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1298 slepc 1
/*                      
2
 
3
   SLEPc singular value solver: "trlanczos"
4
 
5
   Method: Golub-Kahan-Lanczos bidiagonalization with thick-restart
6
 
1328 slepc 7
   Last update: Mar 2007
1298 slepc 8
 
9
*/
10
#include "src/svd/svdimpl.h"                /*I "slepcsvd.h" I*/
11
#include "slepcblaslapack.h"
12
 
13
typedef struct {
14
  PetscTruth oneside;
15
} SVD_TRLANCZOS;
16
 
17
#undef __FUNCT__  
18
#define __FUNCT__ "SVDSetUp_TRLANCZOS"
19
PetscErrorCode SVDSetUp_TRLANCZOS(SVD svd)
20
{
21
  PetscErrorCode  ierr;
1314 slepc 22
  PetscInt        N;
23
  int             i;
1298 slepc 24
 
25
  PetscFunctionBegin;
1314 slepc 26
  ierr = SVDMatGetSize(svd,PETSC_NULL,&N);CHKERRQ(ierr);
1298 slepc 27
  if (svd->ncv == PETSC_DECIDE)
1314 slepc 28
    svd->ncv = PetscMin(N,PetscMax(2*svd->nsv,10));
1298 slepc 29
  if (svd->max_it == PETSC_DECIDE)
1314 slepc 30
    svd->max_it = PetscMax(N/svd->ncv,100);
31
  if (svd->ncv!=svd->n) {  
32
    if (svd->U) {
33
      for (i=0;i<svd->n;i++) { ierr = VecDestroy(svd->U[i]); CHKERRQ(ierr); }
34
      ierr = PetscFree(svd->U);CHKERRQ(ierr);
35
    }
36
    ierr = PetscMalloc(sizeof(Vec)*svd->ncv,&svd->U);CHKERRQ(ierr);
37
    for (i=0;i<svd->ncv;i++) { ierr = SVDMatGetVecs(svd,PETSC_NULL,svd->U+i);CHKERRQ(ierr); }
38
  }
1298 slepc 39
  PetscFunctionReturn(0);
40
}
41
 
42
#undef __FUNCT__  
1328 slepc 43
#define __FUNCT__ "SVDOneSideTRLanczos"
44
static PetscErrorCode SVDOneSideTRLanczos(SVD svd,PetscReal *alpha,PetscReal *beta,PetscScalar* bb,Vec *V,Vec v,Vec* U,int nconv,int l,int n,PetscScalar* work,Vec wv,Vec wu)
45
{
46
  PetscErrorCode ierr;
47
  PetscReal      a,b;
48
  int            i,j,k=nconv+l;
49
 
50
  PetscFunctionBegin;
51
  ierr = SVDMatMult(svd,PETSC_FALSE,V[k],U[k]);CHKERRQ(ierr);
52
  if (l>0) {
53
    ierr = VecSet(wu,0.0);CHKERRQ(ierr);
54
    ierr = VecMAXPY(wu,l,bb,U+nconv);CHKERRQ(ierr);
55
    ierr = VecAXPY(U[k],-1.0,wu);CHKERRQ(ierr);
56
  }
57
  for (i=k+1;i<n;i++) {
58
    ierr = SVDMatMult(svd,PETSC_TRUE,U[i-1],V[i]);CHKERRQ(ierr);
1352 slepc 59
    ierr = IPNormBegin(svd->ip,U[i-1],&a);CHKERRQ(ierr);
60
    ierr = IPMInnerProductBegin(svd->ip,i,V[i],V,work);CHKERRQ(ierr);
61
    ierr = IPNormEnd(svd->ip,U[i-1],&a);CHKERRQ(ierr);
62
    ierr = IPMInnerProductEnd(svd->ip,i,V[i],V,work);CHKERRQ(ierr);
1328 slepc 63
 
64
    ierr = VecScale(U[i-1],1.0/a);CHKERRQ(ierr);
65
    ierr = VecScale(V[i],1.0/a);CHKERRQ(ierr);
66
    for (j=0;j<i;j++) work[j] = - work[j] / a;
67
    ierr = VecMAXPY(V[i],i,work,V);CHKERRQ(ierr);
68
 
69
    ierr = IPOrthogonalizeCGS(svd->ip,i,PETSC_NULL,V,V[i],work,PETSC_NULL,&b,wv);CHKERRQ(ierr);
70
    ierr = VecScale(V[i],1.0/b);CHKERRQ(ierr);
71
 
72
    ierr = SVDMatMult(svd,PETSC_FALSE,V[i],U[i]);CHKERRQ(ierr);
73
    ierr = VecAXPY(U[i],-b,U[i-1]);CHKERRQ(ierr);
74
 
75
    alpha[i-k-1] = a;
76
    beta[i-k-1] = b;
77
  }
78
  ierr = SVDMatMult(svd,PETSC_TRUE,U[n-1],v);CHKERRQ(ierr);
1352 slepc 79
  ierr = IPNormBegin(svd->ip,U[n-1],&a);CHKERRQ(ierr);
80
  ierr = IPMInnerProductBegin(svd->ip,n,v,V,work);CHKERRQ(ierr);
81
  ierr = IPNormEnd(svd->ip,U[n-1],&a);CHKERRQ(ierr);
82
  ierr = IPMInnerProductEnd(svd->ip,n,v,V,work);CHKERRQ(ierr);
1328 slepc 83
 
84
  ierr = VecScale(U[n-1],1.0/a);CHKERRQ(ierr);
85
  ierr = VecScale(v,1.0/a);CHKERRQ(ierr);
86
  for (j=0;j<n;j++) work[j] = - work[j] / a;
87
  ierr = VecMAXPY(v,n,work,V);CHKERRQ(ierr);
88
 
89
  ierr = IPOrthogonalizeCGS(svd->ip,n,PETSC_NULL,V,v,work,PETSC_NULL,&b,wv);CHKERRQ(ierr);
90
 
91
  alpha[n-k-1] = a;
92
  beta[n-k-1] = b;
93
  PetscFunctionReturn(0);
94
}
95
 
96
#undef __FUNCT__  
1298 slepc 97
#define __FUNCT__ "SVDSolve_TRLANCZOS"
98
PetscErrorCode SVDSolve_TRLANCZOS(SVD svd)
99
{
100
  PetscErrorCode ierr;
101
  SVD_TRLANCZOS  *lanczos = (SVD_TRLANCZOS *)svd->data;
1328 slepc 102
  PetscReal      *alpha,*beta,norm;
1341 slepc 103
  PetscScalar    *b,*Q,*PT,*swork;
1328 slepc 104
  PetscInt       *perm;
105
  int            i,j,k,l,m,n,nwork=0;
106
  Vec            v,wv,wu,*workV,*workU,*permV,*permU;
107
  PetscTruth     conv;
1298 slepc 108
 
109
  PetscFunctionBegin;
110
  /* allocate working space */
1307 slepc 111
  ierr = PetscMalloc(sizeof(PetscReal)*svd->n,&alpha);CHKERRQ(ierr);
112
  ierr = PetscMalloc(sizeof(PetscReal)*svd->n,&beta);CHKERRQ(ierr);
113
  ierr = PetscMalloc(sizeof(PetscScalar)*svd->n,&b);CHKERRQ(ierr);
114
  ierr = PetscMalloc(sizeof(PetscScalar)*svd->n*svd->n,&Q);CHKERRQ(ierr);
115
  ierr = PetscMalloc(sizeof(PetscScalar)*svd->n*svd->n,&PT);CHKERRQ(ierr);
1341 slepc 116
  ierr = PetscMalloc(sizeof(PetscScalar)*svd->n,&swork);CHKERRQ(ierr);
1328 slepc 117
  ierr = VecDuplicate(svd->V[0],&v);CHKERRQ(ierr);
118
  ierr = VecDuplicate(svd->V[0],&wv);CHKERRQ(ierr);
119
  ierr = VecDuplicate(svd->U[0],&wu);CHKERRQ(ierr);
120
  ierr = PetscMalloc(sizeof(Vec)*svd->n,&workV);CHKERRQ(ierr);
121
  ierr = PetscMalloc(sizeof(Vec)*svd->n,&workU);CHKERRQ(ierr);
1298 slepc 122
 
123
  /* normalize start vector */
1328 slepc 124
  ierr = VecCopy(svd->vec_initial,svd->V[0]);CHKERRQ(ierr);
125
  ierr = VecNormalize(svd->V[0],&norm);CHKERRQ(ierr);
1298 slepc 126
 
127
  l = 0;
128
  while (svd->reason == SVD_CONVERGED_ITERATING) {
129
    svd->its++;
130
 
131
    /* inner loop */
1328 slepc 132
    if (lanczos->oneside) {
1341 slepc 133
      ierr = SVDOneSideTRLanczos(svd,alpha,beta,b+svd->nconv,svd->V,v,svd->U,svd->nconv,l,svd->n,swork,wv,wu);CHKERRQ(ierr);
1328 slepc 134
    } else {
1341 slepc 135
      ierr = SVDTwoSideLanczos(svd,alpha,beta,svd->V,v,svd->U,svd->nconv+l,svd->n,swork,wv,wu);CHKERRQ(ierr);
1298 slepc 136
    }
1328 slepc 137
    ierr = VecScale(v,1.0/beta[svd->n-svd->nconv-l-1]);CHKERRQ(ierr);
138
 
1298 slepc 139
    /* compute SVD of general matrix */
1328 slepc 140
    n = svd->n - svd->nconv;
1298 slepc 141
    /* first l columns */
142
    for (j=0;j<l;j++) {
143
      for (i=0;i<j;i++) Q[j*n+i] = 0.0;    
1328 slepc 144
      Q[j*n+j] = svd->sigma[svd->nconv+j];
1298 slepc 145
      for (i=j+1;i<n;i++) Q[j*n+i] = 0.0;
146
    }
147
    /* l+1 column */
1328 slepc 148
    for (i=0;i<l;i++) Q[l*n+i] = b[i+svd->nconv];
149
    Q[l*n+l] = alpha[0];
1298 slepc 150
    for (i=l+1;i<n;i++) Q[l*n+i] = 0.0;
151
    /* rest of matrix */
152
    for (j=l+1;j<n;j++) {
153
      for (i=0;i<j-1;i++) Q[j*n+i] = 0.0;
1328 slepc 154
      Q[j*n+j-1] = beta[j-l-1];
155
      Q[j*n+j] = alpha[j-l];
1298 slepc 156
      for (i=j+1;i<n;i++) Q[j*n+i] = 0.0;
157
    }
1328 slepc 158
    ierr = SVDDense(n,n,Q,alpha,PETSC_NULL,PT);CHKERRQ(ierr);
1298 slepc 159
 
160
    /* compute error estimates */
1328 slepc 161
    k = 0;
162
    conv = PETSC_TRUE;
163
    for (i=svd->nconv;i<svd->n;i++) {
164
      if (svd->which == SVD_SMALLEST) j = n-i+svd->nconv-1;
165
      else j = i-svd->nconv;
166
      svd->sigma[i] = alpha[j];
167
      b[i] = Q[j*n+n-1]*beta[n-l-1];
168
      svd->errest[i] = PetscAbsScalar(b[i]);
169
      if (alpha[j] > svd->tol) svd->errest[i] /= alpha[j];
170
      if (conv) {
171
        if (svd->errest[i] < svd->tol) k++;
172
        else conv = PETSC_FALSE;
1304 slepc 173
      }
1298 slepc 174
    }
175
 
1328 slepc 176
    /* check convergence and update l */
177
    if (svd->its >= svd->max_it) svd->reason = SVD_DIVERGED_ITS;
178
    if (svd->nconv+k >= svd->nsv) svd->reason = SVD_CONVERGED_TOL;
179
    if (svd->reason != SVD_CONVERGED_ITERATING) l = 0;
180
    else l = PetscMax((svd->n - svd->nconv - k) / 2,1);
1300 slepc 181
 
1328 slepc 182
    /* allocate work space for converged singular and restart vectors */
183
    if (nwork<k+l) {
184
      for (i=nwork;i<k+l;i++) {
185
        ierr = SVDMatGetVecs(svd,workV+i,workU+i);CHKERRQ(ierr);
1300 slepc 186
      }
1328 slepc 187
      nwork = k+l;
1298 slepc 188
    }
189
 
1328 slepc 190
    /* compute converged singular vectors and restart vectors*/
191
    for (i=0;i<k+l;i++) {
192
      if (svd->which == SVD_SMALLEST) j = n-i-1;
193
      else j = i;
194
      ierr = VecSet(workV[i],0.0);CHKERRQ(ierr);
1341 slepc 195
      for (m=0;m<n;m++) swork[m] = PT[m*n+j];
196
      ierr = VecMAXPY(workV[i],n,swork,svd->V+svd->nconv);CHKERRQ(ierr);
1328 slepc 197
      ierr = VecSet(workU[i],0.0);CHKERRQ(ierr);
198
      ierr = VecMAXPY(workU[i],n,Q+j*n,svd->U+svd->nconv);CHKERRQ(ierr);
199
    }
200
 
1298 slepc 201
    /* copy the last vector to be the next initial vector */
202
    if (svd->reason == SVD_CONVERGED_ITERATING) {
1328 slepc 203
      ierr = VecCopy(v,svd->V[svd->nconv+k+l]);CHKERRQ(ierr);
1298 slepc 204
    }
205
 
1328 slepc 206
    /* copy converged singular vectors and restart vectors from temporary space */
207
    for (i=0;i<k+l;i++) {
208
      ierr = VecCopy(workV[i],svd->V[i+svd->nconv]);CHKERRQ(ierr);
209
      ierr = VecCopy(workU[i],svd->U[i+svd->nconv]);CHKERRQ(ierr);
210
    }
211
 
212
    svd->nconv += k;
213
    SVDMonitor(svd,svd->its,svd->nconv,svd->sigma,svd->errest,svd->n);
1298 slepc 214
  }
215
 
216
  /* sort singular triplets */
217
  ierr = PetscMalloc(sizeof(PetscInt)*svd->nconv,&perm);CHKERRQ(ierr);
1328 slepc 218
  ierr = PetscMalloc(sizeof(Vec)*svd->nconv,&permV);CHKERRQ(ierr);
219
  ierr = PetscMalloc(sizeof(Vec)*svd->nconv,&permU);CHKERRQ(ierr);
1298 slepc 220
  for (i=0;i<svd->nconv;i++) {
221
    alpha[i] = svd->sigma[i];
222
    beta[i] = svd->errest[i];
1328 slepc 223
    permV[i] = svd->V[i];
224
    permU[i] = svd->U[i];
1298 slepc 225
    perm[i] = i;
226
  }
1328 slepc 227
  ierr = PetscSortRealWithPermutation(svd->nconv,svd->sigma,perm);CHKERRQ(ierr);
228
  for (i=0;i<svd->nconv;i++) {
1298 slepc 229
    if (svd->which == SVD_SMALLEST) j = perm[i];
1300 slepc 230
    else j = perm[svd->nconv-i-1];
1328 slepc 231
    svd->sigma[i] = alpha[j];
232
    svd->errest[i] = beta[j];
233
    svd->V[i] = permV[j];
234
    svd->U[i] = permU[j];
1298 slepc 235
  }
236
 
237
  /* free working space */
1328 slepc 238
  ierr = VecDestroy(v);CHKERRQ(ierr);
239
  ierr = VecDestroy(wv);CHKERRQ(ierr);
240
  ierr = VecDestroy(wu);CHKERRQ(ierr);
241
  for (i=0;i<nwork;i++) { ierr = VecDestroy(workV[i]);CHKERRQ(ierr); }
242
  ierr = PetscFree(workV);CHKERRQ(ierr);
243
  for (i=0;i<nwork;i++) { ierr = VecDestroy(workU[i]);CHKERRQ(ierr); }
244
  ierr = PetscFree(workU);CHKERRQ(ierr);
1298 slepc 245
 
246
  ierr = PetscFree(alpha);CHKERRQ(ierr);
247
  ierr = PetscFree(beta);CHKERRQ(ierr);
248
  ierr = PetscFree(b);CHKERRQ(ierr);
249
  ierr = PetscFree(Q);CHKERRQ(ierr);
250
  ierr = PetscFree(PT);CHKERRQ(ierr);
1341 slepc 251
  ierr = PetscFree(swork);CHKERRQ(ierr);
1298 slepc 252
  ierr = PetscFree(perm);CHKERRQ(ierr);
1328 slepc 253
  ierr = PetscFree(permV);CHKERRQ(ierr);
254
  ierr = PetscFree(permU);CHKERRQ(ierr);
1298 slepc 255
  PetscFunctionReturn(0);
256
}
257
 
258
#undef __FUNCT__  
259
#define __FUNCT__ "SVDSetFromOptions_TRLANCZOS"
260
PetscErrorCode SVDSetFromOptions_TRLANCZOS(SVD svd)
261
{
262
  PetscErrorCode ierr;
263
  SVD_TRLANCZOS  *lanczos = (SVD_TRLANCZOS *)svd->data;
264
 
265
  PetscFunctionBegin;
266
  ierr = PetscOptionsBegin(svd->comm,svd->prefix,"TRLANCZOS Singular Value Solver Options","SVD");CHKERRQ(ierr);
1359 slepc 267
  ierr = PetscOptionsTruth("-svd_trlanczos_oneside","Lanczos one-side reorthogonalization","SVDTRLanczosSetOneSide",PETSC_FALSE,&lanczos->oneside,PETSC_NULL);CHKERRQ(ierr);
1298 slepc 268
  ierr = PetscOptionsEnd();CHKERRQ(ierr);
269
  PetscFunctionReturn(0);
270
}
1370 slepc 271
 
1298 slepc 272
EXTERN_C_BEGIN
273
#undef __FUNCT__  
1359 slepc 274
#define __FUNCT__ "SVDTRLanczosSetOneSide_TRLANCZOS"
275
PetscErrorCode SVDTRLanczosSetOneSide_TRLANCZOS(SVD svd,PetscTruth oneside)
1298 slepc 276
{
277
  SVD_TRLANCZOS *lanczos = (SVD_TRLANCZOS *)svd->data;
278
 
279
  PetscFunctionBegin;
280
  lanczos->oneside = oneside;
281
  PetscFunctionReturn(0);
282
}
1370 slepc 283
EXTERN_C_END
1298 slepc 284
 
285
#undef __FUNCT__
1359 slepc 286
#define __FUNCT__ "SVDTRLanczosSetOneSide"
287
PetscErrorCode SVDTRLanczosSetOneSide(SVD svd,PetscTruth oneside)
1298 slepc 288
{
289
  PetscErrorCode ierr, (*f)(SVD,PetscTruth);
290
 
291
  PetscFunctionBegin;
292
  PetscValidHeaderSpecific(svd,SVD_COOKIE,1);
1359 slepc 293
  ierr = PetscObjectQueryFunction((PetscObject)svd,"SVDTRLanczosSetOneSide_C",(void (**)())&f);CHKERRQ(ierr);
1298 slepc 294
  if (f) {
295
    ierr = (*f)(svd,oneside);CHKERRQ(ierr);
296
  }
297
  PetscFunctionReturn(0);
298
}
299
 
300
#undef __FUNCT__  
301
#define __FUNCT__ "SVDView_TRLANCZOS"
302
PetscErrorCode SVDView_TRLANCZOS(SVD svd,PetscViewer viewer)
303
{
304
  PetscErrorCode ierr;
305
  SVD_TRLANCZOS  *lanczos = (SVD_TRLANCZOS *)svd->data;
306
 
307
  PetscFunctionBegin;
308
  ierr = PetscViewerASCIIPrintf(viewer,"Lanczos reorthogonalization: %s\n",lanczos->oneside ? "one-side" : "two-side");CHKERRQ(ierr);
309
  PetscFunctionReturn(0);
310
}
311
 
312
EXTERN_C_BEGIN
313
#undef __FUNCT__  
314
#define __FUNCT__ "SVDCreate_TRLANCZOS"
315
PetscErrorCode SVDCreate_TRLANCZOS(SVD svd)
316
{
317
  PetscErrorCode ierr;
318
  SVD_TRLANCZOS  *lanczos;
319
 
320
  PetscFunctionBegin;
321
  ierr = PetscNew(SVD_TRLANCZOS,&lanczos);CHKERRQ(ierr);
322
  PetscLogObjectMemory(svd,sizeof(SVD_TRLANCZOS));
323
  svd->data                = (void *)lanczos;
324
  svd->ops->setup          = SVDSetUp_TRLANCZOS;
325
  svd->ops->solve          = SVDSolve_TRLANCZOS;
326
  svd->ops->setfromoptions = SVDSetFromOptions_TRLANCZOS;
327
  svd->ops->view           = SVDView_TRLANCZOS;
328
  lanczos->oneside         = PETSC_FALSE;
1359 slepc 329
  ierr = PetscObjectComposeFunctionDynamic((PetscObject)svd,"SVDTRLanczosSetOneSide_C","SVDTRLanczosSetOneSide_TRLANCZOS",SVDTRLanczosSetOneSide_TRLANCZOS);CHKERRQ(ierr);
1298 slepc 330
  PetscFunctionReturn(0);
331
}
332
EXTERN_C_END