| Line | Branch | Exec | Source |
|---|---|---|---|
| 1 | /* | ||
| 2 | - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - | ||
| 3 | SLEPc - Scalable Library for Eigenvalue Problem Computations | ||
| 4 | Copyright (c) 2002-, Universitat Politecnica de Valencia, Spain | ||
| 5 | |||
| 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" | ||
| 12 | |||
| 13 | Method: Nonlinear Arnoldi | ||
| 14 | |||
| 15 | Algorithm: | ||
| 16 | |||
| 17 | Arnoldi for nonlinear eigenproblems. | ||
| 18 | |||
| 19 | References: | ||
| 20 | |||
| 21 | [1] H. Voss, "An Arnoldi method for nonlinear eigenvalue problems", | ||
| 22 | BIT 44:387-401, 2004. | ||
| 23 | */ | ||
| 24 | |||
| 25 | #include <slepc/private/nepimpl.h> /*I "slepcnep.h" I*/ | ||
| 26 | #include <../src/nep/impls/nepdefl.h> | ||
| 27 | |||
| 28 | typedef struct { | ||
| 29 | PetscInt lag; /* interval to rebuild preconditioner */ | ||
| 30 | KSP ksp; /* linear solver object */ | ||
| 31 | } NEP_NARNOLDI; | ||
| 32 | |||
| 33 | 144 | static PetscErrorCode NEPSetUp_NArnoldi(NEP nep) | |
| 34 | { | ||
| 35 |
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144 | PetscFunctionBegin; |
| 36 |
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144 | PetscCall(NEPSetDimensions_Default(nep,nep->nev,&nep->ncv,&nep->mpd)); |
| 37 |
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144 | 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 |
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144 | if (nep->max_it==PETSC_DETERMINE) nep->max_it = nep->nev*nep->ncv; |
| 39 |
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144 | if (!nep->which) nep->which = NEP_TARGET_MAGNITUDE; |
| 40 |
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144 | PetscCheck(nep->which==NEP_TARGET_MAGNITUDE,PetscObjectComm((PetscObject)nep),PETSC_ERR_SUP,"This solver supports only target magnitude eigenvalues"); |
| 41 |
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144 | NEPCheckUnsupported(nep,NEP_FEATURE_CALLBACK | NEP_FEATURE_REGION | NEP_FEATURE_TWOSIDED); |
| 42 |
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144 | PetscCall(NEPAllocateSolution(nep,0)); |
| 43 |
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144 | PetscCall(NEPSetWorkVecs(nep,3)); |
| 44 |
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36 | PetscFunctionReturn(PETSC_SUCCESS); |
| 45 | } | ||
| 46 | |||
| 47 | 136 | static PetscErrorCode NEPSolve_NArnoldi(NEP nep) | |
| 48 | { | ||
| 49 | 136 | NEP_NARNOLDI *ctx = (NEP_NARNOLDI*)nep->data; | |
| 50 | 136 | Mat T,H,A; | |
| 51 | 136 | Vec f,r,u,uu; | |
| 52 | 136 | PetscScalar *X,lambda=0.0,lambda2=0.0,*eigr,sigma; | |
| 53 | 136 | PetscReal beta,resnorm=0.0,nrm,perr=0.0; | |
| 54 | 136 | PetscInt n; | |
| 55 | 136 | PetscBool breakdown,skip=PETSC_FALSE; | |
| 56 | 136 | BV Vext; | |
| 57 | 136 | DS ds; | |
| 58 | 136 | NEP_EXT_OP extop=NULL; | |
| 59 | 136 | SlepcSC sc; | |
| 60 | 136 | KSPConvergedReason kspreason; | |
| 61 | |||
| 62 |
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136 | PetscFunctionBegin; |
| 63 | /* get initial space and shift */ | ||
| 64 |
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136 | PetscCall(NEPGetDefaultShift(nep,&sigma)); |
| 65 |
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136 | if (!nep->nini) { |
| 66 |
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128 | PetscCall(BVSetRandomColumn(nep->V,0)); |
| 67 |
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128 | PetscCall(BVNormColumn(nep->V,0,NORM_2,&nrm)); |
| 68 |
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128 | PetscCall(BVScaleColumn(nep->V,0,1.0/nrm)); |
| 69 | n = 1; | ||
| 70 | } else n = nep->nini; | ||
| 71 | |||
| 72 |
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136 | if (!ctx->ksp) PetscCall(NEPNArnoldiGetKSP(nep,&ctx->ksp)); |
| 73 |
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136 | PetscCall(NEPDeflationInitialize(nep,nep->V,ctx->ksp,PETSC_FALSE,nep->nev,&extop)); |
| 74 |
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136 | PetscCall(NEPDeflationCreateBV(extop,nep->ncv,&Vext)); |
| 75 | |||
| 76 | /* prepare linear solver */ | ||
| 77 |
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136 | PetscCall(NEPDeflationSolveSetUp(extop,sigma)); |
| 78 | |||
| 79 |
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136 | PetscCall(BVGetColumn(Vext,0,&f)); |
| 80 |
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136 | PetscCall(VecDuplicate(f,&r)); |
| 81 |
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136 | PetscCall(VecDuplicate(f,&u)); |
| 82 |
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136 | PetscCall(BVGetColumn(nep->V,0,&uu)); |
| 83 |
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136 | PetscCall(NEPDeflationCopyToExtendedVec(extop,uu,NULL,f,PETSC_FALSE)); |
| 84 |
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136 | PetscCall(BVRestoreColumn(nep->V,0,&uu)); |
| 85 |
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136 | PetscCall(VecCopy(f,r)); |
| 86 |
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136 | PetscCall(NEPDeflationFunctionSolve(extop,r,f)); |
| 87 |
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136 | PetscCall(VecNorm(f,NORM_2,&nrm)); |
| 88 |
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136 | PetscCall(VecScale(f,1.0/nrm)); |
| 89 |
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136 | PetscCall(BVRestoreColumn(Vext,0,&f)); |
| 90 | |||
| 91 |
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136 | PetscCall(DSCreate(PetscObjectComm((PetscObject)nep),&ds)); |
| 92 |
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136 | PetscCall(DSSetType(ds,DSNEP)); |
| 93 |
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136 | PetscCall(DSNEPSetFN(ds,nep->nt,nep->f)); |
| 94 |
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136 | PetscCall(DSAllocate(ds,nep->ncv)); |
| 95 |
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136 | PetscCall(DSGetSlepcSC(ds,&sc)); |
| 96 | 136 | sc->comparison = nep->sc->comparison; | |
| 97 | 136 | sc->comparisonctx = nep->sc->comparisonctx; | |
| 98 |
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136 | PetscCall(DSSetFromOptions(ds)); |
| 99 | |||
| 100 | /* build projected matrices for initial space */ | ||
| 101 |
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136 | PetscCall(DSSetDimensions(ds,n,0,0)); |
| 102 |
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136 | PetscCall(NEPDeflationProjectOperator(extop,Vext,ds,0,n)); |
| 103 | |||
| 104 |
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136 | PetscCall(PetscMalloc1(nep->ncv,&eigr)); |
| 105 | |||
| 106 | /* Restart loop */ | ||
| 107 |
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1508 | while (nep->reason == NEP_CONVERGED_ITERATING) { |
| 108 | 1372 | nep->its++; | |
| 109 | |||
| 110 | /* solve projected problem */ | ||
| 111 |
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1372 | PetscCall(DSSetDimensions(ds,n,0,0)); |
| 112 |
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1372 | PetscCall(DSSetState(ds,DS_STATE_RAW)); |
| 113 |
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1372 | PetscCall(DSSolve(ds,eigr,NULL)); |
| 114 |
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1372 | PetscCall(DSSynchronize(ds,eigr,NULL)); |
| 115 |
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1372 | if (nep->its>1) lambda2 = lambda; |
| 116 | 1372 | lambda = eigr[0]; | |
| 117 | 1372 | nep->eigr[nep->nconv] = lambda; | |
| 118 | |||
| 119 | /* compute Ritz vector, x = V*s */ | ||
| 120 |
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1372 | PetscCall(DSGetArray(ds,DS_MAT_X,&X)); |
| 121 |
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1372 | PetscCall(BVSetActiveColumns(Vext,0,n)); |
| 122 |
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1372 | PetscCall(BVMultVec(Vext,1.0,0.0,u,X)); |
| 123 |
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1372 | PetscCall(DSRestoreArray(ds,DS_MAT_X,&X)); |
| 124 | |||
| 125 | /* compute the residual, r = T(lambda)*x */ | ||
| 126 |
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1372 | PetscCall(NEPDeflationComputeFunction(extop,lambda,&T)); |
| 127 |
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1372 | PetscCall(MatMult(T,u,r)); |
| 128 | |||
| 129 | /* convergence test */ | ||
| 130 |
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1372 | PetscCall(VecNorm(r,NORM_2,&resnorm)); |
| 131 |
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1372 | if (nep->its>1) perr=nep->errest[nep->nconv]; |
| 132 |
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1372 | PetscCall((*nep->converged)(nep,lambda,0,resnorm,&nep->errest[nep->nconv],nep->convergedctx)); |
| 133 |
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1372 | if (nep->errest[nep->nconv]<=nep->tol) { |
| 134 | 184 | nep->nconv = nep->nconv + 1; | |
| 135 |
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184 | PetscCall(NEPDeflationLocking(extop,u,lambda)); |
| 136 | skip = PETSC_TRUE; | ||
| 137 | } | ||
| 138 |
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1372 | PetscCall((*nep->stopping)(nep,nep->its,nep->max_it,nep->nconv,nep->nev,&nep->reason,nep->stoppingctx)); |
| 139 |
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1372 | 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)); |
| 140 | |||
| 141 |
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1372 | if (nep->reason == NEP_CONVERGED_ITERATING) { |
| 142 |
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1236 | if (!skip) { |
| 143 |
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1188 | if (n>=nep->ncv) { |
| 144 | ✗ | nep->reason = NEP_DIVERGED_SUBSPACE_EXHAUSTED; | |
| 145 | ✗ | break; | |
| 146 | } | ||
| 147 |
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1188 | if (ctx->lag && !(nep->its%ctx->lag) && nep->its>=2*ctx->lag && perr && nep->errest[nep->nconv]>.5*perr) PetscCall(NEPDeflationSolveSetUp(extop,lambda2)); |
| 148 | |||
| 149 | /* continuation vector: f = T(sigma)\r */ | ||
| 150 |
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1188 | PetscCall(BVGetColumn(Vext,n,&f)); |
| 151 |
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1188 | PetscCall(NEPDeflationFunctionSolve(extop,r,f)); |
| 152 |
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1188 | PetscCall(BVRestoreColumn(Vext,n,&f)); |
| 153 |
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1188 | PetscCall(KSPGetConvergedReason(ctx->ksp,&kspreason)); |
| 154 |
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1188 | 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 | } | ||
| 159 | |||
| 160 | /* orthonormalize */ | ||
| 161 |
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1188 | PetscCall(BVOrthonormalizeColumn(Vext,n,PETSC_FALSE,&beta,&breakdown)); |
| 162 |
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1188 | 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 | } | ||
| 167 | |||
| 168 | /* update projected matrices */ | ||
| 169 |
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1188 | PetscCall(DSSetDimensions(ds,n+1,0,0)); |
| 170 |
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1188 | PetscCall(NEPDeflationProjectOperator(extop,Vext,ds,n,n+1)); |
| 171 | n++; | ||
| 172 | } else { | ||
| 173 | 48 | nep->its--; /* do not count this as a full iteration */ | |
| 174 |
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48 | PetscCall(BVGetColumn(Vext,0,&f)); |
| 175 |
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48 | PetscCall(NEPDeflationSetRandomVec(extop,f)); |
| 176 |
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48 | PetscCall(NEPDeflationSolveSetUp(extop,sigma)); |
| 177 |
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48 | PetscCall(VecCopy(f,r)); |
| 178 |
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48 | PetscCall(NEPDeflationFunctionSolve(extop,r,f)); |
| 179 |
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48 | PetscCall(VecNorm(f,NORM_2,&nrm)); |
| 180 |
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48 | PetscCall(VecScale(f,1.0/nrm)); |
| 181 |
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48 | PetscCall(BVRestoreColumn(Vext,0,&f)); |
| 182 | 48 | n = 1; | |
| 183 |
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48 | PetscCall(DSSetDimensions(ds,n,0,0)); |
| 184 |
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48 | PetscCall(NEPDeflationProjectOperator(extop,Vext,ds,n-1,n)); |
| 185 | skip = PETSC_FALSE; | ||
| 186 | } | ||
| 187 | } | ||
| 188 | } | ||
| 189 | |||
| 190 |
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136 | PetscCall(NEPDeflationGetInvariantPair(extop,NULL,&H)); |
| 191 |
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136 | PetscCall(DSSetType(nep->ds,DSNHEP)); |
| 192 |
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136 | PetscCall(DSAllocate(nep->ds,PetscMax(nep->nconv,1))); |
| 193 |
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136 | PetscCall(DSSetDimensions(nep->ds,nep->nconv,0,nep->nconv)); |
| 194 |
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136 | PetscCall(DSGetMat(nep->ds,DS_MAT_A,&A)); |
| 195 |
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136 | PetscCall(MatCopy(H,A,SAME_NONZERO_PATTERN)); |
| 196 |
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136 | PetscCall(DSRestoreMat(nep->ds,DS_MAT_A,&A)); |
| 197 |
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136 | PetscCall(MatDestroy(&H)); |
| 198 |
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136 | PetscCall(DSSolve(nep->ds,nep->eigr,nep->eigi)); |
| 199 |
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136 | PetscCall(NEPDeflationReset(extop)); |
| 200 |
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136 | PetscCall(VecDestroy(&u)); |
| 201 |
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136 | PetscCall(VecDestroy(&r)); |
| 202 |
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136 | PetscCall(BVDestroy(&Vext)); |
| 203 |
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136 | PetscCall(DSDestroy(&ds)); |
| 204 |
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136 | PetscCall(PetscFree(eigr)); |
| 205 |
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34 | PetscFunctionReturn(PETSC_SUCCESS); |
| 206 | } | ||
| 207 | |||
| 208 | 16 | static PetscErrorCode NEPNArnoldiSetLagPreconditioner_NArnoldi(NEP nep,PetscInt lag) | |
| 209 | { | ||
| 210 | 16 | NEP_NARNOLDI *ctx = (NEP_NARNOLDI*)nep->data; | |
| 211 | |||
| 212 |
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16 | PetscFunctionBegin; |
| 213 |
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16 | PetscCheck(lag>=0,PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Lag must be non-negative"); |
| 214 | 16 | ctx->lag = lag; | |
| 215 |
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16 | PetscFunctionReturn(PETSC_SUCCESS); |
| 216 | } | ||
| 217 | |||
| 218 | /*@ | ||
| 219 | NEPNArnoldiSetLagPreconditioner - Determines when the preconditioner is rebuilt in the | ||
| 220 | nonlinear solve. | ||
| 221 | |||
| 222 | Logically Collective | ||
| 223 | |||
| 224 | Input Parameters: | ||
| 225 | + nep - the nonlinear eigensolver context | ||
| 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. | ||
| 229 | |||
| 230 | Options Database Key: | ||
| 231 | . -nep_narnoldi_lag_preconditioner \<lag\> - sets the lag value | ||
| 232 | |||
| 233 | Notes: | ||
| 234 | The default is 1. | ||
| 235 | The preconditioner is ALWAYS built in the first iteration of a nonlinear solve. | ||
| 236 | |||
| 237 | Level: intermediate | ||
| 238 | |||
| 239 | .seealso: [](ch:nep), `NEPNARNOLDI`, `NEPNArnoldiGetLagPreconditioner()` | ||
| 240 | @*/ | ||
| 241 | 16 | PetscErrorCode NEPNArnoldiSetLagPreconditioner(NEP nep,PetscInt lag) | |
| 242 | { | ||
| 243 |
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16 | PetscFunctionBegin; |
| 244 |
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16 | PetscValidHeaderSpecific(nep,NEP_CLASSID,1); |
| 245 |
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16 | PetscValidLogicalCollectiveInt(nep,lag,2); |
| 246 |
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16 | PetscTryMethod(nep,"NEPNArnoldiSetLagPreconditioner_C",(NEP,PetscInt),(nep,lag)); |
| 247 |
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16 | PetscFunctionReturn(PETSC_SUCCESS); |
| 248 | } | ||
| 249 | |||
| 250 | 8 | static PetscErrorCode NEPNArnoldiGetLagPreconditioner_NArnoldi(NEP nep,PetscInt *lag) | |
| 251 | { | ||
| 252 | 8 | NEP_NARNOLDI *ctx = (NEP_NARNOLDI*)nep->data; | |
| 253 | |||
| 254 |
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8 | PetscFunctionBegin; |
| 255 | 8 | *lag = ctx->lag; | |
| 256 |
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8 | PetscFunctionReturn(PETSC_SUCCESS); |
| 257 | } | ||
| 258 | |||
| 259 | /*@ | ||
| 260 | NEPNArnoldiGetLagPreconditioner - Indicates how often the preconditioner is rebuilt. | ||
| 261 | |||
| 262 | Not Collective | ||
| 263 | |||
| 264 | Input Parameter: | ||
| 265 | . nep - the nonlinear eigensolver context | ||
| 266 | |||
| 267 | Output Parameter: | ||
| 268 | . lag - the lag parameter | ||
| 269 | |||
| 270 | Level: intermediate | ||
| 271 | |||
| 272 | .seealso: [](ch:nep), `NEPNARNOLDI`, `NEPNArnoldiSetLagPreconditioner()` | ||
| 273 | @*/ | ||
| 274 | 8 | PetscErrorCode NEPNArnoldiGetLagPreconditioner(NEP nep,PetscInt *lag) | |
| 275 | { | ||
| 276 |
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8 | PetscFunctionBegin; |
| 277 |
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8 | PetscValidHeaderSpecific(nep,NEP_CLASSID,1); |
| 278 |
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8 | PetscAssertPointer(lag,2); |
| 279 |
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8 | PetscUseMethod(nep,"NEPNArnoldiGetLagPreconditioner_C",(NEP,PetscInt*),(nep,lag)); |
| 280 |
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8 | PetscFunctionReturn(PETSC_SUCCESS); |
| 281 | } | ||
| 282 | |||
| 283 | 96 | static PetscErrorCode NEPSetFromOptions_NArnoldi(NEP nep,PetscOptionItems PetscOptionsObject) | |
| 284 | { | ||
| 285 | 96 | PetscInt i; | |
| 286 | 96 | PetscBool flg; | |
| 287 | 96 | NEP_NARNOLDI *ctx = (NEP_NARNOLDI*)nep->data; | |
| 288 | |||
| 289 |
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96 | PetscFunctionBegin; |
| 290 |
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96 | PetscOptionsHeadBegin(PetscOptionsObject,"NEP N-Arnoldi Options"); |
| 291 | 96 | i = 0; | |
| 292 |
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96 | PetscCall(PetscOptionsInt("-nep_narnoldi_lag_preconditioner","Interval to rebuild preconditioner","NEPNArnoldiSetLagPreconditioner",ctx->lag,&i,&flg)); |
| 293 |
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96 | if (flg) PetscCall(NEPNArnoldiSetLagPreconditioner(nep,i)); |
| 294 | |||
| 295 |
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96 | PetscOptionsHeadEnd(); |
| 296 | |||
| 297 |
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96 | if (!ctx->ksp) PetscCall(NEPNArnoldiGetKSP(nep,&ctx->ksp)); |
| 298 |
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96 | PetscCall(KSPSetFromOptions(ctx->ksp)); |
| 299 |
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24 | PetscFunctionReturn(PETSC_SUCCESS); |
| 300 | } | ||
| 301 | |||
| 302 | 8 | static PetscErrorCode NEPNArnoldiSetKSP_NArnoldi(NEP nep,KSP ksp) | |
| 303 | { | ||
| 304 | 8 | NEP_NARNOLDI *ctx = (NEP_NARNOLDI*)nep->data; | |
| 305 | |||
| 306 |
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8 | PetscFunctionBegin; |
| 307 |
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8 | PetscCall(PetscObjectReference((PetscObject)ksp)); |
| 308 |
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8 | PetscCall(KSPDestroy(&ctx->ksp)); |
| 309 | 8 | ctx->ksp = ksp; | |
| 310 | 8 | nep->state = NEP_STATE_INITIAL; | |
| 311 |
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8 | PetscFunctionReturn(PETSC_SUCCESS); |
| 312 | } | ||
| 313 | |||
| 314 | /*@ | ||
| 315 | NEPNArnoldiSetKSP - Associate a linear solver object (`KSP`) to the nonlinear | ||
| 316 | eigenvalue solver. | ||
| 317 | |||
| 318 | Collective | ||
| 319 | |||
| 320 | Input Parameters: | ||
| 321 | + nep - the nonlinear eigensolver context | ||
| 322 | - ksp - the linear solver object | ||
| 323 | |||
| 324 | Level: advanced | ||
| 325 | |||
| 326 | .seealso: [](ch:nep), `NEPNARNOLDI`, `NEPNArnoldiGetKSP()` | ||
| 327 | @*/ | ||
| 328 | 8 | PetscErrorCode NEPNArnoldiSetKSP(NEP nep,KSP ksp) | |
| 329 | { | ||
| 330 |
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8 | PetscFunctionBegin; |
| 331 |
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8 | PetscValidHeaderSpecific(nep,NEP_CLASSID,1); |
| 332 |
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8 | PetscValidHeaderSpecific(ksp,KSP_CLASSID,2); |
| 333 |
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8 | PetscCheckSameComm(nep,1,ksp,2); |
| 334 |
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8 | PetscTryMethod(nep,"NEPNArnoldiSetKSP_C",(NEP,KSP),(nep,ksp)); |
| 335 |
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8 | PetscFunctionReturn(PETSC_SUCCESS); |
| 336 | } | ||
| 337 | |||
| 338 | 88 | static PetscErrorCode NEPNArnoldiGetKSP_NArnoldi(NEP nep,KSP *ksp) | |
| 339 | { | ||
| 340 | 88 | NEP_NARNOLDI *ctx = (NEP_NARNOLDI*)nep->data; | |
| 341 | |||
| 342 |
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88 | PetscFunctionBegin; |
| 343 |
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88 | if (!ctx->ksp) { |
| 344 |
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88 | PetscCall(KSPCreate(PetscObjectComm((PetscObject)nep),&ctx->ksp)); |
| 345 |
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88 | PetscCall(PetscObjectIncrementTabLevel((PetscObject)ctx->ksp,(PetscObject)nep,1)); |
| 346 |
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88 | PetscCall(KSPSetOptionsPrefix(ctx->ksp,((PetscObject)nep)->prefix)); |
| 347 |
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88 | PetscCall(KSPAppendOptionsPrefix(ctx->ksp,"nep_narnoldi_")); |
| 348 |
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88 | PetscCall(PetscObjectSetOptions((PetscObject)ctx->ksp,((PetscObject)nep)->options)); |
| 349 |
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88 | PetscCall(KSPSetErrorIfNotConverged(ctx->ksp,PETSC_TRUE)); |
| 350 |
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96 | PetscCall(KSPSetTolerances(ctx->ksp,SlepcDefaultTol(nep->tol),PETSC_CURRENT,PETSC_CURRENT,PETSC_CURRENT)); |
| 351 | } | ||
| 352 | 88 | *ksp = ctx->ksp; | |
| 353 |
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88 | PetscFunctionReturn(PETSC_SUCCESS); |
| 354 | } | ||
| 355 | |||
| 356 | /*@ | ||
| 357 | NEPNArnoldiGetKSP - Retrieve the linear solver object (`KSP`) associated with | ||
| 358 | the nonlinear eigenvalue solver. | ||
| 359 | |||
| 360 | Collective | ||
| 361 | |||
| 362 | Input Parameter: | ||
| 363 | . nep - the nonlinear eigensolver context | ||
| 364 | |||
| 365 | Output Parameter: | ||
| 366 | . ksp - the linear solver object | ||
| 367 | |||
| 368 | Level: advanced | ||
| 369 | |||
| 370 | .seealso: [](ch:nep), `NEPNARNOLDI`, `NEPNArnoldiSetKSP()` | ||
| 371 | @*/ | ||
| 372 | 88 | PetscErrorCode NEPNArnoldiGetKSP(NEP nep,KSP *ksp) | |
| 373 | { | ||
| 374 |
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88 | PetscFunctionBegin; |
| 375 |
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88 | PetscValidHeaderSpecific(nep,NEP_CLASSID,1); |
| 376 |
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88 | PetscAssertPointer(ksp,2); |
| 377 |
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88 | PetscUseMethod(nep,"NEPNArnoldiGetKSP_C",(NEP,KSP*),(nep,ksp)); |
| 378 |
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88 | PetscFunctionReturn(PETSC_SUCCESS); |
| 379 | } | ||
| 380 | |||
| 381 | 8 | static PetscErrorCode NEPView_NArnoldi(NEP nep,PetscViewer viewer) | |
| 382 | { | ||
| 383 | 8 | NEP_NARNOLDI *ctx = (NEP_NARNOLDI*)nep->data; | |
| 384 | 8 | PetscBool isascii; | |
| 385 | |||
| 386 |
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8 | PetscFunctionBegin; |
| 387 |
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8 | PetscCall(PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii)); |
| 388 |
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8 | if (isascii) { |
| 389 |
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8 | if (ctx->lag) PetscCall(PetscViewerASCIIPrintf(viewer," updating the preconditioner every %" PetscInt_FMT " iterations\n",ctx->lag)); |
| 390 |
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8 | if (!ctx->ksp) PetscCall(NEPNArnoldiGetKSP(nep,&ctx->ksp)); |
| 391 |
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8 | PetscCall(PetscViewerASCIIPushTab(viewer)); |
| 392 |
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8 | PetscCall(KSPView(ctx->ksp,viewer)); |
| 393 |
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8 | PetscCall(PetscViewerASCIIPopTab(viewer)); |
| 394 | } | ||
| 395 |
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2 | PetscFunctionReturn(PETSC_SUCCESS); |
| 396 | } | ||
| 397 | |||
| 398 | 144 | static PetscErrorCode NEPReset_NArnoldi(NEP nep) | |
| 399 | { | ||
| 400 | 144 | NEP_NARNOLDI *ctx = (NEP_NARNOLDI*)nep->data; | |
| 401 | |||
| 402 |
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144 | PetscFunctionBegin; |
| 403 |
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144 | PetscCall(KSPReset(ctx->ksp)); |
| 404 |
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36 | PetscFunctionReturn(PETSC_SUCCESS); |
| 405 | } | ||
| 406 | |||
| 407 | 96 | static PetscErrorCode NEPDestroy_NArnoldi(NEP nep) | |
| 408 | { | ||
| 409 | 96 | NEP_NARNOLDI *ctx = (NEP_NARNOLDI*)nep->data; | |
| 410 | |||
| 411 |
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96 | PetscFunctionBegin; |
| 412 |
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96 | PetscCall(KSPDestroy(&ctx->ksp)); |
| 413 |
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96 | PetscCall(PetscFree(nep->data)); |
| 414 |
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96 | PetscCall(PetscObjectComposeFunction((PetscObject)nep,"NEPNArnoldiSetLagPreconditioner_C",NULL)); |
| 415 |
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96 | PetscCall(PetscObjectComposeFunction((PetscObject)nep,"NEPNArnoldiGetLagPreconditioner_C",NULL)); |
| 416 |
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96 | PetscCall(PetscObjectComposeFunction((PetscObject)nep,"NEPNArnoldiSetKSP_C",NULL)); |
| 417 |
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96 | PetscCall(PetscObjectComposeFunction((PetscObject)nep,"NEPNArnoldiGetKSP_C",NULL)); |
| 418 |
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24 | PetscFunctionReturn(PETSC_SUCCESS); |
| 419 | } | ||
| 420 | |||
| 421 | /*MC | ||
| 422 | NEPNARNOLDI - NEPNARNOLDI = "narnoldi" - Nonlinear Arnoldi method. | ||
| 423 | |||
| 424 | Notes: | ||
| 425 | This solver implements the N-Arnoldi method {cite:p}`Vos04`, a | ||
| 426 | projection method using an expanding subspace formed with the | ||
| 427 | RII iterate vectors. Hence there are similarities with `NEPRII`. | ||
| 428 | Call `NEPNArnoldiGetKSP()` to configure the linear solver, and | ||
| 429 | `NEPNArnoldiSetLagPreconditioner()` to reduce the cost of updating | ||
| 430 | the preconditioner. | ||
| 431 | |||
| 432 | The solver incorporates deflation, so that several eigenpairs con be | ||
| 433 | computed. Details of the implementation in SLEPc can be found in | ||
| 434 | {cite:p}`Cam21`. | ||
| 435 | |||
| 436 | Level: beginner | ||
| 437 | |||
| 438 | .seealso: [](ch:nep), `NEP`, `NEPType`, `NEPSetType()`, `NEPNArnoldiGetKSP()`, `NEPNArnoldiSetLagPreconditioner()` | ||
| 439 | M*/ | ||
| 440 | 96 | SLEPC_EXTERN PetscErrorCode NEPCreate_NArnoldi(NEP nep) | |
| 441 | { | ||
| 442 | 96 | NEP_NARNOLDI *ctx; | |
| 443 | |||
| 444 |
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96 | PetscFunctionBegin; |
| 445 |
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96 | PetscCall(PetscNew(&ctx)); |
| 446 | 96 | nep->data = (void*)ctx; | |
| 447 | 96 | ctx->lag = 1; | |
| 448 | |||
| 449 | 96 | nep->useds = PETSC_TRUE; | |
| 450 | |||
| 451 | 96 | nep->ops->solve = NEPSolve_NArnoldi; | |
| 452 | 96 | nep->ops->setup = NEPSetUp_NArnoldi; | |
| 453 | 96 | nep->ops->setfromoptions = NEPSetFromOptions_NArnoldi; | |
| 454 | 96 | nep->ops->reset = NEPReset_NArnoldi; | |
| 455 | 96 | nep->ops->destroy = NEPDestroy_NArnoldi; | |
| 456 | 96 | nep->ops->view = NEPView_NArnoldi; | |
| 457 | 96 | nep->ops->computevectors = NEPComputeVectors_Schur; | |
| 458 | |||
| 459 |
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96 | PetscCall(PetscObjectComposeFunction((PetscObject)nep,"NEPNArnoldiSetLagPreconditioner_C",NEPNArnoldiSetLagPreconditioner_NArnoldi)); |
| 460 |
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96 | PetscCall(PetscObjectComposeFunction((PetscObject)nep,"NEPNArnoldiGetLagPreconditioner_C",NEPNArnoldiGetLagPreconditioner_NArnoldi)); |
| 461 |
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96 | PetscCall(PetscObjectComposeFunction((PetscObject)nep,"NEPNArnoldiSetKSP_C",NEPNArnoldiSetKSP_NArnoldi)); |
| 462 |
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96 | PetscCall(PetscObjectComposeFunction((PetscObject)nep,"NEPNArnoldiGetKSP_C",NEPNArnoldiGetKSP_NArnoldi)); |
| 463 |
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24 | PetscFunctionReturn(PETSC_SUCCESS); |
| 464 | } | ||
| 465 |