(KSP, PetscInt, Vec **, PetscInt, Vec **);
202: PETSC_DEPRECATED_FUNCTION(3, 6, 0, "KSPCreateVecs()", ) static inline PetscErrorCode KSPGetVecs(KSP ksp, PetscInt n, Vec **x, PetscInt m, Vec **y)
203: {
204: return KSPCreateVecs(ksp, n, x, m, y);
205: }
207: /*S
208: KSPPSolveFn - A function prototype for functions provided to `KSPSetPreSolve()` and `KSPSetPostSolve()`
210: Calling Sequence:
211: + ksp - the `KSP` context
212: . rhs - the right-hand side vector
213: . x - the solution vector
214: - ctx - optional context that was provided with `KSPSetPreSolve()` or `KSPSetPostSolve()`
216: Level: intermediate
218: .seealso: [](ch_snes), `KSP`, `KSPSetPreSolve()`, `KSPSetPostSolve()`, `PCShellPSolveFn`
219: S*/
220: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPPSolveFn(KSP ksp, Vec rhs, Vec x, void *ctx);
222: PETSC_EXTERN PetscErrorCode KSPSetPreSolve(KSP, KSPPSolveFn *, void *);
223: PETSC_EXTERN PetscErrorCode KSPSetPostSolve(KSP, KSPPSolveFn *, void *);
225: PETSC_EXTERN PetscErrorCode KSPSetPC(KSP, PC);
226: PETSC_EXTERN PetscErrorCode KSPGetPC(KSP, PC *);
227: PETSC_EXTERN PetscErrorCode KSPSetNestLevel(KSP, PetscInt);
228: PETSC_EXTERN PetscErrorCode KSPGetNestLevel(KSP, PetscInt *);
230: /*S
231: KSPMonitorFn - A function prototype for functions provided to `KSPMonitorSet()`
233: Calling Sequence:
234: + ksp - iterative solver obtained from `KSPCreate()`
235: . it - iteration number
236: . rnorm - (estimated) 2-norm of (preconditioned) residual
237: - ctx - optional monitoring context, as provided with `KSPMonitorSet()`
239: Level: beginner
241: .seealso: [](ch_snes), `KSP`, `KSPMonitorSet()`
242: S*/
243: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPMonitorFn(KSP ksp, PetscInt it, PetscReal rnorm, void *ctx);
245: PETSC_EXTERN PetscErrorCode KSPMonitor(KSP, PetscInt, PetscReal);
246: PETSC_EXTERN PetscErrorCode KSPMonitorSet(KSP, KSPMonitorFn *, void *, PetscCtxDestroyFn *);
247: PETSC_EXTERN PetscErrorCode KSPMonitorCancel(KSP);
248: PETSC_EXTERN PetscErrorCode KSPGetMonitorContext(KSP, void *);
249: PETSC_EXTERN PetscErrorCode KSPGetResidualHistory(KSP, const PetscReal *[], PetscInt *);
250: PETSC_EXTERN PetscErrorCode KSPSetResidualHistory(KSP, PetscReal[], PetscCount, PetscBool);
251: PETSC_EXTERN PetscErrorCode KSPGetErrorHistory(KSP, const PetscReal *[], PetscInt *);
252: PETSC_EXTERN PetscErrorCode KSPSetErrorHistory(KSP, PetscReal[], PetscCount, PetscBool);
254: PETSC_EXTERN PetscErrorCode KSPBuildSolutionDefault(KSP, Vec, Vec *);
255: PETSC_EXTERN PetscErrorCode KSPBuildResidualDefault(KSP, Vec, Vec, Vec *);
256: PETSC_EXTERN PetscErrorCode KSPDestroyDefault(KSP);
257: PETSC_EXTERN PetscErrorCode KSPSetWorkVecs(KSP, PetscInt);
259: PETSC_EXTERN PetscErrorCode PCKSPGetKSP(PC, KSP *);
260: PETSC_EXTERN PetscErrorCode PCKSPSetKSP(PC, KSP);
261: PETSC_EXTERN PetscErrorCode PCBJacobiGetSubKSP(PC, PetscInt *, PetscInt *, KSP *[]);
262: PETSC_EXTERN PetscErrorCode PCASMGetSubKSP(PC, PetscInt *, PetscInt *, KSP *[]);
263: PETSC_EXTERN PetscErrorCode PCGASMGetSubKSP(PC, PetscInt *, PetscInt *, KSP *[]);
264: PETSC_EXTERN PetscErrorCode PCPatchGetSubKSP(PC, PetscInt *, KSP *[]);
265: PETSC_EXTERN PetscErrorCode PCFieldSplitGetSubKSP(PC, PetscInt *, KSP *[]);
266: PETSC_EXTERN PetscErrorCode PCFieldSplitSchurGetSubKSP(PC, PetscInt *, KSP *[]);
267: PETSC_EXTERN PetscErrorCode PCMGGetSmoother(PC, PetscInt, KSP *);
268: PETSC_EXTERN PetscErrorCode PCMGGetSmootherDown(PC, PetscInt, KSP *);
269: PETSC_EXTERN PetscErrorCode PCMGGetSmootherUp(PC, PetscInt, KSP *);
270: PETSC_EXTERN PetscErrorCode PCMGGetCoarseSolve(PC, KSP *);
271: PETSC_EXTERN PetscErrorCode PCGalerkinGetKSP(PC, KSP *);
272: PETSC_EXTERN PetscErrorCode PCDeflationGetCoarseKSP(PC, KSP *);
274: /*S
275: PCMGCoarseSpaceConstructorFn - A function prototype for functions registered with `PCMGRegisterCoarseSpaceConstructor()`
277: Calling Sequence:
278: + pc - The `PC` object
279: . l - The multigrid level, 0 is the coarse level
280: . dm - The `DM` for this level
281: . smooth - The level smoother
282: . Nc - The size of the coarse space
283: . initGuess - Basis for an initial guess for the space
284: - coarseSp - A basis for the computed coarse space
286: Level: beginner
288: .seealso: [](ch_ksp), `PCMGRegisterCoarseSpaceConstructor()`, `PCMGGetCoarseSpaceConstructor()`
289: S*/
290: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode PCMGCoarseSpaceConstructorFn(PC pc, PetscInt l, DM dm, KSP smooth, PetscInt Nc, Mat initGuess, Mat *coarseSp);
292: PETSC_EXTERN PetscFunctionList PCMGCoarseList;
293: PETSC_EXTERN PetscErrorCode PCMGRegisterCoarseSpaceConstructor(const char[], PCMGCoarseSpaceConstructorFn *);
294: PETSC_EXTERN PetscErrorCode PCMGGetCoarseSpaceConstructor(const char[], PCMGCoarseSpaceConstructorFn **);
296: PETSC_EXTERN PetscErrorCode KSPBuildSolution(KSP, Vec, Vec *);
297: PETSC_EXTERN PetscErrorCode KSPBuildResidual(KSP, Vec, Vec, Vec *);
299: /*E
300: KSPChebyshevKind - Which kind of Chebyshev polynomial to use with `KSPCHEBYSHEV`
302: Values:
303: + `KSP_CHEBYSHEV_FIRST` - "classic" first-kind Chebyshev polynomial
304: . `KSP_CHEBYSHEV_FOURTH` - fourth-kind Chebyshev polynomial
305: - `KSP_CHEBYSHEV_OPT_FOURTH` - optimized fourth-kind Chebyshev polynomial
307: Level: intermediate
309: .seealso: [](ch_ksp), `KSPCHEBYSHEV`, `KSPChebyshevSetKind()`, `KSPChebyshevGetKind()`
310: E*/
311: typedef enum {
312: KSP_CHEBYSHEV_FIRST,
313: KSP_CHEBYSHEV_FOURTH,
314: KSP_CHEBYSHEV_OPT_FOURTH
315: } KSPChebyshevKind;
317: PETSC_EXTERN PetscErrorCode KSPRichardsonSetScale(KSP, PetscReal);
318: PETSC_EXTERN PetscErrorCode KSPRichardsonSetSelfScale(KSP, PetscBool);
319: PETSC_EXTERN PetscErrorCode KSPChebyshevSetEigenvalues(KSP, PetscReal, PetscReal);
320: PETSC_EXTERN PetscErrorCode KSPChebyshevEstEigSet(KSP, PetscReal, PetscReal, PetscReal, PetscReal);
321: PETSC_EXTERN PetscErrorCode KSPChebyshevEstEigSetUseNoisy(KSP, PetscBool);
322: PETSC_EXTERN PetscErrorCode KSPChebyshevSetKind(KSP, KSPChebyshevKind);
323: PETSC_EXTERN PetscErrorCode KSPChebyshevGetKind(KSP, KSPChebyshevKind *);
324: PETSC_EXTERN PetscErrorCode KSPChebyshevEstEigGetKSP(KSP, KSP *);
325: PETSC_EXTERN PetscErrorCode KSPComputeExtremeSingularValues(KSP, PetscReal *, PetscReal *);
326: PETSC_EXTERN PetscErrorCode KSPComputeEigenvalues(KSP, PetscInt, PetscReal[], PetscReal[], PetscInt *);
327: PETSC_EXTERN PetscErrorCode KSPComputeEigenvaluesExplicitly(KSP, PetscInt, PetscReal[], PetscReal[]);
328: PETSC_EXTERN PetscErrorCode KSPComputeRitz(KSP, PetscBool, PetscBool, PetscInt *, Vec[], PetscReal[], PetscReal[]);
330: /*E
332: KSPFCDTruncationType - Define how stored directions are used to orthogonalize in flexible conjugate directions (FCD) methods
334: Values:
335: + `KSP_FCD_TRUNC_TYPE_STANDARD` - uses all (up to mmax) stored directions
336: - `KSP_FCD_TRUNC_TYPE_NOTAY` - uses the last max(1,mod(i,mmax)) stored directions at iteration i=0,1..
338: Level: intermediate
340: .seealso: [](ch_ksp), `KSP`, `KSPFCG`, `KSPPIPEFCG`, `KSPPIPEGCR`, `KSPFCGSetTruncationType()`, `KSPFCGGetTruncationType()`
341: E*/
342: typedef enum {
343: KSP_FCD_TRUNC_TYPE_STANDARD,
344: KSP_FCD_TRUNC_TYPE_NOTAY
345: } KSPFCDTruncationType;
346: PETSC_EXTERN const char *const KSPFCDTruncationTypes[];
348: PETSC_EXTERN PetscErrorCode KSPFCGSetMmax(KSP, PetscInt);
349: PETSC_EXTERN PetscErrorCode KSPFCGGetMmax(KSP, PetscInt *);
350: PETSC_EXTERN PetscErrorCode KSPFCGSetNprealloc(KSP, PetscInt);
351: PETSC_EXTERN PetscErrorCode KSPFCGGetNprealloc(KSP, PetscInt *);
352: PETSC_EXTERN PetscErrorCode KSPFCGSetTruncationType(KSP, KSPFCDTruncationType);
353: PETSC_EXTERN PetscErrorCode KSPFCGGetTruncationType(KSP, KSPFCDTruncationType *);
355: PETSC_EXTERN PetscErrorCode KSPPIPEFCGSetMmax(KSP, PetscInt);
356: PETSC_EXTERN PetscErrorCode KSPPIPEFCGGetMmax(KSP, PetscInt *);
357: PETSC_EXTERN PetscErrorCode KSPPIPEFCGSetNprealloc(KSP, PetscInt);
358: PETSC_EXTERN PetscErrorCode KSPPIPEFCGGetNprealloc(KSP, PetscInt *);
359: PETSC_EXTERN PetscErrorCode KSPPIPEFCGSetTruncationType(KSP, KSPFCDTruncationType);
360: PETSC_EXTERN PetscErrorCode KSPPIPEFCGGetTruncationType(KSP, KSPFCDTruncationType *);
362: PETSC_EXTERN PetscErrorCode KSPPIPEGCRSetMmax(KSP, PetscInt);
363: PETSC_EXTERN PetscErrorCode KSPPIPEGCRGetMmax(KSP, PetscInt *);
364: PETSC_EXTERN PetscErrorCode KSPPIPEGCRSetNprealloc(KSP, PetscInt);
365: PETSC_EXTERN PetscErrorCode KSPPIPEGCRGetNprealloc(KSP, PetscInt *);
366: PETSC_EXTERN PetscErrorCode KSPPIPEGCRSetTruncationType(KSP, KSPFCDTruncationType);
367: PETSC_EXTERN PetscErrorCode KSPPIPEGCRGetTruncationType(KSP, KSPFCDTruncationType *);
368: PETSC_EXTERN PetscErrorCode KSPPIPEGCRSetUnrollW(KSP, PetscBool);
369: PETSC_EXTERN PetscErrorCode KSPPIPEGCRGetUnrollW(KSP, PetscBool *);
371: /*S
372: KSPFlexibleModifyPCFn - A prototype of a function used to modify the preconditioner during the use of flexible `KSP` methods, such as `KSPFGMRES`
374: Calling Sequence:
375: + ksp - the `KSP` context being used.
376: . total_its - the total number of iterations that have occurred.
377: . local_its - the number of iterations since last restart if applicable
378: . res_norm - the current residual norm
379: - ctx - optional context variable set with `KSPFlexibleSetModifyPC()`, `KSPPIPEGCRSetModifyPC()`, `KSPGCRSetModifyPC()`, `KSPFGMRESSetModifyPC()`
381: Level: beginner
383: .seealso: [](ch_ksp), `KSP`, `KSPFlexibleSetModifyPC()`, `KSPPIPEGCRSetModifyPC()`, `KSPGCRSetModifyPC()`, `KSPFGMRESSetModifyPC()`
384: S*/
385: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPFlexibleModifyPCFn(KSP ksp, PetscInt total_its, PetscInt local_its, PetscReal res_norm, void *ctx);
387: PETSC_EXTERN PetscErrorCode KSPFlexibleSetModifyPC(KSP, KSPFlexibleModifyPCFn *, void *, PetscCtxDestroyFn *);
388: PETSC_EXTERN PetscErrorCode KSPPIPEGCRSetModifyPC(KSP, KSPFlexibleModifyPCFn *, void *, PetscCtxDestroyFn *);
390: PETSC_EXTERN PetscErrorCode KSPGMRESSetRestart(KSP, PetscInt);
391: PETSC_EXTERN PetscErrorCode KSPGMRESGetRestart(KSP, PetscInt *);
392: PETSC_EXTERN PetscErrorCode KSPGMRESSetHapTol(KSP, PetscReal);
393: PETSC_EXTERN PetscErrorCode KSPGMRESSetBreakdownTolerance(KSP, PetscReal);
395: PETSC_EXTERN PetscErrorCode KSPGMRESSetPreAllocateVectors(KSP);
396: PETSC_EXTERN PetscErrorCode KSPGMRESSetOrthogonalization(KSP, PetscErrorCode (*)(KSP, PetscInt));
397: PETSC_EXTERN PetscErrorCode KSPGMRESGetOrthogonalization(KSP, PetscErrorCode (**)(KSP, PetscInt));
398: PETSC_EXTERN PetscErrorCode KSPGMRESModifiedGramSchmidtOrthogonalization(KSP, PetscInt);
399: PETSC_EXTERN PetscErrorCode KSPGMRESClassicalGramSchmidtOrthogonalization(KSP, PetscInt);
401: PETSC_EXTERN PetscErrorCode KSPLGMRESSetAugDim(KSP, PetscInt);
402: PETSC_EXTERN PetscErrorCode KSPLGMRESSetConstant(KSP);
404: PETSC_EXTERN PetscErrorCode KSPPIPEFGMRESSetShift(KSP, PetscScalar);
406: PETSC_EXTERN PetscErrorCode KSPGCRSetRestart(KSP, PetscInt);
407: PETSC_EXTERN PetscErrorCode KSPGCRGetRestart(KSP, PetscInt *);
408: PETSC_EXTERN PetscErrorCode KSPGCRSetModifyPC(KSP, KSPFlexibleModifyPCFn *, void *, PetscCtxDestroyFn *);
410: PETSC_EXTERN PetscErrorCode KSPMINRESSetRadius(KSP, PetscReal);
411: PETSC_EXTERN PetscErrorCode KSPMINRESGetUseQLP(KSP, PetscBool *);
412: PETSC_EXTERN PetscErrorCode KSPMINRESSetUseQLP(KSP, PetscBool);
414: PETSC_EXTERN PetscErrorCode KSPFETIDPGetInnerBDDC(KSP, PC *);
415: PETSC_EXTERN PetscErrorCode KSPFETIDPSetInnerBDDC(KSP, PC);
416: PETSC_EXTERN PetscErrorCode KSPFETIDPGetInnerKSP(KSP, KSP *);
417: PETSC_EXTERN PetscErrorCode KSPFETIDPSetPressureOperator(KSP, Mat);
419: PETSC_EXTERN PetscErrorCode KSPHPDDMSetDeflationMat(KSP, Mat);
420: PETSC_EXTERN PetscErrorCode KSPHPDDMGetDeflationMat(KSP, Mat *);
421: #if PetscDefined(HAVE_HPDDM)
422: PETSC_DEPRECATED_FUNCTION(3, 18, 0, "KSPHPDDMSetDeflationMat()", ) static inline PetscErrorCode KSPHPDDMSetDeflationSpace(KSP ksp, Mat U)
423: {
424: return KSPHPDDMSetDeflationMat(ksp, U);
425: }
426: PETSC_DEPRECATED_FUNCTION(3, 18, 0, "KSPHPDDMGetDeflationMat()", ) static inline PetscErrorCode KSPHPDDMGetDeflationSpace(KSP ksp, Mat *U)
427: {
428: return KSPHPDDMGetDeflationMat(ksp, U);
429: }
430: #endif
431: PETSC_DEPRECATED_FUNCTION(3, 14, 0, "KSPMatSolve()", ) static inline PetscErrorCode KSPHPDDMMatSolve(KSP ksp, Mat B, Mat X)
432: {
433: return KSPMatSolve(ksp, B, X);
434: }
435: /*E
436: KSPHPDDMType - Type of Krylov method used by `KSPHPDDM`
438: Values:
439: + `KSP_HPDDM_TYPE_GMRES` (default) - Generalized Minimal Residual method
440: . `KSP_HPDDM_TYPE_BGMRES` - block GMRES
441: . `KSP_HPDDM_TYPE_CG` - Conjugate Gradient
442: . `KSP_HPDDM_TYPE_BCG` - block CG
443: . `KSP_HPDDM_TYPE_GCRODR` - Generalized Conjugate Residual method with inner Orthogonalization and Deflated Restarting
444: . `KSP_HPDDM_TYPE_BGCRODR` - block GCRODR
445: . `KSP_HPDDM_TYPE_BFBCG` - breakdown-free BCG
446: - `KSP_HPDDM_TYPE_PREONLY` - apply the preconditioner only
448: Level: intermediate
450: .seealso: [](ch_ksp), `KSPHPDDM`, `KSPHPDDMSetType()`
451: E*/
452: typedef enum {
453: KSP_HPDDM_TYPE_GMRES = 0,
454: KSP_HPDDM_TYPE_BGMRES = 1,
455: KSP_HPDDM_TYPE_CG = 2,
456: KSP_HPDDM_TYPE_BCG = 3,
457: KSP_HPDDM_TYPE_GCRODR = 4,
458: KSP_HPDDM_TYPE_BGCRODR = 5,
459: KSP_HPDDM_TYPE_BFBCG = 6,
460: KSP_HPDDM_TYPE_PREONLY = 7
461: } KSPHPDDMType;
462: PETSC_EXTERN const char *const KSPHPDDMTypes[];
464: /*E
465: KSPHPDDMPrecision - Precision of Krylov bases used by `KSPHPDDM`
467: Values:
468: + `KSP_HPDDM_PRECISION_HALF` - default when PETSc is configured `--with-precision=__fp16`
469: . `KSP_HPDDM_PRECISION_SINGLE` - default when PETSc is configured `--with-precision=single`
470: . `KSP_HPDDM_PRECISION_DOUBLE` - default when PETSc is configured `--with-precision=double`
471: - `KSP_HPDDM_PRECISION_QUADRUPLE` - default when PETSc is configured `--with-precision=__float128`
473: Level: intermediate
475: .seealso: [](ch_ksp), `KSP`, `KSPHPDDM`
476: E*/
477: typedef enum {
478: KSP_HPDDM_PRECISION_HALF = 0,
479: KSP_HPDDM_PRECISION_SINGLE = 1,
480: KSP_HPDDM_PRECISION_DOUBLE = 2,
481: KSP_HPDDM_PRECISION_QUADRUPLE = 3
482: } KSPHPDDMPrecision;
483: PETSC_EXTERN PetscErrorCode KSPHPDDMSetType(KSP, KSPHPDDMType);
484: PETSC_EXTERN PetscErrorCode KSPHPDDMGetType(KSP, KSPHPDDMType *);
486: /*E
487: KSPGMRESCGSRefinementType - How the classical (unmodified) Gram-Schmidt is performed in the GMRES solvers
489: Values:
490: + `KSP_GMRES_CGS_REFINE_NEVER` - one step of classical Gram-Schmidt
491: . `KSP_GMRES_CGS_REFINE_IFNEEDED` - a second step is performed if the first step does not satisfy some criteria
492: - `KSP_GMRES_CGS_REFINE_ALWAYS` - always perform two steps
494: Level: advanced
496: .seealso: [](ch_ksp), `KSP`, `KSPGMRES`, `KSPGMRESClassicalGramSchmidtOrthogonalization()`, `KSPGMRESSetOrthogonalization()`,
497: `KSPGMRESGetOrthogonalization()`,
498: `KSPGMRESSetCGSRefinementType()`, `KSPGMRESGetCGSRefinementType()`, `KSPGMRESModifiedGramSchmidtOrthogonalization()`
499: E*/
500: typedef enum {
501: KSP_GMRES_CGS_REFINE_NEVER,
502: KSP_GMRES_CGS_REFINE_IFNEEDED,
503: KSP_GMRES_CGS_REFINE_ALWAYS
504: } KSPGMRESCGSRefinementType;
505: PETSC_EXTERN const char *const KSPGMRESCGSRefinementTypes[];
507: /*MC
508: KSP_GMRES_CGS_REFINE_NEVER - Do the classical (unmodified) Gram-Schmidt process
510: Level: advanced
512: Note:
513: Possibly unstable, but the fastest to compute
515: .seealso: [](ch_ksp), `KSPGMRES`, `KSPGMRESCGSRefinementType`, `KSPGMRESClassicalGramSchmidtOrthogonalization()`, `KSPGMRESSetOrthogonalization()`,
516: `KSP`, `KSPGMRESGetOrthogonalization()`,
517: `KSPGMRESSetCGSRefinementType()`, `KSPGMRESGetCGSRefinementType()`, `KSP_GMRES_CGS_REFINE_IFNEEDED`, `KSP_GMRES_CGS_REFINE_ALWAYS`,
518: `KSPGMRESModifiedGramSchmidtOrthogonalization()`
519: M*/
521: /*MC
522: KSP_GMRES_CGS_REFINE_IFNEEDED - Do the classical (unmodified) Gram-Schmidt process and one step of
523: iterative refinement if an estimate of the orthogonality of the resulting vectors indicates
524: poor orthogonality.
526: Level: advanced
528: Note:
529: This is slower than `KSP_GMRES_CGS_REFINE_NEVER` because it requires an extra norm computation to
530: estimate the orthogonality but is more stable.
532: .seealso: [](ch_ksp), `KSPGMRES`, `KSPGMRESCGSRefinementType`, `KSPGMRESClassicalGramSchmidtOrthogonalization()`, `KSPGMRESSetOrthogonalization()`,
533: `KSP`, `KSPGMRESGetOrthogonalization()`,
534: `KSPGMRESSetCGSRefinementType()`, `KSPGMRESGetCGSRefinementType()`, `KSP_GMRES_CGS_REFINE_NEVER`, `KSP_GMRES_CGS_REFINE_ALWAYS`,
535: `KSPGMRESModifiedGramSchmidtOrthogonalization()`
536: M*/
538: /*MC
539: KSP_GMRES_CGS_REFINE_ALWAYS - Do two steps of the classical (unmodified) Gram-Schmidt process.
541: Level: advanced
543: Notes:
544: This is roughly twice the cost of `KSP_GMRES_CGS_REFINE_NEVER` because it performs the process twice
545: but it saves the extra norm calculation needed by `KSP_GMRES_CGS_REFINE_IFNEEDED`.
547: You should only use this if you absolutely know that the iterative refinement is needed.
549: .seealso: [](ch_ksp), `KSPGMRES`, `KSPGMRESCGSRefinementType`, `KSPGMRESClassicalGramSchmidtOrthogonalization()`, `KSPGMRESSetOrthogonalization()`,
550: `KSP`, `KSPGMRESGetOrthogonalization()`,
551: `KSPGMRESSetCGSRefinementType()`, `KSPGMRESGetCGSRefinementType()`, `KSP_GMRES_CGS_REFINE_IFNEEDED`, `KSP_GMRES_CGS_REFINE_ALWAYS`,
552: `KSPGMRESModifiedGramSchmidtOrthogonalization()`
553: M*/
555: PETSC_EXTERN PetscErrorCode KSPGMRESSetCGSRefinementType(KSP, KSPGMRESCGSRefinementType);
556: PETSC_EXTERN PetscErrorCode KSPGMRESGetCGSRefinementType(KSP, KSPGMRESCGSRefinementType *);
558: PETSC_EXTERN KSPFlexibleModifyPCFn KSPFGMRESModifyPCNoChange;
559: PETSC_EXTERN KSPFlexibleModifyPCFn KSPFGMRESModifyPCKSP;
560: PETSC_EXTERN PetscErrorCode KSPFGMRESSetModifyPC(KSP, KSPFlexibleModifyPCFn *, void *, PetscCtxDestroyFn *);
562: PETSC_EXTERN PetscErrorCode KSPQCGSetTrustRegionRadius(KSP, PetscReal);
563: PETSC_EXTERN PetscErrorCode KSPQCGGetQuadratic(KSP, PetscReal *);
564: PETSC_EXTERN PetscErrorCode KSPQCGGetTrialStepNorm(KSP, PetscReal *);
566: PETSC_EXTERN PetscErrorCode KSPBCGSLSetXRes(KSP, PetscReal);
567: PETSC_EXTERN PetscErrorCode KSPBCGSLSetPol(KSP, PetscBool);
568: PETSC_EXTERN PetscErrorCode KSPBCGSLSetEll(KSP, PetscInt);
569: PETSC_EXTERN PetscErrorCode KSPBCGSLSetUsePseudoinverse(KSP, PetscBool);
571: PETSC_EXTERN PetscErrorCode KSPSetFromOptions(KSP);
572: PETSC_EXTERN PetscErrorCode KSPResetFromOptions(KSP);
574: PETSC_EXTERN PetscErrorCode KSPMonitorSetFromOptions(KSP, const char[], const char[], void *);
575: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorResidual;
576: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorResidualView;
577: PETSC_DEPRECATED_FUNCTION(3, 23, 0, "KSPMonitorResidualDraw()", ) static inline PetscErrorCode KSPMonitorResidualDraw(KSP ksp, PetscInt n, PetscReal rnorm, PetscViewerAndFormat *vf)
578: {
579: return KSPMonitorResidualView(ksp, n, rnorm, vf);
580: }
581: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorResidualDrawLG;
582: PETSC_EXTERN PetscErrorCode KSPMonitorResidualDrawLGCreate(PetscViewer, PetscViewerFormat, void *, PetscViewerAndFormat **);
583: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorResidualShort;
584: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorResidualRange;
585: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorTrueResidual;
586: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorTrueResidualView;
587: PETSC_DEPRECATED_FUNCTION(3, 23, 0, "KSPMonitorTrueResidualDraw()", ) static inline PetscErrorCode KSPMonitorTrueResidualDraw(KSP ksp, PetscInt n, PetscReal rnorm, PetscViewerAndFormat *vf)
588: {
589: return KSPMonitorTrueResidualView(ksp, n, rnorm, vf);
590: }
591: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorTrueResidualDrawLG;
592: PETSC_EXTERN PetscErrorCode KSPMonitorTrueResidualDrawLGCreate(PetscViewer, PetscViewerFormat, void *, PetscViewerAndFormat **);
593: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorTrueResidualMax;
594: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorError;
595: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorErrorDraw;
596: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorErrorDrawLG;
597: PETSC_EXTERN PetscErrorCode KSPMonitorErrorDrawLGCreate(PetscViewer, PetscViewerFormat, void *, PetscViewerAndFormat **);
598: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorSolution;
599: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorSolutionDraw;
600: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorSolutionDrawLG;
601: PETSC_EXTERN PetscErrorCode KSPMonitorSolutionDrawLGCreate(PetscViewer, PetscViewerFormat, void *, PetscViewerAndFormat **);
602: PETSC_EXTERN KSPMonitorRegisterFn KSPMonitorSingularValue;
603: PETSC_EXTERN PetscErrorCode KSPMonitorSingularValueCreate(PetscViewer, PetscViewerFormat, void *, PetscViewerAndFormat **);
604: PETSC_DEPRECATED_FUNCTION(3, 15, 0, "KSPMonitorResidual()", ) static inline PetscErrorCode KSPMonitorDefault(KSP ksp, PetscInt n, PetscReal rnorm, PetscViewerAndFormat *vf)
605: {
606: return KSPMonitorResidual(ksp, n, rnorm, vf);
607: }
608: PETSC_DEPRECATED_FUNCTION(3, 15, 0, "KSPMonitorTrueResidual()", ) static inline PetscErrorCode KSPMonitorTrueResidualNorm(KSP ksp, PetscInt n, PetscReal rnorm, PetscViewerAndFormat *vf)
609: {
610: return KSPMonitorTrueResidual(ksp, n, rnorm, vf);
611: }
612: PETSC_DEPRECATED_FUNCTION(3, 15, 0, "KSPMonitorTrueResidualMax()", ) static inline PetscErrorCode KSPMonitorTrueResidualMaxNorm(KSP ksp, PetscInt n, PetscReal rnorm, PetscViewerAndFormat *vf)
613: {
614: return KSPMonitorTrueResidualMax(ksp, n, rnorm, vf);
615: }
617: PETSC_EXTERN PetscErrorCode KSPGMRESMonitorKrylov(KSP, PetscInt, PetscReal, void *);
618: PETSC_EXTERN PetscErrorCode KSPMonitorDynamicTolerance(KSP, PetscInt, PetscReal, void *);
619: PETSC_EXTERN PetscErrorCode KSPMonitorDynamicToleranceDestroy(void **);
620: PETSC_EXTERN PetscErrorCode KSPMonitorDynamicToleranceCreate(void *);
621: PETSC_EXTERN PetscErrorCode KSPMonitorDynamicToleranceSetCoefficient(void *, PetscReal);
622: PETSC_EXTERN PetscErrorCode KSPMonitorSAWs(KSP, PetscInt, PetscReal, void *);
623: PETSC_EXTERN PetscErrorCode KSPMonitorSAWsCreate(KSP, void **);
624: PETSC_EXTERN PetscErrorCode KSPMonitorSAWsDestroy(void **);
626: PETSC_EXTERN PetscErrorCode KSPUnwindPreconditioner(KSP, Vec, Vec);
627: PETSC_EXTERN PetscErrorCode KSPInitialResidual(KSP, Vec, Vec, Vec, Vec, Vec);
629: PETSC_EXTERN PetscErrorCode KSPSetOperators(KSP, Mat, Mat);
630: PETSC_EXTERN PetscErrorCode KSPGetOperators(KSP, Mat *, Mat *);
631: PETSC_EXTERN PetscErrorCode KSPGetOperatorsSet(KSP, PetscBool *, PetscBool *);
632: PETSC_EXTERN PetscErrorCode KSPSetOptionsPrefix(KSP, const char[]);
633: PETSC_EXTERN PetscErrorCode KSPAppendOptionsPrefix(KSP, const char[]);
634: PETSC_EXTERN PetscErrorCode KSPGetOptionsPrefix(KSP, const char *[]);
636: PETSC_EXTERN PetscErrorCode KSPSetDiagonalScale(KSP, PetscBool);
637: PETSC_EXTERN PetscErrorCode KSPGetDiagonalScale(KSP, PetscBool *);
638: PETSC_EXTERN PetscErrorCode KSPSetDiagonalScaleFix(KSP, PetscBool);
639: PETSC_EXTERN PetscErrorCode KSPGetDiagonalScaleFix(KSP, PetscBool *);
641: /*S
642: KSPConvergedReasonViewFn - A prototype of a function used with `KSPConvergedReasonViewSet()`
644: Calling Sequence:
645: + ksp - the `KSP` object whose `KSPConvergedReason` is to be viewed
646: - ctx - context used by the function, set with `KSPConvergedReasonViewSet()`
648: Level: beginner
650: .seealso: [](ch_ksp), `KSP`, `KSPConvergedReasonView()`, `KSPConvergedReasonViewSet()`, `KSPConvergedReasonViewFromOptions()`, `KSPView()`
651: S*/
652: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPConvergedReasonViewFn(KSP ksp, void *ctx);
654: PETSC_EXTERN PetscErrorCode KSPView(KSP, PetscViewer);
655: PETSC_EXTERN PetscErrorCode KSPLoad(KSP, PetscViewer);
656: PETSC_EXTERN PetscErrorCode KSPViewFromOptions(KSP, PetscObject, const char[]);
657: PETSC_EXTERN PetscErrorCode KSPConvergedReasonView(KSP, PetscViewer);
658: PETSC_EXTERN PetscErrorCode KSPConvergedReasonViewSet(KSP, KSPConvergedReasonViewFn *, void *, PetscCtxDestroyFn *);
659: PETSC_EXTERN PetscErrorCode KSPConvergedReasonViewFromOptions(KSP);
660: PETSC_EXTERN PetscErrorCode KSPConvergedReasonViewCancel(KSP);
661: PETSC_EXTERN PetscErrorCode KSPConvergedRateView(KSP, PetscViewer);
663: PETSC_DEPRECATED_FUNCTION(3, 14, 0, "KSPConvergedReasonView()", ) static inline PetscErrorCode KSPReasonView(KSP ksp, PetscViewer v)
664: {
665: return KSPConvergedReasonView(ksp, v);
666: }
667: PETSC_DEPRECATED_FUNCTION(3, 14, 0, "KSPConvergedReasonViewFromOptions()", ) static inline PetscErrorCode KSPReasonViewFromOptions(KSP ksp)
668: {
669: return KSPConvergedReasonViewFromOptions(ksp);
670: }
672: #define KSP_FILE_CLASSID 1211223
674: PETSC_EXTERN PetscErrorCode KSPLSQRSetExactMatNorm(KSP, PetscBool);
675: PETSC_EXTERN PetscErrorCode KSPLSQRSetComputeStandardErrorVec(KSP, PetscBool);
676: PETSC_EXTERN PetscErrorCode KSPLSQRGetStandardErrorVec(KSP, Vec *);
677: PETSC_EXTERN PetscErrorCode KSPLSQRGetNorms(KSP, PetscReal *, PetscReal *);
678: PETSC_EXTERN KSPMonitorRegisterFn KSPLSQRMonitorResidual;
679: PETSC_EXTERN KSPMonitorRegisterFn KSPLSQRMonitorResidualDrawLG;
680: PETSC_EXTERN PetscErrorCode KSPLSQRMonitorResidualDrawLGCreate(PetscViewer, PetscViewerFormat, void *, PetscViewerAndFormat **);
682: PETSC_EXTERN PetscErrorCode PCRedundantGetKSP(PC, KSP *);
683: PETSC_EXTERN PetscErrorCode PCRedistributeGetKSP(PC, KSP *);
684: PETSC_EXTERN PetscErrorCode PCTelescopeGetKSP(PC, KSP *);
685: PETSC_EXTERN PetscErrorCode PCMPIGetKSP(PC, KSP *);
687: /*E
688: KSPNormType - Norm calculated by the `KSP` and passed in the Krylov convergence
689: test routines.
691: Values:
692: + `KSP_NORM_DEFAULT` - use the default for the current `KSPType`
693: . `KSP_NORM_NONE` - use no norm calculation
694: . `KSP_NORM_PRECONDITIONED` - use the preconditioned residual norm
695: . `KSP_NORM_UNPRECONDITIONED` - use the unpreconditioned residual norm
696: - `KSP_NORM_NATURAL` - use the natural norm (the norm induced by the linear operator)
698: Level: advanced
700: Note:
701: Each solver only supports a subset of these and some may support different ones
702: depending on whether left or right preconditioning is used, see `KSPSetPCSide()`
704: .seealso: [](ch_ksp), `KSP`, `PCSide`, `KSPSolve()`, `KSPGetConvergedReason()`, `KSPSetNormType()`,
705: `KSPSetConvergenceTest()`, `KSPSetPCSide()`, `KSP_NORM_DEFAULT`, `KSP_NORM_NONE`, `KSP_NORM_PRECONDITIONED`, `KSP_NORM_UNPRECONDITIONED`, `KSP_NORM_NATURAL`
706: E*/
707: typedef enum {
708: KSP_NORM_DEFAULT = -1,
709: KSP_NORM_NONE = 0,
710: KSP_NORM_PRECONDITIONED = 1,
711: KSP_NORM_UNPRECONDITIONED = 2,
712: KSP_NORM_NATURAL = 3
713: } KSPNormType;
714: #define KSP_NORM_MAX (KSP_NORM_NATURAL + 1)
715: PETSC_EXTERN const char *const *const KSPNormTypes;
717: /*MC
718: KSP_NORM_NONE - Do not compute a norm during the Krylov process. This will
719: possibly save some computation but means the convergence test cannot
720: be based on a norm of a residual etc.
722: Level: advanced
724: Note:
725: Some Krylov methods need to compute a residual norm (such as `KPSGMRES`) and then this option is ignored
727: .seealso: [](ch_ksp), `KSPNormType`, `KSP`, `KSPSetNormType()`, `KSP_NORM_PRECONDITIONED`, `KSP_NORM_UNPRECONDITIONED`, `KSP_NORM_NATURAL`
728: M*/
730: /*MC
731: KSP_NORM_PRECONDITIONED - Compute the norm of the preconditioned residual B*(b - A*x), if left preconditioning, and pass that to the
732: convergence test routine.
734: Level: advanced
736: .seealso: [](ch_ksp), `KSPNormType`, `KSP`, `KSPSetNormType()`, `KSP_NORM_NONE`, `KSP_NORM_UNPRECONDITIONED`, `KSP_NORM_NATURAL`, `KSPSetConvergenceTest()`
737: M*/
739: /*MC
740: KSP_NORM_UNPRECONDITIONED - Compute the norm of the true residual (b - A*x) and pass that to the
741: convergence test routine.
743: Level: advanced
745: .seealso: [](ch_ksp), `KSPNormType`, `KSP`, `KSPSetNormType()`, `KSP_NORM_NONE`, `KSP_NORM_PRECONDITIONED`, `KSP_NORM_NATURAL`, `KSPSetConvergenceTest()`
746: M*/
748: /*MC
749: KSP_NORM_NATURAL - Compute the 'natural norm' of residual sqrt((b - A*x)*B*(b - A*x)) and pass that to the
750: convergence test routine. This is only supported by `KSPCG`, `KSPCR`, `KSPCGNE`, `KSPCGS`, `KSPFCG`, `KSPPIPEFCG`, `KSPPIPEGCR`
752: Level: advanced
754: .seealso: [](ch_ksp), `KSPNormType`, `KSP`, `KSPSetNormType()`, `KSP_NORM_NONE`, `KSP_NORM_PRECONDITIONED`, `KSP_NORM_UNPRECONDITIONED`, `KSPSetConvergenceTest()`
755: M*/
757: PETSC_EXTERN PetscErrorCode KSPSetNormType(KSP, KSPNormType);
758: PETSC_EXTERN PetscErrorCode KSPGetNormType(KSP, KSPNormType *);
759: PETSC_EXTERN PetscErrorCode KSPSetSupportedNorm(KSP, KSPNormType, PCSide, PetscInt);
760: PETSC_EXTERN PetscErrorCode KSPSetCheckNormIteration(KSP, PetscInt);
761: PETSC_EXTERN PetscErrorCode KSPSetLagNorm(KSP, PetscBool);
763: #define KSP_CONVERGED_CG_NEG_CURVE_DEPRECATED KSP_CONVERGED_CG_NEG_CURVE PETSC_DEPRECATED_ENUM(3, 19, 0, "KSP_CONVERGED_NEG_CURVE", )
764: #define KSP_CONVERGED_CG_CONSTRAINED_DEPRECATED KSP_CONVERGED_CG_CONSTRAINED PETSC_DEPRECATED_ENUM(3, 19, 0, "KSP_CONVERGED_STEP_LENGTH", )
765: #define KSP_CONVERGED_RTOL_NORMAL_DEPRECATED KSP_CONVERGED_RTOL_NORMAL PETSC_DEPRECATED_ENUM(3, 24, 0, "KSP_CONVERGED_RTOL_NORMAL_EQUATIONS", )
766: #define KSP_CONVERGED_ATOL_NORMAL_DEPRECATED KSP_CONVERGED_ATOL_NORMAL PETSC_DEPRECATED_ENUM(3, 24, 0, "KSP_CONVERGED_ATOL_NORMAL_EQUATIONS", )
767: /*E
768: KSPConvergedReason - reason a Krylov method was determined to have converged or diverged
770: Values:
771: + `KSP_CONVERGED_RTOL_NORMAL_EQUATIONS` - requested decrease in the residual of the normal equations, for `KSPLSQR`
772: . `KSP_CONVERGED_ATOL_NORMAL_EQUATIONS` - requested absolute value in the residual of the normal equations, for `KSPLSQR`
773: . `KSP_CONVERGED_RTOL` - requested decrease in the residual
774: . `KSP_CONVERGED_ATOL` - requested absolute value in the residual
775: . `KSP_CONVERGED_ITS` - requested number of iterations
776: . `KSP_CONVERGED_NEG_CURVE` - see note below
777: . `KSP_CONVERGED_STEP_LENGTH` - see note below
778: . `KSP_CONVERGED_HAPPY_BREAKDOWN` - happy breakdown (meaning early convergence of the `KSPType` occurred).
779: . `KSP_CONVERGED_USER` - the user has indicated convergence for an arbitrary reason
780: . `KSP_DIVERGED_NULL` - breakdown when solving the Hessenberg system within `KSPGMRES`
781: . `KSP_DIVERGED_ITS` - requested number of iterations
782: . `KSP_DIVERGED_DTOL` - large increase in the residual norm indicating the solution is diverging
783: . `KSP_DIVERGED_BREAKDOWN` - breakdown in the Krylov method
784: . `KSP_DIVERGED_BREAKDOWN_BICG` - breakdown in the `KSPBCGS` Krylov method
785: . `KSP_DIVERGED_NONSYMMETRIC` - the operator or preonditioner was not symmetric for a `KSPType` that requires symmetry
786: . `KSP_DIVERGED_INDEFINITE_PC` - the preconditioner was indefinite for a `KSPType` that requires it be definite, such as `KSPCG`
787: . `KSP_DIVERGED_NANORINF` - a not a number of infinity was detected in a vector during the computation
788: . `KSP_DIVERGED_INDEFINITE_MAT` - the operator was indefinite for a `KSPType` that requires it be definite, such as `KSPCG`
789: . `KSP_DIVERGED_PC_FAILED` - the action of the preconditioner failed for some reason
790: - `KSP_DIVERGED_USER` - the user has indicated divergence for an arbitrary reason
792: Level: beginner
794: Note:
795: The values `KSP_CONVERGED_NEG_CURVE`, and `KSP_CONVERGED_STEP_LENGTH` are returned only by `KSPCG`, `KSPMINRES` and by
796: the special `KSPNASH`, `KSPSTCG`, and `KSPGLTR` solvers which are used by the `SNESNEWTONTR` (trust region) solver.
798: Developer Note:
799: The string versions of these are `KSPConvergedReasons`; if you change
800: any of the values here also change them that array of names.
802: .seealso: [](ch_ksp), `KSP`, `KSPSolve()`, `KSPGetConvergedReason()`, `KSPSetTolerances()`, `KSPConvergedReasonView()`
803: E*/
804: typedef enum { /* converged */
805: KSP_CONVERGED_RTOL_NORMAL_DEPRECATED = 1,
806: KSP_CONVERGED_RTOL_NORMAL_EQUATIONS = 1,
807: KSP_CONVERGED_ATOL_NORMAL_DEPRECATED = 9,
808: KSP_CONVERGED_ATOL_NORMAL_EQUATIONS = 9,
809: KSP_CONVERGED_RTOL = 2,
810: KSP_CONVERGED_ATOL = 3,
811: KSP_CONVERGED_ITS = 4,
812: KSP_CONVERGED_NEG_CURVE = 5,
813: KSP_CONVERGED_CG_NEG_CURVE_DEPRECATED = 5,
814: KSP_CONVERGED_CG_CONSTRAINED_DEPRECATED = 6,
815: KSP_CONVERGED_STEP_LENGTH = 6,
816: KSP_CONVERGED_HAPPY_BREAKDOWN = 7,
817: KSP_CONVERGED_USER = 8,
818: /* diverged */
819: KSP_DIVERGED_NULL = -2,
820: KSP_DIVERGED_ITS = -3,
821: KSP_DIVERGED_DTOL = -4,
822: KSP_DIVERGED_BREAKDOWN = -5,
823: KSP_DIVERGED_BREAKDOWN_BICG = -6,
824: KSP_DIVERGED_NONSYMMETRIC = -7,
825: KSP_DIVERGED_INDEFINITE_PC = -8,
826: KSP_DIVERGED_NANORINF = -9,
827: KSP_DIVERGED_INDEFINITE_MAT = -10,
828: KSP_DIVERGED_PC_FAILED = -11,
829: KSP_DIVERGED_PCSETUP_FAILED_DEPRECATED = -11,
830: KSP_DIVERGED_USER = -12,
832: KSP_CONVERGED_ITERATING = 0
833: } KSPConvergedReason;
834: PETSC_EXTERN const char *const *KSPConvergedReasons;
836: /*MC
837: KSP_CONVERGED_RTOL - $||r|| \le rtol*||b||$ or $rtol*||b - A*x_0||$ if `KSPConvergedDefaultSetUIRNorm()` was called
839: Level: beginner
841: Notes:
842: See `KSPNormType` and `KSPSetNormType()` for possible norms that may be used. By default
843: for left preconditioning it is the 2-norm of the preconditioned residual, and the
844: 2-norm of the residual for right preconditioning
846: See also `KSP_CONVERGED_ATOL` which may apply before this tolerance.
848: .seealso: [](ch_ksp), `KSPNormType`, `KSP_CONVERGED_ATOL`, `KSP_DIVERGED_DTOL`, `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
849: M*/
851: /*MC
852: KSP_CONVERGED_ATOL - $||r|| \le atol$
854: Level: beginner
856: Notes:
857: See `KSPNormType` and `KSPSetNormType()` for possible norms that may be used. By default
858: for left preconditioning it is the 2-norm of the preconditioned residual, and the
859: 2-norm of the residual for right preconditioning
861: See also `KSP_CONVERGED_RTOL` which may apply before this tolerance.
863: .seealso: [](ch_ksp), `KSPNormType`, `KSP_CONVERGED_RTOL`, `KSP_DIVERGED_DTOL`, `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
864: M*/
866: /*MC
867: KSP_DIVERGED_DTOL - $||r|| \ge dtol*||b||$
869: Level: beginner
871: Note:
872: See `KSPNormType` and `KSPSetNormType()` for possible norms that may be used. By default
873: for left preconditioning it is the 2-norm of the preconditioned residual, and the
874: 2-norm of the residual for right preconditioning
876: .seealso: [](ch_ksp), `KSPNormType`, `KSP_CONVERGED_ATOL`, `KSP_CONVERGED_RTOL`, `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
877: M*/
879: /*MC
880: KSP_DIVERGED_ITS - Ran out of iterations before any convergence criteria was
881: reached
883: Level: beginner
885: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
886: M*/
888: /*MC
889: KSP_CONVERGED_ITS - Used by the `KSPPREONLY` solver after the single iteration of
890: the preconditioner is applied. Also used when the `KSPConvergedSkip()` convergence
891: test routine is set in `KSP`.
893: Level: beginner
895: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
896: M*/
898: /*MC
899: KSP_DIVERGED_BREAKDOWN - A breakdown in the Krylov method was detected so the
900: method could not continue to enlarge the Krylov space. Could be due to a singular matrix or
901: preconditioner. In `KSPHPDDM`, this is also returned when some search directions within a block
902: are collinear.
904: Level: beginner
906: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
907: M*/
909: /*MC
910: KSP_DIVERGED_BREAKDOWN_BICG - A breakdown in the `KSPBICG` method was detected so the
911: method could not continue to enlarge the Krylov space.
913: Level: beginner
915: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
916: M*/
918: /*MC
919: KSP_DIVERGED_NONSYMMETRIC - It appears the operator or preconditioner is not
920: symmetric and this Krylov method (`KSPCG`, `KSPMINRES`, `KSPCR`) requires symmetry
922: Level: beginner
924: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
925: M*/
927: /*MC
928: KSP_DIVERGED_INDEFINITE_PC - It appears the preconditioner is indefinite (has both
929: positive and negative eigenvalues) and this Krylov method (`KSPCG`) requires it to
930: be symmetric positive definite (SPD).
932: Level: beginner
934: Note:
935: This can happen with the `PCICC` preconditioner, use the options database option `-pc_factor_shift_positive_definite` to force
936: the `PCICC` preconditioner to generate a positive definite preconditioner
938: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
939: M*/
941: /*MC
942: KSP_DIVERGED_PC_FAILED - It was not possible to build or use the requested preconditioner. This is usually due to a
943: zero pivot in a factorization. It can also result from a failure in a subpreconditioner inside a nested preconditioner
944: such as `PCFIELDSPLIT`.
946: Level: beginner
948: Note:
949: Run with `-ksp_error_if_not_converged` to stop the program when the error is detected and print an error message with details.
951: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
952: M*/
954: /*MC
955: KSP_CONVERGED_ITERATING - This flag is returned if `KSPGetConvergedReason()` is called
956: while `KSPSolve()` is still running.
958: Level: beginner
960: .seealso: [](ch_ksp), `KSPSolve()`, `KSPGetConvergedReason()`, `KSPConvergedReason`, `KSPSetTolerances()`
961: M*/
963: /*S
964: KSPConvergenceTestFn - A prototype of a function used with `KSPSetConvergenceTest()`
966: Calling Sequence:
967: + ksp - iterative solver obtained from `KSPCreate()`
968: . it - iteration number
969: . rnorm - (estimated) 2-norm of (preconditioned) residual
970: . reason - the reason why it has converged or diverged
971: - ctx - optional convergence context, as set by `KSPSetConvergenceTest()`
973: Level: beginner
975: .seealso: [](ch_ksp), `KSP`, `KSPSetConvergenceTest()`, `KSPGetConvergenceTest()`
976: S*/
977: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPConvergenceTestFn(KSP ksp, PetscInt it, PetscReal rnorm, KSPConvergedReason *reason, void *ctx);
979: PETSC_EXTERN PetscErrorCode KSPSetConvergenceTest(KSP, KSPConvergenceTestFn *, void *, PetscCtxDestroyFn *);
980: PETSC_EXTERN PetscErrorCode KSPGetConvergenceTest(KSP, KSPConvergenceTestFn **, void **, PetscCtxDestroyFn **);
981: PETSC_EXTERN PetscErrorCode KSPGetAndClearConvergenceTest(KSP, KSPConvergenceTestFn **, void **, PetscCtxDestroyFn **);
982: PETSC_EXTERN PetscErrorCode KSPGetConvergenceContext(KSP, void *);
983: PETSC_EXTERN KSPConvergenceTestFn KSPConvergedDefault;
984: PETSC_EXTERN KSPConvergenceTestFn KSPLSQRConvergedDefault;
985: PETSC_EXTERN PetscCtxDestroyFn KSPConvergedDefaultDestroy;
986: PETSC_EXTERN PetscErrorCode KSPConvergedDefaultCreate(void **);
987: PETSC_EXTERN PetscErrorCode KSPConvergedDefaultSetUIRNorm(KSP);
988: PETSC_EXTERN PetscErrorCode KSPConvergedDefaultSetUMIRNorm(KSP);
989: PETSC_EXTERN PetscErrorCode KSPConvergedDefaultSetConvergedMaxits(KSP, PetscBool);
990: PETSC_EXTERN PetscErrorCode KSPConvergedSkip(KSP, PetscInt, PetscReal, KSPConvergedReason *, void *);
991: PETSC_EXTERN PetscErrorCode KSPGetConvergedReason(KSP, KSPConvergedReason *);
992: PETSC_EXTERN PetscErrorCode KSPGetConvergedReasonString(KSP, const char *[]);
993: PETSC_EXTERN PetscErrorCode KSPComputeConvergenceRate(KSP, PetscReal *, PetscReal *, PetscReal *, PetscReal *);
994: PETSC_EXTERN PetscErrorCode KSPSetConvergedNegativeCurvature(KSP, PetscBool);
995: PETSC_EXTERN PetscErrorCode KSPGetConvergedNegativeCurvature(KSP, PetscBool *);
997: PETSC_DEPRECATED_FUNCTION(3, 5, 0, "KSPConvergedDefault()", ) static inline void KSPDefaultConverged(void)
998: { /* never called */
999: }
1000: #define KSPDefaultConverged (KSPDefaultConverged, KSPConvergedDefault)
1001: PETSC_DEPRECATED_FUNCTION(3, 5, 0, "KSPConvergedDefaultDestroy()", ) static inline void KSPDefaultConvergedDestroy(void)
1002: { /* never called */
1003: }
1004: #define KSPDefaultConvergedDestroy (KSPDefaultConvergedDestroy, KSPConvergedDefaultDestroy)
1005: PETSC_DEPRECATED_FUNCTION(3, 5, 0, "KSPConvergedDefaultCreate()", ) static inline void KSPDefaultConvergedCreate(void)
1006: { /* never called */
1007: }
1008: #define KSPDefaultConvergedCreate (KSPDefaultConvergedCreate, KSPConvergedDefaultCreate)
1009: PETSC_DEPRECATED_FUNCTION(3, 5, 0, "KSPConvergedDefaultSetUIRNorm()", ) static inline void KSPDefaultConvergedSetUIRNorm(void)
1010: { /* never called */
1011: }
1012: #define KSPDefaultConvergedSetUIRNorm (KSPDefaultConvergedSetUIRNorm, KSPConvergedDefaultSetUIRNorm)
1013: PETSC_DEPRECATED_FUNCTION(3, 5, 0, "KSPConvergedDefaultSetUMIRNorm()", ) static inline void KSPDefaultConvergedSetUMIRNorm(void)
1014: { /* never called */
1015: }
1016: #define KSPDefaultConvergedSetUMIRNorm (KSPDefaultConvergedSetUMIRNorm, KSPConvergedDefaultSetUMIRNorm)
1017: PETSC_DEPRECATED_FUNCTION(3, 5, 0, "KSPConvergedSkip()", ) static inline void KSPSkipConverged(void)
1018: { /* never called */
1019: }
1020: #define KSPSkipConverged (KSPSkipConverged, KSPConvergedSkip)
1022: PETSC_EXTERN PetscErrorCode KSPComputeOperator(KSP, MatType, Mat *);
1023: PETSC_DEPRECATED_FUNCTION(3, 12, 0, "KSPComputeOperator()", ) static inline PetscErrorCode KSPComputeExplicitOperator(KSP A, Mat *B)
1024: {
1025: return KSPComputeOperator(A, PETSC_NULLPTR, B);
1026: }
1028: /*E
1029: KSPCGType - Determines what type of `KSPCG` to use
1031: Values:
1032: + `KSP_CG_SYMMETRIC` - the matrix is complex symmetric
1033: - `KSP_CG_HERMITIAN` - the matrix is complex Hermitian
1035: Level: beginner
1037: .seealso: [](ch_ksp), `KSPCG`, `KSP`, `KSPCGSetType()`
1038: E*/
1039: typedef enum {
1040: KSP_CG_SYMMETRIC = 0,
1041: KSP_CG_HERMITIAN = 1
1042: } KSPCGType;
1043: PETSC_EXTERN const char *const KSPCGTypes[];
1045: PETSC_EXTERN PetscErrorCode KSPCGSetType(KSP, KSPCGType);
1046: PETSC_EXTERN PetscErrorCode KSPCGUseSingleReduction(KSP, PetscBool);
1048: PETSC_EXTERN PetscErrorCode KSPCGSetRadius(KSP, PetscReal);
1049: PETSC_EXTERN PetscErrorCode KSPCGSetObjectiveTarget(KSP, PetscReal);
1050: PETSC_EXTERN PetscErrorCode KSPCGGetNormD(KSP, PetscReal *);
1051: PETSC_EXTERN PetscErrorCode KSPCGGetObjFcn(KSP, PetscReal *);
1053: PETSC_EXTERN PetscErrorCode KSPGLTRGetMinEig(KSP, PetscReal *);
1054: PETSC_EXTERN PetscErrorCode KSPGLTRGetLambda(KSP, PetscReal *);
1055: PETSC_DEPRECATED_FUNCTION(3, 12, 0, "KSPGLTRGetMinEig()", ) static inline PetscErrorCode KSPCGGLTRGetMinEig(KSP ksp, PetscReal *x)
1056: {
1057: return KSPGLTRGetMinEig(ksp, x);
1058: }
1059: PETSC_DEPRECATED_FUNCTION(3, 12, 0, "KSPGLTRGetLambda()", ) static inline PetscErrorCode KSPCGGLTRGetLambda(KSP ksp, PetscReal *x)
1060: {
1061: return KSPGLTRGetLambda(ksp, x);
1062: }
1064: PETSC_EXTERN PetscErrorCode KSPPythonSetType(KSP, const char[]);
1065: PETSC_EXTERN PetscErrorCode KSPPythonGetType(KSP, const char *[]);
1067: PETSC_EXTERN PetscErrorCode PCSetPreSolve(PC, PetscErrorCode (*)(PC, KSP));
1068: PETSC_EXTERN PetscErrorCode PCSetPostSolve(PC, PetscErrorCode (*)(PC, KSP));
1069: PETSC_EXTERN PetscErrorCode PCPreSolve(PC, KSP);
1070: PETSC_EXTERN PetscErrorCode PCPostSolve(PC, KSP);
1072: PETSC_EXTERN PetscErrorCode KSPMonitorLGRange(KSP, PetscInt, PetscReal, void *);
1074: /*S
1075: PCShellPSolveFn - A function prototype for functions provided to `PCShellSetPreSolve()` and `PCShellSetPostSolve()`
1077: Calling Sequence:
1078: + pc - the preconditioner `PC` context
1079: . ksp - the `KSP` context
1080: . xin - input vector
1081: - xout - output vector
1083: Level: intermediate
1085: .seealso: [](ch_snes), `KSPPSolveFn`, `KSP`, `PCShellSetPreSolve()`, `PCShellSetPostSolve()`
1086: S*/
1087: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode PCShellPSolveFn(PC pc, KSP ksp, Vec xim, Vec xout);
1089: PETSC_EXTERN PetscErrorCode PCShellSetPreSolve(PC, PCShellPSolveFn *);
1090: PETSC_EXTERN PetscErrorCode PCShellSetPostSolve(PC, PCShellPSolveFn *);
1092: /*S
1093: KSPGuess - Abstract PETSc object that manages all initial guess generation methods for Krylov methods.
1095: Level: intermediate
1097: Note:
1098: These methods generate initial guesses based on a series of previous, related, linear solves. For example,
1099: in implicit time-stepping with `TS`.
1101: .seealso: [](ch_ksp), `KSPCreate()`, `KSPGuessSetType()`, `KSPGuessType`
1102: S*/
1103: typedef struct _p_KSPGuess *KSPGuess;
1105: /*J
1106: KSPGuessType - String with the name of a PETSc initial guess approach for Krylov methods.
1108: Values:
1109: + `KSPGUESSFISCHER` - methodology developed by Paul Fischer
1110: - `KSPGUESSPOD` - methodology based on proper orthogonal decomposition (POD)
1112: Level: intermediate
1114: .seealso: [](ch_ksp), `KSP`, `KSPGuess`
1115: J*/
1116: typedef const char *KSPGuessType;
1117: #define KSPGUESSFISCHER "fischer"
1118: #define KSPGUESSPOD "pod"
1120: PETSC_EXTERN PetscErrorCode KSPGuessRegister(const char[], PetscErrorCode (*)(KSPGuess));
1121: PETSC_EXTERN PetscErrorCode KSPSetGuess(KSP, KSPGuess);
1122: PETSC_EXTERN PetscErrorCode KSPGetGuess(KSP, KSPGuess *);
1123: PETSC_EXTERN PetscErrorCode KSPGuessView(KSPGuess, PetscViewer);
1124: PETSC_EXTERN PetscErrorCode KSPGuessDestroy(KSPGuess *);
1125: PETSC_EXTERN PetscErrorCode KSPGuessCreate(MPI_Comm, KSPGuess *);
1126: PETSC_EXTERN PetscErrorCode KSPGuessSetType(KSPGuess, KSPGuessType);
1127: PETSC_EXTERN PetscErrorCode KSPGuessGetType(KSPGuess, KSPGuessType *);
1128: PETSC_EXTERN PetscErrorCode KSPGuessSetTolerance(KSPGuess, PetscReal);
1129: PETSC_EXTERN PetscErrorCode KSPGuessSetUp(KSPGuess);
1130: PETSC_EXTERN PetscErrorCode KSPGuessUpdate(KSPGuess, Vec, Vec);
1131: PETSC_EXTERN PetscErrorCode KSPGuessFormGuess(KSPGuess, Vec, Vec);
1132: PETSC_EXTERN PetscErrorCode KSPGuessSetFromOptions(KSPGuess);
1133: PETSC_EXTERN PetscErrorCode KSPGuessFischerSetModel(KSPGuess, PetscInt, PetscInt);
1134: PETSC_EXTERN PetscErrorCode KSPSetUseFischerGuess(KSP, PetscInt, PetscInt);
1135: PETSC_EXTERN PetscErrorCode KSPSetInitialGuessKnoll(KSP, PetscBool);
1136: PETSC_EXTERN PetscErrorCode KSPGetInitialGuessKnoll(KSP, PetscBool *);
1138: /*E
1139: MatSchurComplementAinvType - Determines how to approximate the inverse of the (0,0) block in Schur complement matrix assembly routines
1141: Level: intermediate
1143: .seealso: `MatSchurComplementGetAinvType()`, `MatSchurComplementSetAinvType()`, `MatSchurComplementGetPmat()`, `MatGetSchurComplement()`,
1144: `MatCreateSchurComplementPmat()`, `MatCreateSchurComplement()`
1145: E*/
1146: typedef enum {
1147: MAT_SCHUR_COMPLEMENT_AINV_DIAG,
1148: MAT_SCHUR_COMPLEMENT_AINV_LUMP,
1149: MAT_SCHUR_COMPLEMENT_AINV_BLOCK_DIAG,
1150: MAT_SCHUR_COMPLEMENT_AINV_FULL
1151: } MatSchurComplementAinvType;
1152: PETSC_EXTERN const char *const MatSchurComplementAinvTypes[];
1154: PETSC_EXTERN PetscErrorCode MatCreateSchurComplement(Mat, Mat, Mat, Mat, Mat, Mat *);
1155: PETSC_EXTERN PetscErrorCode MatSchurComplementGetKSP(Mat, KSP *);
1156: PETSC_EXTERN PetscErrorCode MatSchurComplementSetKSP(Mat, KSP);
1157: PETSC_EXTERN PetscErrorCode MatSchurComplementSetSubMatrices(Mat, Mat, Mat, Mat, Mat, Mat);
1158: PETSC_EXTERN PetscErrorCode MatSchurComplementUpdateSubMatrices(Mat, Mat, Mat, Mat, Mat, Mat);
1159: PETSC_EXTERN PetscErrorCode MatSchurComplementGetSubMatrices(Mat, Mat *, Mat *, Mat *, Mat *, Mat *);
1160: PETSC_EXTERN PetscErrorCode MatSchurComplementSetAinvType(Mat, MatSchurComplementAinvType);
1161: PETSC_EXTERN PetscErrorCode MatSchurComplementGetAinvType(Mat, MatSchurComplementAinvType *);
1162: PETSC_EXTERN PetscErrorCode MatSchurComplementGetPmat(Mat, MatReuse, Mat *);
1163: PETSC_EXTERN PetscErrorCode MatSchurComplementComputeExplicitOperator(Mat, Mat *);
1164: PETSC_EXTERN PetscErrorCode MatGetSchurComplement(Mat, IS, IS, IS, IS, MatReuse, Mat *, MatSchurComplementAinvType, MatReuse, Mat *);
1165: PETSC_EXTERN PetscErrorCode MatCreateSchurComplementPmat(Mat, Mat, Mat, Mat, MatSchurComplementAinvType, MatReuse, Mat *);
1167: PETSC_EXTERN PetscErrorCode MatCreateLMVMDFP(MPI_Comm, PetscInt, PetscInt, Mat *);
1168: PETSC_EXTERN PetscErrorCode MatCreateLMVMBFGS(MPI_Comm, PetscInt, PetscInt, Mat *);
1169: PETSC_EXTERN PetscErrorCode MatCreateLMVMDBFGS(MPI_Comm, PetscInt, PetscInt, Mat *);
1170: PETSC_EXTERN PetscErrorCode MatCreateLMVMDDFP(MPI_Comm, PetscInt, PetscInt, Mat *);
1171: PETSC_EXTERN PetscErrorCode MatCreateLMVMDQN(MPI_Comm, PetscInt, PetscInt, Mat *);
1172: PETSC_EXTERN PetscErrorCode MatCreateLMVMSR1(MPI_Comm, PetscInt, PetscInt, Mat *);
1173: PETSC_EXTERN PetscErrorCode MatCreateLMVMBroyden(MPI_Comm, PetscInt, PetscInt, Mat *);
1174: PETSC_EXTERN PetscErrorCode MatCreateLMVMBadBroyden(MPI_Comm, PetscInt, PetscInt, Mat *);
1175: PETSC_EXTERN PetscErrorCode MatCreateLMVMSymBroyden(MPI_Comm, PetscInt, PetscInt, Mat *);
1176: PETSC_EXTERN PetscErrorCode MatCreateLMVMSymBadBroyden(MPI_Comm, PetscInt, PetscInt, Mat *);
1177: PETSC_EXTERN PetscErrorCode MatCreateLMVMDiagBroyden(MPI_Comm, PetscInt, PetscInt, Mat *);
1179: PETSC_EXTERN PetscErrorCode MatLMVMUpdate(Mat, Vec, Vec);
1180: PETSC_EXTERN PetscErrorCode MatLMVMIsAllocated(Mat, PetscBool *);
1181: PETSC_EXTERN PetscErrorCode MatLMVMAllocate(Mat, Vec, Vec);
1182: PETSC_EXTERN PetscErrorCode MatLMVMReset(Mat, PetscBool);
1183: PETSC_EXTERN PetscErrorCode MatLMVMResetShift(Mat);
1184: PETSC_EXTERN PetscErrorCode MatLMVMClearJ0(Mat);
1185: PETSC_EXTERN PetscErrorCode MatLMVMSetJ0(Mat, Mat);
1186: PETSC_EXTERN PetscErrorCode MatLMVMSetJ0Scale(Mat, PetscReal);
1187: PETSC_EXTERN PetscErrorCode MatLMVMSetJ0Diag(Mat, Vec);
1188: PETSC_EXTERN PetscErrorCode MatLMVMSetJ0PC(Mat, PC);
1189: PETSC_EXTERN PetscErrorCode MatLMVMSetJ0KSP(Mat, KSP);
1190: PETSC_EXTERN PetscErrorCode MatLMVMApplyJ0Fwd(Mat, Vec, Vec);
1191: PETSC_EXTERN PetscErrorCode MatLMVMApplyJ0Inv(Mat, Vec, Vec);
1192: PETSC_EXTERN PetscErrorCode MatLMVMGetLastUpdate(Mat, Vec *, Vec *);
1193: PETSC_EXTERN PetscErrorCode MatLMVMGetJ0(Mat, Mat *);
1194: PETSC_EXTERN PetscErrorCode MatLMVMGetJ0PC(Mat, PC *);
1195: PETSC_EXTERN PetscErrorCode MatLMVMGetJ0KSP(Mat, KSP *);
1196: PETSC_EXTERN PetscErrorCode MatLMVMSetHistorySize(Mat, PetscInt);
1197: PETSC_EXTERN PetscErrorCode MatLMVMGetHistorySize(Mat, PetscInt *);
1198: PETSC_EXTERN PetscErrorCode MatLMVMGetUpdateCount(Mat, PetscInt *);
1199: PETSC_EXTERN PetscErrorCode MatLMVMGetRejectCount(Mat, PetscInt *);
1200: PETSC_EXTERN PetscErrorCode MatLMVMSymBroydenSetDelta(Mat, PetscScalar);
1202: /*E
1203: MatLMVMMultAlgorithm - The type of algorithm used for matrix-vector products and solves used internally by a `MatLMVM` matrix
1205: Values:
1206: + `MAT_LMVM_MULT_RECURSIVE` - Use recursive formulas for products and solves
1207: . `MAT_LMVM_MULT_DENSE` - Use dense formulas for products and solves when possible
1208: - `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
1210: Level: advanced
1212: Options Database Keys:
1213: . -mat_lmvm_mult_algorithm - the algorithm to use for multiplication (recursive, dense, compact_dense)
1215: .seealso: [](ch_matrices), `MatLMVM`, `MatLMVMSetMultAlgorithm()`, `MatLMVMGetMultAlgorithm()`
1216: E*/
1217: typedef enum {
1218: MAT_LMVM_MULT_RECURSIVE,
1219: MAT_LMVM_MULT_DENSE,
1220: MAT_LMVM_MULT_COMPACT_DENSE,
1221: } MatLMVMMultAlgorithm;
1223: PETSC_EXTERN const char *const MatLMVMMultAlgorithms[];
1225: PETSC_EXTERN PetscErrorCode MatLMVMSetMultAlgorithm(Mat, MatLMVMMultAlgorithm);
1226: PETSC_EXTERN PetscErrorCode MatLMVMGetMultAlgorithm(Mat, MatLMVMMultAlgorithm *);
1228: /*E
1229: MatLMVMSymBroydenScaleType - Rescaling type for the initial Hessian of a symmetric Broyden matrix.
1231: Values:
1232: + `MAT_LMVM_SYMBROYDEN_SCALE_NONE` - no rescaling
1233: . `MAT_LMVM_SYMBROYDEN_SCALE_SCALAR` - scalar rescaling
1234: . `MAT_LMVM_SYMBROYDEN_SCALE_DIAGONAL` - diagonal rescaling
1235: . `MAT_LMVM_SYMBROYDEN_SCALE_USER` - same as `MAT_LMVM_SYMBROYDN_SCALE_NONE`
1236: - `MAT_LMVM_SYMBROYDEN_SCALE_DECIDE` - let PETSc decide rescaling
1238: Level: intermediate
1240: .seealso: [](ch_matrices), `MatLMVM`, `MatLMVMSymBroydenSetScaleType()`
1241: E*/
1242: typedef enum {
1243: MAT_LMVM_SYMBROYDEN_SCALE_NONE = 0,
1244: MAT_LMVM_SYMBROYDEN_SCALE_SCALAR = 1,
1245: MAT_LMVM_SYMBROYDEN_SCALE_DIAGONAL = 2,
1246: MAT_LMVM_SYMBROYDEN_SCALE_USER = 3,
1247: MAT_LMVM_SYMBROYDEN_SCALE_DECIDE = 4
1248: } MatLMVMSymBroydenScaleType;
1249: PETSC_EXTERN const char *const MatLMVMSymBroydenScaleTypes[];
1251: PETSC_EXTERN PetscErrorCode MatLMVMSymBroydenSetScaleType(Mat, MatLMVMSymBroydenScaleType);
1252: PETSC_EXTERN PetscErrorCode MatLMVMSymBroydenGetPhi(Mat, PetscReal *);
1253: PETSC_EXTERN PetscErrorCode MatLMVMSymBroydenSetPhi(Mat, PetscReal);
1254: PETSC_EXTERN PetscErrorCode MatLMVMSymBadBroydenGetPsi(Mat, PetscReal *);
1255: PETSC_EXTERN PetscErrorCode MatLMVMSymBadBroydenSetPsi(Mat, PetscReal);
1257: /*E
1258: MatLMVMDenseType - Memory storage strategy for dense variants of `MATLMVM`.
1260: Values:
1261: + `MAT_LMVM_DENSE_REORDER` - reorders memory to minimize kernel launch
1262: - `MAT_LMVM_DENSE_INPLACE` - computes inplace to minimize memory movement
1264: Level: intermediate
1266: .seealso: [](ch_matrices), `MatLMVM`, `MatLMVMDenseSetType()`
1267: E*/
1268: typedef enum {
1269: MAT_LMVM_DENSE_REORDER,
1270: MAT_LMVM_DENSE_INPLACE
1271: } MatLMVMDenseType;
1272: PETSC_EXTERN const char *const MatLMVMDenseTypes[];
1274: PETSC_EXTERN PetscErrorCode MatLMVMDenseSetType(Mat, MatLMVMDenseType);
1276: PETSC_EXTERN PetscErrorCode KSPSetDM(KSP, DM);
1277: PETSC_EXTERN PetscErrorCode KSPSetDMActive(KSP, PetscBool);
1278: PETSC_EXTERN PetscErrorCode KSPGetDM(KSP, DM *);
1279: PETSC_EXTERN PetscErrorCode KSPSetApplicationContext(KSP, void *);
1280: PETSC_EXTERN PetscErrorCode KSPGetApplicationContext(KSP, void *);
1282: /*S
1283: KSPComputeRHSFn - A prototype of a `KSP` evaluation function that would be passed to `KSPSetComputeRHS()`
1285: Calling Sequence:
1286: + ksp - `ksp` context
1287: . b - output vector
1288: - ctx - [optional] user-defined function context
1290: Level: beginner
1292: .seealso: [](ch_ksp), `KSP`, `KSPSetComputeRHS()`, `SNESGetFunction()`, `KSPComputeInitialGuessFn`, `KSPComputeOperatorsFn`
1293: S*/
1294: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPComputeRHSFn(KSP ksp, Vec b, void *ctx);
1296: PETSC_EXTERN PetscErrorCode KSPSetComputeRHS(KSP, KSPComputeRHSFn *, void *);
1298: /*S
1299: KSPComputeOperatorsFn - A prototype of a `KSP` evaluation function that would be passed to `KSPSetComputeOperators()`
1301: Calling Sequence:
1302: + ksp - `KSP` context
1303: . A - the operator that defines the linear system
1304: . P - an operator from which to build the preconditioner (often the same as `A`)
1305: - ctx - [optional] user-defined function context
1307: Level: beginner
1309: .seealso: [](ch_ksp), `KSP`, `KSPSetComputeRHS()`, `SNESGetFunction()`, `KSPComputeRHSFn`, `KSPComputeInitialGuessFn`
1310: S*/
1311: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPComputeOperatorsFn(KSP ksp, Mat A, Mat P, void *ctx);
1313: PETSC_EXTERN PetscErrorCode KSPSetComputeOperators(KSP, KSPComputeOperatorsFn, void *);
1315: /*S
1316: KSPComputeInitialGuessFn - A prototype of a `KSP` evaluation function that would be passed to `KSPSetComputeInitialGuess()`
1318: Calling Sequence:
1319: + ksp - `ksp` context
1320: . x - output vector
1321: - ctx - [optional] user-defined function context
1323: Level: beginner
1325: .seealso: [](ch_ksp), `KSP`, `KSPSetComputeInitialGuess()`, `SNESGetFunction()`, `KSPComputeRHSFn`, `KSPComputeOperatorsFn`
1326: S*/
1327: PETSC_EXTERN_TYPEDEF typedef PetscErrorCode KSPComputeInitialGuessFn(KSP ksp, Vec x, void *ctx);
1329: PETSC_EXTERN PetscErrorCode KSPSetComputeInitialGuess(KSP, KSPComputeInitialGuessFn *, void *);
1330: PETSC_EXTERN PetscErrorCode DMKSPSetComputeOperators(DM, KSPComputeOperatorsFn *, void *);
1331: PETSC_EXTERN PetscErrorCode DMKSPGetComputeOperators(DM, KSPComputeOperatorsFn **, void *);
1332: PETSC_EXTERN PetscErrorCode DMKSPSetComputeRHS(DM, KSPComputeRHSFn *, void *);
1333: PETSC_EXTERN PetscErrorCode DMKSPGetComputeRHS(DM, KSPComputeRHSFn **, void *);
1334: PETSC_EXTERN PetscErrorCode DMKSPSetComputeInitialGuess(DM, KSPComputeInitialGuessFn *, void *);
1335: PETSC_EXTERN PetscErrorCode DMKSPGetComputeInitialGuess(DM, KSPComputeInitialGuessFn **, void *);
1337: PETSC_EXTERN PetscErrorCode DMGlobalToLocalSolve(DM, Vec, Vec);
1338: PETSC_EXTERN PetscErrorCode DMSwarmProjectFields(DM, DM, PetscInt, const char *[], Vec[], ScatterMode);
1339: PETSC_EXTERN PetscErrorCode DMSwarmProjectGradientFields(DM, DM, PetscInt, const char *[], Vec[], ScatterMode);
1341: PETSC_EXTERN PetscErrorCode DMAdaptInterpolator(DM, DM, Mat, KSP, Mat, Mat, Mat *, void *);
1342: PETSC_EXTERN PetscErrorCode DMCheckInterpolator(DM, Mat, Mat, Mat, PetscReal);
1344: PETSC_EXTERN PetscErrorCode PCBJKOKKOSSetKSP(PC, KSP);
1345: PETSC_EXTERN PetscErrorCode PCBJKOKKOSGetKSP(PC, KSP *);
1347: PETSC_EXTERN PetscErrorCode DMCopyDMKSP(DM, DM);
1349: #include <petscdstypes.h>
1350: PETSC_EXTERN PetscErrorCode DMProjectField(DM, PetscReal, Vec, PetscPointFn **, InsertMode, Vec);