Actual source code: dsghep.c
slepc-3.17.2 2022-08-09
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: PetscErrorCode DSAllocate_GHEP(DS ds,PetscInt ld)
15: {
16: DSAllocateMat_Private(ds,DS_MAT_A);
17: DSAllocateMat_Private(ds,DS_MAT_B);
18: DSAllocateMat_Private(ds,DS_MAT_Q);
19: PetscFree(ds->perm);
20: PetscMalloc1(ld,&ds->perm);
21: PetscLogObjectMemory((PetscObject)ds,ld*sizeof(PetscInt));
22: PetscFunctionReturn(0);
23: }
25: PetscErrorCode DSView_GHEP(DS ds,PetscViewer viewer)
26: {
27: PetscViewerFormat format;
29: PetscViewerGetFormat(viewer,&format);
30: if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) PetscFunctionReturn(0);
31: DSViewMat(ds,viewer,DS_MAT_A);
32: DSViewMat(ds,viewer,DS_MAT_B);
33: if (ds->state>DS_STATE_INTERMEDIATE) DSViewMat(ds,viewer,DS_MAT_Q);
34: if (ds->mat[DS_MAT_X]) DSViewMat(ds,viewer,DS_MAT_X);
35: PetscFunctionReturn(0);
36: }
38: PetscErrorCode DSVectors_GHEP(DS ds,DSMatType mat,PetscInt *j,PetscReal *rnorm)
39: {
40: PetscScalar *Q = ds->mat[DS_MAT_Q];
41: PetscInt ld = ds->ld;
44: switch (mat) {
45: case DS_MAT_X:
46: case DS_MAT_Y:
47: if (j) {
48: if (ds->state>=DS_STATE_CONDENSED) PetscArraycpy(ds->mat[mat]+(*j)*ld,Q+(*j)*ld,ld);
49: else {
50: PetscArrayzero(ds->mat[mat]+(*j)*ld,ld);
51: *(ds->mat[mat]+(*j)+(*j)*ld) = 1.0;
52: }
53: } else {
54: if (ds->state>=DS_STATE_CONDENSED) PetscArraycpy(ds->mat[mat],Q,ld*ld);
55: else DSSetIdentity(ds,mat);
56: }
57: break;
58: case DS_MAT_U:
59: case DS_MAT_V:
60: SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_SUP,"Not implemented yet");
61: default:
62: SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_OUTOFRANGE,"Invalid mat parameter");
63: }
64: PetscFunctionReturn(0);
65: }
67: PetscErrorCode DSSort_GHEP(DS ds,PetscScalar *wr,PetscScalar *wi,PetscScalar *rr,PetscScalar *ri,PetscInt *k)
68: {
69: PetscInt n,l,i,*perm,ld=ds->ld;
70: PetscScalar *A;
72: if (!ds->sc) PetscFunctionReturn(0);
73: n = ds->n;
74: l = ds->l;
75: A = ds->mat[DS_MAT_A];
76: perm = ds->perm;
77: for (i=l;i<n;i++) wr[i] = A[i+i*ld];
78: if (rr) DSSortEigenvalues_Private(ds,rr,ri,perm,PETSC_FALSE);
79: else DSSortEigenvalues_Private(ds,wr,NULL,perm,PETSC_FALSE);
80: for (i=l;i<n;i++) A[i+i*ld] = wr[perm[i]];
81: for (i=l;i<n;i++) wr[i] = A[i+i*ld];
82: DSPermuteColumns_Private(ds,l,n,n,DS_MAT_Q,perm);
83: PetscFunctionReturn(0);
84: }
86: PetscErrorCode DSSolve_GHEP(DS ds,PetscScalar *wr,PetscScalar *wi)
87: {
88: PetscScalar *work,*A,*B,*Q;
89: PetscBLASInt itype = 1,*iwork,info,n1,liwork,ld,lrwork=0,lwork;
90: PetscInt off,i;
91: #if defined(PETSC_USE_COMPLEX)
92: PetscReal *rwork,*rr;
93: #endif
95: PetscBLASIntCast(ds->n-ds->l,&n1);
96: PetscBLASIntCast(ds->ld,&ld);
97: PetscBLASIntCast(5*ds->n+3,&liwork);
98: #if defined(PETSC_USE_COMPLEX)
99: PetscBLASIntCast(ds->n*ds->n+2*ds->n,&lwork);
100: PetscBLASIntCast(2*ds->n*ds->n+5*ds->n+1+n1,&lrwork);
101: #else
102: PetscBLASIntCast(2*ds->n*ds->n+6*ds->n+1,&lwork);
103: #endif
104: DSAllocateWork_Private(ds,lwork,lrwork,liwork);
105: work = ds->work;
106: iwork = ds->iwork;
107: off = ds->l+ds->l*ld;
108: A = ds->mat[DS_MAT_A];
109: B = ds->mat[DS_MAT_B];
110: Q = ds->mat[DS_MAT_Q];
111: #if defined(PETSC_USE_COMPLEX)
112: rr = ds->rwork;
113: rwork = ds->rwork + n1;
114: lrwork = ds->lrwork - n1;
115: PetscStackCallBLAS("LAPACKsygvd",LAPACKsygvd_(&itype,"V","U",&n1,A+off,&ld,B+off,&ld,rr,work,&lwork,rwork,&lrwork,iwork,&liwork,&info));
116: for (i=0;i<n1;i++) wr[ds->l+i] = rr[i];
117: #else
118: PetscStackCallBLAS("LAPACKsygvd",LAPACKsygvd_(&itype,"V","U",&n1,A+off,&ld,B+off,&ld,wr+ds->l,work,&lwork,iwork,&liwork,&info));
119: #endif
120: SlepcCheckLapackInfo("sygvd",info);
121: PetscArrayzero(Q+ds->l*ld,n1*ld);
122: for (i=ds->l;i<ds->n;i++) PetscArraycpy(Q+ds->l+i*ld,A+ds->l+i*ld,n1);
123: PetscArrayzero(B+ds->l*ld,n1*ld);
124: PetscArrayzero(A+ds->l*ld,n1*ld);
125: for (i=ds->l;i<ds->n;i++) {
126: if (wi) wi[i] = 0.0;
127: B[i+i*ld] = 1.0;
128: A[i+i*ld] = wr[i];
129: }
130: PetscFunctionReturn(0);
131: }
133: PetscErrorCode DSSynchronize_GHEP(DS ds,PetscScalar eigr[],PetscScalar eigi[])
134: {
135: PetscInt ld=ds->ld,l=ds->l,k;
136: PetscMPIInt n,rank,off=0,size,ldn;
138: k = 2*(ds->n-l)*ld;
139: if (ds->state>DS_STATE_RAW) k += (ds->n-l)*ld;
140: if (eigr) k += (ds->n-l);
141: DSAllocateWork_Private(ds,k,0,0);
142: PetscMPIIntCast(k*sizeof(PetscScalar),&size);
143: PetscMPIIntCast(ds->n-l,&n);
144: PetscMPIIntCast(ld*(ds->n-l),&ldn);
145: MPI_Comm_rank(PetscObjectComm((PetscObject)ds),&rank);
146: if (!rank) {
147: MPI_Pack(ds->mat[DS_MAT_A]+l*ld,ldn,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds));
148: MPI_Pack(ds->mat[DS_MAT_B]+l*ld,ldn,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds));
149: if (ds->state>DS_STATE_RAW) MPI_Pack(ds->mat[DS_MAT_Q]+l*ld,ldn,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds));
150: if (eigr) MPI_Pack(eigr+l,n,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds));
151: }
152: MPI_Bcast(ds->work,size,MPI_BYTE,0,PetscObjectComm((PetscObject)ds));
153: if (rank) {
154: MPI_Unpack(ds->work,size,&off,ds->mat[DS_MAT_A]+l*ld,ldn,MPIU_SCALAR,PetscObjectComm((PetscObject)ds));
155: MPI_Unpack(ds->work,size,&off,ds->mat[DS_MAT_B]+l*ld,ldn,MPIU_SCALAR,PetscObjectComm((PetscObject)ds));
156: if (ds->state>DS_STATE_RAW) MPI_Unpack(ds->work,size,&off,ds->mat[DS_MAT_Q]+l*ld,ldn,MPIU_SCALAR,PetscObjectComm((PetscObject)ds));
157: if (eigr) MPI_Unpack(ds->work,size,&off,eigr+l,n,MPIU_SCALAR,PetscObjectComm((PetscObject)ds));
158: }
159: PetscFunctionReturn(0);
160: }
162: PetscErrorCode DSHermitian_GHEP(DS ds,DSMatType m,PetscBool *flg)
163: {
164: if (m==DS_MAT_A || m==DS_MAT_B) *flg = PETSC_TRUE;
165: else *flg = PETSC_FALSE;
166: PetscFunctionReturn(0);
167: }
169: /*MC
170: DSGHEP - Dense Generalized Hermitian Eigenvalue Problem.
172: Level: beginner
174: Notes:
175: The problem is expressed as A*X = B*X*Lambda, where both A and B are
176: real symmetric (or complex Hermitian) and B is positive-definite. Lambda
177: is a diagonal matrix whose diagonal elements are the arguments of DSSolve().
178: After solve, A is overwritten with Lambda, and B is overwritten with I.
180: No intermediate state is implemented, nor compact storage.
182: Used DS matrices:
183: + DS_MAT_A - first problem matrix
184: . DS_MAT_B - second problem matrix
185: - DS_MAT_Q - matrix of B-orthogonal eigenvectors, which is equal to X
187: Implemented methods:
188: . 0 - Divide and Conquer (_sygvd)
190: .seealso: DSCreate(), DSSetType(), DSType
191: M*/
192: SLEPC_EXTERN PetscErrorCode DSCreate_GHEP(DS ds)
193: {
194: ds->ops->allocate = DSAllocate_GHEP;
195: ds->ops->view = DSView_GHEP;
196: ds->ops->vectors = DSVectors_GHEP;
197: ds->ops->solve[0] = DSSolve_GHEP;
198: ds->ops->sort = DSSort_GHEP;
199: ds->ops->synchronize = DSSynchronize_GHEP;
200: ds->ops->hermitian = DSHermitian_GHEP;
201: PetscFunctionReturn(0);
202: }