Date: 2016-03-29T14:56:53+00:00

Actual source code: dsghep.c
slepc-3.6.3 2016-03-29
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      1: /*
      2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
      4:    Copyright (c) 2002-2015, Universitat Politecnica de Valencia, Spain

      6:    This file is part of SLEPc.

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

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

     17:    You  should have received a copy of the GNU Lesser General  Public  License
     18:    along with SLEPc. If not, see <http://www.gnu.org/licenses/>.
     19:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     20: */

     22: #include <slepc/private/dsimpl.h>
     23: #include <slepcblaslapack.h>

     27: PetscErrorCode DSAllocate_GHEP(DS ds,PetscInt ld)
     28: {

     32:   DSAllocateMat_Private(ds,DS_MAT_A);
     33:   DSAllocateMat_Private(ds,DS_MAT_B);
     34:   DSAllocateMat_Private(ds,DS_MAT_Q);
     35:   PetscFree(ds->perm);
     36:   PetscMalloc1(ld,&ds->perm);
     37:   PetscLogObjectMemory((PetscObject)ds,ld*sizeof(PetscInt));
     38:   return(0);
     39: }

     43: PetscErrorCode DSView_GHEP(DS ds,PetscViewer viewer)
     44: {

     48:   DSViewMat(ds,viewer,DS_MAT_A);
     49:   DSViewMat(ds,viewer,DS_MAT_B);
     50:   if (ds->state>DS_STATE_INTERMEDIATE) {
     51:     DSViewMat(ds,viewer,DS_MAT_Q);
     52:   }
     53:   return(0);
     54: }

     58: PetscErrorCode DSVectors_GHEP(DS ds,DSMatType mat,PetscInt *j,PetscReal *rnorm)
     59: {
     60:   PetscScalar    *Q = ds->mat[DS_MAT_Q];
     61:   PetscInt       ld = ds->ld,i;

     65:   if (rnorm) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not implemented yet");
     66:   switch (mat) {
     67:     case DS_MAT_X:
     68:     case DS_MAT_Y:
     69:       if (j) {
     70:         if (ds->state>=DS_STATE_CONDENSED) {
     71:           PetscMemcpy(ds->mat[mat]+(*j)*ld,Q+(*j)*ld,ld*sizeof(PetscScalar));
     72:         } else {
     73:           PetscMemzero(ds->mat[mat]+(*j)*ld,ld*sizeof(PetscScalar));
     74:           *(ds->mat[mat]+(*j)+(*j)*ld) = 1.0;
     75:         }
     76:       } else {
     77:         if (ds->state>=DS_STATE_CONDENSED) {
     78:           PetscMemcpy(ds->mat[mat],Q,ld*ld*sizeof(PetscScalar));
     79:         } else {
     80:           PetscMemzero(ds->mat[mat],ld*ld*sizeof(PetscScalar));
     81:           for (i=0;i<ds->n;i++) *(ds->mat[mat]+i+i*ld) = 1.0;
     82:         }
     83:       }
     84:       break;
     85:     case DS_MAT_U:
     86:     case DS_MAT_VT:
     87:       SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not implemented yet");
     88:       break;
     89:     default:
     90:       SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_OUTOFRANGE,"Invalid mat parameter");
     91:   }
     92:   return(0);
     93: }

     97: PetscErrorCode DSNormalize_GHEP(DS ds,DSMatType mat,PetscInt col)
     98: {
    100:   PetscInt       i,i0,i1;
    101:   PetscBLASInt   ld,n,one = 1;
    102:   PetscScalar    norm,*x;

    105:   switch (mat) {
    106:     case DS_MAT_X:
    107:     case DS_MAT_Y:
    108:     case DS_MAT_Q:
    109:       break;
    110:     case DS_MAT_U:
    111:     case DS_MAT_VT:
    112:       SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not implemented yet");
    113:       break;
    114:     default:
    115:       SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_OUTOFRANGE,"Invalid mat parameter");
    116:   }
    117:   /* All the matrices resulting from DSVectors and DSSolve are B-normalized,
    118:      but function returns 2-normalized vectors. */
    119:   PetscBLASIntCast(ds->n,&n);
    120:   PetscBLASIntCast(ds->ld,&ld);
    121:   DSGetArray(ds,mat,&x);
    122:   if (col < 0) {
    123:     i0 = 0; i1 = ds->n;
    124:   } else {
    125:     i0 = col; i1 = col+1;
    126:   }
    127:   for (i=i0;i<i1;i++) {
    128:     norm = BLASnrm2_(&n,&x[ld*i],&one);
    129:     norm = 1.0/norm;
    130:     PetscStackCallBLAS("BLASscal",BLASscal_(&n,&norm,&x[ld*i],&one));
    131:   }
    132:   return(0);
    133: }

    137: PetscErrorCode DSSort_GHEP(DS ds,PetscScalar *wr,PetscScalar *wi,PetscScalar *rr,PetscScalar *ri,PetscInt *k)
    138: {
    140:   PetscInt       n,l,i,*perm,ld=ds->ld;
    141:   PetscScalar    *A;

    144:   if (!ds->sc) return(0);
    145:   n = ds->n;
    146:   l = ds->l;
    147:   A  = ds->mat[DS_MAT_A];
    148:   perm = ds->perm;
    149:   for (i=l;i<n;i++) wr[i] = A[i+i*ld];
    150:   if (rr) {
    151:     DSSortEigenvalues_Private(ds,rr,ri,perm,PETSC_FALSE);
    152:   } else {
    153:     DSSortEigenvalues_Private(ds,wr,NULL,perm,PETSC_FALSE);
    154:   }
    155:   for (i=l;i<n;i++) A[i+i*ld] = wr[perm[i]];
    156:   for (i=l;i<n;i++) wr[i] = A[i+i*ld];
    157:   DSPermuteColumns_Private(ds,l,n,DS_MAT_Q,perm);
    158:   return(0);
    159: }

    163: PetscErrorCode DSSolve_GHEP(DS ds,PetscScalar *wr,PetscScalar *wi)
    164: {
    165: #if defined(SLEPC_MISSING_LAPACK_SYGVD)
    167:   SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SYGVD - Lapack routine is unavailable");
    168: #else
    170:   PetscScalar    *work,*A,*B,*Q;
    171:   PetscBLASInt   itype = 1,*iwork,info,n1,liwork,ld,lrwork=0,lwork;
    172:   PetscInt       off,i;
    173: #if defined(PETSC_USE_COMPLEX)
    174:   PetscReal      *rwork,*rr;
    175: #endif

    178:   PetscBLASIntCast(ds->n-ds->l,&n1);
    179:   PetscBLASIntCast(ds->ld,&ld);
    180:   PetscBLASIntCast(5*ds->n+3,&liwork);
    181: #if defined(PETSC_USE_COMPLEX)
    182:   PetscBLASIntCast(ds->n*ds->n+2*ds->n,&lwork);
    183:   PetscBLASIntCast(2*ds->n*ds->n+5*ds->n+1+n1,&lrwork);
    184: #else
    185:   PetscBLASIntCast(2*ds->n*ds->n+6*ds->n+1,&lwork);
    186: #endif
    187:   DSAllocateWork_Private(ds,lwork,lrwork,liwork);
    188:   work = ds->work;
    189:   iwork = ds->iwork;
    190:   off = ds->l+ds->l*ld;
    191:   A = ds->mat[DS_MAT_A];
    192:   B = ds->mat[DS_MAT_B];
    193:   Q = ds->mat[DS_MAT_Q];
    194: #if defined(PETSC_USE_COMPLEX)
    195:   rr = ds->rwork;
    196:   rwork = ds->rwork + n1;
    197:   lrwork = ds->lrwork - n1;
    198:   PetscStackCallBLAS("LAPACKsygvd",LAPACKsygvd_(&itype,"V","U",&n1,A+off,&ld,B+off,&ld,rr,work,&lwork,rwork,&lrwork,iwork,&liwork,&info));
    199:   if (info) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in Lapack ZHEGVD %d",info);
    200:   for (i=0;i<n1;i++) wr[ds->l+i] = rr[i];
    201: #else
    202:   PetscStackCallBLAS("LAPACKsygvd",LAPACKsygvd_(&itype,"V","U",&n1,A+off,&ld,B+off,&ld,wr+ds->l,work,&lwork,iwork,&liwork,&info));
    203:   if (info) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in Lapack DSYGVD %d",info);
    204: #endif
    205:   PetscMemzero(Q+ds->l*ld,n1*ld*sizeof(PetscScalar));
    206:   for (i=ds->l;i<ds->n;i++) {
    207:     PetscMemcpy(Q+ds->l+i*ld,A+ds->l+i*ld,n1*sizeof(PetscScalar));
    208:   }
    209:   PetscMemzero(B+ds->l*ld,n1*ld*sizeof(PetscScalar));
    210:   PetscMemzero(A+ds->l*ld,n1*ld*sizeof(PetscScalar));
    211:   for (i=ds->l;i<ds->n;i++) {
    212:     if (wi) wi[i] = 0.0;
    213:     B[i+i*ld] = 1.0;
    214:     A[i+i*ld] = wr[i];
    215:   }
    216:   return(0);
    217: #endif
    218: }

    222: PETSC_EXTERN PetscErrorCode DSCreate_GHEP(DS ds)
    223: {
    225:   ds->ops->allocate      = DSAllocate_GHEP;
    226:   ds->ops->view          = DSView_GHEP;
    227:   ds->ops->vectors       = DSVectors_GHEP;
    228:   ds->ops->solve[0]      = DSSolve_GHEP;
    229:   ds->ops->sort          = DSSort_GHEP;
    230:   ds->ops->normalize     = DSNormalize_GHEP;
    231:   return(0);
    232: }