Actual source code: dsghep.c

slepc-main 2024-11-15
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  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: */

 11: #include <slepc/private/dsimpl.h>
 12: #include <slepcblaslapack.h>

 14: static PetscErrorCode DSAllocate_GHEP(DS ds,PetscInt ld)
 15: {
 16:   PetscFunctionBegin;
 17:   PetscCall(DSAllocateMat_Private(ds,DS_MAT_A));
 18:   PetscCall(DSAllocateMat_Private(ds,DS_MAT_B));
 19:   PetscCall(DSAllocateMat_Private(ds,DS_MAT_Q));
 20:   PetscCall(PetscFree(ds->perm));
 21:   PetscCall(PetscMalloc1(ld,&ds->perm));
 22:   PetscFunctionReturn(PETSC_SUCCESS);
 23: }

 25: static PetscErrorCode DSView_GHEP(DS ds,PetscViewer viewer)
 26: {
 27:   PetscViewerFormat format;

 29:   PetscFunctionBegin;
 30:   PetscCall(PetscViewerGetFormat(viewer,&format));
 31:   if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) PetscFunctionReturn(PETSC_SUCCESS);
 32:   PetscCall(DSViewMat(ds,viewer,DS_MAT_A));
 33:   PetscCall(DSViewMat(ds,viewer,DS_MAT_B));
 34:   if (ds->state>DS_STATE_INTERMEDIATE) PetscCall(DSViewMat(ds,viewer,DS_MAT_Q));
 35:   if (ds->omat[DS_MAT_X]) PetscCall(DSViewMat(ds,viewer,DS_MAT_X));
 36:   PetscFunctionReturn(PETSC_SUCCESS);
 37: }

 39: static PetscErrorCode DSVectors_GHEP(DS ds,DSMatType mat,PetscInt *j,PetscReal *rnorm)
 40: {
 41:   PetscScalar       *Z;
 42:   const PetscScalar *Q;
 43:   PetscInt          ld = ds->ld;

 45:   PetscFunctionBegin;
 46:   PetscCheck(!rnorm,PetscObjectComm((PetscObject)ds),PETSC_ERR_SUP,"Not implemented yet");
 47:   switch (mat) {
 48:     case DS_MAT_X:
 49:     case DS_MAT_Y:
 50:       if (j) {
 51:         PetscCall(MatDenseGetArray(ds->omat[mat],&Z));
 52:         if (ds->state>=DS_STATE_CONDENSED) {
 53:           PetscCall(MatDenseGetArrayRead(ds->omat[DS_MAT_Q],&Q));
 54:           PetscCall(PetscArraycpy(Z+(*j)*ld,Q+(*j)*ld,ld));
 55:           PetscCall(MatDenseRestoreArrayRead(ds->omat[DS_MAT_Q],&Q));
 56:         } else {
 57:           PetscCall(PetscArrayzero(Z+(*j)*ld,ld));
 58:           Z[(*j)+(*j)*ld] = 1.0;
 59:         }
 60:         PetscCall(MatDenseRestoreArray(ds->omat[mat],&Z));
 61:       } else {
 62:         if (ds->state>=DS_STATE_CONDENSED) PetscCall(MatCopy(ds->omat[DS_MAT_Q],ds->omat[mat],SAME_NONZERO_PATTERN));
 63:         else PetscCall(DSSetIdentity(ds,mat));
 64:       }
 65:       break;
 66:     case DS_MAT_U:
 67:     case DS_MAT_V:
 68:       SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_SUP,"Not implemented yet");
 69:     default:
 70:       SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_OUTOFRANGE,"Invalid mat parameter");
 71:   }
 72:   PetscFunctionReturn(PETSC_SUCCESS);
 73: }

 75: static PetscErrorCode DSSort_GHEP(DS ds,PetscScalar *wr,PetscScalar *wi,PetscScalar *rr,PetscScalar *ri,PetscInt *k)
 76: {
 77:   PetscInt       n,l,i,*perm,ld=ds->ld;
 78:   PetscScalar    *A;

 80:   PetscFunctionBegin;
 81:   if (!ds->sc) PetscFunctionReturn(PETSC_SUCCESS);
 82:   n = ds->n;
 83:   l = ds->l;
 84:   PetscCall(MatDenseGetArray(ds->omat[DS_MAT_A],&A));
 85:   perm = ds->perm;
 86:   for (i=l;i<n;i++) wr[i] = A[i+i*ld];
 87:   if (rr) PetscCall(DSSortEigenvalues_Private(ds,rr,ri,perm,PETSC_FALSE));
 88:   else PetscCall(DSSortEigenvalues_Private(ds,wr,NULL,perm,PETSC_FALSE));
 89:   for (i=l;i<n;i++) A[i+i*ld] = wr[perm[i]];
 90:   for (i=l;i<n;i++) wr[i] = A[i+i*ld];
 91:   PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_A],&A));
 92:   PetscCall(DSPermuteColumns_Private(ds,l,n,n,DS_MAT_Q,perm));
 93:   PetscFunctionReturn(PETSC_SUCCESS);
 94: }

 96: static PetscErrorCode DSSolve_GHEP(DS ds,PetscScalar *wr,PetscScalar *wi)
 97: {
 98:   PetscScalar    *work,*A,*B,*Q;
 99:   PetscBLASInt   itype = 1,*iwork,info,n1,liwork,ld,lrwork=0,lwork;
100:   PetscInt       off,i;
101: #if defined(PETSC_USE_COMPLEX)
102:   PetscReal      *rwork,*rr;
103: #endif

105:   PetscFunctionBegin;
106:   PetscCall(PetscBLASIntCast(ds->n-ds->l,&n1));
107:   PetscCall(PetscBLASIntCast(ds->ld,&ld));
108:   PetscCall(PetscBLASIntCast(5*ds->n+3,&liwork));
109: #if defined(PETSC_USE_COMPLEX)
110:   PetscCall(PetscBLASIntCast(ds->n*ds->n+2*ds->n,&lwork));
111:   PetscCall(PetscBLASIntCast(2*ds->n*ds->n+5*ds->n+1+n1,&lrwork));
112: #else
113:   PetscCall(PetscBLASIntCast(2*ds->n*ds->n+6*ds->n+1,&lwork));
114: #endif
115:   PetscCall(DSAllocateWork_Private(ds,lwork,lrwork,liwork));
116:   work = ds->work;
117:   iwork = ds->iwork;
118:   off = ds->l+ds->l*ld;
119:   PetscCall(MatDenseGetArray(ds->omat[DS_MAT_A],&A));
120:   PetscCall(MatDenseGetArray(ds->omat[DS_MAT_B],&B));
121:   PetscCall(MatDenseGetArray(ds->omat[DS_MAT_Q],&Q));
122: #if defined(PETSC_USE_COMPLEX)
123:   rr = ds->rwork;
124:   rwork = ds->rwork+n1;
125:   PetscCall(PetscBLASIntCast(ds->lrwork-n1,&lrwork));
126:   PetscCallBLAS("LAPACKsygvd",LAPACKsygvd_(&itype,"V","U",&n1,A+off,&ld,B+off,&ld,rr,work,&lwork,rwork,&lrwork,iwork,&liwork,&info));
127:   for (i=0;i<n1;i++) wr[ds->l+i] = rr[i];
128: #else
129:   PetscCallBLAS("LAPACKsygvd",LAPACKsygvd_(&itype,"V","U",&n1,A+off,&ld,B+off,&ld,wr+ds->l,work,&lwork,iwork,&liwork,&info));
130: #endif
131:   SlepcCheckLapackInfo("sygvd",info);
132:   PetscCall(PetscArrayzero(Q+ds->l*ld,n1*ld));
133:   for (i=ds->l;i<ds->n;i++) PetscCall(PetscArraycpy(Q+ds->l+i*ld,A+ds->l+i*ld,n1));
134:   PetscCall(PetscArrayzero(B+ds->l*ld,n1*ld));
135:   PetscCall(PetscArrayzero(A+ds->l*ld,n1*ld));
136:   for (i=ds->l;i<ds->n;i++) {
137:     if (wi) wi[i] = 0.0;
138:     B[i+i*ld] = 1.0;
139:     A[i+i*ld] = wr[i];
140:   }
141:   PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_A],&A));
142:   PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_B],&B));
143:   PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_Q],&Q));
144:   PetscFunctionReturn(PETSC_SUCCESS);
145: }

147: #if !defined(PETSC_HAVE_MPIUNI)
148: static PetscErrorCode DSSynchronize_GHEP(DS ds,PetscScalar eigr[],PetscScalar eigi[])
149: {
150:   PetscScalar    *A,*B,*Q;
151:   PetscInt       ld=ds->ld,l=ds->l,k;
152:   PetscMPIInt    n,rank,off=0,size,ldn;

154:   PetscFunctionBegin;
155:   k = 2*(ds->n-l)*ld;
156:   if (ds->state>DS_STATE_RAW) k += (ds->n-l)*ld;
157:   if (eigr) k += (ds->n-l);
158:   PetscCall(DSAllocateWork_Private(ds,k,0,0));
159:   PetscCall(PetscMPIIntCast(k*sizeof(PetscScalar),&size));
160:   PetscCall(PetscMPIIntCast(ds->n-l,&n));
161:   PetscCall(PetscMPIIntCast(ld*(ds->n-l),&ldn));
162:   PetscCall(MatDenseGetArray(ds->omat[DS_MAT_A],&A));
163:   PetscCall(MatDenseGetArray(ds->omat[DS_MAT_B],&B));
164:   if (ds->state>DS_STATE_RAW) PetscCall(MatDenseGetArray(ds->omat[DS_MAT_Q],&Q));
165:   PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)ds),&rank));
166:   if (!rank) {
167:     PetscCallMPI(MPI_Pack(A+l*ld,ldn,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds)));
168:     PetscCallMPI(MPI_Pack(B+l*ld,ldn,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds)));
169:     if (ds->state>DS_STATE_RAW) PetscCallMPI(MPI_Pack(Q+l*ld,ldn,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds)));
170:     if (eigr) PetscCallMPI(MPI_Pack(eigr+l,n,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds)));
171:   }
172:   PetscCallMPI(MPI_Bcast(ds->work,size,MPI_BYTE,0,PetscObjectComm((PetscObject)ds)));
173:   if (rank) {
174:     PetscCallMPI(MPI_Unpack(ds->work,size,&off,A+l*ld,ldn,MPIU_SCALAR,PetscObjectComm((PetscObject)ds)));
175:     PetscCallMPI(MPI_Unpack(ds->work,size,&off,B+l*ld,ldn,MPIU_SCALAR,PetscObjectComm((PetscObject)ds)));
176:     if (ds->state>DS_STATE_RAW) PetscCallMPI(MPI_Unpack(ds->work,size,&off,Q+l*ld,ldn,MPIU_SCALAR,PetscObjectComm((PetscObject)ds)));
177:     if (eigr) PetscCallMPI(MPI_Unpack(ds->work,size,&off,eigr+l,n,MPIU_SCALAR,PetscObjectComm((PetscObject)ds)));
178:   }
179:   PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_A],&A));
180:   PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_B],&B));
181:   if (ds->state>DS_STATE_RAW) PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_Q],&Q));
182:   PetscFunctionReturn(PETSC_SUCCESS);
183: }
184: #endif

186: static PetscErrorCode DSHermitian_GHEP(DS ds,DSMatType m,PetscBool *flg)
187: {
188:   PetscFunctionBegin;
189:   if (m==DS_MAT_A || m==DS_MAT_B) *flg = PETSC_TRUE;
190:   else *flg = PETSC_FALSE;
191:   PetscFunctionReturn(PETSC_SUCCESS);
192: }

194: /*MC
195:    DSGHEP - Dense Generalized Hermitian Eigenvalue Problem.

197:    Level: beginner

199:    Notes:
200:    The problem is expressed as A*X = B*X*Lambda, where both A and B are
201:    real symmetric (or complex Hermitian) and B is positive-definite. Lambda
202:    is a diagonal matrix whose diagonal elements are the arguments of DSSolve().
203:    After solve, A is overwritten with Lambda, and B is overwritten with I.

205:    No intermediate state is implemented, nor compact storage.

207:    Used DS matrices:
208: +  DS_MAT_A - first problem matrix
209: .  DS_MAT_B - second problem matrix
210: -  DS_MAT_Q - matrix of B-orthogonal eigenvectors, which is equal to X

212:    Implemented methods:
213: .  0 - Divide and Conquer (_sygvd)

215: .seealso: DSCreate(), DSSetType(), DSType
216: M*/
217: SLEPC_EXTERN PetscErrorCode DSCreate_GHEP(DS ds)
218: {
219:   PetscFunctionBegin;
220:   ds->ops->allocate      = DSAllocate_GHEP;
221:   ds->ops->view          = DSView_GHEP;
222:   ds->ops->vectors       = DSVectors_GHEP;
223:   ds->ops->solve[0]      = DSSolve_GHEP;
224:   ds->ops->sort          = DSSort_GHEP;
225: #if !defined(PETSC_HAVE_MPIUNI)
226:   ds->ops->synchronize   = DSSynchronize_GHEP;
227: #endif
228:   ds->ops->hermitian     = DSHermitian_GHEP;
229:   PetscFunctionReturn(PETSC_SUCCESS);
230: }