Actual source code: ks-twosided.c

      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 eigensolver: "krylovschur"

     13:    Method: Two-sided Arnoldi with Krylov-Schur restart (for left eigenvectors)

     15:    References:

     17:        [1] I.N. Zwaan and M.E. Hochstenbach, "Krylov-Schur-type restarts
     18:            for the two-sided Arnoldi method", SIAM J. Matrix Anal. Appl.
     19:            38(2):297-321, 2017.

     21: */

     23: #include <slepc/private/epsimpl.h>
     24: #include "krylovschur.h"
     25: #include <slepcblaslapack.h>

     27: static PetscErrorCode EPSTwoSidedRQUpdate1(EPS eps,Mat M,PetscInt nv,PetscReal beta,PetscReal betat)
     28: {
     29:   PetscScalar       *T,*S,*A,*w;
     30:   const PetscScalar *pM;
     31:   Vec               u;
     32:   PetscInt          ld,ncv=eps->ncv,i,l,nnv;
     33:   PetscBLASInt      info,n_,ncv_,*p,one=1;

     35:   PetscFunctionBegin;
     36:   PetscCall(DSGetLeadingDimension(eps->ds,&ld));
     37:   PetscCall(PetscMalloc3(nv,&p,ncv*ncv,&A,ncv,&w));
     38:   PetscCall(BVGetActiveColumns(eps->V,&l,&nnv));
     39:   PetscCall(BVSetActiveColumns(eps->V,0,nv));
     40:   PetscCall(BVSetActiveColumns(eps->W,0,nv));
     41:   PetscCall(BVGetColumn(eps->V,nv,&u));
     42:   PetscCall(BVDotVec(eps->W,u,w));
     43:   PetscCall(BVRestoreColumn(eps->V,nv,&u));
     44:   PetscCall(MatDenseGetArrayRead(M,&pM));
     45:   PetscCall(PetscArraycpy(A,pM,ncv*ncv));
     46:   PetscCall(MatDenseRestoreArrayRead(M,&pM));
     47:   PetscCall(PetscBLASIntCast(nv,&n_));
     48:   PetscCall(PetscBLASIntCast(ncv,&ncv_));
     49:   PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
     50:   PetscCallBLAS("LAPACKgetrf",LAPACKgetrf_(&n_,&n_,A,&ncv_,p,&info));
     51:   SlepcCheckLapackInfo("getrf",info);
     52:   PetscCall(PetscLogFlops(2.0*n_*n_*n_/3.0));
     53:   PetscCallBLAS("LAPACKgetrs",LAPACKgetrs_("N",&n_,&one,A,&ncv_,p,w,&ncv_,&info));
     54:   SlepcCheckLapackInfo("getrs",info);
     55:   PetscCall(PetscLogFlops(2.0*n_*n_-n_));
     56:   PetscCall(BVMultColumn(eps->V,-1.0,1.0,nv,w));
     57:   PetscCall(DSGetArray(eps->ds,DS_MAT_A,&S));
     58:   for (i=0;i<nv;i++) S[(nv-1)*ld+i] += beta*w[i];
     59:   PetscCall(DSRestoreArray(eps->ds,DS_MAT_A,&S));
     60:   PetscCall(BVGetColumn(eps->W,nv,&u));
     61:   PetscCall(BVDotVec(eps->V,u,w));
     62:   PetscCall(BVRestoreColumn(eps->W,nv,&u));
     63:   PetscCallBLAS("LAPACKgetrs",LAPACKgetrs_("C",&n_,&one,A,&ncv_,p,w,&ncv_,&info));
     64:   PetscCall(PetscFPTrapPop());
     65:   PetscCall(BVMultColumn(eps->W,-1.0,1.0,nv,w));
     66:   PetscCall(DSGetArray(eps->ds,DS_MAT_B,&T));
     67:   for (i=0;i<nv;i++) T[(nv-1)*ld+i] += betat*w[i];
     68:   PetscCall(DSRestoreArray(eps->ds,DS_MAT_B,&T));
     69:   PetscCall(PetscFree3(p,A,w));
     70:   PetscCall(BVSetActiveColumns(eps->V,l,nnv));
     71:   PetscCall(BVSetActiveColumns(eps->W,l,nnv));
     72:   PetscFunctionReturn(PETSC_SUCCESS);
     73: }

     75: static PetscErrorCode EPSTwoSidedRQUpdate2(EPS eps,Mat M,PetscInt k)
     76: {
     77:   PetscScalar    *Q,*pM,*w,zero=0.0,sone=1.0,*c,*A;
     78:   PetscBLASInt   n_,ncv_,ld_;
     79:   PetscReal      norm;
     80:   PetscInt       l,nv,ncv=eps->ncv,ld,i,j;

     82:   PetscFunctionBegin;
     83:   PetscCall(DSGetLeadingDimension(eps->ds,&ld));
     84:   PetscCall(BVGetActiveColumns(eps->V,&l,&nv));
     85:   PetscCall(BVSetActiveColumns(eps->V,0,nv));
     86:   PetscCall(BVSetActiveColumns(eps->W,0,nv));
     87:   PetscCall(PetscMalloc2(ncv*ncv,&w,ncv,&c));
     88:   /* u = u - V*V'*u */
     89:   PetscCall(BVOrthogonalizeColumn(eps->V,k,c,&norm,NULL));
     90:   PetscCall(BVScaleColumn(eps->V,k,1.0/norm));
     91:   PetscCall(DSGetArray(eps->ds,DS_MAT_A,&A));
     92:   /* H = H + V'*u*b' */
     93:   for (j=l;j<k;j++) {
     94:     for (i=0;i<k;i++) A[i+j*ld] += c[i]*A[k+j*ld];
     95:     A[k+j*ld] *= norm;
     96:   }
     97:   PetscCall(DSRestoreArray(eps->ds,DS_MAT_A,&A));
     98:   PetscCall(BVOrthogonalizeColumn(eps->W,k,c,&norm,NULL));
     99:   PetscCall(BVScaleColumn(eps->W,k,1.0/norm));
    100:   PetscCall(DSGetArray(eps->ds,DS_MAT_B,&A));
    101:   /* H = H + V'*u*b' */
    102:   for (j=l;j<k;j++) {
    103:     for (i=0;i<k;i++) A[i+j*ld] += c[i]*A[k+j*ld];
    104:     A[k+j*ld] *= norm;
    105:   }
    106:   PetscCall(DSRestoreArray(eps->ds,DS_MAT_B,&A));

    108:   /* M = Q'*M*Q */
    109:   PetscCall(MatDenseGetArray(M,&pM));
    110:   PetscCall(PetscBLASIntCast(ncv,&ncv_));
    111:   PetscCall(PetscBLASIntCast(nv,&n_));
    112:   PetscCall(PetscBLASIntCast(ld,&ld_));
    113:   PetscCall(DSGetArray(eps->ds,DS_MAT_Q,&Q));
    114:   PetscCallBLAS("BLASgemm",BLASgemm_("N","N",&n_,&n_,&n_,&sone,pM,&ncv_,Q,&ld_,&zero,w,&ncv_));
    115:   PetscCall(DSRestoreArray(eps->ds,DS_MAT_Q,&Q));
    116:   PetscCall(DSGetArray(eps->ds,DS_MAT_Z,&Q));
    117:   PetscCallBLAS("BLASgemm",BLASgemm_("C","N",&n_,&n_,&n_,&sone,Q,&ld_,w,&ncv_,&zero,pM,&ncv_));
    118:   PetscCall(DSRestoreArray(eps->ds,DS_MAT_Z,&Q));
    119:   PetscCall(MatDenseRestoreArray(M,&pM));
    120:   PetscCall(PetscFree2(w,c));
    121:   PetscCall(BVSetActiveColumns(eps->V,l,nv));
    122:   PetscCall(BVSetActiveColumns(eps->W,l,nv));
    123:   PetscFunctionReturn(PETSC_SUCCESS);
    124: }

    126: PetscErrorCode EPSSolve_KrylovSchur_TwoSided(EPS eps)
    127: {
    128:   EPS_KRYLOVSCHUR *ctx = (EPS_KRYLOVSCHUR*)eps->data;
    129:   Mat             M,U,Op,OpHT,S,T;
    130:   PetscReal       norm,norm2,beta,betat;
    131:   PetscInt        ld,l,nv,nvt,k,nconv,dsn,dsk;
    132:   PetscBool       breakdownt,breakdown,breakdownl;

    134:   PetscFunctionBegin;
    135:   PetscCall(DSGetLeadingDimension(eps->ds,&ld));
    136:   PetscCall(EPSGetStartVector(eps,0,NULL));
    137:   PetscCall(EPSGetLeftStartVector(eps,0,NULL));
    138:   l = 0;
    139:   PetscCall(MatCreateSeqDense(PETSC_COMM_SELF,eps->ncv,eps->ncv,NULL,&M));

    141:   PetscCall(STGetOperator(eps->st,&Op));
    142:   PetscCall(MatCreateHermitianTranspose(Op,&OpHT));

    144:   /* Restart loop */
    145:   while (eps->reason == EPS_CONVERGED_ITERATING) {
    146:     eps->its++;

    148:     /* Compute an nv-step Arnoldi factorization for Op */
    149:     nv = PetscMin(eps->nconv+eps->mpd,eps->ncv);
    150:     PetscCall(DSSetDimensions(eps->ds,nv,eps->nconv,eps->nconv+l));
    151:     PetscCall(DSGetMat(eps->ds,DS_MAT_A,&S));
    152:     PetscCall(BVMatArnoldi(eps->V,Op,S,eps->nconv+l,&nv,&beta,&breakdown));
    153:     PetscCall(DSRestoreMat(eps->ds,DS_MAT_A,&S));

    155:     /* Compute an nv-step Arnoldi factorization for Op' */
    156:     nvt = nv;
    157:     PetscCall(DSSetDimensions(eps->ds,nv,eps->nconv,eps->nconv+l));
    158:     PetscCall(DSGetMat(eps->ds,DS_MAT_B,&T));
    159:     PetscCall(BVMatArnoldi(eps->W,OpHT,T,eps->nconv+l,&nvt,&betat,&breakdownt));
    160:     PetscCall(DSRestoreMat(eps->ds,DS_MAT_B,&T));

    162:     /* Make sure both factorizations have the same length */
    163:     nv = PetscMin(nv,nvt);
    164:     PetscCall(DSSetDimensions(eps->ds,nv,eps->nconv,eps->nconv+l));
    165:     if (l==0) PetscCall(DSSetState(eps->ds,DS_STATE_INTERMEDIATE));
    166:     else PetscCall(DSSetState(eps->ds,DS_STATE_RAW));
    167:     breakdown = (breakdown || breakdownt)? PETSC_TRUE: PETSC_FALSE;

    169:     /* Update M, modify Rayleigh quotients S and T */
    170:     PetscCall(BVSetActiveColumns(eps->V,eps->nconv+l,nv));
    171:     PetscCall(BVSetActiveColumns(eps->W,eps->nconv+l,nv));
    172:     PetscCall(BVMatProject(eps->V,NULL,eps->W,M));

    174:     PetscCall(EPSTwoSidedRQUpdate1(eps,M,nv,beta,betat));

    176:     /* Solve projected problem */
    177:     PetscCall(DSSolve(eps->ds,eps->eigr,eps->eigi));
    178:     PetscCall(DSSort(eps->ds,eps->eigr,eps->eigi,NULL,NULL,NULL));
    179:     PetscCall(DSSynchronize(eps->ds,eps->eigr,eps->eigi));
    180:     PetscCall(DSUpdateExtraRow(eps->ds));

    182:     /* Check convergence */
    183:     PetscCall(BVNormColumn(eps->V,nv,NORM_2,&norm));
    184:     PetscCall(BVNormColumn(eps->W,nv,NORM_2,&norm2));
    185:     PetscCall(EPSKrylovConvergence(eps,PETSC_FALSE,eps->nconv,nv-eps->nconv,beta*norm,betat*norm2,1.0,&k));
    186:     PetscCall((*eps->stopping)(eps,eps->its,eps->max_it,k,eps->nev,&eps->reason,eps->stoppingctx));
    187:     nconv = k;

    189:     /* Update l */
    190:     if (eps->reason != EPS_CONVERGED_ITERATING || breakdown || k==nv) l = 0;
    191:     else {
    192:       l = PetscMax(1,(PetscInt)((nv-k)*ctx->keep));
    193:       PetscCall(DSGetTruncateSize(eps->ds,k,nv,&l));
    194:     }
    195:     if (!ctx->lock && l>0) { l += k; k = 0; } /* non-locking variant: reset no. of converged pairs */
    196:     if (l) PetscCall(PetscInfo(eps,"Preparing to restart keeping l=%" PetscInt_FMT " vectors\n",l));

    198:     /* Update the corresponding vectors V(:,idx) = V*Q(:,idx) */
    199:     PetscCall(BVSetActiveColumns(eps->V,eps->nconv,nv));
    200:     PetscCall(BVSetActiveColumns(eps->W,eps->nconv,nv));
    201:     PetscCall(DSGetMat(eps->ds,DS_MAT_Q,&U));
    202:     PetscCall(BVMultInPlace(eps->V,U,eps->nconv,k+l));
    203:     PetscCall(DSRestoreMat(eps->ds,DS_MAT_Q,&U));
    204:     PetscCall(DSGetMat(eps->ds,DS_MAT_Z,&U));
    205:     PetscCall(BVMultInPlace(eps->W,U,eps->nconv,k+l));
    206:     PetscCall(DSRestoreMat(eps->ds,DS_MAT_Z,&U));
    207:     if (eps->reason == EPS_CONVERGED_ITERATING && !breakdown) {
    208:       PetscCall(BVCopyColumn(eps->V,nv,k+l));
    209:       PetscCall(BVCopyColumn(eps->W,nv,k+l));
    210:     }

    212:     if (eps->reason == EPS_CONVERGED_ITERATING) {
    213:       if (breakdown || k==nv) {
    214:         /* Start a new Arnoldi factorization */
    215:         PetscCall(PetscInfo(eps,"Breakdown in Krylov-Schur method (it=%" PetscInt_FMT " norm=%g)\n",eps->its,(double)beta));
    216:         if (k<eps->nev) {
    217:           PetscCall(EPSGetStartVector(eps,k,&breakdown));
    218:           PetscCall(EPSGetLeftStartVector(eps,k,&breakdownl));
    219:           if (breakdown || breakdownl) {
    220:             eps->reason = EPS_DIVERGED_BREAKDOWN;
    221:             PetscCall(PetscInfo(eps,"Unable to generate more start vectors\n"));
    222:           }
    223:         }
    224:       } else {
    225:         PetscCall(DSGetDimensions(eps->ds,&dsn,NULL,&dsk,NULL));
    226:         PetscCall(DSSetDimensions(eps->ds,dsn,k,dsk));
    227:         PetscCall(DSTruncate(eps->ds,k+l,PETSC_FALSE));
    228:       }
    229:       PetscCall(EPSTwoSidedRQUpdate2(eps,M,k+l));
    230:     }
    231:     eps->nconv = k;
    232:     PetscCall(EPSMonitor(eps,eps->its,nconv,eps->eigr,eps->eigi,eps->errest,nv));
    233:   }

    235:   PetscCall(STRestoreOperator(eps->st,&Op));
    236:   PetscCall(MatDestroy(&OpHT));

    238:   PetscCall(DSTruncate(eps->ds,eps->nconv,PETSC_TRUE));
    239:   PetscCall(MatDestroy(&M));
    240:   PetscFunctionReturn(PETSC_SUCCESS);
    241: }