Actual source code: dspep.c
slepc-3.10.1 2018-10-23
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      1: /*
      2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
      4:    Copyright (c) 2002-2018, 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: */

     11: #include <slepc/private/dsimpl.h>       /*I "slepcds.h" I*/
     12: #include <slepcblaslapack.h>

     14: typedef struct {
     15:   PetscInt  d;              /* polynomial degree */
     16:   PetscReal *pbc;           /* polynomial basis coefficients */
     17: } DS_PEP;

     19: PetscErrorCode DSAllocate_PEP(DS ds,PetscInt ld)
     20: {
     22:   DS_PEP         *ctx = (DS_PEP*)ds->data;
     23:   PetscInt       i;

     26:   if (!ctx->d) SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_WRONGSTATE,"DSPEP requires specifying the polynomial degree via DSPEPSetDegree()");
     27:   DSAllocateMat_Private(ds,DS_MAT_X);
     28:   DSAllocateMat_Private(ds,DS_MAT_Y);
     29:   for (i=0;i<=ctx->d;i++) {
     30:     DSAllocateMat_Private(ds,DSMatExtra[i]);
     31:   }
     32:   PetscFree(ds->perm);
     33:   PetscMalloc1(ld*ctx->d,&ds->perm);
     34:   PetscLogObjectMemory((PetscObject)ds,ld*ctx->d*sizeof(PetscInt));
     35:   return(0);
     36: }

     38: PetscErrorCode DSView_PEP(DS ds,PetscViewer viewer)
     39: {
     40:   PetscErrorCode    ierr;
     41:   DS_PEP            *ctx = (DS_PEP*)ds->data;
     42:   PetscViewerFormat format;
     43:   PetscInt          i;

     46:   PetscViewerGetFormat(viewer,&format);
     47:   PetscViewerASCIIPrintf(viewer,"polynomial degree: %D\n",ctx->d);
     48:   if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) return(0);
     49:   for (i=0;i<=ctx->d;i++) {
     50:     DSViewMat(ds,viewer,DSMatExtra[i]);
     51:   }
     52:   if (ds->state>DS_STATE_INTERMEDIATE) {
     53:     DSViewMat(ds,viewer,DS_MAT_X);
     54:   }
     55:   return(0);
     56: }

     58: PetscErrorCode DSVectors_PEP(DS ds,DSMatType mat,PetscInt *j,PetscReal *rnorm)
     59: {
     61:   if (rnorm) SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_SUP,"Not implemented yet");
     62:   switch (mat) {
     63:     case DS_MAT_X:
     64:       break;
     65:     case DS_MAT_Y:
     66:       break;
     67:     default:
     68:       SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_OUTOFRANGE,"Invalid mat parameter");
     69:   }
     70:   return(0);
     71: }

     73: PetscErrorCode DSSort_PEP(DS ds,PetscScalar *wr,PetscScalar *wi,PetscScalar *rr,PetscScalar *ri,PetscInt *kout)
     74: {
     76:   DS_PEP         *ctx = (DS_PEP*)ds->data;
     77:   PetscInt       n,i,j,k,p,*perm,told,ld;
     78:   PetscScalar    *A,*X,*Y,rtmp,rtmp2;

     81:   if (!ds->sc) return(0);
     82:   n = ds->n*ctx->d;
     83:   A  = ds->mat[DS_MAT_A];
     84:   perm = ds->perm;
     85:   for (i=0;i<n;i++) perm[i] = i;
     86:   told = ds->t;
     87:   ds->t = n;  /* force the sorting routines to consider d*n eigenvalues */
     88:   if (rr) {
     89:     DSSortEigenvalues_Private(ds,rr,ri,perm,PETSC_FALSE);
     90:   } else {
     91:     DSSortEigenvalues_Private(ds,wr,wi,perm,PETSC_FALSE);
     92:   }
     93:   ds->t = told;  /* restore value of t */
     94:   for (i=0;i<n;i++) A[i]  = wr[perm[i]];
     95:   for (i=0;i<n;i++) wr[i] = A[i];
     96:   for (i=0;i<n;i++) A[i]  = wi[perm[i]];
     97:   for (i=0;i<n;i++) wi[i] = A[i];
     98:   /* cannot use DSPermuteColumns_Private() since matrix is not square */
     99:   ld = ds->ld;
    100:   X  = ds->mat[DS_MAT_X];
    101:   Y  = ds->mat[DS_MAT_Y];
    102:   for (i=0;i<n;i++) {
    103:     p = perm[i];
    104:     if (p != i) {
    105:       j = i + 1;
    106:       while (perm[j] != i) j++;
    107:       perm[j] = p; perm[i] = i;
    108:       /* swap columns i and j */
    109:       for (k=0;k<ds->n;k++) {
    110:         rtmp  = X[k+p*ld]; X[k+p*ld] = X[k+i*ld]; X[k+i*ld] = rtmp;
    111:         rtmp2 = Y[k+p*ld]; Y[k+p*ld] = Y[k+i*ld]; Y[k+i*ld] = rtmp2;
    112:       }
    113:     }
    114:   }
    115:   return(0);
    116: }

    118: PetscErrorCode DSSolve_PEP_QZ(DS ds,PetscScalar *wr,PetscScalar *wi)
    119: {
    120: #if defined(SLEPC_MISSING_LAPACK_GGEV)
    122:   SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GGEV - Lapack routine is unavailable");
    123: #else
    125:   DS_PEP         *ctx = (DS_PEP*)ds->data;
    126:   PetscInt       i,j,k,off;
    127:   PetscScalar    *A,*B,*W,*X,*U,*Y,*E,*work,*beta,norm;
    128:   PetscReal      *ca,*cb,*cg;
    129:   PetscBLASInt   info,n,ldd,nd,lrwork=0,lwork,one=1;
    130: #if defined(PETSC_USE_COMPLEX)
    131:   PetscReal      *rwork;
    132: #else
    133:   PetscScalar    norm0;
    134: #endif

    137:   if (!ds->mat[DS_MAT_A]) {
    138:     DSAllocateMat_Private(ds,DS_MAT_A);
    139:   }
    140:   if (!ds->mat[DS_MAT_B]) {
    141:     DSAllocateMat_Private(ds,DS_MAT_B);
    142:   }
    143:   if (!ds->mat[DS_MAT_W]) {
    144:     DSAllocateMat_Private(ds,DS_MAT_W);
    145:   }
    146:   if (!ds->mat[DS_MAT_U]) {
    147:     DSAllocateMat_Private(ds,DS_MAT_U);
    148:   }
    149:   PetscBLASIntCast(ds->n*ctx->d,&nd);
    150:   PetscBLASIntCast(ds->n,&n);
    151:   PetscBLASIntCast(ds->ld*ctx->d,&ldd);
    152: #if defined(PETSC_USE_COMPLEX)
    153:   PetscBLASIntCast(nd+2*nd,&lwork);
    154:   PetscBLASIntCast(8*nd,&lrwork);
    155: #else
    156:   PetscBLASIntCast(nd+8*nd,&lwork);
    157: #endif
    158:   DSAllocateWork_Private(ds,lwork,lrwork,0);
    159:   beta = ds->work;
    160:   work = ds->work + nd;
    161:   lwork -= nd;
    162:   A = ds->mat[DS_MAT_A];
    163:   B = ds->mat[DS_MAT_B];
    164:   W = ds->mat[DS_MAT_W];
    165:   U = ds->mat[DS_MAT_U];
    166:   X = ds->mat[DS_MAT_X];
    167:   Y = ds->mat[DS_MAT_Y];
    168:   E = ds->mat[DSMatExtra[ctx->d]];

    170:   /* build matrices A and B of the linearization */
    171:   PetscMemzero(A,ldd*ldd*sizeof(PetscScalar));
    172:   if (!ctx->pbc) { /* monomial basis */
    173:     for (i=0;i<nd-ds->n;i++) A[i+(i+ds->n)*ldd] = 1.0;
    174:     for (i=0;i<ctx->d;i++) {
    175:       off = i*ds->n*ldd+(ctx->d-1)*ds->n;
    176:       for (j=0;j<ds->n;j++) {
    177:         PetscMemcpy(A+off+j*ldd,ds->mat[DSMatExtra[i]]+j*ds->ld,ds->n*sizeof(PetscScalar));
    178:       }
    179:     }
    180:   } else {
    181:     ca = ctx->pbc;
    182:     cb = ca+ctx->d+1;
    183:     cg = cb+ctx->d+1;
    184:     for (i=0;i<ds->n;i++) {
    185:       A[i+(i+ds->n)*ldd] = ca[0];
    186:       A[i+i*ldd] = cb[0];
    187:     }
    188:     for (;i<nd-ds->n;i++) {
    189:       j = i/ds->n;
    190:       A[i+(i+ds->n)*ldd] = ca[j];
    191:       A[i+i*ldd] = cb[j];
    192:       A[i+(i-ds->n)*ldd] = cg[j];
    193:     }
    194:     for (i=0;i<ctx->d-2;i++) {
    195:       off = i*ds->n*ldd+(ctx->d-1)*ds->n;
    196:       for (j=0;j<ds->n;j++)
    197:         for (k=0;k<ds->n;k++)
    198:           *(A+off+j*ldd+k) = *(ds->mat[DSMatExtra[i]]+j*ds->ld+k)*ca[ctx->d-1];
    199:     }
    200:     off = i*ds->n*ldd+(ctx->d-1)*ds->n;
    201:     for (j=0;j<ds->n;j++)
    202:       for (k=0;k<ds->n;k++)
    203:         *(A+off+j*ldd+k) = *(ds->mat[DSMatExtra[i]]+j*ds->ld+k)*ca[ctx->d-1]-E[j*ds->ld+k]*cg[ctx->d-1];
    204:     off = (++i)*ds->n*ldd+(ctx->d-1)*ds->n;
    205:     for (j=0;j<ds->n;j++)
    206:       for (k=0;k<ds->n;k++)
    207:         *(A+off+j*ldd+k) = *(ds->mat[DSMatExtra[i]]+j*ds->ld+k)*ca[ctx->d-1]-E[j*ds->ld+k]*cb[ctx->d-1];
    208:   }
    209:   PetscMemzero(B,ldd*ldd*sizeof(PetscScalar));
    210:   for (i=0;i<nd-ds->n;i++) B[i+i*ldd] = 1.0;
    211:   off = (ctx->d-1)*ds->n*(ldd+1);
    212:   for (j=0;j<ds->n;j++) {
    213:     for (i=0;i<ds->n;i++) B[off+i+j*ldd] = -E[i+j*ds->ld];
    214:   }

    216:   /* solve generalized eigenproblem */
    217: #if defined(PETSC_USE_COMPLEX)
    218:   rwork = ds->rwork;
    219:   PetscStackCallBLAS("LAPACKggev",LAPACKggev_("V","V",&nd,A,&ldd,B,&ldd,wr,beta,U,&ldd,W,&ldd,work,&lwork,rwork,&info));
    220: #else
    221:   PetscStackCallBLAS("LAPACKggev",LAPACKggev_("V","V",&nd,A,&ldd,B,&ldd,wr,wi,beta,U,&ldd,W,&ldd,work,&lwork,&info));
    222: #endif
    223:   SlepcCheckLapackInfo("ggev",info);

    225:   /* copy eigenvalues */
    226:   for (i=0;i<nd;i++) {
    227:     if (beta[i]==0.0) wr[i] = (PetscRealPart(wr[i])>0.0)? PETSC_MAX_REAL: PETSC_MIN_REAL;
    228:     else wr[i] /= beta[i];
    229: #if !defined(PETSC_USE_COMPLEX)
    230:     if (beta[i]==0.0) wi[i] = 0.0;
    231:     else wi[i] /= beta[i];
    232: #else
    233:     if (wi) wi[i] = 0.0;
    234: #endif
    235:   }

    237:   /* copy and normalize eigenvectors */
    238:   for (j=0;j<nd;j++) {
    239:     PetscMemcpy(X+j*ds->ld,W+j*ldd,ds->n*sizeof(PetscScalar));
    240:     PetscMemcpy(Y+j*ds->ld,U+ds->n*(ctx->d-1)+j*ldd,ds->n*sizeof(PetscScalar));
    241:   }
    242:   for (j=0;j<nd;j++) {
    243: #if !defined(PETSC_USE_COMPLEX)
    244:     if (wi[j] != 0.0) {
    245:       norm = BLASnrm2_(&n,X+j*ds->ld,&one);
    246:       norm0 = BLASnrm2_(&n,X+(j+1)*ds->ld,&one);
    247:       norm = 1.0/SlepcAbsEigenvalue(norm,norm0);
    248:       PetscStackCallBLAS("BLASscal",BLASscal_(&n,&norm,X+j*ds->ld,&one));
    249:       PetscStackCallBLAS("BLASscal",BLASscal_(&n,&norm,X+(j+1)*ds->ld,&one));
    250:       norm = BLASnrm2_(&n,Y+j*ds->ld,&one);
    251:       norm0 = BLASnrm2_(&n,Y+(j+1)*ds->ld,&one);
    252:       norm = 1.0/SlepcAbsEigenvalue(norm,norm0);
    253:       PetscStackCallBLAS("BLASscal",BLASscal_(&n,&norm,Y+j*ds->ld,&one));
    254:       PetscStackCallBLAS("BLASscal",BLASscal_(&n,&norm,Y+(j+1)*ds->ld,&one));
    255:       j++;
    256:     } else
    257: #endif
    258:     {
    259:       norm = 1.0/BLASnrm2_(&n,X+j*ds->ld,&one);
    260:       PetscStackCallBLAS("BLASscal",BLASscal_(&n,&norm,X+j*ds->ld,&one));
    261:       norm = 1.0/BLASnrm2_(&n,Y+j*ds->ld,&one);
    262:       PetscStackCallBLAS("BLASscal",BLASscal_(&n,&norm,Y+j*ds->ld,&one));
    263:     }
    264:   }
    265:   return(0);
    266: #endif
    267: }

    269: PetscErrorCode DSSynchronize_PEP(DS ds,PetscScalar eigr[],PetscScalar eigi[])
    270: {
    272:   DS_PEP         *ctx = (DS_PEP*)ds->data;
    273:   PetscInt       ld=ds->ld,k=0;
    274:   PetscMPIInt    ldnd,rank,off=0,size,dn;

    277:   if (ds->state>=DS_STATE_CONDENSED) k += 2*ctx->d*ds->n*ld;
    278:   if (eigr) k += ctx->d*ds->n;
    279:   if (eigi) k += ctx->d*ds->n;
    280:   DSAllocateWork_Private(ds,k,0,0);
    281:   PetscMPIIntCast(k*sizeof(PetscScalar),&size);
    282:   PetscMPIIntCast(ds->n*ctx->d*ld,&ldnd);
    283:   PetscMPIIntCast(ctx->d*ds->n,&dn);
    284:   MPI_Comm_rank(PetscObjectComm((PetscObject)ds),&rank);
    285:   if (!rank) {
    286:     if (ds->state>=DS_STATE_CONDENSED) {
    287:       MPI_Pack(ds->mat[DS_MAT_X],ldnd,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds));
    288:       MPI_Pack(ds->mat[DS_MAT_Y],ldnd,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds));
    289:     }
    290:     if (eigr) {
    291:       MPI_Pack(eigr,dn,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds));
    292:     }
    293:     if (eigi) {
    294:       MPI_Pack(eigi,dn,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds));
    295:     }
    296:   }
    297:   MPI_Bcast(ds->work,size,MPI_BYTE,0,PetscObjectComm((PetscObject)ds));
    298:   if (rank) {
    299:     if (ds->state>=DS_STATE_CONDENSED) {
    300:       MPI_Unpack(ds->work,size,&off,ds->mat[DS_MAT_X],ldnd,MPIU_SCALAR,PetscObjectComm((PetscObject)ds));
    301:       MPI_Unpack(ds->work,size,&off,ds->mat[DS_MAT_Y],ldnd,MPIU_SCALAR,PetscObjectComm((PetscObject)ds));
    302:     }
    303:     if (eigr) {
    304:       MPI_Unpack(ds->work,size,&off,eigr,dn,MPIU_SCALAR,PetscObjectComm((PetscObject)ds));
    305:     }
    306:     if (eigi) {
    307:       MPI_Unpack(ds->work,size,&off,eigi,dn,MPIU_SCALAR,PetscObjectComm((PetscObject)ds));
    308:     }
    309:   }
    310:   return(0);
    311: }

    313: static PetscErrorCode DSPEPSetDegree_PEP(DS ds,PetscInt d)
    314: {
    315:   DS_PEP *ctx = (DS_PEP*)ds->data;

    318:   if (d<0) SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_OUTOFRANGE,"The degree must be a non-negative integer");
    319:   if (d>=DS_NUM_EXTRA) SETERRQ1(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_OUTOFRANGE,"Only implemented for polynomials of degree at most %D",DS_NUM_EXTRA-1);
    320:   ctx->d = d;
    321:   return(0);
    322: }

    324: /*@
    325:    DSPEPSetDegree - Sets the polynomial degree for a DSPEP.

    327:    Logically Collective on DS

    329:    Input Parameters:
    330: +  ds - the direct solver context
    331: -  d  - the degree

    333:    Level: intermediate

    335: .seealso: DSPEPGetDegree()
    336: @*/
    337: PetscErrorCode DSPEPSetDegree(DS ds,PetscInt d)
    338: {

    344:   PetscTryMethod(ds,"DSPEPSetDegree_C",(DS,PetscInt),(ds,d));
    345:   return(0);
    346: }

    348: static PetscErrorCode DSPEPGetDegree_PEP(DS ds,PetscInt *d)
    349: {
    350:   DS_PEP *ctx = (DS_PEP*)ds->data;

    353:   *d = ctx->d;
    354:   return(0);
    355: }

    357: /*@
    358:    DSPEPGetDegree - Returns the polynomial degree for a DSPEP.

    360:    Not collective

    362:    Input Parameter:
    363: .  ds - the direct solver context

    365:    Output Parameters:
    366: .  d - the degree

    368:    Level: intermediate

    370: .seealso: DSPEPSetDegree()
    371: @*/
    372: PetscErrorCode DSPEPGetDegree(DS ds,PetscInt *d)
    373: {

    379:   PetscUseMethod(ds,"DSPEPGetDegree_C",(DS,PetscInt*),(ds,d));
    380:   return(0);
    381: }

    383: static PetscErrorCode DSPEPSetCoefficients_PEP(DS ds,PetscReal *pbc)
    384: {
    386:   DS_PEP         *ctx = (DS_PEP*)ds->data;
    387:   PetscInt       i;

    390:   if (!ctx->d) SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_WRONGSTATE,"Must first specify the polynomial degree via DSPEPSetDegree()");
    391:   if (ctx->pbc) { PetscFree(ctx->pbc); }
    392:   PetscMalloc1(3*(ctx->d+1),&ctx->pbc);
    393:   for (i=0;i<3*(ctx->d+1);i++) ctx->pbc[i] = pbc[i];
    394:   ds->state = DS_STATE_RAW;
    395:   return(0);
    396: }

    398: /*@C
    399:    DSPEPSetCoefficients - Sets the polynomial basis coefficients for a DSPEP.

    401:    Logically Collective on DS

    403:    Input Parameters:
    404: +  ds  - the direct solver context
    405: -  pbc - the polynomial basis coefficients

    407:    Notes:
    408:    This function is required only in the case of a polynomial specified in a
    409:    non-monomial basis, to provide the coefficients that will be used
    410:    during the linearization, multiplying the identity blocks on the three main
    411:    diagonal blocks. Depending on the polynomial basis (Chebyshev, Legendre, ...)
    412:    the coefficients must be different.

    414:    There must be a total of 3*(d+1) coefficients, where d is the degree of the
    415:    polynomial. The coefficients are arranged in three groups: alpha, beta, and
    416:    gamma, according to the definition of the three-term recurrence. In the case
    417:    of the monomial basis, alpha=1 and beta=gamma=0, in which case it is not
    418:    necessary to invoke this function.

    420:    Level: advanced

    422: .seealso: DSPEPGetCoefficients(), DSPEPSetDegree()
    423: @*/
    424: PetscErrorCode DSPEPSetCoefficients(DS ds,PetscReal *pbc)
    425: {

    430:   PetscTryMethod(ds,"DSPEPSetCoefficients_C",(DS,PetscReal*),(ds,pbc));
    431:   return(0);
    432: }

    434: static PetscErrorCode DSPEPGetCoefficients_PEP(DS ds,PetscReal **pbc)
    435: {
    437:   DS_PEP         *ctx = (DS_PEP*)ds->data;
    438:   PetscInt       i;

    441:   if (!ctx->d) SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_WRONGSTATE,"Must first specify the polynomial degree via DSPEPSetDegree()");
    442:   PetscCalloc1(3*(ctx->d+1),pbc);
    443:   if (ctx->pbc) for (i=0;i<3*(ctx->d+1);i++) (*pbc)[i] = ctx->pbc[i];
    444:   else for (i=0;i<ctx->d+1;i++) (*pbc)[i] = 1.0;
    445:   return(0);
    446: }

    448: /*@C
    449:    DSPEPGetCoefficients - Returns the polynomial basis coefficients for a DSPEP.

    451:    Not collective

    453:    Input Parameter:
    454: .  ds - the direct solver context

    456:    Output Parameters:
    457: .  pbc - the polynomial basis coefficients

    459:    Note:
    460:    The returned array has length 3*(d+1) and should be freed by the user.

    462:    Fortran Note:
    463:    The calling sequence from Fortran is
    464: .vb
    465:    DSPEPGetCoefficients(eps,pbc,ierr)
    466:    double precision pbc(d+1) output
    467: .ve

    469:    Level: advanced

    471: .seealso: DSPEPSetCoefficients()
    472: @*/
    473: PetscErrorCode DSPEPGetCoefficients(DS ds,PetscReal **pbc)
    474: {

    480:   PetscUseMethod(ds,"DSPEPGetCoefficients_C",(DS,PetscReal**),(ds,pbc));
    481:   return(0);
    482: }

    484: PetscErrorCode DSDestroy_PEP(DS ds)
    485: {
    487:   DS_PEP         *ctx = (DS_PEP*)ds->data;

    490:   if (ctx->pbc) { PetscFree(ctx->pbc); }
    491:   PetscFree(ds->data);
    492:   PetscObjectComposeFunction((PetscObject)ds,"DSPEPSetDegree_C",NULL);
    493:   PetscObjectComposeFunction((PetscObject)ds,"DSPEPGetDegree_C",NULL);
    494:   PetscObjectComposeFunction((PetscObject)ds,"DSPEPSetCoefficients_C",NULL);
    495:   PetscObjectComposeFunction((PetscObject)ds,"DSPEPGetCoefficients_C",NULL);
    496:   return(0);
    497: }

    499: PetscErrorCode DSMatGetSize_PEP(DS ds,DSMatType t,PetscInt *rows,PetscInt *cols)
    500: {
    501:   DS_PEP *ctx = (DS_PEP*)ds->data;

    504:   if (!ctx->d) SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_WRONGSTATE,"DSPEP requires specifying the polynomial degree via DSPEPSetDegree()");
    505:   *rows = ds->n;
    506:   if (t==DS_MAT_A || t==DS_MAT_B || t==DS_MAT_W || t==DS_MAT_U) *rows *= ctx->d;
    507:   *cols = ds->n;
    508:   if (t==DS_MAT_A || t==DS_MAT_B || t==DS_MAT_W || t==DS_MAT_U || t==DS_MAT_X || t==DS_MAT_Y) *cols *= ctx->d;
    509:   return(0);
    510: }

    512: PETSC_EXTERN PetscErrorCode DSCreate_PEP(DS ds)
    513: {
    514:   DS_PEP         *ctx;

    518:   PetscNewLog(ds,&ctx);
    519:   ds->data = (void*)ctx;

    521:   ds->ops->allocate      = DSAllocate_PEP;
    522:   ds->ops->view          = DSView_PEP;
    523:   ds->ops->vectors       = DSVectors_PEP;
    524:   ds->ops->solve[0]      = DSSolve_PEP_QZ;
    525:   ds->ops->sort          = DSSort_PEP;
    526:   ds->ops->synchronize   = DSSynchronize_PEP;
    527:   ds->ops->destroy       = DSDestroy_PEP;
    528:   ds->ops->matgetsize    = DSMatGetSize_PEP;
    529:   PetscObjectComposeFunction((PetscObject)ds,"DSPEPSetDegree_C",DSPEPSetDegree_PEP);
    530:   PetscObjectComposeFunction((PetscObject)ds,"DSPEPGetDegree_C",DSPEPGetDegree_PEP);
    531:   PetscObjectComposeFunction((PetscObject)ds,"DSPEPSetCoefficients_C",DSPEPSetCoefficients_PEP);
    532:   PetscObjectComposeFunction((PetscObject)ds,"DSPEPGetCoefficients_C",DSPEPGetCoefficients_PEP);
    533:   return(0);
    534: }