Actual source code: rich.c

  1: /*
  2:             This implements Richardson Iteration.
  3: */
  4: #include <../src/ksp/ksp/impls/rich/richardsonimpl.h>

  6: static PetscErrorCode KSPSetUp_Richardson(KSP ksp)
  7: {
  8:   KSP_Richardson *richardsonP = (KSP_Richardson *)ksp->data;

 10:   PetscFunctionBegin;
 11:   if (richardsonP->selfscale) {
 12:     PetscCall(KSPSetWorkVecs(ksp, 4));
 13:   } else {
 14:     PetscCall(KSPSetWorkVecs(ksp, 2));
 15:   }
 16:   PetscFunctionReturn(PETSC_SUCCESS);
 17: }

 19: static PetscErrorCode KSPSolve_Richardson(KSP ksp)
 20: {
 21:   PetscInt        i, maxit;
 22:   PetscReal       rnorm = 0.0, abr;
 23:   PetscScalar     scale, rdot;
 24:   Vec             x, b, r, z, w = NULL, y = NULL;
 25:   PetscInt        xs, ws;
 26:   Mat             Amat, Pmat;
 27:   KSP_Richardson *richardsonP = (KSP_Richardson *)ksp->data;
 28:   PetscBool       exists, diagonalscale;
 29:   MatNullSpace    nullsp;

 31:   PetscFunctionBegin;
 32:   PetscCall(PCGetDiagonalScale(ksp->pc, &diagonalscale));
 33:   PetscCheck(!diagonalscale, PetscObjectComm((PetscObject)ksp), PETSC_ERR_SUP, "Krylov method %s does not support diagonal scaling", ((PetscObject)ksp)->type_name);

 35:   ksp->its = 0;

 37:   PetscCall(PCGetOperators(ksp->pc, &Amat, &Pmat));
 38:   x = ksp->vec_sol;
 39:   b = ksp->vec_rhs;
 40:   PetscCall(VecGetSize(x, &xs));
 41:   PetscCall(VecGetSize(ksp->work[0], &ws));
 42:   if (xs != ws) {
 43:     if (richardsonP->selfscale) {
 44:       PetscCall(KSPSetWorkVecs(ksp, 4));
 45:     } else {
 46:       PetscCall(KSPSetWorkVecs(ksp, 2));
 47:     }
 48:   }
 49:   r = ksp->work[0];
 50:   z = ksp->work[1];
 51:   if (richardsonP->selfscale) {
 52:     w = ksp->work[2];
 53:     y = ksp->work[3];
 54:   }
 55:   maxit = ksp->max_it;

 57:   /* if user has provided fast Richardson code use that */
 58:   PetscCall(PCApplyRichardsonExists(ksp->pc, &exists));
 59:   PetscCall(MatGetNullSpace(Pmat, &nullsp));
 60:   if (exists && maxit > 0 && richardsonP->scale == 1.0 && (ksp->converged == KSPConvergedDefault || ksp->converged == KSPConvergedSkip) && !ksp->numbermonitors && !ksp->transpose_solve && !nullsp) {
 61:     PCRichardsonConvergedReason reason;
 62:     PetscCall(PCApplyRichardson(ksp->pc, b, x, r, ksp->rtol, ksp->abstol, ksp->divtol, maxit, ksp->guess_zero, &ksp->its, &reason));
 63:     ksp->reason = (KSPConvergedReason)reason;
 64:     PetscFunctionReturn(PETSC_SUCCESS);
 65:   } else {
 66:     PetscCall(PetscInfo(ksp, "KSPSolve_Richardson: Warning, skipping optimized PCApplyRichardson()\n"));
 67:   }

 69:   if (!ksp->guess_zero) { /*   r <- b - A x     */
 70:     PetscCall(KSP_MatMult(ksp, Amat, x, r));
 71:     PetscCall(VecAYPX(r, -1.0, b));
 72:   } else {
 73:     PetscCall(VecCopy(b, r));
 74:   }

 76:   ksp->its = 0;
 77:   if (richardsonP->selfscale) {
 78:     PetscCall(KSP_PCApply(ksp, r, z)); /*   z <- B r          */
 79:     for (i = 0; i < maxit; i++) {
 80:       if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
 81:         PetscCall(VecNorm(r, NORM_2, &rnorm)); /*   rnorm <- r'*r     */
 82:       } else if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
 83:         PetscCall(VecNorm(z, NORM_2, &rnorm)); /*   rnorm <- z'*z     */
 84:       } else rnorm = 0.0;

 86:       KSPCheckNorm(ksp, rnorm);
 87:       ksp->rnorm = rnorm;
 88:       PetscCall(KSPMonitor(ksp, i, rnorm));
 89:       PetscCall(KSPLogResidualHistory(ksp, rnorm));
 90:       PetscCall((*ksp->converged)(ksp, i, rnorm, &ksp->reason, ksp->cnvP));
 91:       if (ksp->reason) break;
 92:       PetscCall(KSP_PCApplyBAorAB(ksp, z, y, w)); /* y = BAz = BABr */
 93:       PetscCall(VecDotNorm2(z, y, &rdot, &abr));  /*   rdot = (Br)^T(BABR); abr = (BABr)^T (BABr) */
 94:       scale = rdot / abr;
 95:       PetscCall(PetscInfo(ksp, "Self-scale factor %g\n", (double)PetscRealPart(scale)));
 96:       PetscCall(VecAXPY(x, scale, z));  /*   x  <- x + scale z */
 97:       PetscCall(VecAXPY(r, -scale, w)); /*  r <- r - scale*Az */
 98:       PetscCall(VecAXPY(z, -scale, y)); /*  z <- z - scale*y */
 99:       ksp->its++;
100:     }
101:   } else {
102:     for (i = 0; i < maxit; i++) {
103:       if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
104:         PetscCall(VecNorm(r, NORM_2, &rnorm)); /*   rnorm <- r'*r     */
105:       } else if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
106:         PetscCall(KSP_PCApply(ksp, r, z));     /*   z <- B r          */
107:         PetscCall(VecNorm(z, NORM_2, &rnorm)); /*   rnorm <- z'*z     */
108:       } else rnorm = 0.0;
109:       ksp->rnorm = rnorm;
110:       PetscCall(KSPMonitor(ksp, i, rnorm));
111:       PetscCall(KSPLogResidualHistory(ksp, rnorm));
112:       PetscCall((*ksp->converged)(ksp, i, rnorm, &ksp->reason, ksp->cnvP));
113:       if (ksp->reason) break;
114:       if (ksp->normtype != KSP_NORM_PRECONDITIONED) { PetscCall(KSP_PCApply(ksp, r, z)); /*   z <- B r          */ }

116:       PetscCall(VecAXPY(x, richardsonP->scale, z)); /*   x  <- x + scale z */
117:       ksp->its++;

119:       if (i + 1 < maxit || ksp->normtype != KSP_NORM_NONE) {
120:         PetscCall(KSP_MatMult(ksp, Amat, x, r)); /*   r  <- b - Ax      */
121:         PetscCall(VecAYPX(r, -1.0, b));
122:       }
123:     }
124:   }
125:   if (!ksp->reason) {
126:     if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
127:       PetscCall(VecNorm(r, NORM_2, &rnorm)); /*   rnorm <- r'*r     */
128:     } else if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
129:       PetscCall(KSP_PCApply(ksp, r, z));     /*   z <- B r          */
130:       PetscCall(VecNorm(z, NORM_2, &rnorm)); /*   rnorm <- z'*z     */
131:     } else rnorm = 0.0;

133:     KSPCheckNorm(ksp, rnorm);
134:     ksp->rnorm = rnorm;
135:     PetscCall(KSPLogResidualHistory(ksp, rnorm));
136:     PetscCall(KSPMonitor(ksp, i, rnorm));
137:     if (ksp->its >= ksp->max_it) {
138:       if (ksp->normtype != KSP_NORM_NONE) {
139:         PetscCall((*ksp->converged)(ksp, i, rnorm, &ksp->reason, ksp->cnvP));
140:         if (!ksp->reason) ksp->reason = KSP_DIVERGED_ITS;
141:       } else {
142:         ksp->reason = KSP_CONVERGED_ITS;
143:       }
144:     }
145:   }
146:   PetscFunctionReturn(PETSC_SUCCESS);
147: }

149: static PetscErrorCode KSPView_Richardson(KSP ksp, PetscViewer viewer)
150: {
151:   KSP_Richardson *richardsonP = (KSP_Richardson *)ksp->data;
152:   PetscBool       iascii;

154:   PetscFunctionBegin;
155:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &iascii));
156:   if (iascii) {
157:     if (richardsonP->selfscale) {
158:       PetscCall(PetscViewerASCIIPrintf(viewer, "  using self-scale best computed damping factor\n"));
159:     } else {
160:       PetscCall(PetscViewerASCIIPrintf(viewer, "  damping factor=%g\n", (double)richardsonP->scale));
161:     }
162:   }
163:   PetscFunctionReturn(PETSC_SUCCESS);
164: }

166: static PetscErrorCode KSPSetFromOptions_Richardson(KSP ksp, PetscOptionItems *PetscOptionsObject)
167: {
168:   KSP_Richardson *rich = (KSP_Richardson *)ksp->data;
169:   PetscReal       tmp;
170:   PetscBool       flg, flg2;

172:   PetscFunctionBegin;
173:   PetscOptionsHeadBegin(PetscOptionsObject, "KSP Richardson Options");
174:   PetscCall(PetscOptionsReal("-ksp_richardson_scale", "damping factor", "KSPRichardsonSetScale", rich->scale, &tmp, &flg));
175:   if (flg) PetscCall(KSPRichardsonSetScale(ksp, tmp));
176:   PetscCall(PetscOptionsBool("-ksp_richardson_self_scale", "dynamically determine optimal damping factor", "KSPRichardsonSetSelfScale", rich->selfscale, &flg2, &flg));
177:   if (flg) PetscCall(KSPRichardsonSetSelfScale(ksp, flg2));
178:   PetscOptionsHeadEnd();
179:   PetscFunctionReturn(PETSC_SUCCESS);
180: }

182: static PetscErrorCode KSPDestroy_Richardson(KSP ksp)
183: {
184:   PetscFunctionBegin;
185:   PetscCall(PetscObjectComposeFunction((PetscObject)ksp, "KSPRichardsonSetScale_C", NULL));
186:   PetscCall(PetscObjectComposeFunction((PetscObject)ksp, "KSPRichardsonSetSelfScale_C", NULL));
187:   PetscCall(KSPDestroyDefault(ksp));
188:   PetscFunctionReturn(PETSC_SUCCESS);
189: }

191: static PetscErrorCode KSPRichardsonSetScale_Richardson(KSP ksp, PetscReal scale)
192: {
193:   KSP_Richardson *richardsonP;

195:   PetscFunctionBegin;
196:   richardsonP        = (KSP_Richardson *)ksp->data;
197:   richardsonP->scale = scale;
198:   PetscFunctionReturn(PETSC_SUCCESS);
199: }

201: static PetscErrorCode KSPRichardsonSetSelfScale_Richardson(KSP ksp, PetscBool selfscale)
202: {
203:   KSP_Richardson *richardsonP;

205:   PetscFunctionBegin;
206:   richardsonP            = (KSP_Richardson *)ksp->data;
207:   richardsonP->selfscale = selfscale;
208:   PetscFunctionReturn(PETSC_SUCCESS);
209: }

211: static PetscErrorCode KSPBuildResidual_Richardson(KSP ksp, Vec t, Vec v, Vec *V)
212: {
213:   PetscFunctionBegin;
214:   if (ksp->normtype == KSP_NORM_NONE) {
215:     PetscCall(KSPBuildResidualDefault(ksp, t, v, V));
216:   } else {
217:     PetscCall(VecCopy(ksp->work[0], v));
218:     *V = v;
219:   }
220:   PetscFunctionReturn(PETSC_SUCCESS);
221: }

223: /*MC
224:     KSPRICHARDSON - The preconditioned Richardson iterative method {cite}`richarson1911`

226:    Options Database Key:
227: .   -ksp_richardson_scale - damping factor on the correction (defaults to 1.0)

229:    Level: beginner

231:    Notes:
232:    $ x^{n+1} = x^{n} + scale*B(b - A x^{n})$

234:    Here B is the application of the preconditioner

236:    This method often (usually) will not converge unless scale is very small.

238:    For some preconditioners, currently `PCSOR`, the convergence test is skipped to improve speed,
239:    thus it always iterates the maximum number of iterations you've selected. When -ksp_monitor
240:    (or any other monitor) is turned on, the norm is computed at each iteration and so the convergence test is run unless
241:    you specifically call `KSPSetNormType`(ksp,`KSP_NORM_NONE`);

243:    For some preconditioners, currently `PCMG` and `PCHYPRE` with BoomerAMG if -ksp_monitor (and also
244:    any other monitor) is not turned on then the convergence test is done by the preconditioner itself and
245:    so the solver may run more or fewer iterations then if -ksp_monitor is selected.

247:    Supports only left preconditioning

249:    If using direct solvers such as `PCLU` and `PCCHOLESKY` one generally uses `KSPPREONLY` instead of this which uses exactly one iteration

251:    `-ksp_type richardson -pc_type jacobi` gives one classical Jacobi preconditioning

253: .seealso: [](ch_ksp), `KSPCreate()`, `KSPSetType()`, `KSPType`, `KSP`,
254:           `KSPRichardsonSetScale()`, `KSPPREONLY`, `KSPRichardsonSetSelfScale()`
255: M*/

257: PETSC_EXTERN PetscErrorCode KSPCreate_Richardson(KSP ksp)
258: {
259:   KSP_Richardson *richardsonP;

261:   PetscFunctionBegin;
262:   PetscCall(PetscNew(&richardsonP));
263:   ksp->data = (void *)richardsonP;

265:   PetscCall(KSPSetSupportedNorm(ksp, KSP_NORM_PRECONDITIONED, PC_LEFT, 3));
266:   PetscCall(KSPSetSupportedNorm(ksp, KSP_NORM_UNPRECONDITIONED, PC_LEFT, 2));
267:   PetscCall(KSPSetSupportedNorm(ksp, KSP_NORM_NONE, PC_LEFT, 1));

269:   ksp->ops->setup          = KSPSetUp_Richardson;
270:   ksp->ops->solve          = KSPSolve_Richardson;
271:   ksp->ops->destroy        = KSPDestroy_Richardson;
272:   ksp->ops->buildsolution  = KSPBuildSolutionDefault;
273:   ksp->ops->buildresidual  = KSPBuildResidual_Richardson;
274:   ksp->ops->view           = KSPView_Richardson;
275:   ksp->ops->setfromoptions = KSPSetFromOptions_Richardson;

277:   PetscCall(PetscObjectComposeFunction((PetscObject)ksp, "KSPRichardsonSetScale_C", KSPRichardsonSetScale_Richardson));
278:   PetscCall(PetscObjectComposeFunction((PetscObject)ksp, "KSPRichardsonSetSelfScale_C", KSPRichardsonSetSelfScale_Richardson));

280:   richardsonP->scale = 1.0;
281:   PetscFunctionReturn(PETSC_SUCCESS);
282: }