Date: 2016-03-29T14:59:04+00:00

Actual source code: stoar.c
slepc-3.6.3 2016-03-29
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      1: /*

      3:    SLEPc polynomial eigensolver: "stoar"

      5:    Method: S-TOAR

      7:    Algorithm:

      9:        Symmetric Two-Level Orthogonal Arnoldi.

     11:    References:

     13:        [1] C. Campos and J.E. Roman, " Restarted Q-Arnoldi-type methods
     14:            exploiting symmetry in quadratic eigenvalue problems",
     15:            submitted, 2015.

     17:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     18:    SLEPc - Scalable Library for Eigenvalue Problem Computations
     19:    Copyright (c) 2002-2015, Universitat Politecnica de Valencia, Spain

     21:    This file is part of SLEPc.

     23:    SLEPc is free software: you can redistribute it and/or modify it under  the
     24:    terms of version 3 of the GNU Lesser General Public License as published by
     25:    the Free Software Foundation.

     27:    SLEPc  is  distributed in the hope that it will be useful, but WITHOUT  ANY
     28:    WARRANTY;  without even the implied warranty of MERCHANTABILITY or  FITNESS
     29:    FOR  A  PARTICULAR PURPOSE. See the GNU Lesser General Public  License  for
     30:    more details.

     32:    You  should have received a copy of the GNU Lesser General  Public  License
     33:    along with SLEPc. If not, see <http://www.gnu.org/licenses/>.
     34:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     35: */

     37: #include <slepc/private/pepimpl.h>         /*I "slepcpep.h" I*/
     38:  #include ../src/pep/impls/krylov/pepkrylov.h
     39: #include <slepcblaslapack.h>

     43: /*
     44:   Compute B-norm of v=[v1;v2] whith  B=diag(-pep->T[0],pep->T[2])
     45: */
     46: static PetscErrorCode PEPSTOARNorm(PEP pep,PetscInt j,PetscReal *norm)
     47: {
     49:   PEP_TOAR      *ctx = (PEP_TOAR*)pep->data;
     50:   PetscBLASInt   n_,one=1,ld_;
     51:   PetscScalar    sone=1.0,szero=0.0,*sp,*sq,*w1,*w2,*qK,*qM;
     52:   PetscInt       n,i,lds=ctx->d*ctx->ld;

     55:   qK = ctx->qB;
     56:   qM = ctx->qB+ctx->ld*ctx->ld;
     57:   n = j+2;
     58:   PetscMalloc2(n,&w1,n,&w2);
     59:   sp = ctx->S+lds*j;
     60:   sq = sp+ctx->ld;
     61:   PetscBLASIntCast(n,&n_);
     62:   PetscBLASIntCast(ctx->ld,&ld_);
     63:   PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n_,&n_,&sone,qK,&ld_,sp,&one,&szero,w1,&one));
     64:   PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n_,&n_,&sone,qM,&ld_,sq,&one,&szero,w2,&one));
     65:   *norm = 0.0;
     66:   for (i=0;i<n;i++) *norm += PetscRealPart(w1[i]*PetscConj(sp[i])+w2[i]*PetscConj(sq[i]));
     67:   *norm = (*norm>0.0)?PetscSqrtReal(*norm):-PetscSqrtReal(-*norm);
     68:   PetscFree2(w1,w2);
     69:   return(0);
     70: }

     74: static PetscErrorCode PEPSTOARqKqMupdates(PEP pep,PetscInt j,Vec *wv,PetscInt nwv)
     75: {
     77:   PEP_TOAR      *ctx = (PEP_TOAR*)pep->data;
     78:   PetscInt       i,ld=ctx->ld;
     79:   PetscScalar    *qK,*qM;
     80:   Vec            vj,v1,v2;

     83:   qK = ctx->qB;
     84:   qM = ctx->qB+ctx->ld*ctx->ld;
     85:   if (!wv||nwv<2) {
     86:     if (!wv) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid argument %d",3);
     87:     else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid argument %d",4);
     88:   }
     89:   v1 = wv[0];
     90:   v2 = wv[1];
     91:   BVGetColumn(pep->V,j,&vj);
     92:   STMatMult(pep->st,0,vj,v1);
     93:   STMatMult(pep->st,2,vj,v2);
     94:   BVRestoreColumn(pep->V,j,&vj);
     95:   for (i=0;i<=j;i++) {
     96:     BVGetColumn(pep->V,i,&vj);
     97:     VecDot(v1,vj,qK+j*ld+i);
     98:     VecDot(v2,vj,qM+j*ld+i);
     99:     *(qM+j*ld+i) *= pep->sfactor*pep->sfactor;
    100:     BVRestoreColumn(pep->V,i,&vj);
    101:   }
    102:   for (i=0;i<j;i++) {
    103:     qK[i+j*ld] = -qK[i+ld*j];
    104:     qK[j+i*ld] = PetscConj(qK[i+j*ld]);
    105:     qM[j+i*ld] = PetscConj(qM[i+j*ld]);
    106:   }
    107:   qK[j+j*ld] = -PetscRealPart(qK[j+ld*j]);
    108:   qM[j+j*ld] = PetscRealPart(qM[j+ld*j]);
    109:   return(0);
    110: }

    114: PetscErrorCode PEPSetUp_STOAR(PEP pep)
    115: {
    117:   PetscBool      sinv,flg,lindep;
    118:   PEP_TOAR      *ctx = (PEP_TOAR*)pep->data;
    119:   PetscInt       ld,i;
    120:   PetscReal      norm,*omega;

    123:   PEPSetDimensions_Default(pep,pep->nev,&pep->ncv,&pep->mpd);
    124:   if (!ctx->lock && pep->mpd<pep->ncv) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"Should not use mpd parameter in non-locking variant");
    125:   if (!pep->max_it) pep->max_it = PetscMax(100,2*pep->n/pep->ncv);
    126:   if (!pep->which) {
    127:     PetscObjectTypeCompare((PetscObject)pep->st,STSINVERT,&sinv);
    128:     if (sinv) pep->which = PEP_TARGET_MAGNITUDE;
    129:     else pep->which = PEP_LARGEST_MAGNITUDE;
    130:   }
    131:   if (pep->problem_type!=PEP_HERMITIAN) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"Requested method is only available for Hermitian problems");

    133:   if (pep->nmat!=3) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"Solver only available for quadratic problems");
    134:   if (pep->basis!=PEP_BASIS_MONOMIAL) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"Solver not implemented for non-monomial bases");
    135:   STGetTransform(pep->st,&flg);
    136:   if (!flg) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"Solver requires the ST transformation flag set, see STSetTransform()");

    138:   PEPAllocateSolution(pep,2);
    139:   PEPSetWorkVecs(pep,4);
    140:   ld = pep->ncv+2;
    141:   DSSetType(pep->ds,DSGHIEP);
    142:   DSSetCompact(pep->ds,PETSC_TRUE);
    143:   DSAllocate(pep->ds,ld);
    144:   STGetNumMatrices(pep->st,&ctx->d);
    145:   ctx->d--;
    146:   ctx->ld = ld;
    147:   PetscCalloc1(ctx->d*ld*ld,&ctx->S);
    148:   PetscCalloc1(2*ld*ld,&ctx->qB);

    150:   /* process starting vector */
    151:   if (pep->nini>-2) {
    152:     BVSetRandomColumn(pep->V,0,pep->rand);
    153:     BVSetRandomColumn(pep->V,1,pep->rand);
    154:   } else {
    155:     BVInsertVec(pep->V,0,pep->IS[0]);
    156:     BVInsertVec(pep->V,1,pep->IS[1]);
    157:   }
    158:   BVOrthogonalizeColumn(pep->V,0,NULL,&norm,&lindep);
    159:   if (!lindep) {
    160:     BVScaleColumn(pep->V,0,1.0/norm);
    161:     ctx->S[0] = norm;
    162:     PEPSTOARqKqMupdates(pep,0,pep->work,2);
    163:   } else {
    164:     SETERRQ(PetscObjectComm((PetscObject)pep),1,"Problem with initial vector");
    165:   }
    166:   BVOrthogonalizeColumn(pep->V,1,ctx->S+ld,&norm,&lindep);
    167:   if (!lindep) {
    168:     BVScaleColumn(pep->V,1,1.0/norm);
    169:     ctx->S[1] = norm;
    170:     PEPSTOARqKqMupdates(pep,1,pep->work,2);
    171:   } else {
    172:     SETERRQ(PetscObjectComm((PetscObject)pep),1,"Problem with initial vector");
    173:   }

    175:   PEPSTOARNorm(pep,0,&norm);
    176:   for (i=0;i<2;i++) { ctx->S[i+ld] /= norm; ctx->S[i] /= norm; }
    177:   DSGetArrayReal(pep->ds,DS_MAT_D,&omega);
    178:   omega[0] = (norm>0)?1.0:-1.0;
    179:   DSRestoreArrayReal(pep->ds,DS_MAT_D,&omega);
    180:   if (pep->nini<0) {
    181:     SlepcBasisDestroy_Private(&pep->nini,&pep->IS);
    182:   }
    183:   return(0);
    184: }

    188: /*
    189:   Computes GS orthogonalization  x = [z;x] - [Sp;Sq]*y,
    190:   where y = Omega\([Sp;Sq]'*[qK zeros(size(qK,1)) ;zeros(size(qK,1)) qM]*[z;x]).
    191:   n: Column from S to be orthogonalized against previous columns.
    192: */
    193: static PetscErrorCode PEPSTOAROrth2(PEP pep,PetscInt k,PetscReal *Omega,PetscScalar *y)
    194: {
    196:   PEP_TOAR      *ctx = (PEP_TOAR*)pep->data;
    197:   PetscBLASInt   n_,lds_,k_,one=1,ld_;
    198:   PetscScalar    *S=ctx->S,sonem=-1.0,sone=1.0,szero=0.0,*tp,*tq,*xp,*xq,*c,*qK,*qM;
    199:   PetscInt       i,lds=ctx->d*ctx->ld,n,j;
    200:
    202:   qK = ctx->qB;
    203:   qM = ctx->qB+ctx->ld*ctx->ld;
    204:   n = k+2;
    205:   PetscMalloc3(n,&tp,n,&tq,k,&c);
    206:   PetscBLASIntCast(n,&n_); /* Size of qK and qM */
    207:   PetscBLASIntCast(ctx->ld,&ld_);
    208:   PetscBLASIntCast(lds,&lds_);
    209:   PetscBLASIntCast(k,&k_); /* Number of vectors to orthogonalize against */
    210:   xp = S+k*lds;
    211:   xq = S+ctx->ld+k*lds;
    212:   PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n_,&n_,&sone,qK,&ld_,xp,&one,&szero,tp,&one));
    213:   PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n_,&n_,&sone,qM,&ld_,xq,&one,&szero,tq,&one));
    214:   PetscStackCallBLAS("BLASgemv",BLASgemv_("C",&n_,&k_,&sone,ctx->S,&lds_,tp,&one,&szero,y,&one));
    215:   PetscStackCallBLAS("BLASgemv",BLASgemv_("C",&n_,&k_,&sone,S+ctx->ld,&lds_,tq,&one,&sone,y,&one));
    216:   for (i=0;i<k;i++) y[i] /= Omega[i];
    217:   PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n_,&k_,&sonem,S,&lds_,y,&one,&sone,xp,&one));
    218:   PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n_,&k_,&sonem,S+ctx->ld,&lds_,y,&one,&sone,xq,&one));
    219:   /* three times */
    220:   for (j=0;j<2;j++) {
    221:     PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n_,&n_,&sone,qK,&ld_,xp,&one,&szero,tp,&one));
    222:     PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n_,&n_,&sone,qM,&ld_,xq,&one,&szero,tq,&one));
    223:     PetscStackCallBLAS("BLASgemv",BLASgemv_("C",&n_,&k_,&sone,ctx->S,&lds_,tp,&one,&szero,c,&one));
    224:     PetscStackCallBLAS("BLASgemv",BLASgemv_("C",&n_,&k_,&sone,S+ctx->ld,&lds_,tq,&one,&sone,c,&one));
    225:     for (i=0;i<k;i++) c[i] /= Omega[i];
    226:     PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n_,&k_,&sonem,S,&lds_,c,&one,&sone,xp,&one));
    227:     PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n_,&k_,&sonem,S+ctx->ld,&lds_,c,&one,&sone,xq,&one));
    228:     for (i=0;i<k;i++) y[i] += c[i];
    229:   }
    230:   PetscFree3(tp,tq,c);
    231:   return(0);
    232: }

    236: /*
    237:   Compute a run of Lanczos iterations
    238: */
    239: static PetscErrorCode PEPSTOARrun(PEP pep,PetscReal *a,PetscReal *b,PetscReal *omega,PetscInt k,PetscInt *M,PetscBool *breakdown,PetscBool *symmlost,PetscScalar *work,PetscInt nw,Vec *t_,PetscInt nwv)
    240: {
    242:   PEP_TOAR      *ctx = (PEP_TOAR*)pep->data;
    243:   PetscInt       i,j,m=*M,nwu=0,lwa,l;
    244:   PetscInt       lds=ctx->d*ctx->ld,offq=ctx->ld;
    245:   Vec            v=t_[0],t=t_[1],q=t_[2];
    246:   PetscReal      norm,sym=0.0,fro=0.0,*f;
    247:   PetscScalar    *y,*S=ctx->S;
    248:   PetscBLASInt   j_,one=1;
    249:   PetscBool      lindep;

    252:   *breakdown = PETSC_FALSE; /* ----- */
    253:   if (!t_||nwv<3) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid argument %d",12);
    254:   lwa = (ctx->ld)*4;
    255:   if (!work||nw<lwa) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid argument %d",10);
    256:   DSGetDimensions(pep->ds,NULL,NULL,&l,NULL,NULL);
    257:   y = work;
    258:   nwu += ctx->ld;
    259:   for (j=k;j<m;j++) {
    260:     /* apply operator */
    261:     BVSetActiveColumns(pep->V,0,j+2);
    262:     BVMultVec(pep->V,1.0,0.0,v,S+j*lds);
    263:     STMatMult(pep->st,0,v,t);
    264:     BVMultVec(pep->V,1.0,0.0,v,S+offq+j*lds);
    265:     STMatMult(pep->st,1,v,q);
    266:     VecAXPY(t,pep->sfactor,q);
    267:     STMatSolve(pep->st,t,q);
    268:     VecScale(q,-1.0/(pep->sfactor*pep->sfactor));

    270:     /* orthogonalize */
    271:     BVOrthogonalizeVec(pep->V,q,S+offq+(j+1)*lds,&norm,&lindep);
    272:     if (lindep) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"STOAR does not support detection of linearly dependent TOAR vectors");
    273:     *(S+offq+(j+1)*lds+j+2) = norm;
    274:     VecScale(q,1.0/norm);
    275:     BVInsertVec(pep->V,j+2,q);
    276:     for (i=0;i<=j+1;i++) *(S+(j+1)*lds+i) = *(S+offq+j*lds+i);
    277:
    278:     /* update qK and qM */
    279:     PEPSTOARqKqMupdates(pep,j+2,t_,2);

    281:     /* level-2 orthogonalization */
    282:     PEPSTOAROrth2(pep,j+1,omega,y);
    283:     a[j] = PetscRealPart(y[j])/omega[j];
    284:     PEPSTOARNorm(pep,j+1,&norm);
    285:     omega[j+1] = (norm > 0)?1.0:-1.0;
    286:     for (i=0;i<=j+2;i++) {
    287:       S[i+(j+1)*lds] /= norm;
    288:       S[i+offq+(j+1)*lds] /= norm;
    289:     }
    290:     b[j] = PetscAbsReal(norm);

    292:     /* check symmetry */
    293:     DSGetArrayReal(pep->ds,DS_MAT_T,&f);
    294:     if (j==k) {
    295:       for (i=l;i<j-1;i++) y[i] = PetscAbsScalar(y[i])-PetscAbsReal(f[2*ctx->ld+i]);
    296:       for (i=0;i<l;i++) y[i] = 0.0;
    297:     }
    298:     DSRestoreArrayReal(pep->ds,DS_MAT_T,&f);
    299:     if (j>0) y[j-1] = PetscAbsScalar(y[j-1])-PetscAbsReal(b[j-1]);
    300:     PetscBLASIntCast(j,&j_);
    301:     sym = SlepcAbs(BLASnrm2_(&j_,y,&one),sym);
    302:     fro = SlepcAbs(fro,SlepcAbs(a[j],b[j]));
    303:     if (j>0) fro = SlepcAbs(fro,b[j-1]);
    304:     if (sym/fro>PetscMax(PETSC_SQRT_MACHINE_EPSILON,10*pep->tol)) {
    305:       *symmlost = PETSC_TRUE;
    306:       *M=j+1;
    307:       break;
    308:     }
    309:   }
    310:   return(0);
    311: }

    315: static PetscErrorCode PEPSTOARTrunc(PEP pep,PetscInt rs1,PetscInt cs1,PetscScalar *work,PetscInt nw,PetscReal *rwork,PetscInt nrw)
    316: {
    318:   PEP_TOAR      *ctx = (PEP_TOAR*)pep->data;
    319:   Mat            G;
    320:   PetscInt       lwa,nwu=0,lrwa,nrwu=0;
    321:   PetscInt       i,n,lds=2*ctx->ld;
    322:   PetscScalar    *M,*V,*U,*S=ctx->S,sone=1.0,zero=0.0,t,*qK,*qM;
    323:   PetscReal      *sg;
    324:   PetscBLASInt   cs1_,rs1_,cs1t2,cs1p1,n_,info,lw_,lds_,ld_;

    327:   qK = ctx->qB;
    328:   qM = ctx->qB+ctx->ld*ctx->ld;
    329:   n = (rs1>2*cs1)?2*cs1:rs1;
    330:   lwa = cs1*rs1*4+n*(rs1+2*cs1)+(cs1+1)*(cs1+2);
    331:   lrwa = n+cs1+1+5*n;
    332:   if (!work||nw<lwa) {
    333:     if (nw<lwa) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid argument %d",6);
    334:     if (!work) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid argument %d",5);
    335:   }
    336:   if (!rwork||nrw<lrwa) {
    337:     if (nrw<lrwa) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid argument %d",8);
    338:     if (!work) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid argument %d",7);
    339:   }
    340:   M = work+nwu;
    341:   nwu += rs1*cs1*2;
    342:   U = work+nwu;
    343:   nwu += rs1*n;
    344:   V = work+nwu;
    345:   nwu += 2*cs1*n;
    346:   sg = rwork+nrwu;
    347:   nrwu += n;
    348:   for (i=0;i<cs1;i++) {
    349:     PetscMemcpy(M+i*rs1,S+i*lds,rs1*sizeof(PetscScalar));
    350:     PetscMemcpy(M+(i+cs1)*rs1,S+i*lds+ctx->ld,rs1*sizeof(PetscScalar));
    351:   }
    352:   PetscBLASIntCast(n,&n_);
    353:   PetscBLASIntCast(cs1,&cs1_);
    354:   PetscBLASIntCast(rs1,&rs1_);
    355:   PetscBLASIntCast(cs1*2,&cs1t2);
    356:   PetscBLASIntCast(cs1+1,&cs1p1);
    357:   PetscBLASIntCast(lds,&lds_);
    358:   PetscBLASIntCast(ctx->ld,&ld_);
    359:   PetscBLASIntCast(lwa-nwu,&lw_);
    360: #if !defined(PETSC_USE_COMPLEX)
    361:   PetscStackCallBLAS("LAPACKgesvd",LAPACKgesvd_("S","S",&rs1_,&cs1t2,M,&rs1_,sg,U,&rs1_,V,&n_,work+nwu,&lw_,&info));
    362: #else
    363:   PetscStackCallBLAS("LAPACKgesvd",LAPACKgesvd_("S","S",&rs1_,&cs1t2,M,&rs1_,sg,U,&rs1_,V,&n_,work+nwu,&lw_,rwork+nrwu,&info));
    364: #endif
    365:   if (info) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in Lapack xGESVD %d",info);

    367:   /* Update the corresponding vectors V(:,idx) = V*Q(:,idx) */
    368:   MatCreateSeqDense(PETSC_COMM_SELF,rs1,2*cs1,U,&G);
    369:   BVSetActiveColumns(pep->V,0,rs1);
    370:   BVMultInPlace(pep->V,G,0,cs1+1);
    371:   MatDestroy(&G);
    372:
    373:   /* Update S */
    374:   PetscMemzero(S,lds*ctx->ld*sizeof(PetscScalar));

    376:   for (i=0;i<cs1+1;i++) {
    377:     t = sg[i];
    378:     PetscStackCallBLAS("BLASscal",BLASscal_(&cs1t2,&t,V+i,&n_));
    379:   }
    380:   for (i=0;i<cs1;i++) {
    381:     PetscMemcpy(S+i*lds,V+i*n,(cs1+1)*sizeof(PetscScalar));
    382:     PetscMemcpy(S+ctx->ld+i*lds,V+(cs1+i)*n,(cs1+1)*sizeof(PetscScalar));
    383:   }

    385:   /* Update qM and qK */
    386:   PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&rs1_,&cs1p1,&rs1_,&sone,qK,&ld_,U,&rs1_,&zero,work+nwu,&rs1_));
    387:   PetscStackCallBLAS("BLASgemm",BLASgemm_("C","N",&cs1p1,&cs1p1,&rs1_,&sone,U,&rs1_,work+nwu,&rs1_,&zero,qK,&ld_));
    388:   PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&rs1_,&cs1p1,&rs1_,&sone,qM,&ld_,U,&rs1_,&zero,work+nwu,&rs1_));
    389:   PetscStackCallBLAS("BLASgemm",BLASgemm_("C","N",&cs1p1,&cs1p1,&rs1_,&sone,U,&rs1_,work+nwu,&rs1_,&zero,qM,&ld_));
    390:   return(0);
    391: }

    395: /*
    396:   S <- S*Q
    397:   columns s-s+ncu of S
    398:   rows 0-sr of S
    399:   size(Q) qr x ncu
    400: */
    401: static PetscErrorCode PEPSTOARSupdate(PetscScalar *S,PetscInt ld,PetscInt sr,PetscInt s,PetscInt ncu,PetscInt qr,PetscScalar *Q,PetscInt ldq,PetscScalar *work,PetscInt nw)
    402: {
    404:   PetscScalar    a=1.0,b=0.0;
    405:   PetscBLASInt   sr_,ncu_,ldq_,lds_,qr_;
    406:   PetscInt       lwa,j,lds=2*ld;

    409:   lwa = sr*ncu;
    410:   if (!work||nw<lwa) {
    411:     if (nw<lwa) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid argument %d",10);
    412:     if (!work) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid argument %d",9);
    413:   }
    414:   PetscBLASIntCast(sr,&sr_);
    415:   PetscBLASIntCast(qr,&qr_);
    416:   PetscBLASIntCast(ncu,&ncu_);
    417:   PetscBLASIntCast(lds,&lds_);
    418:   PetscBLASIntCast(ldq,&ldq_);
    419:   PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&sr_,&ncu_,&qr_,&a,S,&lds_,Q,&ldq_,&b,work,&sr_));
    420:   for (j=0;j<ncu;j++) {
    421:     PetscMemcpy(S+lds*(s+j),work+j*sr,sr*sizeof(PetscScalar));
    422:   }
    423:   PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&sr_,&ncu_,&qr_,&a,S+ld,&lds_,Q,&ldq_,&b,work,&sr_));
    424:   for (j=0;j<ncu;j++) {
    425:     PetscMemcpy(S+lds*(s+j)+ld,work+j*sr,sr*sizeof(PetscScalar));
    426:   }
    427:   return(0);
    428: }

    430: #if 0
    433: static PetscErrorCode PEPSTOARpreKConvergence(PEP pep,PetscInt nv,PetscReal *norm,Vec *w)
    434: {
    436:   PEP_TOAR      *ctx = (PEP_TOAR*)pep->data;
    437:   PetscBLASInt   n_,one=1;
    438:   PetscInt       lds=2*ctx->ld;
    439:   PetscReal      t1,t2;
    440:   PetscScalar    *S=ctx->S;

    443:   PetscBLASIntCast(nv+2,&n_);
    444:   t1 = BLASnrm2_(&n_,S+nv*2*ctx->ld,&one);
    445:   t2 = BLASnrm2_(&n_,S+(nv*2+1)*ctx->ld,&one);
    446:   *norm = SlepcAbs(t1,t2);
    447:   BVSetActiveColumns(pep->V,0,nv+2);
    448:   BVMultVec(pep->V,1.0,0.0,w[1],S+nv*lds);
    449:   STMatMult(pep->st,0,w[1],w[2]);
    450:   VecNorm(w[2],NORM_2,&t1);
    451:   BVMultVec(pep->V,1.0,0.0,w[1],S+ctx->ld+nv*lds);
    452:   STMatMult(pep->st,2,w[1],w[2]);
    453:   VecNorm(w[2],NORM_2,&t2);
    454:   t2 *= pep->sfactor*pep->sfactor;
    455:   *norm = PetscMax(*norm,SlepcAbs(t1,t2));
    456:   return(0);
    457: }
    458: #endif

    462: PetscErrorCode PEPSolve_STOAR(PEP pep)
    463: {
    465:   PEP_TOAR      *ctx = (PEP_TOAR*)pep->data;
    466:   PetscInt       j,k,l,nv=0,ld=ctx->ld,lds=ctx->d*ctx->ld,off,ldds,t;
    467:   PetscInt       lwa,lrwa,nwu=0,nrwu=0,nconv=0;
    468:   PetscScalar    *S=ctx->S,*Q,*work;
    469:   PetscReal      beta,norm=1.0,*omega,*a,*b,*r,*rwork;
    470:   PetscBool      breakdown,symmlost=PETSC_FALSE,sinv;

    473:   BVSetMatrix(pep->V,NULL,PETSC_FALSE);
    474:   lwa = 9*ld*ld+5*ld;
    475:   lrwa = 8*ld;
    476:   PetscMalloc2(lwa,&work,lrwa,&rwork); /* REVIEW */
    477:   PetscObjectTypeCompare((PetscObject)pep->st,STSINVERT,&sinv);
    478:   RGSetScale(pep->rg,sinv?1.0/pep->sfactor:pep->sfactor);
    479:   STScaleShift(pep->st,sinv?pep->sfactor:1.0/pep->sfactor);

    481:   /* Restart loop */
    482:   l = 0;
    483:   DSGetLeadingDimension(pep->ds,&ldds);
    484:   while (pep->reason == PEP_CONVERGED_ITERATING) {
    485:     pep->its++;
    486:     DSGetArrayReal(pep->ds,DS_MAT_T,&a);
    487:     b = a+ldds;
    488:     r = b+ldds;
    489:     DSGetArrayReal(pep->ds,DS_MAT_D,&omega);
    490:
    491:     /* Compute an nv-step Lanczos factorization */
    492:     nv = PetscMin(pep->nconv+pep->mpd,pep->ncv);
    493:     PEPSTOARrun(pep,a,b,omega,pep->nconv+l,&nv,&breakdown,&symmlost,work+nwu,lwa-nwu,pep->work,3);
    494:     beta = b[nv-1];
    495:     if (symmlost) {
    496:       pep->reason = PEP_DIVERGED_SYMMETRY_LOST;
    497:       if (nv==pep->nconv+l+1) { pep->nconv = nconv; break; }
    498:     }
    499:     DSRestoreArrayReal(pep->ds,DS_MAT_T,&a);
    500:     DSRestoreArrayReal(pep->ds,DS_MAT_D,&omega);
    501:     DSSetDimensions(pep->ds,nv,0,pep->nconv,pep->nconv+l);
    502:     if (l==0) {
    503:       DSSetState(pep->ds,DS_STATE_INTERMEDIATE);
    504:     } else {
    505:       DSSetState(pep->ds,DS_STATE_RAW);
    506:     }

    508:     /* Solve projected problem */
    509:     DSSolve(pep->ds,pep->eigr,pep->eigi);
    510:     DSSort(pep->ds,pep->eigr,pep->eigi,NULL,NULL,NULL);

    512:     /* Check convergence */
    513:     /* PEPSTOARpreKConvergence(pep,nv,&norm,pep->work);*/
    514:     norm = 1.0;
    515:     DSGetDimensions(pep->ds,NULL,NULL,NULL,NULL,&t);
    516:     PEPKrylovConvergence(pep,PETSC_FALSE,pep->nconv,t-pep->nconv,PetscAbsReal(beta)*norm,&k);
    517:     nconv = k;
    518:     if (pep->its >= pep->max_it) pep->reason = PEP_DIVERGED_ITS;
    519:     if (k >= pep->nev) pep->reason = PEP_CONVERGED_TOL;

    521:     /* Update l */
    522:     if (pep->reason != PEP_CONVERGED_ITERATING || breakdown) l = 0;
    523:     else {
    524:       l = PetscMax(1,(PetscInt)((nv-k)/2));
    525:       l = PetscMin(l,t);
    526:       DSGetArrayReal(pep->ds,DS_MAT_T,&a);
    527:       if (*(a+ldds+k+l-1)!=0) {
    528:         if (k+l<nv-1) l = l+1;
    529:         else l = l-1;
    530:       }
    531:       DSRestoreArrayReal(pep->ds,DS_MAT_T,&a);
    532:     }
    533:     if (!ctx->lock && l>0) { l += k; k = 0; } /* non-locking variant: reset no. of converged pairs */

    535:     /* Update S */
    536:     off = pep->nconv*ldds;
    537:     DSGetArray(pep->ds,DS_MAT_Q,&Q);
    538:     PEPSTOARSupdate(S,ld,nv+2,pep->nconv,k+l-pep->nconv,nv,Q+off,ldds,work+nwu,lwa-nwu);
    539:     DSRestoreArray(pep->ds,DS_MAT_Q,&Q);

    541:     /* Copy last column of S */
    542:     PetscMemcpy(S+lds*(k+l),S+lds*nv,lds*sizeof(PetscScalar));

    544:     if (pep->reason == PEP_CONVERGED_ITERATING) {
    545:       if (breakdown) {
    546:         /* Stop if breakdown */
    547:         PetscInfo2(pep,"Breakdown STOAR method (it=%D norm=%g)\n",pep->its,(double)beta);
    548:         pep->reason = PEP_DIVERGED_BREAKDOWN;
    549:       } else {
    550:         /* Prepare the Rayleigh quotient for restart */
    551:         DSGetArray(pep->ds,DS_MAT_Q,&Q);
    552:         DSGetArrayReal(pep->ds,DS_MAT_T,&a);
    553:         DSGetArrayReal(pep->ds,DS_MAT_D,&omega);
    554:         r = a + 2*ldds;
    555:         for (j=k;j<k+l;j++) {
    556:           r[j] = PetscRealPart(Q[nv-1+j*ldds]*beta);
    557:         }
    558:         b = a+ldds;
    559:         b[k+l-1] = r[k+l-1];
    560:         omega[k+l] = omega[nv];
    561:         DSRestoreArray(pep->ds,DS_MAT_Q,&Q);
    562:         DSRestoreArrayReal(pep->ds,DS_MAT_T,&a);
    563:         DSRestoreArrayReal(pep->ds,DS_MAT_D,&omega);
    564:         /* Truncate S */
    565:         DSGetArrayReal(pep->ds,DS_MAT_D,&omega);
    566:         PEPSTOARTrunc(pep,nv+2,k+l+1,work+nwu,lwa-nwu,rwork+nrwu,lrwa-nrwu);
    567:         DSRestoreArrayReal(pep->ds,DS_MAT_D,&omega);
    568:       }
    569:     }

    572:     pep->nconv = k;
    573:     PEPMonitor(pep,pep->its,pep->nconv,pep->eigr,pep->eigi,pep->errest,nv);
    574:   }

    576:   if (pep->nconv>0) {
    577:     /* Truncate S */
    578:     DSGetArrayReal(pep->ds,DS_MAT_D,&omega);
    579:     PEPSTOARTrunc(pep,nv+2,pep->nconv,work+nwu,lwa-nwu,rwork+nrwu,lrwa-nrwu);
    580:     DSRestoreArrayReal(pep->ds,DS_MAT_D,&omega);
    581:
    582:     /* Extraction */
    583:     DSSetDimensions(pep->ds,pep->nconv,0,0,0);
    584:     DSSetState(pep->ds,DS_STATE_RAW);
    585:
    586:     for (j=0;j<pep->nconv;j++) {
    587:       pep->eigr[j] *= pep->sfactor;
    588:       pep->eigi[j] *= pep->sfactor;
    589:     }
    590:   }
    591:   STScaleShift(pep->st,sinv?1.0/pep->sfactor:pep->sfactor);
    592:   RGSetScale(pep->rg,1.0);

    594:   /* truncate Schur decomposition and change the state to raw so that
    595:      DSVectors() computes eigenvectors from scratch */
    596:   DSSetDimensions(pep->ds,pep->nconv,0,0,0);
    597:   DSSetState(pep->ds,DS_STATE_RAW);
    598:   PetscFree2(work,rwork);
    599:   return(0);
    600: }

    604: PetscErrorCode PEPSetFromOptions_STOAR(PetscOptions *PetscOptionsObject,PEP pep)
    605: {
    607:   PetscBool      flg,lock;

    610:   PetscOptionsHead(PetscOptionsObject,"PEP STOAR Options");
    611:   PetscOptionsBool("-pep_stoar_locking","Choose between locking and non-locking variants","PEPSTOARSetLocking",PETSC_FALSE,&lock,&flg);
    612:   if (flg) {
    613:     PEPSTOARSetLocking(pep,lock);
    614:   }
    615:   PetscOptionsTail();
    616:   return(0);
    617: }

    621: static PetscErrorCode PEPSTOARSetLocking_STOAR(PEP pep,PetscBool lock)
    622: {
    623:   PEP_TOAR *ctx = (PEP_TOAR*)pep->data;

    626:   ctx->lock = lock;
    627:   return(0);
    628: }

    632: /*@
    633:    PEPSTOARSetLocking - Choose between locking and non-locking variants of
    634:    the STOAR method.

    636:    Logically Collective on PEP

    638:    Input Parameters:
    639: +  pep  - the eigenproblem solver context
    640: -  lock - true if the locking variant must be selected

    642:    Options Database Key:
    643: .  -pep_stoar_locking - Sets the locking flag

    645:    Notes:
    646:    The default is to lock converged eigenpairs when the method restarts.
    647:    This behaviour can be changed so that all directions are kept in the
    648:    working subspace even if already converged to working accuracy (the
    649:    non-locking variant).

    651:    Level: advanced

    653: .seealso: PEPSTOARGetLocking()
    654: @*/
    655: PetscErrorCode PEPSTOARSetLocking(PEP pep,PetscBool lock)
    656: {

    662:   PetscTryMethod(pep,"PEPSTOARSetLocking_C",(PEP,PetscBool),(pep,lock));
    663:   return(0);
    664: }

    668: static PetscErrorCode PEPSTOARGetLocking_STOAR(PEP pep,PetscBool *lock)
    669: {
    670:   PEP_TOAR *ctx = (PEP_TOAR*)pep->data;

    673:   *lock = ctx->lock;
    674:   return(0);
    675: }

    679: /*@
    680:    PEPSTOARGetLocking - Gets the locking flag used in the STOAR method.

    682:    Not Collective

    684:    Input Parameter:
    685: .  pep - the eigenproblem solver context

    687:    Output Parameter:
    688: .  lock - the locking flag

    690:    Level: advanced

    692: .seealso: PEPSTOARSetLocking()
    693: @*/
    694: PetscErrorCode PEPSTOARGetLocking(PEP pep,PetscBool *lock)
    695: {

    701:   PetscTryMethod(pep,"PEPSTOARGetLocking_C",(PEP,PetscBool*),(pep,lock));
    702:   return(0);
    703: }

    707: PetscErrorCode PEPView_STOAR(PEP pep,PetscViewer viewer)
    708: {
    710:   PEP_TOAR      *ctx = (PEP_TOAR*)pep->data;
    711:   PetscBool      isascii;

    714:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii);
    715:   if (isascii) {
    716:     PetscViewerASCIIPrintf(viewer,"  STOAR: using the %slocking variant\n",ctx->lock?"":"non-");
    717:   }
    718:   return(0);
    719: }

    723: PetscErrorCode PEPDestroy_STOAR(PEP pep)
    724: {

    728:   PetscFree(pep->data);
    729:   PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARSetLocking_C",NULL);
    730:   PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARGetLocking_C",NULL);
    731:   return(0);
    732: }

    736: PETSC_EXTERN PetscErrorCode PEPCreate_STOAR(PEP pep)
    737: {
    739:   PEP_TOAR      *ctx;

    742:   PetscNewLog(pep,&ctx);
    743:   pep->data = (void*)ctx;
    744:   ctx->lock = PETSC_TRUE;

    746:   pep->ops->solve          = PEPSolve_STOAR;
    747:   pep->ops->setup          = PEPSetUp_STOAR;
    748:   pep->ops->setfromoptions = PEPSetFromOptions_STOAR;
    749:   pep->ops->view           = PEPView_STOAR;
    750:   pep->ops->destroy        = PEPDestroy_STOAR;
    751:   pep->ops->backtransform  = PEPBackTransform_Default;
    752:   pep->ops->computevectors = PEPComputeVectors_Default;
    753:   pep->ops->extractvectors = PEPExtractVectors_TOAR;
    754:   pep->ops->reset          = PEPReset_TOAR;
    755:   PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARSetLocking_C",PEPSTOARSetLocking_STOAR);
    756:   PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARGetLocking_C",PEPSTOARGetLocking_STOAR);
    757:   return(0);
    758: }