Date: 2024-10-28T09:13:46+00:00

Actual source code: narnoldi.c
slepc-3.22.1 2024-10-28
Report Typos and Errors

      1: /*
      2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
      4:    Copyright (c) 2002-, Universitat Politecnica de Valencia, Spain

      6:    This file is part of SLEPc.
      7:    SLEPc is distributed under a 2-clause BSD license (see LICENSE).
      8:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      9: */
     10: /*
     11:    SLEPc nonlinear eigensolver: "narnoldi"

     13:    Method: Nonlinear Arnoldi

     15:    Algorithm:

     17:        Arnoldi for nonlinear eigenproblems.

     19:    References:

     21:        [1] H. Voss, "An Arnoldi method for nonlinear eigenvalue problems",
     22:            BIT 44:387-401, 2004.
     23: */

     25: #include <slepc/private/nepimpl.h>
     26: #include <../src/nep/impls/nepdefl.h>

     28: typedef struct {
     29:   PetscInt lag;             /* interval to rebuild preconditioner */
     30:   KSP      ksp;             /* linear solver object */
     31: } NEP_NARNOLDI;

     33: static PetscErrorCode NEPSetUp_NArnoldi(NEP nep)
     34: {
     35:   PetscFunctionBegin;
     36:   PetscCall(NEPSetDimensions_Default(nep,nep->nev,&nep->ncv,&nep->mpd));
     37:   PetscCheck(nep->ncv<=nep->nev+nep->mpd,PetscObjectComm((PetscObject)nep),PETSC_ERR_USER_INPUT,"The value of ncv must not be larger than nev+mpd");
     38:   if (nep->max_it==PETSC_DETERMINE) nep->max_it = nep->nev*nep->ncv;
     39:   if (!nep->which) nep->which = NEP_TARGET_MAGNITUDE;
     40:   PetscCheck(nep->which==NEP_TARGET_MAGNITUDE,PetscObjectComm((PetscObject)nep),PETSC_ERR_SUP,"This solver supports only target magnitude eigenvalues");
     41:   NEPCheckUnsupported(nep,NEP_FEATURE_CALLBACK | NEP_FEATURE_REGION | NEP_FEATURE_TWOSIDED);
     42:   PetscCall(NEPAllocateSolution(nep,0));
     43:   PetscCall(NEPSetWorkVecs(nep,3));
     44:   PetscFunctionReturn(PETSC_SUCCESS);
     45: }

     47: static PetscErrorCode NEPSolve_NArnoldi(NEP nep)
     48: {
     49:   NEP_NARNOLDI       *ctx = (NEP_NARNOLDI*)nep->data;
     50:   Mat                T,H,A;
     51:   Vec                f,r,u,uu;
     52:   PetscScalar        *X,lambda=0.0,lambda2=0.0,*eigr,sigma;
     53:   PetscReal          beta,resnorm=0.0,nrm,perr=0.0;
     54:   PetscInt           n;
     55:   PetscBool          breakdown,skip=PETSC_FALSE;
     56:   BV                 Vext;
     57:   DS                 ds;
     58:   NEP_EXT_OP         extop=NULL;
     59:   SlepcSC            sc;
     60:   KSPConvergedReason kspreason;

     62:   PetscFunctionBegin;
     63:   /* get initial space and shift */
     64:   PetscCall(NEPGetDefaultShift(nep,&sigma));
     65:   if (!nep->nini) {
     66:     PetscCall(BVSetRandomColumn(nep->V,0));
     67:     PetscCall(BVNormColumn(nep->V,0,NORM_2,&nrm));
     68:     PetscCall(BVScaleColumn(nep->V,0,1.0/nrm));
     69:     n = 1;
     70:   } else n = nep->nini;

     72:   if (!ctx->ksp) PetscCall(NEPNArnoldiGetKSP(nep,&ctx->ksp));
     73:   PetscCall(NEPDeflationInitialize(nep,nep->V,ctx->ksp,PETSC_FALSE,nep->nev,&extop));
     74:   PetscCall(NEPDeflationCreateBV(extop,nep->ncv,&Vext));

     76:   /* prepare linear solver */
     77:   PetscCall(NEPDeflationSolveSetUp(extop,sigma));

     79:   PetscCall(BVGetColumn(Vext,0,&f));
     80:   PetscCall(VecDuplicate(f,&r));
     81:   PetscCall(VecDuplicate(f,&u));
     82:   PetscCall(BVGetColumn(nep->V,0,&uu));
     83:   PetscCall(NEPDeflationCopyToExtendedVec(extop,uu,NULL,f,PETSC_FALSE));
     84:   PetscCall(BVRestoreColumn(nep->V,0,&uu));
     85:   PetscCall(VecCopy(f,r));
     86:   PetscCall(NEPDeflationFunctionSolve(extop,r,f));
     87:   PetscCall(VecNorm(f,NORM_2,&nrm));
     88:   PetscCall(VecScale(f,1.0/nrm));
     89:   PetscCall(BVRestoreColumn(Vext,0,&f));

     91:   PetscCall(DSCreate(PetscObjectComm((PetscObject)nep),&ds));
     92:   PetscCall(DSSetType(ds,DSNEP));
     93:   PetscCall(DSNEPSetFN(ds,nep->nt,nep->f));
     94:   PetscCall(DSAllocate(ds,nep->ncv));
     95:   PetscCall(DSGetSlepcSC(ds,&sc));
     96:   sc->comparison    = nep->sc->comparison;
     97:   sc->comparisonctx = nep->sc->comparisonctx;
     98:   PetscCall(DSSetFromOptions(ds));

    100:   /* build projected matrices for initial space */
    101:   PetscCall(DSSetDimensions(ds,n,0,0));
    102:   PetscCall(NEPDeflationProjectOperator(extop,Vext,ds,0,n));

    104:   PetscCall(PetscMalloc1(nep->ncv,&eigr));

    106:   /* Restart loop */
    107:   while (nep->reason == NEP_CONVERGED_ITERATING) {
    108:     nep->its++;

    110:     /* solve projected problem */
    111:     PetscCall(DSSetDimensions(ds,n,0,0));
    112:     PetscCall(DSSetState(ds,DS_STATE_RAW));
    113:     PetscCall(DSSolve(ds,eigr,NULL));
    114:     PetscCall(DSSynchronize(ds,eigr,NULL));
    115:     if (nep->its>1) lambda2 = lambda;
    116:     lambda = eigr[0];
    117:     nep->eigr[nep->nconv] = lambda;

    119:     /* compute Ritz vector, x = V*s */
    120:     PetscCall(DSGetArray(ds,DS_MAT_X,&X));
    121:     PetscCall(BVSetActiveColumns(Vext,0,n));
    122:     PetscCall(BVMultVec(Vext,1.0,0.0,u,X));
    123:     PetscCall(DSRestoreArray(ds,DS_MAT_X,&X));

    125:     /* compute the residual, r = T(lambda)*x */
    126:     PetscCall(NEPDeflationComputeFunction(extop,lambda,&T));
    127:     PetscCall(MatMult(T,u,r));

    129:     /* convergence test */
    130:     PetscCall(VecNorm(r,NORM_2,&resnorm));
    131:     if (nep->its>1) perr=nep->errest[nep->nconv];
    132:     PetscCall((*nep->converged)(nep,lambda,0,resnorm,&nep->errest[nep->nconv],nep->convergedctx));
    133:     if (nep->errest[nep->nconv]<=nep->tol) {
    134:       nep->nconv = nep->nconv + 1;
    135:       PetscCall(NEPDeflationLocking(extop,u,lambda));
    136:       skip = PETSC_TRUE;
    137:     }
    138:     PetscCall((*nep->stopping)(nep,nep->its,nep->max_it,nep->nconv,nep->nev,&nep->reason,nep->stoppingctx));
    139:     if (!skip || nep->reason>0) PetscCall(NEPMonitor(nep,nep->its,nep->nconv,nep->eigr,nep->eigi,nep->errest,(nep->reason>0)?nep->nconv:nep->nconv+1));

    141:     if (nep->reason == NEP_CONVERGED_ITERATING) {
    142:       if (!skip) {
    143:         if (n>=nep->ncv) {
    144:           nep->reason = NEP_DIVERGED_SUBSPACE_EXHAUSTED;
    145:           break;
    146:         }
    147:         if (ctx->lag && !(nep->its%ctx->lag) && nep->its>=2*ctx->lag && perr && nep->errest[nep->nconv]>.5*perr) PetscCall(NEPDeflationSolveSetUp(extop,lambda2));

    149:         /* continuation vector: f = T(sigma)\r */
    150:         PetscCall(BVGetColumn(Vext,n,&f));
    151:         PetscCall(NEPDeflationFunctionSolve(extop,r,f));
    152:         PetscCall(BVRestoreColumn(Vext,n,&f));
    153:         PetscCall(KSPGetConvergedReason(ctx->ksp,&kspreason));
    154:         if (kspreason<0) {
    155:           PetscCall(PetscInfo(nep,"iter=%" PetscInt_FMT ", linear solve failed, stopping solve\n",nep->its));
    156:           nep->reason = NEP_DIVERGED_LINEAR_SOLVE;
    157:           break;
    158:         }

    160:         /* orthonormalize */
    161:         PetscCall(BVOrthonormalizeColumn(Vext,n,PETSC_FALSE,&beta,&breakdown));
    162:         if (breakdown || beta==0.0) {
    163:           PetscCall(PetscInfo(nep,"iter=%" PetscInt_FMT ", orthogonalization failed, stopping solve\n",nep->its));
    164:           nep->reason = NEP_DIVERGED_BREAKDOWN;
    165:           break;
    166:         }

    168:         /* update projected matrices */
    169:         PetscCall(DSSetDimensions(ds,n+1,0,0));
    170:         PetscCall(NEPDeflationProjectOperator(extop,Vext,ds,n,n+1));
    171:         n++;
    172:       } else {
    173:         nep->its--;  /* do not count this as a full iteration */
    174:         PetscCall(BVGetColumn(Vext,0,&f));
    175:         PetscCall(NEPDeflationSetRandomVec(extop,f));
    176:         PetscCall(NEPDeflationSolveSetUp(extop,sigma));
    177:         PetscCall(VecCopy(f,r));
    178:         PetscCall(NEPDeflationFunctionSolve(extop,r,f));
    179:         PetscCall(VecNorm(f,NORM_2,&nrm));
    180:         PetscCall(VecScale(f,1.0/nrm));
    181:         PetscCall(BVRestoreColumn(Vext,0,&f));
    182:         n = 1;
    183:         PetscCall(DSSetDimensions(ds,n,0,0));
    184:         PetscCall(NEPDeflationProjectOperator(extop,Vext,ds,n-1,n));
    185:         skip = PETSC_FALSE;
    186:       }
    187:     }
    188:   }

    190:   PetscCall(NEPDeflationGetInvariantPair(extop,NULL,&H));
    191:   PetscCall(DSSetType(nep->ds,DSNHEP));
    192:   PetscCall(DSAllocate(nep->ds,PetscMax(nep->nconv,1)));
    193:   PetscCall(DSSetDimensions(nep->ds,nep->nconv,0,nep->nconv));
    194:   PetscCall(DSGetMat(nep->ds,DS_MAT_A,&A));
    195:   PetscCall(MatCopy(H,A,SAME_NONZERO_PATTERN));
    196:   PetscCall(DSRestoreMat(nep->ds,DS_MAT_A,&A));
    197:   PetscCall(MatDestroy(&H));
    198:   PetscCall(DSSolve(nep->ds,nep->eigr,nep->eigi));
    199:   PetscCall(NEPDeflationReset(extop));
    200:   PetscCall(VecDestroy(&u));
    201:   PetscCall(VecDestroy(&r));
    202:   PetscCall(BVDestroy(&Vext));
    203:   PetscCall(DSDestroy(&ds));
    204:   PetscCall(PetscFree(eigr));
    205:   PetscFunctionReturn(PETSC_SUCCESS);
    206: }

    208: static PetscErrorCode NEPNArnoldiSetLagPreconditioner_NArnoldi(NEP nep,PetscInt lag)
    209: {
    210:   NEP_NARNOLDI *ctx = (NEP_NARNOLDI*)nep->data;

    212:   PetscFunctionBegin;
    213:   PetscCheck(lag>=0,PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Lag must be non-negative");
    214:   ctx->lag = lag;
    215:   PetscFunctionReturn(PETSC_SUCCESS);
    216: }

    218: /*@
    219:    NEPNArnoldiSetLagPreconditioner - Determines when the preconditioner is rebuilt in the
    220:    nonlinear solve.

    222:    Logically Collective

    224:    Input Parameters:
    225: +  nep - nonlinear eigenvalue solver
    226: -  lag - 0 indicates NEVER rebuild, 1 means rebuild every time the Jacobian is
    227:           computed within the nonlinear iteration, 2 means every second time
    228:           the Jacobian is built, etc.

    230:    Options Database Keys:
    231: .  -nep_narnoldi_lag_preconditioner <lag> - the lag value

    233:    Notes:
    234:    The default is 1.
    235:    The preconditioner is ALWAYS built in the first iteration of a nonlinear solve.

    237:    Level: intermediate

    239: .seealso: NEPNArnoldiGetLagPreconditioner()
    240: @*/
    241: PetscErrorCode NEPNArnoldiSetLagPreconditioner(NEP nep,PetscInt lag)
    242: {
    243:   PetscFunctionBegin;
    246:   PetscTryMethod(nep,"NEPNArnoldiSetLagPreconditioner_C",(NEP,PetscInt),(nep,lag));
    247:   PetscFunctionReturn(PETSC_SUCCESS);
    248: }

    250: static PetscErrorCode NEPNArnoldiGetLagPreconditioner_NArnoldi(NEP nep,PetscInt *lag)
    251: {
    252:   NEP_NARNOLDI *ctx = (NEP_NARNOLDI*)nep->data;

    254:   PetscFunctionBegin;
    255:   *lag = ctx->lag;
    256:   PetscFunctionReturn(PETSC_SUCCESS);
    257: }

    259: /*@
    260:    NEPNArnoldiGetLagPreconditioner - Indicates how often the preconditioner is rebuilt.

    262:    Not Collective

    264:    Input Parameter:
    265: .  nep - nonlinear eigenvalue solver

    267:    Output Parameter:
    268: .  lag - the lag parameter

    270:    Level: intermediate

    272: .seealso: NEPNArnoldiSetLagPreconditioner()
    273: @*/
    274: PetscErrorCode NEPNArnoldiGetLagPreconditioner(NEP nep,PetscInt *lag)
    275: {
    276:   PetscFunctionBegin;
    278:   PetscAssertPointer(lag,2);
    279:   PetscUseMethod(nep,"NEPNArnoldiGetLagPreconditioner_C",(NEP,PetscInt*),(nep,lag));
    280:   PetscFunctionReturn(PETSC_SUCCESS);
    281: }

    283: static PetscErrorCode NEPSetFromOptions_NArnoldi(NEP nep,PetscOptionItems *PetscOptionsObject)
    284: {
    285:   PetscInt       i;
    286:   PetscBool      flg;
    287:   NEP_NARNOLDI   *ctx = (NEP_NARNOLDI*)nep->data;

    289:   PetscFunctionBegin;
    290:   PetscOptionsHeadBegin(PetscOptionsObject,"NEP N-Arnoldi Options");
    291:     i = 0;
    292:     PetscCall(PetscOptionsInt("-nep_narnoldi_lag_preconditioner","Interval to rebuild preconditioner","NEPNArnoldiSetLagPreconditioner",ctx->lag,&i,&flg));
    293:     if (flg) PetscCall(NEPNArnoldiSetLagPreconditioner(nep,i));

    295:   PetscOptionsHeadEnd();

    297:   if (!ctx->ksp) PetscCall(NEPNArnoldiGetKSP(nep,&ctx->ksp));
    298:   PetscCall(KSPSetFromOptions(ctx->ksp));
    299:   PetscFunctionReturn(PETSC_SUCCESS);
    300: }

    302: static PetscErrorCode NEPNArnoldiSetKSP_NArnoldi(NEP nep,KSP ksp)
    303: {
    304:   NEP_NARNOLDI   *ctx = (NEP_NARNOLDI*)nep->data;

    306:   PetscFunctionBegin;
    307:   PetscCall(PetscObjectReference((PetscObject)ksp));
    308:   PetscCall(KSPDestroy(&ctx->ksp));
    309:   ctx->ksp = ksp;
    310:   nep->state = NEP_STATE_INITIAL;
    311:   PetscFunctionReturn(PETSC_SUCCESS);
    312: }

    314: /*@
    315:    NEPNArnoldiSetKSP - Associate a linear solver object (KSP) to the nonlinear
    316:    eigenvalue solver.

    318:    Collective

    320:    Input Parameters:
    321: +  nep - eigenvalue solver
    322: -  ksp - the linear solver object

    324:    Level: advanced

    326: .seealso: NEPNArnoldiGetKSP()
    327: @*/
    328: PetscErrorCode NEPNArnoldiSetKSP(NEP nep,KSP ksp)
    329: {
    330:   PetscFunctionBegin;
    333:   PetscCheckSameComm(nep,1,ksp,2);
    334:   PetscTryMethod(nep,"NEPNArnoldiSetKSP_C",(NEP,KSP),(nep,ksp));
    335:   PetscFunctionReturn(PETSC_SUCCESS);
    336: }

    338: static PetscErrorCode NEPNArnoldiGetKSP_NArnoldi(NEP nep,KSP *ksp)
    339: {
    340:   NEP_NARNOLDI   *ctx = (NEP_NARNOLDI*)nep->data;

    342:   PetscFunctionBegin;
    343:   if (!ctx->ksp) {
    344:     PetscCall(KSPCreate(PetscObjectComm((PetscObject)nep),&ctx->ksp));
    345:     PetscCall(PetscObjectIncrementTabLevel((PetscObject)ctx->ksp,(PetscObject)nep,1));
    346:     PetscCall(KSPSetOptionsPrefix(ctx->ksp,((PetscObject)nep)->prefix));
    347:     PetscCall(KSPAppendOptionsPrefix(ctx->ksp,"nep_narnoldi_"));
    348:     PetscCall(PetscObjectSetOptions((PetscObject)ctx->ksp,((PetscObject)nep)->options));
    349:     PetscCall(KSPSetErrorIfNotConverged(ctx->ksp,PETSC_TRUE));
    350:     PetscCall(KSPSetTolerances(ctx->ksp,SlepcDefaultTol(nep->tol),PETSC_CURRENT,PETSC_CURRENT,PETSC_CURRENT));
    351:   }
    352:   *ksp = ctx->ksp;
    353:   PetscFunctionReturn(PETSC_SUCCESS);
    354: }

    356: /*@
    357:    NEPNArnoldiGetKSP - Retrieve the linear solver object (KSP) associated with
    358:    the nonlinear eigenvalue solver.

    360:    Collective

    362:    Input Parameter:
    363: .  nep - nonlinear eigenvalue solver

    365:    Output Parameter:
    366: .  ksp - the linear solver object

    368:    Level: advanced

    370: .seealso: NEPNArnoldiSetKSP()
    371: @*/
    372: PetscErrorCode NEPNArnoldiGetKSP(NEP nep,KSP *ksp)
    373: {
    374:   PetscFunctionBegin;
    376:   PetscAssertPointer(ksp,2);
    377:   PetscUseMethod(nep,"NEPNArnoldiGetKSP_C",(NEP,KSP*),(nep,ksp));
    378:   PetscFunctionReturn(PETSC_SUCCESS);
    379: }

    381: static PetscErrorCode NEPView_NArnoldi(NEP nep,PetscViewer viewer)
    382: {
    383:   NEP_NARNOLDI   *ctx = (NEP_NARNOLDI*)nep->data;
    384:   PetscBool      isascii;

    386:   PetscFunctionBegin;
    387:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii));
    388:   if (isascii) {
    389:     if (ctx->lag) PetscCall(PetscViewerASCIIPrintf(viewer,"  updating the preconditioner every %" PetscInt_FMT " iterations\n",ctx->lag));
    390:     if (!ctx->ksp) PetscCall(NEPNArnoldiGetKSP(nep,&ctx->ksp));
    391:     PetscCall(PetscViewerASCIIPushTab(viewer));
    392:     PetscCall(KSPView(ctx->ksp,viewer));
    393:     PetscCall(PetscViewerASCIIPopTab(viewer));
    394:   }
    395:   PetscFunctionReturn(PETSC_SUCCESS);
    396: }

    398: static PetscErrorCode NEPReset_NArnoldi(NEP nep)
    399: {
    400:   NEP_NARNOLDI   *ctx = (NEP_NARNOLDI*)nep->data;

    402:   PetscFunctionBegin;
    403:   PetscCall(KSPReset(ctx->ksp));
    404:   PetscFunctionReturn(PETSC_SUCCESS);
    405: }

    407: static PetscErrorCode NEPDestroy_NArnoldi(NEP nep)
    408: {
    409:   NEP_NARNOLDI   *ctx = (NEP_NARNOLDI*)nep->data;

    411:   PetscFunctionBegin;
    412:   PetscCall(KSPDestroy(&ctx->ksp));
    413:   PetscCall(PetscFree(nep->data));
    414:   PetscCall(PetscObjectComposeFunction((PetscObject)nep,"NEPNArnoldiSetLagPreconditioner_C",NULL));
    415:   PetscCall(PetscObjectComposeFunction((PetscObject)nep,"NEPNArnoldiGetLagPreconditioner_C",NULL));
    416:   PetscCall(PetscObjectComposeFunction((PetscObject)nep,"NEPNArnoldiSetKSP_C",NULL));
    417:   PetscCall(PetscObjectComposeFunction((PetscObject)nep,"NEPNArnoldiGetKSP_C",NULL));
    418:   PetscFunctionReturn(PETSC_SUCCESS);
    419: }

    421: SLEPC_EXTERN PetscErrorCode NEPCreate_NArnoldi(NEP nep)
    422: {
    423:   NEP_NARNOLDI   *ctx;

    425:   PetscFunctionBegin;
    426:   PetscCall(PetscNew(&ctx));
    427:   nep->data = (void*)ctx;
    428:   ctx->lag  = 1;

    430:   nep->useds = PETSC_TRUE;

    432:   nep->ops->solve          = NEPSolve_NArnoldi;
    433:   nep->ops->setup          = NEPSetUp_NArnoldi;
    434:   nep->ops->setfromoptions = NEPSetFromOptions_NArnoldi;
    435:   nep->ops->reset          = NEPReset_NArnoldi;
    436:   nep->ops->destroy        = NEPDestroy_NArnoldi;
    437:   nep->ops->view           = NEPView_NArnoldi;
    438:   nep->ops->computevectors = NEPComputeVectors_Schur;

    440:   PetscCall(PetscObjectComposeFunction((PetscObject)nep,"NEPNArnoldiSetLagPreconditioner_C",NEPNArnoldiSetLagPreconditioner_NArnoldi));
    441:   PetscCall(PetscObjectComposeFunction((PetscObject)nep,"NEPNArnoldiGetLagPreconditioner_C",NEPNArnoldiGetLagPreconditioner_NArnoldi));
    442:   PetscCall(PetscObjectComposeFunction((PetscObject)nep,"NEPNArnoldiSetKSP_C",NEPNArnoldiSetKSP_NArnoldi));
    443:   PetscCall(PetscObjectComposeFunction((PetscObject)nep,"NEPNArnoldiGetKSP_C",NEPNArnoldiGetKSP_NArnoldi));
    444:   PetscFunctionReturn(PETSC_SUCCESS);
    445: }