Actual source code: cyclic.c
slepc-3.15.0 2021-03-31
1: /*
2: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
3: SLEPc - Scalable Library for Eigenvalue Problem Computations
4: Copyright (c) 2002-2021, 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: SLEPc singular value solver: "cyclic"
13: Method: Uses a Hermitian eigensolver for H(A) = [ 0 A ; A^T 0 ]
14: */
16: #include <slepc/private/svdimpl.h>
17: #include <slepc/private/epsimpl.h>
18: #include "cyclic.h"
20: static PetscErrorCode MatMult_Cyclic(Mat B,Vec x,Vec y)
21: {
22: PetscErrorCode ierr;
23: SVD svd;
24: SVD_CYCLIC *cyclic;
25: const PetscScalar *px;
26: PetscScalar *py;
27: PetscInt m;
30: MatShellGetContext(B,(void**)&svd);
31: cyclic = (SVD_CYCLIC*)svd->data;
32: MatGetLocalSize(svd->A,&m,NULL);
33: VecGetArrayRead(x,&px);
34: VecGetArray(y,&py);
35: VecPlaceArray(cyclic->x1,px);
36: VecPlaceArray(cyclic->x2,px+m);
37: VecPlaceArray(cyclic->y1,py);
38: VecPlaceArray(cyclic->y2,py+m);
39: MatMult(svd->A,cyclic->x2,cyclic->y1);
40: MatMult(svd->AT,cyclic->x1,cyclic->y2);
41: VecResetArray(cyclic->x1);
42: VecResetArray(cyclic->x2);
43: VecResetArray(cyclic->y1);
44: VecResetArray(cyclic->y2);
45: VecRestoreArrayRead(x,&px);
46: VecRestoreArray(y,&py);
47: return(0);
48: }
50: static PetscErrorCode MatGetDiagonal_Cyclic(Mat B,Vec diag)
51: {
55: VecSet(diag,0.0);
56: return(0);
57: }
59: PetscErrorCode SVDSetUp_Cyclic(SVD svd)
60: {
61: PetscErrorCode ierr;
62: SVD_CYCLIC *cyclic = (SVD_CYCLIC*)svd->data;
63: PetscInt M,N,m,n,i,isl,Istart,Iend;
64: const PetscScalar *isa;
65: PetscScalar *va;
66: PetscBool trackall,issinv;
67: Vec v;
68: Mat Zm,Zn;
69: ST st;
70: #if defined(PETSC_HAVE_CUDA)
71: PetscBool cuda;
72: #endif
75: SVDCheckStandard(svd);
76: MatGetSize(svd->A,&M,&N);
77: MatGetLocalSize(svd->A,&m,&n);
78: if (!cyclic->mat) {
79: if (cyclic->explicitmatrix) {
80: if (!svd->expltrans) SETERRQ(PetscObjectComm((PetscObject)svd),PETSC_ERR_SUP,"Cannot use explicit cyclic matrix with implicit transpose");
81: MatCreate(PetscObjectComm((PetscObject)svd),&Zm);
82: MatSetSizes(Zm,m,m,M,M);
83: MatSetFromOptions(Zm);
84: MatSetUp(Zm);
85: MatGetOwnershipRange(Zm,&Istart,&Iend);
86: for (i=Istart;i<Iend;i++) {
87: MatSetValue(Zm,i,i,0.0,INSERT_VALUES);
88: }
89: MatAssemblyBegin(Zm,MAT_FINAL_ASSEMBLY);
90: MatAssemblyEnd(Zm,MAT_FINAL_ASSEMBLY);
91: MatCreate(PetscObjectComm((PetscObject)svd),&Zn);
92: MatSetSizes(Zn,n,n,N,N);
93: MatSetFromOptions(Zn);
94: MatSetUp(Zn);
95: MatGetOwnershipRange(Zn,&Istart,&Iend);
96: for (i=Istart;i<Iend;i++) {
97: MatSetValue(Zn,i,i,0.0,INSERT_VALUES);
98: }
99: MatAssemblyBegin(Zn,MAT_FINAL_ASSEMBLY);
100: MatAssemblyEnd(Zn,MAT_FINAL_ASSEMBLY);
101: MatCreateTile(1.0,Zm,1.0,svd->A,1.0,svd->AT,1.0,Zn,&cyclic->mat);
102: PetscLogObjectParent((PetscObject)svd,(PetscObject)cyclic->mat);
103: MatDestroy(&Zm);
104: MatDestroy(&Zn);
105: } else {
106: MatCreateVecsEmpty(svd->A,&cyclic->x2,&cyclic->x1);
107: MatCreateVecsEmpty(svd->A,&cyclic->y2,&cyclic->y1);
108: PetscLogObjectParent((PetscObject)svd,(PetscObject)cyclic->x1);
109: PetscLogObjectParent((PetscObject)svd,(PetscObject)cyclic->x2);
110: PetscLogObjectParent((PetscObject)svd,(PetscObject)cyclic->y1);
111: PetscLogObjectParent((PetscObject)svd,(PetscObject)cyclic->y2);
112: MatCreateShell(PetscObjectComm((PetscObject)svd),m+n,m+n,M+N,M+N,svd,&cyclic->mat);
113: MatShellSetOperation(cyclic->mat,MATOP_GET_DIAGONAL,(void(*)(void))MatGetDiagonal_Cyclic);
114: #if defined(PETSC_HAVE_CUDA)
115: PetscObjectTypeCompareAny((PetscObject)(svd->A?svd->A:svd->AT),&cuda,MATSEQAIJCUSPARSE,MATMPIAIJCUSPARSE,"");
116: if (cuda) {
117: MatShellSetVecType(cyclic->mat,VECCUDA);
118: MatShellSetOperation(cyclic->mat,MATOP_MULT,(void(*)(void))MatMult_Cyclic_CUDA);
119: } else
120: #endif
121: {
122: MatShellSetOperation(cyclic->mat,MATOP_MULT,(void(*)(void))MatMult_Cyclic);
123: }
124: }
125: PetscLogObjectParent((PetscObject)svd,(PetscObject)cyclic->mat);
126: }
128: if (!cyclic->eps) { SVDCyclicGetEPS(svd,&cyclic->eps); }
129: EPSSetOperators(cyclic->eps,cyclic->mat,NULL);
130: EPSSetProblemType(cyclic->eps,EPS_HEP);
131: if (!cyclic->usereps) {
132: if (svd->which == SVD_LARGEST) {
133: EPSGetST(cyclic->eps,&st);
134: PetscObjectTypeCompare((PetscObject)st,STSINVERT,&issinv);
135: if (issinv) {
136: EPSSetWhichEigenpairs(cyclic->eps,EPS_TARGET_MAGNITUDE);
137: } else {
138: EPSSetWhichEigenpairs(cyclic->eps,EPS_LARGEST_REAL);
139: }
140: } else {
141: EPSSetEigenvalueComparison(cyclic->eps,SlepcCompareSmallestPosReal,NULL);
142: EPSSetTarget(cyclic->eps,0.0);
143: }
144: EPSSetDimensions(cyclic->eps,svd->nsv,svd->ncv,svd->mpd);
145: EPSSetTolerances(cyclic->eps,svd->tol==PETSC_DEFAULT?SLEPC_DEFAULT_TOL/10.0:svd->tol,svd->max_it);
146: switch (svd->conv) {
147: case SVD_CONV_ABS:
148: EPSSetConvergenceTest(cyclic->eps,EPS_CONV_ABS);break;
149: case SVD_CONV_REL:
150: EPSSetConvergenceTest(cyclic->eps,EPS_CONV_REL);break;
151: case SVD_CONV_MAXIT:
152: SETERRQ(PetscObjectComm((PetscObject)svd),PETSC_ERR_SUP,"Maxit convergence test not supported in this solver");
153: case SVD_CONV_USER:
154: SETERRQ(PetscObjectComm((PetscObject)svd),PETSC_ERR_SUP,"User-defined convergence test not supported in this solver");
155: }
156: }
157: SVDCheckUnsupported(svd,SVD_FEATURE_STOPPING);
158: /* Transfer the trackall option from svd to eps */
159: SVDGetTrackAll(svd,&trackall);
160: EPSSetTrackAll(cyclic->eps,trackall);
161: /* Transfer the initial subspace from svd to eps */
162: if (svd->nini<0 || svd->ninil<0) {
163: for (i=0;i<-PetscMin(svd->nini,svd->ninil);i++) {
164: MatCreateVecs(cyclic->mat,&v,NULL);
165: VecGetArray(v,&va);
166: if (i<-svd->ninil) {
167: VecGetSize(svd->ISL[i],&isl);
168: if (isl!=m) SETERRQ(PetscObjectComm((PetscObject)svd),PETSC_ERR_SUP,"Size mismatch for left initial vector");
169: VecGetArrayRead(svd->ISL[i],&isa);
170: PetscArraycpy(va,isa,m);
171: VecRestoreArrayRead(svd->IS[i],&isa);
172: } else {
173: PetscArrayzero(&va,m);
174: }
175: if (i<-svd->nini) {
176: VecGetSize(svd->IS[i],&isl);
177: if (isl!=n) SETERRQ(PetscObjectComm((PetscObject)svd),PETSC_ERR_SUP,"Size mismatch for right initial vector");
178: VecGetArrayRead(svd->IS[i],&isa);
179: PetscArraycpy(va+m,isa,n);
180: VecRestoreArrayRead(svd->IS[i],&isa);
181: } else {
182: PetscArrayzero(va+m,n);
183: }
184: VecRestoreArray(v,&va);
185: VecDestroy(&svd->IS[i]);
186: svd->IS[i] = v;
187: }
188: svd->nini = PetscMin(svd->nini,svd->ninil);
189: EPSSetInitialSpace(cyclic->eps,-svd->nini,svd->IS);
190: SlepcBasisDestroy_Private(&svd->nini,&svd->IS);
191: SlepcBasisDestroy_Private(&svd->ninil,&svd->ISL);
192: }
193: EPSSetUp(cyclic->eps);
194: EPSGetDimensions(cyclic->eps,NULL,&svd->ncv,&svd->mpd);
195: svd->ncv = PetscMin(svd->ncv,PetscMin(M,N));
196: EPSGetTolerances(cyclic->eps,NULL,&svd->max_it);
197: if (svd->tol==PETSC_DEFAULT) svd->tol = SLEPC_DEFAULT_TOL;
199: svd->leftbasis = PETSC_TRUE;
200: SVDAllocateSolution(svd,0);
201: return(0);
202: }
204: PetscErrorCode SVDSolve_Cyclic(SVD svd)
205: {
207: SVD_CYCLIC *cyclic = (SVD_CYCLIC*)svd->data;
208: PetscInt i,j,nconv;
209: PetscScalar sigma;
212: EPSSolve(cyclic->eps);
213: EPSGetConverged(cyclic->eps,&nconv);
214: EPSGetIterationNumber(cyclic->eps,&svd->its);
215: EPSGetConvergedReason(cyclic->eps,(EPSConvergedReason*)&svd->reason);
216: for (i=0,j=0;i<nconv;i++) {
217: EPSGetEigenvalue(cyclic->eps,i,&sigma,NULL);
218: if (PetscRealPart(sigma) > 0.0) {
219: svd->sigma[j] = PetscRealPart(sigma);
220: j++;
221: }
222: }
223: svd->nconv = j;
224: return(0);
225: }
227: PetscErrorCode SVDComputeVectors_Cyclic(SVD svd)
228: {
229: PetscErrorCode ierr;
230: SVD_CYCLIC *cyclic = (SVD_CYCLIC*)svd->data;
231: PetscInt i,j,M,N,m,n,nconv;
232: PetscScalar sigma;
233: const PetscScalar *px;
234: Vec x,x1,x2;
237: EPSGetConverged(cyclic->eps,&nconv);
238: MatCreateVecs(cyclic->mat,&x,NULL);
239: MatGetSize(svd->A,&M,&N);
240: MatGetLocalSize(svd->A,&m,&n);
241: MatCreateVecsEmpty(svd->A,&x2,&x1);
242: for (i=0,j=0;i<nconv;i++) {
243: EPSGetEigenpair(cyclic->eps,i,&sigma,NULL,x,NULL);
244: if (PetscRealPart(sigma) > 0.0) {
245: VecGetArrayRead(x,&px);
246: VecPlaceArray(x1,px);
247: VecPlaceArray(x2,px+m);
248: BVInsertVec(svd->U,j,x1);
249: BVScaleColumn(svd->U,j,1.0/PETSC_SQRT2);
250: BVInsertVec(svd->V,j,x2);
251: BVScaleColumn(svd->V,j,1.0/PETSC_SQRT2);
252: VecResetArray(x1);
253: VecResetArray(x2);
254: VecRestoreArrayRead(x,&px);
255: j++;
256: }
257: }
258: VecDestroy(&x);
259: VecDestroy(&x1);
260: VecDestroy(&x2);
261: return(0);
262: }
264: static PetscErrorCode EPSMonitor_Cyclic(EPS eps,PetscInt its,PetscInt nconv,PetscScalar *eigr,PetscScalar *eigi,PetscReal *errest,PetscInt nest,void *ctx)
265: {
266: PetscInt i,j;
267: SVD svd = (SVD)ctx;
268: PetscScalar er,ei;
272: nconv = 0;
273: for (i=0,j=0;i<PetscMin(nest,svd->ncv);i++) {
274: er = eigr[i]; ei = eigi[i];
275: STBackTransform(eps->st,1,&er,&ei);
276: if (PetscRealPart(er) > 0.0) {
277: svd->sigma[j] = PetscRealPart(er);
278: svd->errest[j] = errest[i];
279: if (errest[i] && errest[i] < svd->tol) nconv++;
280: j++;
281: }
282: }
283: nest = j;
284: SVDMonitor(svd,its,nconv,svd->sigma,svd->errest,nest);
285: return(0);
286: }
288: PetscErrorCode SVDSetFromOptions_Cyclic(PetscOptionItems *PetscOptionsObject,SVD svd)
289: {
291: PetscBool set,val;
292: SVD_CYCLIC *cyclic = (SVD_CYCLIC*)svd->data;
293: ST st;
296: PetscOptionsHead(PetscOptionsObject,"SVD Cyclic Options");
298: PetscOptionsBool("-svd_cyclic_explicitmatrix","Use cyclic explicit matrix","SVDCyclicSetExplicitMatrix",cyclic->explicitmatrix,&val,&set);
299: if (set) { SVDCyclicSetExplicitMatrix(svd,val); }
301: PetscOptionsTail();
303: if (!cyclic->eps) { SVDCyclicGetEPS(svd,&cyclic->eps); }
304: if (!cyclic->explicitmatrix && !cyclic->usereps) {
305: /* use as default an ST with shell matrix and Jacobi */
306: EPSGetST(cyclic->eps,&st);
307: STSetMatMode(st,ST_MATMODE_SHELL);
308: }
309: EPSSetFromOptions(cyclic->eps);
310: return(0);
311: }
313: static PetscErrorCode SVDCyclicSetExplicitMatrix_Cyclic(SVD svd,PetscBool explicitmatrix)
314: {
315: SVD_CYCLIC *cyclic = (SVD_CYCLIC*)svd->data;
318: if (cyclic->explicitmatrix != explicitmatrix) {
319: cyclic->explicitmatrix = explicitmatrix;
320: svd->state = SVD_STATE_INITIAL;
321: }
322: return(0);
323: }
325: /*@
326: SVDCyclicSetExplicitMatrix - Indicate if the eigensolver operator
327: H(A) = [ 0 A ; A^T 0 ] must be computed explicitly.
329: Logically Collective on svd
331: Input Parameters:
332: + svd - singular value solver
333: - explicit - boolean flag indicating if H(A) is built explicitly
335: Options Database Key:
336: . -svd_cyclic_explicitmatrix <boolean> - Indicates the boolean flag
338: Level: advanced
340: .seealso: SVDCyclicGetExplicitMatrix()
341: @*/
342: PetscErrorCode SVDCyclicSetExplicitMatrix(SVD svd,PetscBool explicitmatrix)
343: {
349: PetscTryMethod(svd,"SVDCyclicSetExplicitMatrix_C",(SVD,PetscBool),(svd,explicitmatrix));
350: return(0);
351: }
353: static PetscErrorCode SVDCyclicGetExplicitMatrix_Cyclic(SVD svd,PetscBool *explicitmatrix)
354: {
355: SVD_CYCLIC *cyclic = (SVD_CYCLIC*)svd->data;
358: *explicitmatrix = cyclic->explicitmatrix;
359: return(0);
360: }
362: /*@
363: SVDCyclicGetExplicitMatrix - Returns the flag indicating if H(A) is built explicitly.
365: Not Collective
367: Input Parameter:
368: . svd - singular value solver
370: Output Parameter:
371: . explicit - the mode flag
373: Level: advanced
375: .seealso: SVDCyclicSetExplicitMatrix()
376: @*/
377: PetscErrorCode SVDCyclicGetExplicitMatrix(SVD svd,PetscBool *explicitmatrix)
378: {
384: PetscUseMethod(svd,"SVDCyclicGetExplicitMatrix_C",(SVD,PetscBool*),(svd,explicitmatrix));
385: return(0);
386: }
388: static PetscErrorCode SVDCyclicSetEPS_Cyclic(SVD svd,EPS eps)
389: {
390: PetscErrorCode ierr;
391: SVD_CYCLIC *cyclic = (SVD_CYCLIC*)svd->data;
394: PetscObjectReference((PetscObject)eps);
395: EPSDestroy(&cyclic->eps);
396: cyclic->eps = eps;
397: cyclic->usereps = PETSC_TRUE;
398: PetscLogObjectParent((PetscObject)svd,(PetscObject)cyclic->eps);
399: svd->state = SVD_STATE_INITIAL;
400: return(0);
401: }
403: /*@
404: SVDCyclicSetEPS - Associate an eigensolver object (EPS) to the
405: singular value solver.
407: Collective on svd
409: Input Parameters:
410: + svd - singular value solver
411: - eps - the eigensolver object
413: Level: advanced
415: .seealso: SVDCyclicGetEPS()
416: @*/
417: PetscErrorCode SVDCyclicSetEPS(SVD svd,EPS eps)
418: {
425: PetscTryMethod(svd,"SVDCyclicSetEPS_C",(SVD,EPS),(svd,eps));
426: return(0);
427: }
429: static PetscErrorCode SVDCyclicGetEPS_Cyclic(SVD svd,EPS *eps)
430: {
432: SVD_CYCLIC *cyclic = (SVD_CYCLIC*)svd->data;
435: if (!cyclic->eps) {
436: EPSCreate(PetscObjectComm((PetscObject)svd),&cyclic->eps);
437: PetscObjectIncrementTabLevel((PetscObject)cyclic->eps,(PetscObject)svd,1);
438: EPSSetOptionsPrefix(cyclic->eps,((PetscObject)svd)->prefix);
439: EPSAppendOptionsPrefix(cyclic->eps,"svd_cyclic_");
440: PetscLogObjectParent((PetscObject)svd,(PetscObject)cyclic->eps);
441: PetscObjectSetOptions((PetscObject)cyclic->eps,((PetscObject)svd)->options);
442: EPSSetWhichEigenpairs(cyclic->eps,EPS_LARGEST_REAL);
443: EPSMonitorSet(cyclic->eps,EPSMonitor_Cyclic,svd,NULL);
444: }
445: *eps = cyclic->eps;
446: return(0);
447: }
449: /*@
450: SVDCyclicGetEPS - Retrieve the eigensolver object (EPS) associated
451: to the singular value solver.
453: Not Collective
455: Input Parameter:
456: . svd - singular value solver
458: Output Parameter:
459: . eps - the eigensolver object
461: Level: advanced
463: .seealso: SVDCyclicSetEPS()
464: @*/
465: PetscErrorCode SVDCyclicGetEPS(SVD svd,EPS *eps)
466: {
472: PetscUseMethod(svd,"SVDCyclicGetEPS_C",(SVD,EPS*),(svd,eps));
473: return(0);
474: }
476: PetscErrorCode SVDView_Cyclic(SVD svd,PetscViewer viewer)
477: {
479: SVD_CYCLIC *cyclic = (SVD_CYCLIC*)svd->data;
480: PetscBool isascii;
483: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii);
484: if (isascii) {
485: if (!cyclic->eps) { SVDCyclicGetEPS(svd,&cyclic->eps); }
486: PetscViewerASCIIPrintf(viewer," %s matrix\n",cyclic->explicitmatrix?"explicit":"implicit");
487: PetscViewerASCIIPushTab(viewer);
488: EPSView(cyclic->eps,viewer);
489: PetscViewerASCIIPopTab(viewer);
490: }
491: return(0);
492: }
494: PetscErrorCode SVDReset_Cyclic(SVD svd)
495: {
497: SVD_CYCLIC *cyclic = (SVD_CYCLIC*)svd->data;
500: EPSReset(cyclic->eps);
501: MatDestroy(&cyclic->mat);
502: VecDestroy(&cyclic->x1);
503: VecDestroy(&cyclic->x2);
504: VecDestroy(&cyclic->y1);
505: VecDestroy(&cyclic->y2);
506: return(0);
507: }
509: PetscErrorCode SVDDestroy_Cyclic(SVD svd)
510: {
512: SVD_CYCLIC *cyclic = (SVD_CYCLIC*)svd->data;
515: EPSDestroy(&cyclic->eps);
516: PetscFree(svd->data);
517: PetscObjectComposeFunction((PetscObject)svd,"SVDCyclicSetEPS_C",NULL);
518: PetscObjectComposeFunction((PetscObject)svd,"SVDCyclicGetEPS_C",NULL);
519: PetscObjectComposeFunction((PetscObject)svd,"SVDCyclicSetExplicitMatrix_C",NULL);
520: PetscObjectComposeFunction((PetscObject)svd,"SVDCyclicGetExplicitMatrix_C",NULL);
521: return(0);
522: }
524: SLEPC_EXTERN PetscErrorCode SVDCreate_Cyclic(SVD svd)
525: {
527: SVD_CYCLIC *cyclic;
530: PetscNewLog(svd,&cyclic);
531: svd->data = (void*)cyclic;
532: svd->ops->solve = SVDSolve_Cyclic;
533: svd->ops->setup = SVDSetUp_Cyclic;
534: svd->ops->setfromoptions = SVDSetFromOptions_Cyclic;
535: svd->ops->destroy = SVDDestroy_Cyclic;
536: svd->ops->reset = SVDReset_Cyclic;
537: svd->ops->view = SVDView_Cyclic;
538: svd->ops->computevectors = SVDComputeVectors_Cyclic;
539: PetscObjectComposeFunction((PetscObject)svd,"SVDCyclicSetEPS_C",SVDCyclicSetEPS_Cyclic);
540: PetscObjectComposeFunction((PetscObject)svd,"SVDCyclicGetEPS_C",SVDCyclicGetEPS_Cyclic);
541: PetscObjectComposeFunction((PetscObject)svd,"SVDCyclicSetExplicitMatrix_C",SVDCyclicSetExplicitMatrix_Cyclic);
542: PetscObjectComposeFunction((PetscObject)svd,"SVDCyclicGetExplicitMatrix_C",SVDCyclicGetExplicitMatrix_Cyclic);
543: return(0);
544: }