Actual source code: cyclic.c
slepc-3.7.0 2016-05-16
1: /*
3: SLEPc singular value solver: "cyclic"
5: Method: Uses a Hermitian eigensolver for H(A) = [ 0 A ; A^T 0 ]
7: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
8: SLEPc - Scalable Library for Eigenvalue Problem Computations
9: Copyright (c) 2002-2016, Universitat Politecnica de Valencia, Spain
11: This file is part of SLEPc.
13: SLEPc is free software: you can redistribute it and/or modify it under the
14: terms of version 3 of the GNU Lesser General Public License as published by
15: the Free Software Foundation.
17: SLEPc is distributed in the hope that it will be useful, but WITHOUT ANY
18: WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
19: FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for
20: more details.
22: You should have received a copy of the GNU Lesser General Public License
23: along with SLEPc. If not, see <http://www.gnu.org/licenses/>.
24: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
25: */
27: #include <slepc/private/svdimpl.h> /*I "slepcsvd.h" I*/
28: #include <slepc/private/epsimpl.h> /*I "slepceps.h" I*/
30: typedef struct {
31: PetscBool explicitmatrix;
32: EPS eps;
33: Mat mat;
34: Vec x1,x2,y1,y2;
35: } SVD_CYCLIC;
39: static PetscErrorCode MatMult_Cyclic(Mat B,Vec x,Vec y)
40: {
41: PetscErrorCode ierr;
42: SVD svd;
43: SVD_CYCLIC *cyclic;
44: const PetscScalar *px;
45: PetscScalar *py;
46: PetscInt m;
49: MatShellGetContext(B,(void**)&svd);
50: cyclic = (SVD_CYCLIC*)svd->data;
51: SVDMatGetLocalSize(svd,&m,NULL);
52: VecGetArrayRead(x,&px);
53: VecGetArray(y,&py);
54: VecPlaceArray(cyclic->x1,px);
55: VecPlaceArray(cyclic->x2,px+m);
56: VecPlaceArray(cyclic->y1,py);
57: VecPlaceArray(cyclic->y2,py+m);
58: SVDMatMult(svd,PETSC_FALSE,cyclic->x2,cyclic->y1);
59: SVDMatMult(svd,PETSC_TRUE,cyclic->x1,cyclic->y2);
60: VecResetArray(cyclic->x1);
61: VecResetArray(cyclic->x2);
62: VecResetArray(cyclic->y1);
63: VecResetArray(cyclic->y2);
64: VecRestoreArrayRead(x,&px);
65: VecRestoreArray(y,&py);
66: return(0);
67: }
71: static PetscErrorCode MatGetDiagonal_Cyclic(Mat B,Vec diag)
72: {
76: VecSet(diag,0.0);
77: return(0);
78: }
82: PetscErrorCode SVDSetUp_Cyclic(SVD svd)
83: {
84: PetscErrorCode ierr;
85: SVD_CYCLIC *cyclic = (SVD_CYCLIC*)svd->data;
86: PetscInt M,N,m,n,i,isl,Istart,Iend;
87: const PetscScalar *isa;
88: PetscScalar *va;
89: PetscBool trackall,gpu;
90: Vec v;
91: Mat Zm,Zn;
94: PetscObjectTypeCompareAny((PetscObject)svd->A,&gpu,MATSEQAIJCUSP,MATMPIAIJCUSP,MATSEQAIJCUSPARSE,MATMPIAIJCUSPARSE,"");
95: if (gpu) SETERRQ(PetscObjectComm((PetscObject)svd),PETSC_ERR_SUP,"Solver not implemented for GPU matrices");
96: SVDMatGetSize(svd,&M,&N);
97: SVDMatGetLocalSize(svd,&m,&n);
98: if (!cyclic->mat) {
99: if (cyclic->explicitmatrix) {
100: if (!svd->AT) SETERRQ(PetscObjectComm((PetscObject)svd),PETSC_ERR_SUP,"Cannot use explicit cyclic matrix with implicit transpose");
101: MatCreate(PetscObjectComm((PetscObject)svd),&Zm);
102: MatSetSizes(Zm,m,m,M,M);
103: MatSetFromOptions(Zm);
104: MatSetUp(Zm);
105: MatGetOwnershipRange(Zm,&Istart,&Iend);
106: for (i=Istart;i<Iend;i++) {
107: MatSetValue(Zm,i,i,0.0,INSERT_VALUES);
108: }
109: MatAssemblyBegin(Zm,MAT_FINAL_ASSEMBLY);
110: MatAssemblyEnd(Zm,MAT_FINAL_ASSEMBLY);
111: MatCreate(PetscObjectComm((PetscObject)svd),&Zn);
112: MatSetSizes(Zn,n,n,N,N);
113: MatSetFromOptions(Zn);
114: MatSetUp(Zn);
115: MatGetOwnershipRange(Zn,&Istart,&Iend);
116: for (i=Istart;i<Iend;i++) {
117: MatSetValue(Zn,i,i,0.0,INSERT_VALUES);
118: }
119: MatAssemblyBegin(Zn,MAT_FINAL_ASSEMBLY);
120: MatAssemblyEnd(Zn,MAT_FINAL_ASSEMBLY);
121: SlepcMatTile(1.0,Zm,1.0,svd->A,1.0,svd->AT,1.0,Zn,&cyclic->mat);
122: PetscLogObjectParent((PetscObject)svd,(PetscObject)cyclic->mat);
123: MatDestroy(&Zm);
124: MatDestroy(&Zn);
125: } else {
126: VecCreateMPIWithArray(PetscObjectComm((PetscObject)svd),1,m,M,NULL,&cyclic->x1);
127: VecCreateMPIWithArray(PetscObjectComm((PetscObject)svd),1,n,N,NULL,&cyclic->x2);
128: VecCreateMPIWithArray(PetscObjectComm((PetscObject)svd),1,m,M,NULL,&cyclic->y1);
129: VecCreateMPIWithArray(PetscObjectComm((PetscObject)svd),1,n,N,NULL,&cyclic->y2);
130: PetscLogObjectParent((PetscObject)svd,(PetscObject)cyclic->x1);
131: PetscLogObjectParent((PetscObject)svd,(PetscObject)cyclic->x2);
132: PetscLogObjectParent((PetscObject)svd,(PetscObject)cyclic->y1);
133: PetscLogObjectParent((PetscObject)svd,(PetscObject)cyclic->y2);
134: MatCreateShell(PetscObjectComm((PetscObject)svd),m+n,m+n,M+N,M+N,svd,&cyclic->mat);
135: MatShellSetOperation(cyclic->mat,MATOP_MULT,(void(*)(void))MatMult_Cyclic);
136: MatShellSetOperation(cyclic->mat,MATOP_GET_DIAGONAL,(void(*)(void))MatGetDiagonal_Cyclic);
137: }
138: PetscLogObjectParent((PetscObject)svd,(PetscObject)cyclic->mat);
139: }
141: if (!cyclic->eps) { SVDCyclicGetEPS(svd,&cyclic->eps); }
142: EPSSetOperators(cyclic->eps,cyclic->mat,NULL);
143: EPSSetProblemType(cyclic->eps,EPS_HEP);
144: if (svd->which == SVD_LARGEST) {
145: EPSSetWhichEigenpairs(cyclic->eps,EPS_LARGEST_REAL);
146: } else {
147: EPSSetEigenvalueComparison(cyclic->eps,SlepcCompareSmallestPosReal,NULL);
148: EPSSetTarget(cyclic->eps,0.0);
149: }
150: EPSSetDimensions(cyclic->eps,svd->nsv,svd->ncv?svd->ncv:PETSC_DEFAULT,svd->mpd?svd->mpd:PETSC_DEFAULT);
151: EPSSetTolerances(cyclic->eps,svd->tol==PETSC_DEFAULT?SLEPC_DEFAULT_TOL/10.0:svd->tol,svd->max_it?svd->max_it:PETSC_DEFAULT);
152: switch (svd->conv) {
153: case SVD_CONV_ABS:
154: EPSSetConvergenceTest(cyclic->eps,EPS_CONV_ABS);break;
155: case SVD_CONV_REL:
156: EPSSetConvergenceTest(cyclic->eps,EPS_CONV_REL);break;
157: case SVD_CONV_USER:
158: SETERRQ(PetscObjectComm((PetscObject)svd),PETSC_ERR_SUP,"User-defined convergence test not supported in this solver");
159: }
160: if (svd->stop!=SVD_STOP_BASIC) SETERRQ(PetscObjectComm((PetscObject)svd),PETSC_ERR_SUP,"User-defined stopping test not supported in this solver");
161: /* Transfer the trackall option from svd to eps */
162: SVDGetTrackAll(svd,&trackall);
163: EPSSetTrackAll(cyclic->eps,trackall);
164: /* Transfer the initial subspace from svd to eps */
165: if (svd->nini<0 || svd->ninil<0) {
166: for (i=0;i<-PetscMin(svd->nini,svd->ninil);i++) {
167: MatCreateVecs(cyclic->mat,&v,NULL);
168: VecGetArray(v,&va);
169: if (i<-svd->ninil) {
170: VecGetSize(svd->ISL[i],&isl);
171: if (isl!=m) SETERRQ(PetscObjectComm((PetscObject)svd),PETSC_ERR_SUP,"Size mismatch for left initial vector");
172: VecGetArrayRead(svd->ISL[i],&isa);
173: PetscMemcpy(va,isa,sizeof(PetscScalar)*m);
174: VecRestoreArrayRead(svd->IS[i],&isa);
175: } else {
176: PetscMemzero(&va,sizeof(PetscScalar)*m);
177: }
178: if (i<-svd->nini) {
179: VecGetSize(svd->IS[i],&isl);
180: if (isl!=n) SETERRQ(PetscObjectComm((PetscObject)svd),PETSC_ERR_SUP,"Size mismatch for right initial vector");
181: VecGetArrayRead(svd->IS[i],&isa);
182: PetscMemcpy(va+m,isa,sizeof(PetscScalar)*n);
183: VecRestoreArrayRead(svd->IS[i],&isa);
184: } else {
185: PetscMemzero(va+m,sizeof(PetscScalar)*n);
186: }
187: VecRestoreArray(v,&va);
188: VecDestroy(&svd->IS[i]);
189: svd->IS[i] = v;
190: }
191: svd->nini = PetscMin(svd->nini,svd->ninil);
192: EPSSetInitialSpace(cyclic->eps,-svd->nini,svd->IS);
193: SlepcBasisDestroy_Private(&svd->nini,&svd->IS);
194: SlepcBasisDestroy_Private(&svd->ninil,&svd->ISL);
195: }
196: EPSSetUp(cyclic->eps);
197: EPSGetDimensions(cyclic->eps,NULL,&svd->ncv,&svd->mpd);
198: svd->ncv = PetscMin(svd->ncv,PetscMin(M,N));
199: EPSGetTolerances(cyclic->eps,NULL,&svd->max_it);
200: if (svd->tol==PETSC_DEFAULT) svd->tol = SLEPC_DEFAULT_TOL;
202: svd->leftbasis = PETSC_TRUE;
203: SVDAllocateSolution(svd,0);
204: return(0);
205: }
209: PetscErrorCode SVDSolve_Cyclic(SVD svd)
210: {
211: PetscErrorCode ierr;
212: SVD_CYCLIC *cyclic = (SVD_CYCLIC*)svd->data;
213: PetscInt i,j,M,N,m,n;
214: PetscScalar sigma;
215: const PetscScalar *px;
216: Vec x,x1,x2;
219: EPSSolve(cyclic->eps);
220: EPSGetConverged(cyclic->eps,&svd->nconv);
221: EPSGetIterationNumber(cyclic->eps,&svd->its);
222: EPSGetConvergedReason(cyclic->eps,(EPSConvergedReason*)&svd->reason);
224: MatCreateVecs(cyclic->mat,&x,NULL);
225: SVDMatGetSize(svd,&M,&N);
226: SVDMatGetLocalSize(svd,&m,&n);
227: VecCreateMPIWithArray(PetscObjectComm((PetscObject)svd),1,m,M,NULL,&x1);
228: VecCreateMPIWithArray(PetscObjectComm((PetscObject)svd),1,n,N,NULL,&x2);
229: for (i=0,j=0;i<svd->nconv;i++) {
230: EPSGetEigenpair(cyclic->eps,i,&sigma,NULL,x,NULL);
231: if (PetscRealPart(sigma) > 0.0) {
232: svd->sigma[j] = PetscRealPart(sigma);
233: VecGetArrayRead(x,&px);
234: VecPlaceArray(x1,px);
235: VecPlaceArray(x2,px+m);
236: BVInsertVec(svd->U,j,x1);
237: BVScaleColumn(svd->U,j,1.0/PetscSqrtReal(2.0));
238: BVInsertVec(svd->V,j,x2);
239: BVScaleColumn(svd->V,j,1.0/PetscSqrtReal(2.0));
240: VecResetArray(x1);
241: VecResetArray(x2);
242: VecRestoreArrayRead(x,&px);
243: j++;
244: }
245: }
246: svd->nconv = j;
248: VecDestroy(&x);
249: VecDestroy(&x1);
250: VecDestroy(&x2);
251: return(0);
252: }
256: static PetscErrorCode EPSMonitor_Cyclic(EPS eps,PetscInt its,PetscInt nconv,PetscScalar *eigr,PetscScalar *eigi,PetscReal *errest,PetscInt nest,void *ctx)
257: {
258: PetscInt i,j;
259: SVD svd = (SVD)ctx;
260: PetscScalar er,ei;
264: nconv = 0;
265: for (i=0,j=0;i<PetscMin(nest,svd->ncv);i++) {
266: er = eigr[i]; ei = eigi[i];
267: STBackTransform(eps->st,1,&er,&ei);
268: if (PetscRealPart(er) > 0.0) {
269: svd->sigma[j] = PetscRealPart(er);
270: svd->errest[j] = errest[i];
271: if (errest[i] && errest[i] < svd->tol) nconv++;
272: j++;
273: }
274: }
275: nest = j;
276: SVDMonitor(svd,its,nconv,svd->sigma,svd->errest,nest);
277: return(0);
278: }
282: PetscErrorCode SVDSetFromOptions_Cyclic(PetscOptionItems *PetscOptionsObject,SVD svd)
283: {
285: PetscBool set,val;
286: SVD_CYCLIC *cyclic = (SVD_CYCLIC*)svd->data;
287: ST st;
290: PetscOptionsHead(PetscOptionsObject,"SVD Cyclic Options");
291: PetscOptionsBool("-svd_cyclic_explicitmatrix","Use cyclic explicit matrix","SVDCyclicSetExplicitMatrix",cyclic->explicitmatrix,&val,&set);
292: if (set) {
293: SVDCyclicSetExplicitMatrix(svd,val);
294: }
295: if (!cyclic->eps) { SVDCyclicGetEPS(svd,&cyclic->eps); }
296: EPSSetFromOptions(cyclic->eps);
297: if (!cyclic->explicitmatrix) {
298: /* use as default an ST with shell matrix and Jacobi */
299: EPSGetST(cyclic->eps,&st);
300: STSetMatMode(st,ST_MATMODE_SHELL);
301: }
302: PetscOptionsTail();
303: return(0);
304: }
308: static PetscErrorCode SVDCyclicSetExplicitMatrix_Cyclic(SVD svd,PetscBool explicitmatrix)
309: {
310: SVD_CYCLIC *cyclic = (SVD_CYCLIC*)svd->data;
313: cyclic->explicitmatrix = explicitmatrix;
314: return(0);
315: }
319: /*@
320: SVDCyclicSetExplicitMatrix - Indicate if the eigensolver operator
321: H(A) = [ 0 A ; A^T 0 ] must be computed explicitly.
323: Logically Collective on SVD
325: Input Parameters:
326: + svd - singular value solver
327: - explicit - boolean flag indicating if H(A) is built explicitly
329: Options Database Key:
330: . -svd_cyclic_explicitmatrix <boolean> - Indicates the boolean flag
332: Level: advanced
334: .seealso: SVDCyclicGetExplicitMatrix()
335: @*/
336: PetscErrorCode SVDCyclicSetExplicitMatrix(SVD svd,PetscBool explicitmatrix)
337: {
343: PetscTryMethod(svd,"SVDCyclicSetExplicitMatrix_C",(SVD,PetscBool),(svd,explicitmatrix));
344: return(0);
345: }
349: static PetscErrorCode SVDCyclicGetExplicitMatrix_Cyclic(SVD svd,PetscBool *explicitmatrix)
350: {
351: SVD_CYCLIC *cyclic = (SVD_CYCLIC*)svd->data;
354: *explicitmatrix = cyclic->explicitmatrix;
355: return(0);
356: }
360: /*@
361: SVDCyclicGetExplicitMatrix - Returns the flag indicating if H(A) is built explicitly
363: Not Collective
365: Input Parameter:
366: . svd - singular value solver
368: Output Parameter:
369: . explicit - the mode flag
371: Level: advanced
373: .seealso: SVDCyclicSetExplicitMatrix()
374: @*/
375: PetscErrorCode SVDCyclicGetExplicitMatrix(SVD svd,PetscBool *explicitmatrix)
376: {
382: PetscUseMethod(svd,"SVDCyclicGetExplicitMatrix_C",(SVD,PetscBool*),(svd,explicitmatrix));
383: return(0);
384: }
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: PetscLogObjectParent((PetscObject)svd,(PetscObject)cyclic->eps);
398: svd->state = SVD_STATE_INITIAL;
399: return(0);
400: }
404: /*@
405: SVDCyclicSetEPS - Associate an eigensolver object (EPS) to the
406: singular value solver.
408: Collective on SVD
410: Input Parameters:
411: + svd - singular value solver
412: - eps - the eigensolver object
414: Level: advanced
416: .seealso: SVDCyclicGetEPS()
417: @*/
418: PetscErrorCode SVDCyclicSetEPS(SVD svd,EPS eps)
419: {
426: PetscTryMethod(svd,"SVDCyclicSetEPS_C",(SVD,EPS),(svd,eps));
427: return(0);
428: }
432: static PetscErrorCode SVDCyclicGetEPS_Cyclic(SVD svd,EPS *eps)
433: {
435: SVD_CYCLIC *cyclic = (SVD_CYCLIC*)svd->data;
438: if (!cyclic->eps) {
439: EPSCreate(PetscObjectComm((PetscObject)svd),&cyclic->eps);
440: EPSSetOptionsPrefix(cyclic->eps,((PetscObject)svd)->prefix);
441: EPSAppendOptionsPrefix(cyclic->eps,"svd_cyclic_");
442: PetscObjectIncrementTabLevel((PetscObject)cyclic->eps,(PetscObject)svd,1);
443: PetscLogObjectParent((PetscObject)svd,(PetscObject)cyclic->eps);
444: EPSSetWhichEigenpairs(cyclic->eps,EPS_LARGEST_REAL);
445: EPSMonitorSet(cyclic->eps,EPSMonitor_Cyclic,svd,NULL);
446: }
447: *eps = cyclic->eps;
448: return(0);
449: }
453: /*@
454: SVDCyclicGetEPS - Retrieve the eigensolver object (EPS) associated
455: to the singular value solver.
457: Not Collective
459: Input Parameter:
460: . svd - singular value solver
462: Output Parameter:
463: . eps - the eigensolver object
465: Level: advanced
467: .seealso: SVDCyclicSetEPS()
468: @*/
469: PetscErrorCode SVDCyclicGetEPS(SVD svd,EPS *eps)
470: {
476: PetscUseMethod(svd,"SVDCyclicGetEPS_C",(SVD,EPS*),(svd,eps));
477: return(0);
478: }
482: PetscErrorCode SVDView_Cyclic(SVD svd,PetscViewer viewer)
483: {
485: SVD_CYCLIC *cyclic = (SVD_CYCLIC*)svd->data;
486: PetscBool isascii;
489: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii);
490: if (isascii) {
491: if (!cyclic->eps) { SVDCyclicGetEPS(svd,&cyclic->eps); }
492: PetscViewerASCIIPrintf(viewer," Cyclic: %s matrix\n",cyclic->explicitmatrix?"explicit":"implicit");
493: PetscViewerASCIIPushTab(viewer);
494: EPSView(cyclic->eps,viewer);
495: PetscViewerASCIIPopTab(viewer);
496: }
497: return(0);
498: }
502: PetscErrorCode SVDReset_Cyclic(SVD svd)
503: {
505: SVD_CYCLIC *cyclic = (SVD_CYCLIC*)svd->data;
508: if (!cyclic->eps) { EPSReset(cyclic->eps); }
509: MatDestroy(&cyclic->mat);
510: VecDestroy(&cyclic->x1);
511: VecDestroy(&cyclic->x2);
512: VecDestroy(&cyclic->y1);
513: VecDestroy(&cyclic->y2);
514: return(0);
515: }
519: PetscErrorCode SVDDestroy_Cyclic(SVD svd)
520: {
522: SVD_CYCLIC *cyclic = (SVD_CYCLIC*)svd->data;
525: EPSDestroy(&cyclic->eps);
526: PetscFree(svd->data);
527: PetscObjectComposeFunction((PetscObject)svd,"SVDCyclicSetEPS_C",NULL);
528: PetscObjectComposeFunction((PetscObject)svd,"SVDCyclicGetEPS_C",NULL);
529: PetscObjectComposeFunction((PetscObject)svd,"SVDCyclicSetExplicitMatrix_C",NULL);
530: PetscObjectComposeFunction((PetscObject)svd,"SVDCyclicGetExplicitMatrix_C",NULL);
531: return(0);
532: }
536: PETSC_EXTERN PetscErrorCode SVDCreate_Cyclic(SVD svd)
537: {
539: SVD_CYCLIC *cyclic;
542: PetscNewLog(svd,&cyclic);
543: svd->data = (void*)cyclic;
544: svd->ops->solve = SVDSolve_Cyclic;
545: svd->ops->setup = SVDSetUp_Cyclic;
546: svd->ops->setfromoptions = SVDSetFromOptions_Cyclic;
547: svd->ops->destroy = SVDDestroy_Cyclic;
548: svd->ops->reset = SVDReset_Cyclic;
549: svd->ops->view = SVDView_Cyclic;
550: PetscObjectComposeFunction((PetscObject)svd,"SVDCyclicSetEPS_C",SVDCyclicSetEPS_Cyclic);
551: PetscObjectComposeFunction((PetscObject)svd,"SVDCyclicGetEPS_C",SVDCyclicGetEPS_Cyclic);
552: PetscObjectComposeFunction((PetscObject)svd,"SVDCyclicSetExplicitMatrix_C",SVDCyclicSetExplicitMatrix_Cyclic);
553: PetscObjectComposeFunction((PetscObject)svd,"SVDCyclicGetExplicitMatrix_C",SVDCyclicGetExplicitMatrix_Cyclic);
554: return(0);
555: }