Actual source code: lapack.c
slepc-3.13.2 2020-05-12
1: /*
2: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
3: SLEPc - Scalable Library for Eigenvalue Problem Computations
4: Copyright (c) 2002-2020, 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: */
10: /*
11: This file implements a wrapper to the LAPACK eigenvalue subroutines.
12: Generalized problems are transformed to standard ones only if necessary.
13: */
15: #include <slepc/private/epsimpl.h>
17: PetscErrorCode EPSSetUp_LAPACK(EPS eps)
18: {
19: PetscErrorCode ierr,ierra,ierrb;
20: PetscBool isshift,flg,denseok=PETSC_FALSE;
21: Mat A,B,OP,shell,Ar,Br,Adense=NULL,Bdense=NULL;
22: PetscScalar shift,*Ap,*Bp;
23: PetscInt i,ld,nmat;
24: KSP ksp;
25: PC pc;
26: Vec v;
29: eps->ncv = eps->n;
30: if (eps->mpd) { PetscInfo(eps,"Warning: parameter mpd ignored\n"); }
31: if (!eps->which) { EPSSetWhichEigenpairs_Default(eps); }
32: if (eps->which==EPS_ALL && eps->inta!=eps->intb) SETERRQ(PetscObjectComm((PetscObject)eps),1,"This solver does not support interval computation");
33: if (eps->balance!=EPS_BALANCE_NONE) { PetscInfo(eps,"Warning: balancing ignored\n"); }
34: if (eps->stopping!=EPSStoppingBasic) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"User-defined stopping test not supported");
35: if (eps->extraction) { PetscInfo(eps,"Warning: extraction type ignored\n"); }
36: EPSAllocateSolution(eps,0);
38: /* attempt to get dense representations of A and B separately */
39: PetscObjectTypeCompare((PetscObject)eps->st,STSHIFT,&isshift);
40: if (isshift) {
41: STGetNumMatrices(eps->st,&nmat);
42: STGetMatrix(eps->st,0,&A);
43: MatHasOperation(A,MATOP_CREATE_SUBMATRICES,&flg);
44: if (flg) {
45: PetscPushErrorHandler(PetscIgnoreErrorHandler,NULL);
46: ierra = MatCreateRedundantMatrix(A,0,PETSC_COMM_SELF,MAT_INITIAL_MATRIX,&Ar);
47: if (!ierra) { ierra |= MatConvert(Ar,MATSEQDENSE,MAT_INITIAL_MATRIX,&Adense); }
48: ierra |= MatDestroy(&Ar);
49: PetscPopErrorHandler();
50: } else ierra = 1;
51: if (nmat>1) {
52: STGetMatrix(eps->st,1,&B);
53: MatHasOperation(B,MATOP_CREATE_SUBMATRICES,&flg);
54: if (flg) {
55: PetscPushErrorHandler(PetscIgnoreErrorHandler,NULL);
56: ierrb = MatCreateRedundantMatrix(B,0,PETSC_COMM_SELF,MAT_INITIAL_MATRIX,&Br);
57: if (!ierrb) { ierrb |= MatConvert(Br,MATSEQDENSE,MAT_INITIAL_MATRIX,&Bdense); }
58: ierrb |= MatDestroy(&Br);
59: PetscPopErrorHandler();
60: } else ierrb = 1;
61: } else ierrb = 0;
62: denseok = PetscNot(ierra || ierrb);
63: }
65: /* setup DS */
66: if (denseok) {
67: if (eps->isgeneralized) {
68: if (eps->ishermitian) {
69: if (eps->ispositive) {
70: DSSetType(eps->ds,DSGHEP);
71: } else {
72: DSSetType(eps->ds,DSGNHEP); /* TODO: should be DSGHIEP */
73: }
74: } else {
75: DSSetType(eps->ds,DSGNHEP);
76: }
77: } else {
78: if (eps->ishermitian) {
79: DSSetType(eps->ds,DSHEP);
80: } else {
81: DSSetType(eps->ds,DSNHEP);
82: }
83: }
84: } else {
85: DSSetType(eps->ds,DSNHEP);
86: }
87: DSAllocate(eps->ds,eps->ncv);
88: DSGetLeadingDimension(eps->ds,&ld);
89: DSSetDimensions(eps->ds,eps->ncv,0,0,0);
91: if (denseok) {
92: STGetShift(eps->st,&shift);
93: if (shift != 0.0) {
94: MatShift(Adense,shift);
95: }
96: /* use dummy pc and ksp to avoid problems when B is not positive definite */
97: STGetKSP(eps->st,&ksp);
98: KSPSetType(ksp,KSPPREONLY);
99: KSPGetPC(ksp,&pc);
100: PCSetType(pc,PCNONE);
101: } else {
102: PetscInfo(eps,"Using slow explicit operator\n");
103: STGetOperator(eps->st,&shell);
104: MatComputeOperator(shell,MATDENSE,&OP);
105: STRestoreOperator(eps->st,&shell);
106: MatDestroy(&Adense);
107: MatCreateRedundantMatrix(OP,0,PETSC_COMM_SELF,MAT_INITIAL_MATRIX,&Adense);
108: MatDestroy(&OP);
109: }
111: /* fill DS matrices */
112: VecCreateSeqWithArray(PETSC_COMM_SELF,1,ld,NULL,&v);
113: DSGetArray(eps->ds,DS_MAT_A,&Ap);
114: for (i=0;i<ld;i++) {
115: VecPlaceArray(v,Ap+i*ld);
116: MatGetColumnVector(Adense,v,i);
117: VecResetArray(v);
118: }
119: DSRestoreArray(eps->ds,DS_MAT_A,&Ap);
120: if (denseok && eps->isgeneralized) {
121: DSGetArray(eps->ds,DS_MAT_B,&Bp);
122: for (i=0;i<ld;i++) {
123: VecPlaceArray(v,Bp+i*ld);
124: MatGetColumnVector(Bdense,v,i);
125: VecResetArray(v);
126: }
127: DSRestoreArray(eps->ds,DS_MAT_B,&Bp);
128: }
129: VecDestroy(&v);
130: DSSetState(eps->ds,DS_STATE_RAW);
131: MatDestroy(&Adense);
132: MatDestroy(&Bdense);
133: return(0);
134: }
136: PetscErrorCode EPSSolve_LAPACK(EPS eps)
137: {
139: PetscInt n=eps->n,i,low,high;
140: PetscScalar *array,*pX,*pY;
141: Vec v,w;
144: DSSolve(eps->ds,eps->eigr,eps->eigi);
145: DSSort(eps->ds,eps->eigr,eps->eigi,NULL,NULL,NULL);
146: DSSynchronize(eps->ds,eps->eigr,eps->eigi);
148: /* right eigenvectors */
149: DSVectors(eps->ds,DS_MAT_X,NULL,NULL);
150: DSGetArray(eps->ds,DS_MAT_X,&pX);
151: for (i=0;i<eps->ncv;i++) {
152: BVGetColumn(eps->V,i,&v);
153: VecGetOwnershipRange(v,&low,&high);
154: VecGetArray(v,&array);
155: PetscArraycpy(array,pX+i*n+low,high-low);
156: VecRestoreArray(v,&array);
157: BVRestoreColumn(eps->V,i,&v);
158: }
159: DSRestoreArray(eps->ds,DS_MAT_X,&pX);
161: /* left eigenvectors */
162: if (eps->twosided) {
163: DSVectors(eps->ds,DS_MAT_Y,NULL,NULL);
164: DSGetArray(eps->ds,DS_MAT_Y,&pY);
165: for (i=0;i<eps->ncv;i++) {
166: BVGetColumn(eps->W,i,&w);
167: VecGetOwnershipRange(w,&low,&high);
168: VecGetArray(w,&array);
169: PetscArraycpy(array,pY+i*n+low,high-low);
170: VecRestoreArray(w,&array);
171: BVRestoreColumn(eps->W,i,&w);
172: }
173: DSRestoreArray(eps->ds,DS_MAT_Y,&pY);
174: }
176: eps->nconv = eps->ncv;
177: eps->its = 1;
178: eps->reason = EPS_CONVERGED_TOL;
179: return(0);
180: }
182: SLEPC_EXTERN PetscErrorCode EPSCreate_LAPACK(EPS eps)
183: {
185: eps->useds = PETSC_TRUE;
186: eps->hasts = PETSC_TRUE;
187: eps->categ = EPS_CATEGORY_OTHER;
189: eps->ops->solve = EPSSolve_LAPACK;
190: eps->ops->setup = EPSSetUp_LAPACK;
191: eps->ops->backtransform = EPSBackTransform_Default;
192: return(0);
193: }