Actual source code: fcg.c
1: /*
2: This file implements the FCG (Flexible Conjugate Gradient) method
3: */
5: #include <../src/ksp/ksp/impls/fcg/fcgimpl.h>
6: extern PetscErrorCode KSPComputeExtremeSingularValues_CG(KSP, PetscReal *, PetscReal *);
7: extern PetscErrorCode KSPComputeEigenvalues_CG(KSP, PetscInt, PetscReal *, PetscReal *, PetscInt *);
9: #define KSPFCG_DEFAULT_MMAX 30 /* maximum number of search directions to keep */
10: #define KSPFCG_DEFAULT_NPREALLOC 10 /* number of search directions to preallocate */
11: #define KSPFCG_DEFAULT_VECB 5 /* number of search directions to allocate each time new direction vectors are needed */
12: #define KSPFCG_DEFAULT_TRUNCSTRAT KSP_FCD_TRUNC_TYPE_NOTAY
14: static PetscErrorCode KSPAllocateVectors_FCG(KSP ksp, PetscInt nvecsneeded, PetscInt chunksize)
15: {
16: PetscInt i;
17: KSP_FCG *fcg = (KSP_FCG *)ksp->data;
18: PetscInt nnewvecs, nvecsprev;
20: PetscFunctionBegin;
21: /* Allocate enough new vectors to add chunksize new vectors, reach nvecsneedtotal, or to reach mmax+1, whichever is smallest */
22: if (fcg->nvecs < PetscMin(fcg->mmax + 1, nvecsneeded)) {
23: nvecsprev = fcg->nvecs;
24: nnewvecs = PetscMin(PetscMax(nvecsneeded - fcg->nvecs, chunksize), fcg->mmax + 1 - fcg->nvecs);
25: PetscCall(KSPCreateVecs(ksp, nnewvecs, &fcg->pCvecs[fcg->nchunks], 0, NULL));
26: PetscCall(KSPCreateVecs(ksp, nnewvecs, &fcg->pPvecs[fcg->nchunks], 0, NULL));
27: fcg->nvecs += nnewvecs;
28: for (i = 0; i < nnewvecs; ++i) {
29: fcg->Cvecs[nvecsprev + i] = fcg->pCvecs[fcg->nchunks][i];
30: fcg->Pvecs[nvecsprev + i] = fcg->pPvecs[fcg->nchunks][i];
31: }
32: fcg->chunksizes[fcg->nchunks] = nnewvecs;
33: ++fcg->nchunks;
34: }
35: PetscFunctionReturn(PETSC_SUCCESS);
36: }
38: static PetscErrorCode KSPSetUp_FCG(KSP ksp)
39: {
40: KSP_FCG *fcg = (KSP_FCG *)ksp->data;
41: PetscInt maxit = ksp->max_it;
42: const PetscInt nworkstd = 2;
44: PetscFunctionBegin;
45: /* Allocate "standard" work vectors (not including the basis and transformed basis vectors) */
46: PetscCall(KSPSetWorkVecs(ksp, nworkstd));
48: /* Allocated space for pointers to additional work vectors
49: note that mmax is the number of previous directions, so we add 1 for the current direction,
50: and an extra 1 for the prealloc (which might be empty) */
51: PetscCall(PetscMalloc5(fcg->mmax + 1, &fcg->Pvecs, fcg->mmax + 1, &fcg->Cvecs, fcg->mmax + 1, &fcg->pPvecs, fcg->mmax + 1, &fcg->pCvecs, fcg->mmax + 2, &fcg->chunksizes));
53: /* If the requested number of preallocated vectors is greater than mmax reduce nprealloc */
54: if (fcg->nprealloc > fcg->mmax + 1) PetscCall(PetscInfo(NULL, "Requested nprealloc=%" PetscInt_FMT " is greater than m_max+1=%" PetscInt_FMT ". Resetting nprealloc = m_max+1.\n", fcg->nprealloc, fcg->mmax + 1));
56: /* Preallocate additional work vectors */
57: PetscCall(KSPAllocateVectors_FCG(ksp, fcg->nprealloc, fcg->nprealloc));
58: /*
59: If user requested computations of eigenvalues then allocate work
60: work space needed
61: */
62: if (ksp->calc_sings) {
63: /* get space to store tridiagonal matrix for Lanczos */
64: PetscCall(PetscMalloc4(maxit, &fcg->e, maxit, &fcg->d, maxit, &fcg->ee, maxit, &fcg->dd));
66: ksp->ops->computeextremesingularvalues = KSPComputeExtremeSingularValues_CG;
67: ksp->ops->computeeigenvalues = KSPComputeEigenvalues_CG;
68: }
69: PetscFunctionReturn(PETSC_SUCCESS);
70: }
72: static PetscErrorCode KSPSolve_FCG(KSP ksp)
73: {
74: PetscInt i, k, idx, mi;
75: KSP_FCG *fcg = (KSP_FCG *)ksp->data;
76: PetscScalar alpha = 0.0, beta = 0.0, dpi = 0.0, dpiold, s;
77: PetscReal dp = 0.0;
78: Vec B, R, Z, X, Pcurr, Ccurr;
79: Mat Amat, Pmat;
80: PetscInt eigs = ksp->calc_sings; /* Variables for eigen estimation - START*/
81: PetscInt stored_max_it = ksp->max_it;
82: PetscScalar alphaold = 0, betaold = 1.0, *e = NULL, *d = NULL; /* Variables for eigen estimation - FINISH */
84: PetscFunctionBegin;
85: #define VecXDot(x, y, a) (fcg->type == KSP_CG_HERMITIAN ? VecDot(x, y, a) : VecTDot(x, y, a))
86: #define VecXMDot(a, b, c, d) (fcg->type == KSP_CG_HERMITIAN ? VecMDot(a, b, c, d) : VecMTDot(a, b, c, d))
88: X = ksp->vec_sol;
89: B = ksp->vec_rhs;
90: R = ksp->work[0];
91: Z = ksp->work[1];
93: PetscCall(PCGetOperators(ksp->pc, &Amat, &Pmat));
94: if (eigs) {
95: e = fcg->e;
96: d = fcg->d;
97: e[0] = 0.0;
98: }
99: /* Compute initial residual needed for convergence check*/
100: ksp->its = 0;
101: if (!ksp->guess_zero) {
102: PetscCall(KSP_MatMult(ksp, Amat, X, R));
103: PetscCall(VecAYPX(R, -1.0, B)); /* r <- b - Ax */
104: } else {
105: PetscCall(VecCopy(B, R)); /* r <- b (x is 0) */
106: }
107: switch (ksp->normtype) {
108: case KSP_NORM_PRECONDITIONED:
109: PetscCall(KSP_PCApply(ksp, R, Z)); /* z <- Br */
110: PetscCall(VecNorm(Z, NORM_2, &dp)); /* dp <- dqrt(z'*z) = sqrt(e'*A'*B'*B*A*e) */
111: KSPCheckNorm(ksp, dp);
112: break;
113: case KSP_NORM_UNPRECONDITIONED:
114: PetscCall(VecNorm(R, NORM_2, &dp)); /* dp <- sqrt(r'*r) = sqrt(e'*A'*A*e) */
115: KSPCheckNorm(ksp, dp);
116: break;
117: case KSP_NORM_NATURAL:
118: PetscCall(KSP_PCApply(ksp, R, Z)); /* z <- Br */
119: PetscCall(VecXDot(R, Z, &s));
120: KSPCheckDot(ksp, s);
121: dp = PetscSqrtReal(PetscAbsScalar(s)); /* dp <- sqrt(r'*z) = sqrt(e'*A'*B*A*e) */
122: break;
123: case KSP_NORM_NONE:
124: dp = 0.0;
125: break;
126: default:
127: SETERRQ(PetscObjectComm((PetscObject)ksp), PETSC_ERR_SUP, "%s", KSPNormTypes[ksp->normtype]);
128: }
130: /* Initial Convergence Check */
131: PetscCall(KSPLogResidualHistory(ksp, dp));
132: PetscCall(KSPMonitor(ksp, 0, dp));
133: ksp->rnorm = dp;
134: if (ksp->normtype == KSP_NORM_NONE) {
135: PetscCall(KSPConvergedSkip(ksp, 0, dp, &ksp->reason, ksp->cnvP));
136: } else {
137: PetscCall((*ksp->converged)(ksp, 0, dp, &ksp->reason, ksp->cnvP));
138: }
139: if (ksp->reason) PetscFunctionReturn(PETSC_SUCCESS);
141: /* Apply PC if not already done for convergence check */
142: if (ksp->normtype == KSP_NORM_UNPRECONDITIONED || ksp->normtype == KSP_NORM_NONE) { PetscCall(KSP_PCApply(ksp, R, Z)); /* z <- Br */ }
144: i = 0;
145: do {
146: ksp->its = i + 1;
148: /* If needbe, allocate a new chunk of vectors in P and C */
149: PetscCall(KSPAllocateVectors_FCG(ksp, i + 1, fcg->vecb));
151: /* Note that we wrap around and start clobbering old vectors */
152: idx = i % (fcg->mmax + 1);
153: Pcurr = fcg->Pvecs[idx];
154: Ccurr = fcg->Cvecs[idx];
156: /* number of old directions to orthogonalize against */
157: switch (fcg->truncstrat) {
158: case KSP_FCD_TRUNC_TYPE_STANDARD:
159: mi = fcg->mmax;
160: break;
161: case KSP_FCD_TRUNC_TYPE_NOTAY:
162: mi = ((i - 1) % fcg->mmax) + 1;
163: break;
164: default:
165: SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Unrecognized Truncation Strategy");
166: }
168: /* Compute a new column of P (Currently does not support modified G-S or iterative refinement)*/
169: PetscCall(VecCopy(Z, Pcurr));
171: {
172: PetscInt l, ndots;
174: l = PetscMax(0, i - mi);
175: ndots = i - l;
176: if (ndots) {
177: PetscInt j;
178: Vec *Pold, *Cold;
179: PetscScalar *dots;
181: PetscCall(PetscMalloc3(ndots, &dots, ndots, &Cold, ndots, &Pold));
182: for (k = l, j = 0; j < ndots; ++k, ++j) {
183: idx = k % (fcg->mmax + 1);
184: Cold[j] = fcg->Cvecs[idx];
185: Pold[j] = fcg->Pvecs[idx];
186: }
187: PetscCall(VecXMDot(Z, ndots, Cold, dots));
188: for (k = 0; k < ndots; ++k) dots[k] = -dots[k];
189: PetscCall(VecMAXPY(Pcurr, ndots, dots, Pold));
190: PetscCall(PetscFree3(dots, Cold, Pold));
191: }
192: }
194: /* Update X and R */
195: betaold = beta;
196: PetscCall(VecXDot(Pcurr, R, &beta)); /* beta <- pi'*r */
197: KSPCheckDot(ksp, beta);
198: if ((i > 0) && (PetscAbsScalar(beta * betaold) < 0.0)) {
199: PetscCheck(!ksp->errorifnotconverged, PetscObjectComm((PetscObject)ksp), PETSC_ERR_NOT_CONVERGED, "Diverged due to indefinite preconditioner, beta %g, betaold %g", (double)PetscRealPart(beta), (double)PetscRealPart(betaold));
200: ksp->reason = KSP_DIVERGED_INDEFINITE_PC;
201: PetscCall(PetscInfo(ksp, "diverging due to indefinite preconditioner\n"));
202: break;
203: }
204: PetscCall(KSP_MatMult(ksp, Amat, Pcurr, Ccurr)); /* w <- A*pi (stored in ci) */
205: dpiold = dpi;
206: PetscCall(VecXDot(Pcurr, Ccurr, &dpi)); /* dpi <- pi'*w */
207: if ((dpi == 0.0) || ((i > 0) && ((PetscSign(PetscRealPart(dpi)) * PetscSign(PetscRealPart(dpiold))) < 0.0))) {
208: PetscCheck(!ksp->errorifnotconverged, PetscObjectComm((PetscObject)ksp), PETSC_ERR_NOT_CONVERGED, "Diverged due to indefinite matrix, dpi %g, dpiold %g", (double)PetscRealPart(dpi), (double)PetscRealPart(dpiold));
209: ksp->reason = KSP_DIVERGED_INDEFINITE_MAT;
210: PetscCall(PetscInfo(ksp, "diverging due to indefinite matrix\n"));
211: break;
212: }
213: alphaold = alpha;
214: alpha = beta / dpi; /* alpha <- beta/dpi */
215: PetscCall(VecAXPY(X, alpha, Pcurr)); /* x <- x + alpha * pi */
216: PetscCall(VecAXPY(R, -alpha, Ccurr)); /* r <- r - alpha * wi */
218: /* Compute norm for convergence check */
219: switch (ksp->normtype) {
220: case KSP_NORM_PRECONDITIONED:
221: PetscCall(KSP_PCApply(ksp, R, Z)); /* z <- Br */
222: PetscCall(VecNorm(Z, NORM_2, &dp)); /* dp <- sqrt(z'*z) = sqrt(e'*A'*B'*B*A*e) */
223: KSPCheckNorm(ksp, dp);
224: break;
225: case KSP_NORM_UNPRECONDITIONED:
226: PetscCall(VecNorm(R, NORM_2, &dp)); /* dp <- sqrt(r'*r) = sqrt(e'*A'*A*e) */
227: KSPCheckNorm(ksp, dp);
228: break;
229: case KSP_NORM_NATURAL:
230: PetscCall(KSP_PCApply(ksp, R, Z)); /* z <- Br */
231: PetscCall(VecXDot(R, Z, &s));
232: KSPCheckDot(ksp, s);
233: dp = PetscSqrtReal(PetscAbsScalar(s)); /* dp <- sqrt(r'*z) = sqrt(e'*A'*B*A*e) */
234: break;
235: case KSP_NORM_NONE:
236: dp = 0.0;
237: break;
238: default:
239: SETERRQ(PetscObjectComm((PetscObject)ksp), PETSC_ERR_SUP, "%s", KSPNormTypes[ksp->normtype]);
240: }
242: if (eigs) {
243: if (i > 0) {
244: PetscCheck(ksp->max_it == stored_max_it, PetscObjectComm((PetscObject)ksp), PETSC_ERR_SUP, "Can not change maxit AND calculate eigenvalues");
245: e[i] = PetscSqrtReal(PetscAbsScalar(beta / betaold)) / alphaold;
246: d[i] = PetscSqrtReal(PetscAbsScalar(beta / betaold)) * e[i] + 1.0 / alpha;
247: } else {
248: d[i] = PetscSqrtReal(PetscAbsScalar(beta)) * e[i] + 1.0 / alpha;
249: }
250: }
252: /* Check for convergence */
253: ksp->rnorm = dp;
254: PetscCall(KSPLogResidualHistory(ksp, dp));
255: PetscCall(KSPMonitor(ksp, i + 1, dp));
256: PetscCall((*ksp->converged)(ksp, i + 1, dp, &ksp->reason, ksp->cnvP));
257: if (ksp->reason) break;
259: /* Apply PC if not already done for convergence check */
260: if (ksp->normtype == KSP_NORM_UNPRECONDITIONED || ksp->normtype == KSP_NORM_NONE) { PetscCall(KSP_PCApply(ksp, R, Z)); /* z <- Br */ }
262: /* Compute current C (which is W/dpi) */
263: PetscCall(VecScale(Ccurr, 1.0 / dpi)); /* w <- ci/dpi */
264: ++i;
265: } while (i < ksp->max_it);
266: if (i >= ksp->max_it) ksp->reason = KSP_DIVERGED_ITS;
267: PetscFunctionReturn(PETSC_SUCCESS);
268: }
270: static PetscErrorCode KSPDestroy_FCG(KSP ksp)
271: {
272: PetscInt i;
273: KSP_FCG *fcg = (KSP_FCG *)ksp->data;
275: PetscFunctionBegin;
276: /* Destroy "standard" work vecs */
277: PetscCall(VecDestroyVecs(ksp->nwork, &ksp->work));
279: /* Destroy P and C vectors and the arrays that manage pointers to them */
280: if (fcg->nvecs) {
281: for (i = 0; i < fcg->nchunks; ++i) {
282: PetscCall(VecDestroyVecs(fcg->chunksizes[i], &fcg->pPvecs[i]));
283: PetscCall(VecDestroyVecs(fcg->chunksizes[i], &fcg->pCvecs[i]));
284: }
285: }
286: PetscCall(PetscFree5(fcg->Pvecs, fcg->Cvecs, fcg->pPvecs, fcg->pCvecs, fcg->chunksizes));
287: /* free space used for singular value calculations */
288: if (ksp->calc_sings) PetscCall(PetscFree4(fcg->e, fcg->d, fcg->ee, fcg->dd));
289: PetscCall(KSPDestroyDefault(ksp));
290: PetscFunctionReturn(PETSC_SUCCESS);
291: }
293: static PetscErrorCode KSPView_FCG(KSP ksp, PetscViewer viewer)
294: {
295: KSP_FCG *fcg = (KSP_FCG *)ksp->data;
296: PetscBool iascii, isstring;
297: const char *truncstr;
299: PetscFunctionBegin;
300: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &iascii));
301: PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERSTRING, &isstring));
303: if (fcg->truncstrat == KSP_FCD_TRUNC_TYPE_STANDARD) truncstr = "Using standard truncation strategy";
304: else if (fcg->truncstrat == KSP_FCD_TRUNC_TYPE_NOTAY) truncstr = "Using Notay's truncation strategy";
305: else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Undefined FCG truncation strategy");
307: if (iascii) {
308: PetscCall(PetscViewerASCIIPrintf(viewer, " m_max=%" PetscInt_FMT "\n", fcg->mmax));
309: PetscCall(PetscViewerASCIIPrintf(viewer, " preallocated %" PetscInt_FMT " directions\n", PetscMin(fcg->nprealloc, fcg->mmax + 1)));
310: PetscCall(PetscViewerASCIIPrintf(viewer, " %s\n", truncstr));
311: } else if (isstring) {
312: PetscCall(PetscViewerStringSPrintf(viewer, "m_max %" PetscInt_FMT " nprealloc %" PetscInt_FMT " %s", fcg->mmax, fcg->nprealloc, truncstr));
313: }
314: PetscFunctionReturn(PETSC_SUCCESS);
315: }
317: /*@
318: KSPFCGSetMmax - set the maximum number of previous directions `KSPFCG` will store for orthogonalization
320: Logically Collective
322: Input Parameters:
323: + ksp - the Krylov space context
324: - mmax - the maximum number of previous directions to orthogonalize against
326: Options Database Key:
327: . -ksp_fcg_mmax <N> - maximum number of search directions
329: Level: intermediate
331: Note:
332: `mmax` + 1 directions are stored (`mmax` previous ones along with a current one)
333: and whether all are used in each iteration also depends on the truncation strategy, see `KSPFCGSetTruncationType()`
335: .seealso: [](ch_ksp), `KSPFCG`, `KSPFCGGetTruncationType()`, `KSPFCGGetNprealloc()`, `KSPFCGetMmax()`
336: @*/
337: PetscErrorCode KSPFCGSetMmax(KSP ksp, PetscInt mmax)
338: {
339: KSP_FCG *fcg = (KSP_FCG *)ksp->data;
341: PetscFunctionBegin;
344: fcg->mmax = mmax;
345: PetscFunctionReturn(PETSC_SUCCESS);
346: }
348: /*@
349: KSPFCGGetMmax - get the maximum number of previous directions `KSPFCG` will store
351: Not Collective
353: Input Parameter:
354: . ksp - the Krylov space context
356: Output Parameter:
357: . mmax - the maximum number of previous directions allowed for orthogonalization
359: Level: intermediate
361: Note:
362: `KSPFCG` stores `mmax`+1 directions at most (`mmax` previous ones, and one current one)
364: .seealso: [](ch_ksp), `KSPFCG`, `KSPFCGGetTruncationType()`, `KSPFCGGetNprealloc()`, `KSPFCGSetMmax()`
365: @*/
366: PetscErrorCode KSPFCGGetMmax(KSP ksp, PetscInt *mmax)
367: {
368: KSP_FCG *fcg = (KSP_FCG *)ksp->data;
370: PetscFunctionBegin;
372: *mmax = fcg->mmax;
373: PetscFunctionReturn(PETSC_SUCCESS);
374: }
376: /*@
377: KSPFCGSetNprealloc - set the number of directions to preallocate with `KSPFCG`
379: Logically Collective
381: Input Parameters:
382: + ksp - the Krylov space context
383: - nprealloc - the number of vectors to preallocate
385: Options Database Key:
386: . -ksp_fcg_nprealloc <N> - number of directions to preallocate
388: Level: advanced
390: .seealso: [](ch_ksp), `KSPFCG`, `KSPFCGGetTruncationType()`, `KSPFCGGetNprealloc()`, `KSPFCGSetMmax()`, `KSPFCGGetMmax()`
391: @*/
392: PetscErrorCode KSPFCGSetNprealloc(KSP ksp, PetscInt nprealloc)
393: {
394: KSP_FCG *fcg = (KSP_FCG *)ksp->data;
396: PetscFunctionBegin;
399: PetscCheck(nprealloc <= fcg->mmax + 1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Cannot preallocate more than m_max+1 vectors");
400: fcg->nprealloc = nprealloc;
401: PetscFunctionReturn(PETSC_SUCCESS);
402: }
404: /*@
405: KSPFCGGetNprealloc - get the number of directions preallocate by `KSPFCG`
407: Not Collective
409: Input Parameter:
410: . ksp - the Krylov space context
412: Output Parameter:
413: . nprealloc - the number of directions preallocated
415: Level: advanced
417: .seealso: [](ch_ksp), `KSPFCG`, `KSPFCGGetTruncationType()`, `KSPFCGSetNprealloc()`, `KSPFCGSetMmax()`, `KSPFCGGetMmax()`
418: @*/
419: PetscErrorCode KSPFCGGetNprealloc(KSP ksp, PetscInt *nprealloc)
420: {
421: KSP_FCG *fcg = (KSP_FCG *)ksp->data;
423: PetscFunctionBegin;
425: *nprealloc = fcg->nprealloc;
426: PetscFunctionReturn(PETSC_SUCCESS);
427: }
429: /*@
430: KSPFCGSetTruncationType - specify how many of its stored previous directions `KSPFCG` uses during orthoganalization
432: Logically Collective
434: Input Parameters:
435: + ksp - the Krylov space context
436: - truncstrat - the choice of strategy
437: .vb
438: KSP_FCD_TRUNC_TYPE_STANDARD uses all (up to mmax) stored directions
439: KSP_FCD_TRUNC_TYPE_NOTAY uses the last max(1,mod(i,mmax)) stored directions at iteration i=0,1,..
440: .ve
442: Options Database Key:
443: . -ksp_fcg_truncation_type <standard, notay> - specify how many of its stored previous directions `KSPFCG` uses during orthoganalization
445: Level: intermediate
447: .seealso: [](ch_ksp), `KSPFCDTruncationType`, `KSPFCGGetTruncationType()`, `KSPFCGSetNprealloc()`, `KSPFCGSetMmax()`, `KSPFCGGetMmax()`,
448: `KSP_FCD_TRUNC_TYPE_STANDARD`, `KSP_FCD_TRUNC_TYPE_NOTAY`
449: @*/
450: PetscErrorCode KSPFCGSetTruncationType(KSP ksp, KSPFCDTruncationType truncstrat)
451: {
452: KSP_FCG *fcg = (KSP_FCG *)ksp->data;
454: PetscFunctionBegin;
457: fcg->truncstrat = truncstrat;
458: PetscFunctionReturn(PETSC_SUCCESS);
459: }
461: /*@
462: KSPFCGGetTruncationType - get the truncation strategy employed by `KSPFCG`
464: Not Collective
466: Input Parameter:
467: . ksp - the Krylov space context
469: Output Parameter:
470: . truncstrat - the strategy type
472: Level: intermediate
474: .seealso: [](ch_ksp), `KSPFCG`, `KSPFCGSetTruncationType()`, `KSPFCDTruncationType`, `KSP_FCD_TRUNC_TYPE_STANDARD`, `KSP_FCD_TRUNC_TYPE_NOTAY`
475: @*/
476: PetscErrorCode KSPFCGGetTruncationType(KSP ksp, KSPFCDTruncationType *truncstrat)
477: {
478: KSP_FCG *fcg = (KSP_FCG *)ksp->data;
480: PetscFunctionBegin;
482: *truncstrat = fcg->truncstrat;
483: PetscFunctionReturn(PETSC_SUCCESS);
484: }
486: static PetscErrorCode KSPSetFromOptions_FCG(KSP ksp, PetscOptionItems PetscOptionsObject)
487: {
488: KSP_FCG *fcg = (KSP_FCG *)ksp->data;
489: PetscInt mmax, nprealloc;
490: PetscBool flg;
492: PetscFunctionBegin;
493: PetscOptionsHeadBegin(PetscOptionsObject, "KSP FCG Options");
494: PetscCall(PetscOptionsInt("-ksp_fcg_mmax", "Maximum number of search directions to store", "KSPFCGSetMmax", fcg->mmax, &mmax, &flg));
495: if (flg) PetscCall(KSPFCGSetMmax(ksp, mmax));
496: PetscCall(PetscOptionsInt("-ksp_fcg_nprealloc", "Number of directions to preallocate", "KSPFCGSetNprealloc", fcg->nprealloc, &nprealloc, &flg));
497: if (flg) PetscCall(KSPFCGSetNprealloc(ksp, nprealloc));
498: PetscCall(PetscOptionsEnum("-ksp_fcg_truncation_type", "Truncation approach for directions", "KSPFCGSetTruncationType", KSPFCDTruncationTypes, (PetscEnum)fcg->truncstrat, (PetscEnum *)&fcg->truncstrat, NULL));
499: PetscOptionsHeadEnd();
500: PetscFunctionReturn(PETSC_SUCCESS);
501: }
503: /*MC
504: KSPFCG - Implements the Flexible Conjugate Gradient method (FCG) {cite}`flexiblecg`, {cite}`generalizedcg`.
505: Unlike most `KSP` methods this allows the preconditioner to be nonlinear. [](sec_flexibleksp)
507: Options Database Keys:
508: + -ksp_fcg_mmax <N> - maximum number of search directions, similar to the restart in `KSPGMRES` and `KSPFGMRES`
509: . -ksp_fcg_nprealloc <N> - number of directions to preallocate
510: - -ksp_fcg_truncation_type <standard,notay> - truncation approach for directions
512: Level: beginner
514: Notes:
515: `KSPFGMRES` provides a flexible GMRES which can be used for matrices that are not symmetric positive-definite (SPD).
517: Supports left preconditioning only.
519: Contributed by:
520: Patrick Sanan
522: .seealso: [](ch_ksp), [](sec_flexibleksp), `KSPGCR`, `KSPFGMRES`, `KSPCG`, `KSPFCGSetMmax()`, `KSPFCGGetMmax()`, `KSPFCGSetNprealloc()`, `KSPFCGGetNprealloc()`, `KSPFCGSetTruncationType()`, `KSPFCGGetTruncationType()`,
523: `KSPFCGGetTruncationType`
524: M*/
525: PETSC_EXTERN PetscErrorCode KSPCreate_FCG(KSP ksp)
526: {
527: KSP_FCG *fcg;
529: PetscFunctionBegin;
530: PetscCall(PetscNew(&fcg));
531: #if !defined(PETSC_USE_COMPLEX)
532: fcg->type = KSP_CG_SYMMETRIC;
533: #else
534: fcg->type = KSP_CG_HERMITIAN;
535: #endif
536: fcg->mmax = KSPFCG_DEFAULT_MMAX;
537: fcg->nprealloc = KSPFCG_DEFAULT_NPREALLOC;
538: fcg->nvecs = 0;
539: fcg->vecb = KSPFCG_DEFAULT_VECB;
540: fcg->nchunks = 0;
541: fcg->truncstrat = KSPFCG_DEFAULT_TRUNCSTRAT;
543: ksp->data = (void *)fcg;
545: PetscCall(KSPSetSupportedNorm(ksp, KSP_NORM_PRECONDITIONED, PC_LEFT, 2));
546: PetscCall(KSPSetSupportedNorm(ksp, KSP_NORM_UNPRECONDITIONED, PC_LEFT, 1));
547: PetscCall(KSPSetSupportedNorm(ksp, KSP_NORM_NATURAL, PC_LEFT, 1));
548: PetscCall(KSPSetSupportedNorm(ksp, KSP_NORM_NONE, PC_LEFT, 1));
550: ksp->ops->setup = KSPSetUp_FCG;
551: ksp->ops->solve = KSPSolve_FCG;
552: ksp->ops->destroy = KSPDestroy_FCG;
553: ksp->ops->view = KSPView_FCG;
554: ksp->ops->setfromoptions = KSPSetFromOptions_FCG;
555: ksp->ops->buildsolution = KSPBuildSolutionDefault;
556: ksp->ops->buildresidual = KSPBuildResidualDefault;
557: PetscFunctionReturn(PETSC_SUCCESS);
558: }