Actual source code: eisen.c


  2: /*
  3:    Defines a  Eisenstat trick SSOR  preconditioner. This uses about
  4:  %50 of the usual amount of floating point ops used for SSOR + Krylov
  5:  method. But it requires actually solving the preconditioned problem
  6:  with both left and right preconditioning.
  7: */
  8: #include <petsc/private/pcimpl.h>

 10: typedef struct {
 11:   Mat       shell, A;
 12:   Vec       b[2], diag; /* temporary storage for true right hand side */
 13:   PetscReal omega;
 14:   PetscBool usediag; /* indicates preconditioner should include diagonal scaling*/
 15: } PC_Eisenstat;

 17: static PetscErrorCode PCMult_Eisenstat(Mat mat, Vec b, Vec x)
 18: {
 19:   PC            pc;
 20:   PC_Eisenstat *eis;

 22:   PetscFunctionBegin;
 23:   PetscCall(MatShellGetContext(mat, &pc));
 24:   eis = (PC_Eisenstat *)pc->data;
 25:   PetscCall(MatSOR(eis->A, b, eis->omega, SOR_EISENSTAT, 0.0, 1, 1, x));
 26:   PetscCall(MatFactorGetError(eis->A, (MatFactorError *)&pc->failedreason));
 27:   PetscFunctionReturn(PETSC_SUCCESS);
 28: }

 30: static PetscErrorCode PCNorm_Eisenstat(Mat mat, NormType type, PetscReal *nrm)
 31: {
 32:   PC            pc;
 33:   PC_Eisenstat *eis;

 35:   PetscFunctionBegin;
 36:   PetscCall(MatShellGetContext(mat, &pc));
 37:   eis = (PC_Eisenstat *)pc->data;
 38:   PetscCall(MatNorm(eis->A, type, nrm));
 39:   PetscFunctionReturn(PETSC_SUCCESS);
 40: }

 42: static PetscErrorCode PCApply_Eisenstat(PC pc, Vec x, Vec y)
 43: {
 44:   PC_Eisenstat *eis = (PC_Eisenstat *)pc->data;
 45:   PetscBool     hasop;

 47:   PetscFunctionBegin;
 48:   if (eis->usediag) {
 49:     PetscCall(MatHasOperation(pc->pmat, MATOP_MULT_DIAGONAL_BLOCK, &hasop));
 50:     if (hasop) {
 51:       PetscCall(MatMultDiagonalBlock(pc->pmat, x, y));
 52:     } else {
 53:       PetscCall(VecPointwiseMult(y, x, eis->diag));
 54:     }
 55:   } else PetscCall(VecCopy(x, y));
 56:   PetscFunctionReturn(PETSC_SUCCESS);
 57: }

 59: static PetscErrorCode PCApplyTranspose_Eisenstat(PC pc, Vec x, Vec y)
 60: {
 61:   PC_Eisenstat *eis = (PC_Eisenstat *)pc->data;
 62:   PetscBool     hasop, set, sym;

 64:   PetscFunctionBegin;
 65:   PetscCall(MatIsSymmetricKnown(eis->A, &set, &sym));
 66:   PetscCheck(set && sym, PetscObjectComm((PetscObject)pc), PETSC_ERR_SUP, "Can only apply transpose of Eisenstat if matrix is symmetric");
 67:   if (eis->usediag) {
 68:     PetscCall(MatHasOperation(pc->pmat, MATOP_MULT_DIAGONAL_BLOCK, &hasop));
 69:     if (hasop) {
 70:       PetscCall(MatMultDiagonalBlock(pc->pmat, x, y));
 71:     } else {
 72:       PetscCall(VecPointwiseMult(y, x, eis->diag));
 73:     }
 74:   } else PetscCall(VecCopy(x, y));
 75:   PetscFunctionReturn(PETSC_SUCCESS);
 76: }

 78: static PetscErrorCode PCPreSolve_Eisenstat(PC pc, KSP ksp, Vec b, Vec x)
 79: {
 80:   PC_Eisenstat *eis = (PC_Eisenstat *)pc->data;
 81:   PetscBool     nonzero;

 83:   PetscFunctionBegin;
 84:   if (pc->presolvedone < 2) {
 85:     PetscCheck(pc->mat == pc->pmat, PetscObjectComm((PetscObject)pc), PETSC_ERR_SUP, "Cannot have different mat and pmat");
 86:     /* swap shell matrix and true matrix */
 87:     eis->A  = pc->mat;
 88:     pc->mat = eis->shell;
 89:   }

 91:   if (!eis->b[pc->presolvedone - 1]) { PetscCall(VecDuplicate(b, &eis->b[pc->presolvedone - 1])); }

 93:   /* if nonzero initial guess, modify x */
 94:   PetscCall(KSPGetInitialGuessNonzero(ksp, &nonzero));
 95:   if (nonzero) {
 96:     PetscCall(VecCopy(x, eis->b[pc->presolvedone - 1]));
 97:     PetscCall(MatSOR(eis->A, eis->b[pc->presolvedone - 1], eis->omega, SOR_APPLY_UPPER, 0.0, 1, 1, x));
 98:     PetscCall(MatFactorGetError(eis->A, (MatFactorError *)&pc->failedreason));
 99:   }

101:   /* save true b, other option is to swap pointers */
102:   PetscCall(VecCopy(b, eis->b[pc->presolvedone - 1]));

104:   /* modify b by (L + D/omega)^{-1} */
105:   PetscCall(MatSOR(eis->A, eis->b[pc->presolvedone - 1], eis->omega, (MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP), 0.0, 1, 1, b));
106:   PetscCall(MatFactorGetError(eis->A, (MatFactorError *)&pc->failedreason));
107:   PetscFunctionReturn(PETSC_SUCCESS);
108: }

110: static PetscErrorCode PCPostSolve_Eisenstat(PC pc, KSP ksp, Vec b, Vec x)
111: {
112:   PC_Eisenstat *eis = (PC_Eisenstat *)pc->data;

114:   PetscFunctionBegin;
115:   /* get back true b */
116:   PetscCall(VecCopy(eis->b[pc->presolvedone], b));

118:   /* modify x by (U + D/omega)^{-1} */
119:   PetscCall(VecCopy(x, eis->b[pc->presolvedone]));
120:   PetscCall(MatSOR(eis->A, eis->b[pc->presolvedone], eis->omega, (MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP), 0.0, 1, 1, x));
121:   PetscCall(MatFactorGetError(eis->A, (MatFactorError *)&pc->failedreason));
122:   if (!pc->presolvedone) pc->mat = eis->A;
123:   PetscFunctionReturn(PETSC_SUCCESS);
124: }

126: static PetscErrorCode PCReset_Eisenstat(PC pc)
127: {
128:   PC_Eisenstat *eis = (PC_Eisenstat *)pc->data;

130:   PetscFunctionBegin;
131:   PetscCall(VecDestroy(&eis->b[0]));
132:   PetscCall(VecDestroy(&eis->b[1]));
133:   PetscCall(MatDestroy(&eis->shell));
134:   PetscCall(VecDestroy(&eis->diag));
135:   PetscFunctionReturn(PETSC_SUCCESS);
136: }

138: static PetscErrorCode PCDestroy_Eisenstat(PC pc)
139: {
140:   PetscFunctionBegin;
141:   PetscCall(PCReset_Eisenstat(pc));
142:   PetscCall(PetscObjectComposeFunction((PetscObject)pc, "PCEisenstatSetOmega_C", NULL));
143:   PetscCall(PetscObjectComposeFunction((PetscObject)pc, "PCEisenstatSetNoDiagonalScaling_C", NULL));
144:   PetscCall(PetscObjectComposeFunction((PetscObject)pc, "PCEisenstatGetOmega_C", NULL));
145:   PetscCall(PetscObjectComposeFunction((PetscObject)pc, "PCEisenstatGetNoDiagonalScaling_C", NULL));
146:   PetscCall(PetscObjectComposeFunction((PetscObject)pc, "PCPreSolveChangeRHS_C", NULL));
147:   PetscCall(PetscFree(pc->data));
148:   PetscFunctionReturn(PETSC_SUCCESS);
149: }

151: static PetscErrorCode PCSetFromOptions_Eisenstat(PC pc, PetscOptionItems *PetscOptionsObject)
152: {
153:   PC_Eisenstat *eis = (PC_Eisenstat *)pc->data;
154:   PetscBool     set, flg;
155:   PetscReal     omega;

157:   PetscFunctionBegin;
158:   PetscOptionsHeadBegin(PetscOptionsObject, "Eisenstat SSOR options");
159:   PetscCall(PetscOptionsReal("-pc_eisenstat_omega", "Relaxation factor 0 < omega < 2", "PCEisenstatSetOmega", eis->omega, &omega, &flg));
160:   if (flg) PetscCall(PCEisenstatSetOmega(pc, omega));
161:   PetscCall(PetscOptionsBool("-pc_eisenstat_no_diagonal_scaling", "Do not use standard diagonal scaling", "PCEisenstatSetNoDiagonalScaling", eis->usediag ? PETSC_FALSE : PETSC_TRUE, &flg, &set));
162:   if (set) PetscCall(PCEisenstatSetNoDiagonalScaling(pc, flg));
163:   PetscOptionsHeadEnd();
164:   PetscFunctionReturn(PETSC_SUCCESS);
165: }

167: static PetscErrorCode PCView_Eisenstat(PC pc, PetscViewer viewer)
168: {
169:   PC_Eisenstat *eis = (PC_Eisenstat *)pc->data;
170:   PetscBool     iascii;

172:   PetscFunctionBegin;
173:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &iascii));
174:   if (iascii) {
175:     PetscCall(PetscViewerASCIIPrintf(viewer, "  omega = %g\n", (double)eis->omega));
176:     if (eis->usediag) {
177:       PetscCall(PetscViewerASCIIPrintf(viewer, "  Using diagonal scaling (default)\n"));
178:     } else {
179:       PetscCall(PetscViewerASCIIPrintf(viewer, "  Not using diagonal scaling\n"));
180:     }
181:   }
182:   PetscFunctionReturn(PETSC_SUCCESS);
183: }

185: static PetscErrorCode PCSetUp_Eisenstat(PC pc)
186: {
187:   PetscInt      M, N, m, n;
188:   PetscBool     set, sym;
189:   PC_Eisenstat *eis = (PC_Eisenstat *)pc->data;

191:   PetscFunctionBegin;
192:   if (!pc->setupcalled) {
193:     PetscCall(MatGetSize(pc->mat, &M, &N));
194:     PetscCall(MatGetLocalSize(pc->mat, &m, &n));
195:     PetscCall(MatIsSymmetricKnown(pc->mat, &set, &sym));
196:     PetscCall(MatCreate(PetscObjectComm((PetscObject)pc), &eis->shell));
197:     PetscCall(MatSetSizes(eis->shell, m, n, M, N));
198:     PetscCall(MatSetType(eis->shell, MATSHELL));
199:     PetscCall(MatSetUp(eis->shell));
200:     PetscCall(MatShellSetContext(eis->shell, pc));
201:     PetscCall(MatShellSetOperation(eis->shell, MATOP_MULT, (void (*)(void))PCMult_Eisenstat));
202:     if (set && sym) PetscCall(MatShellSetOperation(eis->shell, MATOP_MULT_TRANSPOSE, (void (*)(void))PCMult_Eisenstat));
203:     PetscCall(MatShellSetOperation(eis->shell, MATOP_NORM, (void (*)(void))PCNorm_Eisenstat));
204:   }
205:   if (!eis->usediag) PetscFunctionReturn(PETSC_SUCCESS);
206:   if (!pc->setupcalled) { PetscCall(MatCreateVecs(pc->pmat, &eis->diag, NULL)); }
207:   PetscCall(MatGetDiagonal(pc->pmat, eis->diag));
208:   PetscFunctionReturn(PETSC_SUCCESS);
209: }

211: /* --------------------------------------------------------------------*/

213: static PetscErrorCode PCEisenstatSetOmega_Eisenstat(PC pc, PetscReal omega)
214: {
215:   PC_Eisenstat *eis = (PC_Eisenstat *)pc->data;

217:   PetscFunctionBegin;
218:   PetscCheck(omega > 0.0 && omega < 2.0, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_OUTOFRANGE, "Relaxation out of range");
219:   eis->omega = omega;
220:   PetscFunctionReturn(PETSC_SUCCESS);
221: }

223: static PetscErrorCode PCEisenstatSetNoDiagonalScaling_Eisenstat(PC pc, PetscBool flg)
224: {
225:   PC_Eisenstat *eis = (PC_Eisenstat *)pc->data;

227:   PetscFunctionBegin;
228:   eis->usediag = flg;
229:   PetscFunctionReturn(PETSC_SUCCESS);
230: }

232: static PetscErrorCode PCEisenstatGetOmega_Eisenstat(PC pc, PetscReal *omega)
233: {
234:   PC_Eisenstat *eis = (PC_Eisenstat *)pc->data;

236:   PetscFunctionBegin;
237:   *omega = eis->omega;
238:   PetscFunctionReturn(PETSC_SUCCESS);
239: }

241: static PetscErrorCode PCEisenstatGetNoDiagonalScaling_Eisenstat(PC pc, PetscBool *flg)
242: {
243:   PC_Eisenstat *eis = (PC_Eisenstat *)pc->data;

245:   PetscFunctionBegin;
246:   *flg = eis->usediag;
247:   PetscFunctionReturn(PETSC_SUCCESS);
248: }

250: /*@
251:    PCEisenstatSetOmega - Sets the SSOR relaxation coefficient, omega,
252:    to use with Eisenstat's trick (where omega = 1.0 by default)

254:    Logically Collective

256:    Input Parameters:
257: +  pc - the preconditioner context
258: -  omega - relaxation coefficient (0 < omega < 2)

260:    Options Database Key:
261: .  -pc_eisenstat_omega <omega> - Sets omega

263:    Level: intermediate

265:    Notes:
266:    The Eisenstat trick implementation of SSOR requires about 50% of the
267:    usual amount of floating point operations used for SSOR + Krylov method;
268:    however, the preconditioned problem must be solved with both left
269:    and right preconditioning.

271:    To use SSOR without the Eisenstat trick, employ the `PCSOR` preconditioner,
272:    which can be chosen with the database options `-pc_type sor -pc_sor_symmetric`

274: .seealso: `PCSORSetOmega()`, `PCEISENSTAT`
275: @*/
276: PetscErrorCode PCEisenstatSetOmega(PC pc, PetscReal omega)
277: {
278:   PetscFunctionBegin;
281:   PetscTryMethod(pc, "PCEisenstatSetOmega_C", (PC, PetscReal), (pc, omega));
282:   PetscFunctionReturn(PETSC_SUCCESS);
283: }

285: /*@
286:    PCEisenstatSetNoDiagonalScaling - Causes the Eisenstat preconditioner, `PCEISENSTAT`
287:    not to do additional diagonal preconditioning. For matrices with a constant
288:    along the diagonal, this may save a small amount of work.

290:    Logically Collective

292:    Input Parameters:
293: +  pc - the preconditioner context
294: -  flg - `PETSC_TRUE` turns off diagonal scaling inside the algorithm

296:    Options Database Key:
297: .  -pc_eisenstat_no_diagonal_scaling - Activates `PCEisenstatSetNoDiagonalScaling()`

299:    Level: intermediate

301:    Note:
302:      If you use the `KSPSetDiagonalScaling()` or -ksp_diagonal_scale option then you will
303:    likely want to use this routine since it will save you some unneeded flops.

305: .seealso: `PCEisenstatSetOmega()`, `PCEISENSTAT`
306: @*/
307: PetscErrorCode PCEisenstatSetNoDiagonalScaling(PC pc, PetscBool flg)
308: {
309:   PetscFunctionBegin;
311:   PetscTryMethod(pc, "PCEisenstatSetNoDiagonalScaling_C", (PC, PetscBool), (pc, flg));
312:   PetscFunctionReturn(PETSC_SUCCESS);
313: }

315: /*@
316:    PCEisenstatGetOmega - Gets the SSOR relaxation coefficient, omega,
317:    to use with Eisenstat's trick (where omega = 1.0 by default).

319:    Logically Collective

321:    Input Parameter:
322: .  pc - the preconditioner context

324:    Output Parameter:
325: .  omega - relaxation coefficient (0 < omega < 2)

327:    Options Database Key:
328: .  -pc_eisenstat_omega <omega> - Sets omega

330:    Notes:
331:    The Eisenstat trick implementation of SSOR requires about 50% of the
332:    usual amount of floating point operations used for SSOR + Krylov method;
333:    however, the preconditioned problem must be solved with both left
334:    and right preconditioning.

336:    To use SSOR without the Eisenstat trick, employ the PCSOR preconditioner,
337:    which can be chosen with the database options `-pc_type sor -pc_sor_symmetric`

339:    Level: intermediate

341: .seealso: `PCEISENSTAT`, `PCSORGetOmega()`, `PCEisenstatSetOmega()`
342: @*/
343: PetscErrorCode PCEisenstatGetOmega(PC pc, PetscReal *omega)
344: {
345:   PetscFunctionBegin;
347:   PetscUseMethod(pc, "PCEisenstatGetOmega_C", (PC, PetscReal *), (pc, omega));
348:   PetscFunctionReturn(PETSC_SUCCESS);
349: }

351: /*@
352:    PCEisenstatGetNoDiagonalScaling - Tells if the Eisenstat preconditioner
353:    not to do additional diagonal preconditioning. For matrices with a constant
354:    along the diagonal, this may save a small amount of work.

356:    Logically Collective

358:    Input Parameter:
359: .  pc - the preconditioner context

361:    Output Parameter:
362: .  flg - `PETSC_TRUE` means there is no diagonal scaling applied

364:    Options Database Key:
365: .  -pc_eisenstat_no_diagonal_scaling - Activates `PCEisenstatSetNoDiagonalScaling()`

367:    Level: intermediate

369:    Note:
370:      If you use the KSPSetDiagonalScaling() or -ksp_diagonal_scale option then you will
371:    likely want to use this routine since it will save you some unneeded flops.

373: .seealso: , `PCEISENSTAT`, `PCEisenstatGetOmega()`
374: @*/
375: PetscErrorCode PCEisenstatGetNoDiagonalScaling(PC pc, PetscBool *flg)
376: {
377:   PetscFunctionBegin;
379:   PetscUseMethod(pc, "PCEisenstatGetNoDiagonalScaling_C", (PC, PetscBool *), (pc, flg));
380:   PetscFunctionReturn(PETSC_SUCCESS);
381: }

383: static PetscErrorCode PCPreSolveChangeRHS_Eisenstat(PC pc, PetscBool *change)
384: {
385:   PetscFunctionBegin;
386:   *change = PETSC_TRUE;
387:   PetscFunctionReturn(PETSC_SUCCESS);
388: }

390: /*MC
391:      PCEISENSTAT - An implementation of SSOR (symmetric successive over relaxation, symmetric Gauss-Seidel)
392:            preconditioning that incorporates Eisenstat's trick to reduce the amount of computation needed.

394:    Options Database Keys:
395: +  -pc_eisenstat_omega <omega> - Sets omega
396: -  -pc_eisenstat_no_diagonal_scaling - Activates `PCEisenstatSetNoDiagonalScaling()`

398:    Level: beginner

400:    Notes:
401:    Only implemented for the `MATAIJ` matrix format.

403:    Not a true parallel SOR, in parallel this implementation corresponds to block Jacobi with SOR on each block.

405:    Developer Note:
406:    Since this algorithm runs the Krylov method on a transformed linear system the implementation provides `PCPreSolve()` and `PCPostSolve()`
407:    routines that `KSP` uses to set up the transformed linear system.

409: .seealso: `PCCreate()`, `PCSetType()`, `PCType`, `PC`, `PCEisenstatGetOmega()`,
410:           `PCEisenstatSetNoDiagonalScaling()`, `PCEisenstatSetOmega()`, `PCSOR`
411: M*/

413: PETSC_EXTERN PetscErrorCode PCCreate_Eisenstat(PC pc)
414: {
415:   PC_Eisenstat *eis;

417:   PetscFunctionBegin;
418:   PetscCall(PetscNew(&eis));

420:   pc->ops->apply           = PCApply_Eisenstat;
421:   pc->ops->applytranspose  = PCApplyTranspose_Eisenstat;
422:   pc->ops->presolve        = PCPreSolve_Eisenstat;
423:   pc->ops->postsolve       = PCPostSolve_Eisenstat;
424:   pc->ops->applyrichardson = NULL;
425:   pc->ops->setfromoptions  = PCSetFromOptions_Eisenstat;
426:   pc->ops->destroy         = PCDestroy_Eisenstat;
427:   pc->ops->reset           = PCReset_Eisenstat;
428:   pc->ops->view            = PCView_Eisenstat;
429:   pc->ops->setup           = PCSetUp_Eisenstat;

431:   pc->data     = eis;
432:   eis->omega   = 1.0;
433:   eis->b[0]    = NULL;
434:   eis->b[1]    = NULL;
435:   eis->diag    = NULL;
436:   eis->usediag = PETSC_TRUE;

438:   PetscCall(PetscObjectComposeFunction((PetscObject)pc, "PCEisenstatSetOmega_C", PCEisenstatSetOmega_Eisenstat));
439:   PetscCall(PetscObjectComposeFunction((PetscObject)pc, "PCEisenstatSetNoDiagonalScaling_C", PCEisenstatSetNoDiagonalScaling_Eisenstat));
440:   PetscCall(PetscObjectComposeFunction((PetscObject)pc, "PCEisenstatGetOmega_C", PCEisenstatGetOmega_Eisenstat));
441:   PetscCall(PetscObjectComposeFunction((PetscObject)pc, "PCEisenstatGetNoDiagonalScaling_C", PCEisenstatGetNoDiagonalScaling_Eisenstat));
442:   PetscCall(PetscObjectComposeFunction((PetscObject)pc, "PCPreSolveChangeRHS_C", PCPreSolveChangeRHS_Eisenstat));
443:   PetscFunctionReturn(PETSC_SUCCESS);
444: }