Actual source code: ciss.c
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: */
10: /*
11: SLEPc eigensolver: "ciss"
13: Method: Contour Integral Spectral Slicing
15: Algorithm:
17: Contour integral based on Sakurai-Sugiura method to construct a
18: subspace, with various eigenpair extractions (Rayleigh-Ritz,
19: explicit moment).
21: Based on code contributed by Y. Maeda, T. Sakurai.
23: References:
25: [1] T. Sakurai and H. Sugiura, "A projection method for generalized
26: eigenvalue problems", J. Comput. Appl. Math. 159:119-128, 2003.
28: [2] T. Sakurai and H. Tadano, "CIRR: a Rayleigh-Ritz type method with
29: contour integral for generalized eigenvalue problems", Hokkaido
30: Math. J. 36:745-757, 2007.
31: */
33: #include <slepc/private/epsimpl.h>
34: #include <slepc/private/slepccontour.h>
35: #include <slepcblaslapack.h>
37: typedef struct {
38: /* user parameters */
39: PetscInt N; /* number of integration points (32) */
40: PetscInt L; /* block size (16) */
41: PetscInt M; /* moment degree (N/4 = 4) */
42: PetscReal delta; /* threshold of singular value (1e-12) */
43: PetscInt L_max; /* maximum number of columns of the source matrix V */
44: PetscReal spurious_threshold; /* discard spurious eigenpairs */
45: PetscBool isreal; /* A and B are real */
46: PetscInt npart; /* number of partitions */
47: PetscInt refine_inner;
48: PetscInt refine_blocksize;
49: EPSCISSQuadRule quad;
50: EPSCISSExtraction extraction;
51: PetscBool usest;
52: /* private data */
53: SlepcContourData contour;
54: PetscReal *sigma; /* threshold for numerical rank */
55: PetscScalar *weight;
56: PetscScalar *omega;
57: PetscScalar *pp;
58: BV V;
59: BV S;
60: BV pV;
61: BV Y;
62: PetscBool useconj;
63: PetscBool usest_set; /* whether the user set the usest flag or not */
64: PetscObjectId rgid;
65: PetscObjectState rgstate;
66: } EPS_CISS;
68: /*
69: Set up KSP solvers for every integration point, only called if !ctx->usest
70: */
71: static PetscErrorCode EPSCISSSetUp(EPS eps,Mat A,Mat B,Mat Pa,Mat Pb)
72: {
73: EPS_CISS *ctx = (EPS_CISS*)eps->data;
74: SlepcContourData contour;
75: PetscInt i,p_id,nsplit;
76: Mat Amat,Pmat;
77: MatStructure str,strp;
79: PetscFunctionBegin;
80: if (!ctx->contour || !ctx->contour->ksp) PetscCall(EPSCISSGetKSPs(eps,NULL,NULL));
81: PetscAssert(ctx->contour && ctx->contour->ksp,PetscObjectComm((PetscObject)eps),PETSC_ERR_PLIB,"Something went wrong with EPSCISSGetKSPs()");
82: contour = ctx->contour;
83: PetscCall(STGetMatStructure(eps->st,&str));
84: PetscCall(STGetSplitPreconditionerInfo(eps->st,&nsplit,&strp));
85: for (i=0;i<contour->npoints;i++) {
86: p_id = i*contour->subcomm->n + contour->subcomm->color;
87: PetscCall(MatDuplicate(A,MAT_COPY_VALUES,&Amat));
88: if (B) PetscCall(MatAXPY(Amat,-ctx->omega[p_id],B,str));
89: else PetscCall(MatShift(Amat,-ctx->omega[p_id]));
90: if (nsplit) {
91: PetscCall(MatDuplicate(Pa,MAT_COPY_VALUES,&Pmat));
92: if (Pb) PetscCall(MatAXPY(Pmat,-ctx->omega[p_id],Pb,strp));
93: else PetscCall(MatShift(Pmat,-ctx->omega[p_id]));
94: } else Pmat = Amat;
95: PetscCall(EPS_KSPSetOperators(contour->ksp[i],Amat,Amat));
96: PetscCall(MatDestroy(&Amat));
97: if (nsplit) PetscCall(MatDestroy(&Pmat));
98: }
99: PetscFunctionReturn(PETSC_SUCCESS);
100: }
102: /*
103: Y_i = (A-z_i B)^{-1}BV for every integration point, Y=[Y_i] is in the context
104: */
105: static PetscErrorCode EPSCISSSolve(EPS eps,Mat B,BV V,PetscInt L_start,PetscInt L_end)
106: {
107: EPS_CISS *ctx = (EPS_CISS*)eps->data;
108: SlepcContourData contour;
109: PetscInt i,p_id;
110: Mat MV,BMV=NULL,MC;
111: KSP ksp;
113: PetscFunctionBegin;
114: if (!ctx->contour || !ctx->contour->ksp) PetscCall(EPSCISSGetKSPs(eps,NULL,NULL));
115: contour = ctx->contour;
116: PetscAssert(ctx->contour && ctx->contour->ksp,PetscObjectComm((PetscObject)eps),PETSC_ERR_PLIB,"Something went wrong with EPSCISSGetKSPs()");
117: PetscCall(BVSetActiveColumns(V,L_start,L_end));
118: PetscCall(BVGetMat(V,&MV));
119: for (i=0;i<contour->npoints;i++) {
120: p_id = i*contour->subcomm->n + contour->subcomm->color;
121: if (ctx->usest) {
122: PetscCall(STSetShift(eps->st,ctx->omega[p_id]));
123: PetscCall(STGetKSP(eps->st,&ksp));
124: } else ksp = contour->ksp[i];
125: PetscCall(BVSetActiveColumns(ctx->Y,i*ctx->L+L_start,i*ctx->L+L_end));
126: PetscCall(BVGetMat(ctx->Y,&MC));
127: if (B) {
128: if (!i) {
129: PetscCall(MatProductCreate(B,MV,NULL,&BMV));
130: PetscCall(MatProductSetType(BMV,MATPRODUCT_AB));
131: PetscCall(MatProductSetFromOptions(BMV));
132: PetscCall(MatProductSymbolic(BMV));
133: }
134: PetscCall(MatProductNumeric(BMV));
135: PetscCall(KSPMatSolve(ksp,BMV,MC));
136: } else PetscCall(KSPMatSolve(ksp,MV,MC));
137: PetscCall(BVRestoreMat(ctx->Y,&MC));
138: if (ctx->usest && i<contour->npoints-1) PetscCall(KSPReset(ksp));
139: }
140: PetscCall(MatDestroy(&BMV));
141: PetscCall(BVRestoreMat(V,&MV));
142: PetscFunctionReturn(PETSC_SUCCESS);
143: }
145: static PetscErrorCode rescale_eig(EPS eps,PetscInt nv)
146: {
147: EPS_CISS *ctx = (EPS_CISS*)eps->data;
148: PetscInt i;
149: PetscScalar center;
150: PetscReal radius,a,b,c,d,rgscale;
151: #if defined(PETSC_USE_COMPLEX)
152: PetscReal start_ang,end_ang,vscale,theta;
153: #endif
154: PetscBool isring,isellipse,isinterval;
156: PetscFunctionBegin;
157: PetscCall(PetscObjectTypeCompare((PetscObject)eps->rg,RGELLIPSE,&isellipse));
158: PetscCall(PetscObjectTypeCompare((PetscObject)eps->rg,RGRING,&isring));
159: PetscCall(PetscObjectTypeCompare((PetscObject)eps->rg,RGINTERVAL,&isinterval));
160: PetscCall(RGGetScale(eps->rg,&rgscale));
161: if (isinterval) {
162: PetscCall(RGIntervalGetEndpoints(eps->rg,NULL,NULL,&c,&d));
163: if (c==d) {
164: for (i=0;i<nv;i++) {
165: #if defined(PETSC_USE_COMPLEX)
166: eps->eigr[i] = PetscRealPart(eps->eigr[i]);
167: #else
168: eps->eigi[i] = 0;
169: #endif
170: }
171: }
172: }
173: if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {
174: if (isellipse) {
175: PetscCall(RGEllipseGetParameters(eps->rg,¢er,&radius,NULL));
176: for (i=0;i<nv;i++) eps->eigr[i] = rgscale*(center + radius*eps->eigr[i]);
177: } else if (isinterval) {
178: PetscCall(RGIntervalGetEndpoints(eps->rg,&a,&b,&c,&d));
179: if (ctx->quad == EPS_CISS_QUADRULE_CHEBYSHEV) {
180: for (i=0;i<nv;i++) {
181: if (c==d) eps->eigr[i] = ((eps->eigr[i]+1.0)*(b-a)/2.0+a)*rgscale;
182: if (a==b) {
183: #if defined(PETSC_USE_COMPLEX)
184: eps->eigr[i] = ((eps->eigr[i]+1.0)*(d-c)/2.0+c)*rgscale*PETSC_i;
185: #else
186: SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Integration points on a vertical line require complex arithmetic");
187: #endif
188: }
189: }
190: } else {
191: center = (b+a)/2.0+(d+c)/2.0*PETSC_PI;
192: radius = PetscSqrtReal(PetscPowRealInt((b-a)/2.0,2)+PetscPowRealInt((d-c)/2.0,2));
193: for (i=0;i<nv;i++) eps->eigr[i] = center + radius*eps->eigr[i];
194: }
195: } else if (isring) { /* only supported in complex scalars */
196: #if defined(PETSC_USE_COMPLEX)
197: PetscCall(RGRingGetParameters(eps->rg,¢er,&radius,&vscale,&start_ang,&end_ang,NULL));
198: if (ctx->quad == EPS_CISS_QUADRULE_CHEBYSHEV) {
199: for (i=0;i<nv;i++) {
200: theta = (start_ang*2.0+(end_ang-start_ang)*(PetscRealPart(eps->eigr[i])+1.0))*PETSC_PI;
201: eps->eigr[i] = rgscale*center + (rgscale*radius+PetscImaginaryPart(eps->eigr[i]))*PetscCMPLX(PetscCosReal(theta),vscale*PetscSinReal(theta));
202: }
203: } else {
204: for (i=0;i<nv;i++) eps->eigr[i] = rgscale*(center + radius*eps->eigr[i]);
205: }
206: #endif
207: }
208: }
209: PetscFunctionReturn(PETSC_SUCCESS);
210: }
212: static PetscErrorCode EPSSetUp_CISS(EPS eps)
213: {
214: EPS_CISS *ctx = (EPS_CISS*)eps->data;
215: SlepcContourData contour;
216: PetscBool istrivial,isring,isellipse,isinterval,flg;
217: PetscReal c,d;
218: PetscInt nsplit;
219: PetscRandom rand;
220: PetscObjectId id;
221: PetscObjectState state;
222: Mat A[2],Psplit[2];
223: Vec v0;
225: PetscFunctionBegin;
226: EPSCheckNotStructured(eps);
227: if (eps->ncv==PETSC_DETERMINE) {
228: eps->ncv = ctx->L_max*ctx->M;
229: if (eps->ncv>eps->n) {
230: eps->ncv = eps->n;
231: ctx->L_max = eps->ncv/ctx->M;
232: PetscCheck(ctx->L_max,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Cannot adjust solver parameters, try setting a smaller value of M (moment size)");
233: }
234: } else {
235: PetscCall(EPSSetDimensions_Default(eps,&eps->nev,&eps->ncv,&eps->mpd));
236: ctx->L_max = eps->ncv/ctx->M;
237: if (!ctx->L_max) {
238: ctx->L_max = 1;
239: eps->ncv = ctx->L_max*ctx->M;
240: }
241: }
242: ctx->L = PetscMin(ctx->L,ctx->L_max);
243: if (eps->max_it==PETSC_DETERMINE) eps->max_it = 5;
244: if (eps->mpd==PETSC_DETERMINE) eps->mpd = eps->ncv;
245: if (!eps->which) eps->which = EPS_ALL;
246: PetscCheck(eps->which==EPS_ALL,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"This solver supports only computing all eigenvalues");
247: EPSCheckUnsupported(eps,EPS_FEATURE_BALANCE | EPS_FEATURE_ARBITRARY | EPS_FEATURE_EXTRACTION | EPS_FEATURE_STOPPING | EPS_FEATURE_TWOSIDED);
249: /* check region */
250: PetscCall(RGIsTrivial(eps->rg,&istrivial));
251: PetscCheck(!istrivial,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"CISS requires a nontrivial region, e.g. -rg_type ellipse ...");
252: PetscCall(RGGetComplement(eps->rg,&flg));
253: PetscCheck(!flg,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"A region with complement flag set is not allowed");
254: PetscCall(PetscObjectTypeCompare((PetscObject)eps->rg,RGELLIPSE,&isellipse));
255: PetscCall(PetscObjectTypeCompare((PetscObject)eps->rg,RGRING,&isring));
256: PetscCall(PetscObjectTypeCompare((PetscObject)eps->rg,RGINTERVAL,&isinterval));
257: PetscCheck(isellipse || isring || isinterval,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Currently only implemented for interval, elliptic or ring regions");
259: /* if the region has changed, then reset contour data */
260: PetscCall(PetscObjectGetId((PetscObject)eps->rg,&id));
261: PetscCall(PetscObjectStateGet((PetscObject)eps->rg,&state));
262: if (ctx->rgid && (id != ctx->rgid || state != ctx->rgstate)) {
263: PetscCall(SlepcContourDataDestroy(&ctx->contour));
264: PetscCall(PetscInfo(eps,"Resetting the contour data structure due to a change of region\n"));
265: ctx->rgid = id; ctx->rgstate = state;
266: }
268: #if !defined(PETSC_USE_COMPLEX)
269: PetscCheck(!isring,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Ring region only supported for complex scalars");
270: #endif
271: if (isinterval) {
272: PetscCall(RGIntervalGetEndpoints(eps->rg,NULL,NULL,&c,&d));
273: #if !defined(PETSC_USE_COMPLEX)
274: PetscCheck(c==d && c==0.0,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"In real scalars, endpoints of the imaginary axis must be both zero");
275: #endif
276: if (!ctx->quad && c==d) ctx->quad = EPS_CISS_QUADRULE_CHEBYSHEV;
277: }
278: if (!ctx->quad) ctx->quad = EPS_CISS_QUADRULE_TRAPEZOIDAL;
280: /* create contour data structure */
281: if (!ctx->contour) {
282: PetscCall(RGCanUseConjugates(eps->rg,ctx->isreal,&ctx->useconj));
283: PetscCall(SlepcContourDataCreate(ctx->useconj?ctx->N/2:ctx->N,ctx->npart,(PetscObject)eps,&ctx->contour));
284: }
286: PetscCall(EPSAllocateSolution(eps,0));
287: PetscCall(BVGetRandomContext(eps->V,&rand)); /* make sure the random context is available when duplicating */
288: if (ctx->weight) PetscCall(PetscFree4(ctx->weight,ctx->omega,ctx->pp,ctx->sigma));
289: PetscCall(PetscMalloc4(ctx->N,&ctx->weight,ctx->N+1,&ctx->omega,ctx->N,&ctx->pp,ctx->L_max*ctx->M,&ctx->sigma));
291: /* allocate basis vectors */
292: PetscCall(BVDestroy(&ctx->S));
293: PetscCall(BVDuplicateResize(eps->V,ctx->L*ctx->M,&ctx->S));
294: PetscCall(BVDestroy(&ctx->V));
295: PetscCall(BVDuplicateResize(eps->V,ctx->L,&ctx->V));
297: PetscCall(STGetMatrix(eps->st,0,&A[0]));
298: PetscCall(MatIsShell(A[0],&flg));
299: PetscCheck(!flg,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Matrix type shell is not supported in this solver");
300: if (eps->isgeneralized) PetscCall(STGetMatrix(eps->st,1,&A[1]));
302: if (!ctx->usest_set) ctx->usest = (ctx->npart>1)? PETSC_FALSE: PETSC_TRUE;
303: PetscCheck(!ctx->usest || ctx->npart==1,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"The usest flag is not supported when partitions > 1");
305: /* check if a user-defined split preconditioner has been set */
306: PetscCall(STGetSplitPreconditionerInfo(eps->st,&nsplit,NULL));
307: if (nsplit) {
308: PetscCall(STGetSplitPreconditionerTerm(eps->st,0,&Psplit[0]));
309: if (eps->isgeneralized) PetscCall(STGetSplitPreconditionerTerm(eps->st,1,&Psplit[1]));
310: }
312: contour = ctx->contour;
313: PetscCall(SlepcContourRedundantMat(contour,eps->isgeneralized?2:1,A,nsplit?Psplit:NULL));
314: if (contour->pA) {
315: PetscCall(BVGetColumn(ctx->V,0,&v0));
316: PetscCall(SlepcContourScatterCreate(contour,v0));
317: PetscCall(BVRestoreColumn(ctx->V,0,&v0));
318: PetscCall(BVDestroy(&ctx->pV));
319: PetscCall(BVCreate(PetscObjectComm((PetscObject)contour->xsub),&ctx->pV));
320: PetscCall(BVSetSizesFromVec(ctx->pV,contour->xsub,eps->n));
321: PetscCall(BVSetFromOptions(ctx->pV));
322: PetscCall(BVResize(ctx->pV,ctx->L,PETSC_FALSE));
323: }
325: EPSCheckDefinite(eps);
326: EPSCheckSinvertCondition(eps,ctx->usest," (with the usest flag set)");
328: PetscCall(BVDestroy(&ctx->Y));
329: if (contour->pA) {
330: PetscCall(BVCreate(PetscObjectComm((PetscObject)contour->xsub),&ctx->Y));
331: PetscCall(BVSetSizesFromVec(ctx->Y,contour->xsub,eps->n));
332: PetscCall(BVSetFromOptions(ctx->Y));
333: PetscCall(BVResize(ctx->Y,contour->npoints*ctx->L,PETSC_FALSE));
334: } else PetscCall(BVDuplicateResize(eps->V,contour->npoints*ctx->L,&ctx->Y));
336: if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) PetscCall(DSSetType(eps->ds,DSGNHEP));
337: else if (eps->isgeneralized) {
338: if (eps->ishermitian && eps->ispositive) PetscCall(DSSetType(eps->ds,DSGHEP));
339: else PetscCall(DSSetType(eps->ds,DSGNHEP));
340: } else {
341: if (eps->ishermitian) PetscCall(DSSetType(eps->ds,DSHEP));
342: else PetscCall(DSSetType(eps->ds,DSNHEP));
343: }
344: PetscCall(DSAllocate(eps->ds,eps->ncv));
346: #if !defined(PETSC_USE_COMPLEX)
347: PetscCall(EPSSetWorkVecs(eps,3));
348: if (!eps->ishermitian) PetscCall(PetscInfo(eps,"Warning: complex eigenvalues are not calculated exactly without --with-scalar-type=complex in PETSc\n"));
349: #else
350: PetscCall(EPSSetWorkVecs(eps,2));
351: #endif
352: PetscFunctionReturn(PETSC_SUCCESS);
353: }
355: static PetscErrorCode EPSSetUpSort_CISS(EPS eps)
356: {
357: SlepcSC sc;
359: PetscFunctionBegin;
360: /* fill sorting criterion context */
361: eps->sc->comparison = SlepcCompareSmallestReal;
362: eps->sc->comparisonctx = NULL;
363: eps->sc->map = NULL;
364: eps->sc->mapobj = NULL;
366: /* fill sorting criterion for DS */
367: PetscCall(DSGetSlepcSC(eps->ds,&sc));
368: sc->comparison = SlepcCompareLargestMagnitude;
369: sc->comparisonctx = NULL;
370: sc->map = NULL;
371: sc->mapobj = NULL;
372: PetscFunctionReturn(PETSC_SUCCESS);
373: }
375: static PetscErrorCode EPSSolve_CISS(EPS eps)
376: {
377: EPS_CISS *ctx = (EPS_CISS*)eps->data;
378: SlepcContourData contour = ctx->contour;
379: Mat A,B,X,M,pA,pB,T,J,Pa=NULL,Pb=NULL;
380: BV V;
381: PetscInt i,j,ld,nmat,L_add=0,nv=0,L_base=ctx->L,inner,nlocal,*inside,nsplit;
382: PetscScalar *Mu,*H0,*H1=NULL,*rr,*temp;
383: PetscReal error,max_error,norm;
384: PetscBool *fl1;
385: Vec si,si1=NULL,w[3];
386: PetscRandom rand;
387: #if defined(PETSC_USE_COMPLEX)
388: PetscBool isellipse;
389: PetscReal est_eig,eta;
390: #else
391: PetscReal normi;
392: #endif
394: PetscFunctionBegin;
395: w[0] = eps->work[0];
396: #if defined(PETSC_USE_COMPLEX)
397: w[1] = NULL;
398: #else
399: w[1] = eps->work[2];
400: #endif
401: w[2] = eps->work[1];
402: PetscCall(VecGetLocalSize(w[0],&nlocal));
403: PetscCall(DSGetLeadingDimension(eps->ds,&ld));
404: PetscCall(RGComputeQuadrature(eps->rg,ctx->quad==EPS_CISS_QUADRULE_CHEBYSHEV?RG_QUADRULE_CHEBYSHEV:RG_QUADRULE_TRAPEZOIDAL,ctx->N,ctx->omega,ctx->pp,ctx->weight));
405: PetscCall(STGetNumMatrices(eps->st,&nmat));
406: PetscCall(STGetMatrix(eps->st,0,&A));
407: if (nmat>1) PetscCall(STGetMatrix(eps->st,1,&B));
408: else B = NULL;
409: J = (contour->pA && nmat>1)? contour->pA[1]: B;
410: V = contour->pA? ctx->pV: ctx->V;
411: if (!ctx->usest) {
412: T = contour->pA? contour->pA[0]: A;
413: PetscCall(STGetSplitPreconditionerInfo(eps->st,&nsplit,NULL));
414: if (nsplit) {
415: if (contour->pA) {
416: Pa = contour->pP[0];
417: if (nsplit>1) Pb = contour->pP[1];
418: } else {
419: PetscCall(STGetSplitPreconditionerTerm(eps->st,0,&Pa));
420: if (nsplit>1) PetscCall(STGetSplitPreconditionerTerm(eps->st,1,&Pb));
421: }
422: }
423: PetscCall(EPSCISSSetUp(eps,T,J,Pa,Pb));
424: }
425: PetscCall(BVSetActiveColumns(ctx->V,0,ctx->L));
426: PetscCall(BVSetRandomSign(ctx->V));
427: PetscCall(BVGetRandomContext(ctx->V,&rand));
429: if (contour->pA) PetscCall(BVScatter(ctx->V,ctx->pV,contour->scatterin,contour->xdup));
430: PetscCall(EPSCISSSolve(eps,J,V,0,ctx->L));
431: #if defined(PETSC_USE_COMPLEX)
432: PetscCall(PetscObjectTypeCompare((PetscObject)eps->rg,RGELLIPSE,&isellipse));
433: if (isellipse) {
434: PetscCall(BVTraceQuadrature(ctx->Y,ctx->V,ctx->L,ctx->L,ctx->weight,contour->scatterin,contour->subcomm,contour->npoints,ctx->useconj,&est_eig));
435: PetscCall(PetscInfo(eps,"Estimated eigenvalue count: %f\n",(double)est_eig));
436: eta = PetscPowReal(10.0,-PetscLog10Real(eps->tol)/ctx->N);
437: L_add = PetscMax(0,(PetscInt)PetscCeilReal((est_eig*eta)/ctx->M)-ctx->L);
438: if (L_add>ctx->L_max-ctx->L) {
439: PetscCall(PetscInfo(eps,"Number of eigenvalues inside the contour path may be too large\n"));
440: L_add = ctx->L_max-ctx->L;
441: }
442: }
443: #endif
444: if (L_add>0) {
445: PetscCall(PetscInfo(eps,"Changing L %" PetscInt_FMT " -> %" PetscInt_FMT " by Estimate #Eig\n",ctx->L,ctx->L+L_add));
446: PetscCall(BVCISSResizeBases(ctx->S,contour->pA?ctx->pV:ctx->V,ctx->Y,ctx->L,ctx->L+L_add,ctx->M,contour->npoints));
447: PetscCall(BVSetActiveColumns(ctx->V,ctx->L,ctx->L+L_add));
448: PetscCall(BVSetRandomSign(ctx->V));
449: if (contour->pA) PetscCall(BVScatter(ctx->V,ctx->pV,contour->scatterin,contour->xdup));
450: ctx->L += L_add;
451: PetscCall(EPSCISSSolve(eps,J,V,ctx->L-L_add,ctx->L));
452: }
453: PetscCall(PetscMalloc2(ctx->L*ctx->L*ctx->M*2,&Mu,ctx->L*ctx->M*ctx->L*ctx->M,&H0));
454: for (i=0;i<ctx->refine_blocksize;i++) {
455: PetscCall(BVDotQuadrature(ctx->Y,(contour->pA)?ctx->pV:ctx->V,Mu,ctx->M,ctx->L,ctx->L,ctx->weight,ctx->pp,contour->subcomm,contour->npoints,ctx->useconj));
456: PetscCall(CISS_BlockHankel(Mu,0,ctx->L,ctx->M,H0));
457: PetscCall(PetscLogEventBegin(EPS_CISS_SVD,eps,0,0,0));
458: PetscCall(SlepcCISS_BH_SVD(H0,ctx->L*ctx->M,ctx->delta,ctx->sigma,&nv));
459: PetscCall(PetscLogEventEnd(EPS_CISS_SVD,eps,0,0,0));
460: if (ctx->sigma[0]<=ctx->delta || nv < ctx->L*ctx->M || ctx->L == ctx->L_max) break;
461: L_add = L_base;
462: if (ctx->L+L_add>ctx->L_max) L_add = ctx->L_max-ctx->L;
463: PetscCall(PetscInfo(eps,"Changing L %" PetscInt_FMT " -> %" PetscInt_FMT " by SVD(H0)\n",ctx->L,ctx->L+L_add));
464: PetscCall(BVCISSResizeBases(ctx->S,contour->pA?ctx->pV:ctx->V,ctx->Y,ctx->L,ctx->L+L_add,ctx->M,contour->npoints));
465: PetscCall(BVSetActiveColumns(ctx->V,ctx->L,ctx->L+L_add));
466: PetscCall(BVSetRandomSign(ctx->V));
467: if (contour->pA) PetscCall(BVScatter(ctx->V,ctx->pV,contour->scatterin,contour->xdup));
468: ctx->L += L_add;
469: PetscCall(EPSCISSSolve(eps,J,V,ctx->L-L_add,ctx->L));
470: if (L_add) {
471: PetscCall(PetscFree2(Mu,H0));
472: PetscCall(PetscMalloc2(ctx->L*ctx->L*ctx->M*2,&Mu,ctx->L*ctx->M*ctx->L*ctx->M,&H0));
473: }
474: }
475: if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) PetscCall(PetscMalloc1(ctx->L*ctx->M*ctx->L*ctx->M,&H1));
477: while (eps->reason == EPS_CONVERGED_ITERATING) {
478: eps->its++;
479: for (inner=0;inner<=ctx->refine_inner;inner++) {
480: if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {
481: PetscCall(BVDotQuadrature(ctx->Y,(contour->pA)?ctx->pV:ctx->V,Mu,ctx->M,ctx->L,ctx->L,ctx->weight,ctx->pp,contour->subcomm,contour->npoints,ctx->useconj));
482: PetscCall(CISS_BlockHankel(Mu,0,ctx->L,ctx->M,H0));
483: PetscCall(PetscLogEventBegin(EPS_CISS_SVD,eps,0,0,0));
484: PetscCall(SlepcCISS_BH_SVD(H0,ctx->L*ctx->M,ctx->delta,ctx->sigma,&nv));
485: PetscCall(PetscLogEventEnd(EPS_CISS_SVD,eps,0,0,0));
486: break;
487: } else {
488: PetscCall(BVSumQuadrature(ctx->S,ctx->Y,ctx->M,ctx->L,ctx->L,ctx->weight,ctx->pp,contour->scatterin,contour->subcomm,contour->npoints,ctx->useconj));
489: PetscCall(BVSetActiveColumns(ctx->S,0,ctx->L));
490: PetscCall(BVSetActiveColumns(ctx->V,0,ctx->L));
491: PetscCall(BVCopy(ctx->S,ctx->V));
492: PetscCall(BVSVDAndRank(ctx->S,ctx->M,ctx->L,ctx->delta,BV_SVD_METHOD_REFINE,H0,ctx->sigma,&nv));
493: if (ctx->sigma[0]>ctx->delta && nv==ctx->L*ctx->M && inner!=ctx->refine_inner) {
494: if (contour->pA) PetscCall(BVScatter(ctx->V,ctx->pV,contour->scatterin,contour->xdup));
495: PetscCall(EPSCISSSolve(eps,J,V,0,ctx->L));
496: } else break;
497: }
498: }
499: eps->nconv = 0;
500: if (nv == 0) eps->reason = EPS_CONVERGED_TOL;
501: else {
502: PetscCall(DSSetDimensions(eps->ds,nv,0,0));
503: PetscCall(DSSetState(eps->ds,DS_STATE_RAW));
505: if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {
506: PetscCall(CISS_BlockHankel(Mu,0,ctx->L,ctx->M,H0));
507: PetscCall(CISS_BlockHankel(Mu,1,ctx->L,ctx->M,H1));
508: PetscCall(DSGetArray(eps->ds,DS_MAT_A,&temp));
509: for (j=0;j<nv;j++) {
510: for (i=0;i<nv;i++) {
511: temp[i+j*ld] = H1[i+j*ctx->L*ctx->M];
512: }
513: }
514: PetscCall(DSRestoreArray(eps->ds,DS_MAT_A,&temp));
515: PetscCall(DSGetArray(eps->ds,DS_MAT_B,&temp));
516: for (j=0;j<nv;j++) {
517: for (i=0;i<nv;i++) {
518: temp[i+j*ld] = H0[i+j*ctx->L*ctx->M];
519: }
520: }
521: PetscCall(DSRestoreArray(eps->ds,DS_MAT_B,&temp));
522: } else {
523: PetscCall(BVSetActiveColumns(ctx->S,0,nv));
524: PetscCall(DSGetMat(eps->ds,DS_MAT_A,&pA));
525: PetscCall(MatZeroEntries(pA));
526: PetscCall(BVMatProject(ctx->S,A,ctx->S,pA));
527: PetscCall(DSRestoreMat(eps->ds,DS_MAT_A,&pA));
528: if (B) {
529: PetscCall(DSGetMat(eps->ds,DS_MAT_B,&pB));
530: PetscCall(MatZeroEntries(pB));
531: PetscCall(BVMatProject(ctx->S,B,ctx->S,pB));
532: PetscCall(DSRestoreMat(eps->ds,DS_MAT_B,&pB));
533: }
534: }
536: PetscCall(DSSolve(eps->ds,eps->eigr,eps->eigi));
537: PetscCall(DSSynchronize(eps->ds,eps->eigr,eps->eigi));
539: PetscCall(PetscMalloc3(nv,&fl1,nv,&inside,nv,&rr));
540: PetscCall(rescale_eig(eps,nv));
541: PetscCall(DSVectors(eps->ds,DS_MAT_X,NULL,NULL));
542: PetscCall(DSGetMat(eps->ds,DS_MAT_X,&X));
543: PetscCall(SlepcCISS_isGhost(X,nv,ctx->sigma,ctx->spurious_threshold,fl1));
544: PetscCall(DSRestoreMat(eps->ds,DS_MAT_X,&X));
545: PetscCall(RGCheckInside(eps->rg,nv,eps->eigr,eps->eigi,inside));
546: for (i=0;i<nv;i++) {
547: if (fl1[i] && inside[i]>=0) {
548: rr[i] = 1.0;
549: eps->nconv++;
550: } else rr[i] = 0.0;
551: }
552: PetscCall(DSSort(eps->ds,eps->eigr,eps->eigi,rr,NULL,&eps->nconv));
553: PetscCall(DSSynchronize(eps->ds,eps->eigr,eps->eigi));
554: PetscCall(rescale_eig(eps,nv));
555: PetscCall(PetscFree3(fl1,inside,rr));
556: PetscCall(BVSetActiveColumns(eps->V,0,nv));
557: if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {
558: PetscCall(BVSumQuadrature(ctx->S,ctx->Y,ctx->M,ctx->L,ctx->L,ctx->weight,ctx->pp,contour->scatterin,contour->subcomm,contour->npoints,ctx->useconj));
559: PetscCall(BVSetActiveColumns(ctx->S,0,ctx->L));
560: PetscCall(BVCopy(ctx->S,ctx->V));
561: PetscCall(BVSetActiveColumns(ctx->S,0,nv));
562: }
563: PetscCall(BVCopy(ctx->S,eps->V));
565: PetscCall(DSVectors(eps->ds,DS_MAT_X,NULL,NULL));
566: PetscCall(DSGetMat(eps->ds,DS_MAT_X,&X));
567: PetscCall(BVMultInPlace(ctx->S,X,0,eps->nconv));
568: if (eps->ishermitian) PetscCall(BVMultInPlace(eps->V,X,0,eps->nconv));
569: PetscCall(DSRestoreMat(eps->ds,DS_MAT_X,&X));
570: max_error = 0.0;
571: for (i=0;i<eps->nconv;i++) {
572: PetscCall(BVGetColumn(ctx->S,i,&si));
573: #if !defined(PETSC_USE_COMPLEX)
574: if (eps->eigi[i]!=0.0) PetscCall(BVGetColumn(ctx->S,i+1,&si1));
575: #endif
576: PetscCall(EPSComputeResidualNorm_Private(eps,PETSC_FALSE,eps->eigr[i],eps->eigi[i],si,si1,w,&error));
577: if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) { /* vector is not normalized */
578: PetscCall(VecNorm(si,NORM_2,&norm));
579: #if !defined(PETSC_USE_COMPLEX)
580: if (eps->eigi[i]!=0.0) {
581: PetscCall(VecNorm(si1,NORM_2,&normi));
582: norm = SlepcAbsEigenvalue(norm,normi);
583: }
584: #endif
585: error /= norm;
586: }
587: PetscCall((*eps->converged)(eps,eps->eigr[i],eps->eigi[i],error,&error,eps->convergedctx));
588: PetscCall(BVRestoreColumn(ctx->S,i,&si));
589: #if !defined(PETSC_USE_COMPLEX)
590: if (eps->eigi[i]!=0.0) {
591: PetscCall(BVRestoreColumn(ctx->S,i+1,&si1));
592: i++;
593: }
594: #endif
595: max_error = PetscMax(max_error,error);
596: }
598: if (max_error <= eps->tol) eps->reason = EPS_CONVERGED_TOL;
599: else if (eps->its >= eps->max_it) eps->reason = EPS_DIVERGED_ITS;
600: else {
601: if (eps->nconv > ctx->L) nv = eps->nconv;
602: else if (ctx->L > nv) nv = ctx->L;
603: nv = PetscMin(nv,ctx->L*ctx->M);
604: PetscCall(MatCreateSeqDense(PETSC_COMM_SELF,nv,ctx->L,NULL,&M));
605: PetscCall(MatSetRandom(M,rand));
606: PetscCall(BVSetActiveColumns(ctx->S,0,nv));
607: PetscCall(BVMultInPlace(ctx->S,M,0,ctx->L));
608: PetscCall(MatDestroy(&M));
609: PetscCall(BVSetActiveColumns(ctx->S,0,ctx->L));
610: PetscCall(BVSetActiveColumns(ctx->V,0,ctx->L));
611: PetscCall(BVCopy(ctx->S,ctx->V));
612: if (contour->pA) PetscCall(BVScatter(ctx->V,ctx->pV,contour->scatterin,contour->xdup));
613: PetscCall(EPSCISSSolve(eps,J,V,0,ctx->L));
614: }
615: }
616: }
617: if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) PetscCall(PetscFree(H1));
618: PetscCall(PetscFree2(Mu,H0));
619: PetscFunctionReturn(PETSC_SUCCESS);
620: }
622: static PetscErrorCode EPSComputeVectors_CISS(EPS eps)
623: {
624: EPS_CISS *ctx = (EPS_CISS*)eps->data;
625: PetscInt n;
626: Mat Z,B=NULL;
628: PetscFunctionBegin;
629: if (eps->ishermitian) {
630: if (eps->isgeneralized && !eps->ispositive) PetscCall(EPSComputeVectors_Indefinite(eps));
631: else PetscCall(EPSComputeVectors_Hermitian(eps));
632: if (eps->isgeneralized && eps->ispositive && ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {
633: /* normalize to have unit B-norm */
634: PetscCall(STGetMatrix(eps->st,1,&B));
635: PetscCall(BVSetMatrix(eps->V,B,PETSC_FALSE));
636: PetscCall(BVNormalize(eps->V,NULL));
637: PetscCall(BVSetMatrix(eps->V,NULL,PETSC_FALSE));
638: }
639: PetscFunctionReturn(PETSC_SUCCESS);
640: }
641: PetscCall(DSGetDimensions(eps->ds,&n,NULL,NULL,NULL));
642: PetscCall(BVSetActiveColumns(eps->V,0,n));
644: /* right eigenvectors */
645: PetscCall(DSVectors(eps->ds,DS_MAT_X,NULL,NULL));
647: /* V = V * Z */
648: PetscCall(DSGetMat(eps->ds,DS_MAT_X,&Z));
649: PetscCall(BVMultInPlace(eps->V,Z,0,n));
650: PetscCall(DSRestoreMat(eps->ds,DS_MAT_X,&Z));
651: PetscCall(BVSetActiveColumns(eps->V,0,eps->nconv));
653: /* normalize */
654: if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) PetscCall(BVNormalize(eps->V,NULL));
655: PetscFunctionReturn(PETSC_SUCCESS);
656: }
658: static PetscErrorCode EPSCISSSetSizes_CISS(EPS eps,PetscInt ip,PetscInt bs,PetscInt ms,PetscInt npart,PetscInt bsmax,PetscBool realmats)
659: {
660: EPS_CISS *ctx = (EPS_CISS*)eps->data;
661: PetscInt oN,oL,oM,oLmax,onpart;
662: PetscMPIInt size;
664: PetscFunctionBegin;
665: oN = ctx->N;
666: if (ip == PETSC_DETERMINE) {
667: if (ctx->N!=32) { ctx->N =32; ctx->M = ctx->N/4; }
668: } else if (ip != PETSC_CURRENT) {
669: PetscCheck(ip>0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The ip argument must be > 0");
670: PetscCheck(ip%2==0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The ip argument must be an even number");
671: if (ctx->N!=ip) { ctx->N = ip; ctx->M = ctx->N/4; }
672: }
673: oL = ctx->L;
674: if (bs == PETSC_DETERMINE) {
675: ctx->L = 16;
676: } else if (bs != PETSC_CURRENT) {
677: PetscCheck(bs>0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The bs argument must be > 0");
678: ctx->L = bs;
679: }
680: oM = ctx->M;
681: if (ms == PETSC_DETERMINE) {
682: ctx->M = ctx->N/4;
683: } else if (ms != PETSC_CURRENT) {
684: PetscCheck(ms>0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The ms argument must be > 0");
685: PetscCheck(ms<=ctx->N,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The ms argument must be less than or equal to the number of integration points");
686: ctx->M = ms;
687: }
688: onpart = ctx->npart;
689: if (npart == PETSC_DETERMINE) {
690: ctx->npart = 1;
691: } else if (npart != PETSC_CURRENT) {
692: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)eps),&size));
693: PetscCheck(npart>0 && npart<=size,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of npart");
694: ctx->npart = npart;
695: }
696: oLmax = ctx->L_max;
697: if (bsmax == PETSC_DETERMINE) {
698: ctx->L_max = 64;
699: } else if (bsmax != PETSC_CURRENT) {
700: PetscCheck(bsmax>0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The bsmax argument must be > 0");
701: ctx->L_max = PetscMax(bsmax,ctx->L);
702: }
703: if (onpart != ctx->npart || oN != ctx->N || realmats != ctx->isreal) {
704: PetscCall(SlepcContourDataDestroy(&ctx->contour));
705: PetscCall(PetscInfo(eps,"Resetting the contour data structure due to a change of parameters\n"));
706: eps->state = EPS_STATE_INITIAL;
707: }
708: ctx->isreal = realmats;
709: if (oL != ctx->L || oM != ctx->M || oLmax != ctx->L_max) eps->state = EPS_STATE_INITIAL;
710: PetscFunctionReturn(PETSC_SUCCESS);
711: }
713: /*@
714: EPSCISSSetSizes - Sets the values of various size parameters in the CISS solver.
716: Logically Collective
718: Input Parameters:
719: + eps - the linear eigensolver context
720: . ip - number of integration points
721: . bs - block size
722: . ms - moment size
723: . npart - number of partitions when splitting the communicator
724: . bsmax - max block size
725: - realmats - $A$ and $B$ are real
727: Options Database Keys:
728: + -eps_ciss_integration_points ip - sets the number of integration points
729: . -eps_ciss_blocksize bs - sets the block size
730: . -eps_ciss_moments ms - sets the moment size
731: . -eps_ciss_partitions npart - sets the number of partitions
732: . -eps_ciss_maxblocksize bsmax - sets the maximum block size
733: - -eps_ciss_realmats (true|false) - $A$ and $B$ are real
735: Notes:
736: For all integer arguments, you can use `PETSC_CURRENT` to keep the current value, and
737: `PETSC_DETERMINE` to set them to a default value.
739: The default number of partitions is 1. This means the internal `KSP` object is shared
740: among all processes of the `EPS` communicator. Otherwise, the communicator is split
741: into `npart` communicators, so that `npart` `KSP` solves proceed simultaneously.
743: For a detailed description of the parameters see {cite:p}`Mae16`.
745: Level: advanced
747: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSGetSizes()`, `EPSCISSSetThreshold()`, `EPSCISSSetRefinement()`
748: @*/
749: PetscErrorCode EPSCISSSetSizes(EPS eps,PetscInt ip,PetscInt bs,PetscInt ms,PetscInt npart,PetscInt bsmax,PetscBool realmats)
750: {
751: PetscFunctionBegin;
759: PetscTryMethod(eps,"EPSCISSSetSizes_C",(EPS,PetscInt,PetscInt,PetscInt,PetscInt,PetscInt,PetscBool),(eps,ip,bs,ms,npart,bsmax,realmats));
760: PetscFunctionReturn(PETSC_SUCCESS);
761: }
763: static PetscErrorCode EPSCISSGetSizes_CISS(EPS eps,PetscInt *ip,PetscInt *bs,PetscInt *ms,PetscInt *npart,PetscInt *bsmax,PetscBool *realmats)
764: {
765: EPS_CISS *ctx = (EPS_CISS*)eps->data;
767: PetscFunctionBegin;
768: if (ip) *ip = ctx->N;
769: if (bs) *bs = ctx->L;
770: if (ms) *ms = ctx->M;
771: if (npart) *npart = ctx->npart;
772: if (bsmax) *bsmax = ctx->L_max;
773: if (realmats) *realmats = ctx->isreal;
774: PetscFunctionReturn(PETSC_SUCCESS);
775: }
777: /*@
778: EPSCISSGetSizes - Gets the values of various size parameters in the CISS solver.
780: Not Collective
782: Input Parameter:
783: . eps - the linear eigensolver context
785: Output Parameters:
786: + ip - number of integration points
787: . bs - block size
788: . ms - moment size
789: . npart - number of partitions when splitting the communicator
790: . bsmax - max block size
791: - realmats - $A$ and $B$ are real
793: Level: advanced
795: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSSetSizes()`
796: @*/
797: PetscErrorCode EPSCISSGetSizes(EPS eps,PetscInt *ip,PetscInt *bs,PetscInt *ms,PetscInt *npart,PetscInt *bsmax,PetscBool *realmats)
798: {
799: PetscFunctionBegin;
801: PetscUseMethod(eps,"EPSCISSGetSizes_C",(EPS,PetscInt*,PetscInt*,PetscInt*,PetscInt*,PetscInt*,PetscBool*),(eps,ip,bs,ms,npart,bsmax,realmats));
802: PetscFunctionReturn(PETSC_SUCCESS);
803: }
805: static PetscErrorCode EPSCISSSetThreshold_CISS(EPS eps,PetscReal delta,PetscReal spur)
806: {
807: EPS_CISS *ctx = (EPS_CISS*)eps->data;
809: PetscFunctionBegin;
810: if (delta == (PetscReal)PETSC_DETERMINE) {
811: ctx->delta = SLEPC_DEFAULT_TOL*1e-4;
812: } else if (delta != (PetscReal)PETSC_CURRENT) {
813: PetscCheck(delta>0.0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The delta argument must be > 0.0");
814: ctx->delta = delta;
815: }
816: if (spur == (PetscReal)PETSC_DETERMINE) {
817: ctx->spurious_threshold = PetscSqrtReal(SLEPC_DEFAULT_TOL);
818: } else if (spur != (PetscReal)PETSC_CURRENT) {
819: PetscCheck(spur>0.0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The spurious threshold argument must be > 0.0");
820: ctx->spurious_threshold = spur;
821: }
822: PetscFunctionReturn(PETSC_SUCCESS);
823: }
825: /*@
826: EPSCISSSetThreshold - Sets the values of various threshold parameters in
827: the CISS solver.
829: Logically Collective
831: Input Parameters:
832: + eps - the linear eigensolver context
833: . delta - threshold for numerical rank
834: - spur - spurious threshold (to discard spurious eigenpairs)
836: Options Database Keys:
837: + -eps_ciss_delta delta - sets the delta
838: - -eps_ciss_spurious_threshold spur - sets the spurious threshold
840: Notes:
841: `PETSC_CURRENT` can be used to preserve the current value of any of the
842: arguments, and `PETSC_DETERMINE` to set them to a default value.
844: For a detailed description of the parameters see {cite:p}`Mae16`.
846: Level: advanced
848: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSGetThreshold()`, `EPSCISSSetSizes()`, `EPSCISSSetRefinement()`
849: @*/
850: PetscErrorCode EPSCISSSetThreshold(EPS eps,PetscReal delta,PetscReal spur)
851: {
852: PetscFunctionBegin;
856: PetscTryMethod(eps,"EPSCISSSetThreshold_C",(EPS,PetscReal,PetscReal),(eps,delta,spur));
857: PetscFunctionReturn(PETSC_SUCCESS);
858: }
860: static PetscErrorCode EPSCISSGetThreshold_CISS(EPS eps,PetscReal *delta,PetscReal *spur)
861: {
862: EPS_CISS *ctx = (EPS_CISS*)eps->data;
864: PetscFunctionBegin;
865: if (delta) *delta = ctx->delta;
866: if (spur) *spur = ctx->spurious_threshold;
867: PetscFunctionReturn(PETSC_SUCCESS);
868: }
870: /*@
871: EPSCISSGetThreshold - Gets the values of various threshold parameters
872: in the CISS solver.
874: Not Collective
876: Input Parameter:
877: . eps - the linear eigensolver context
879: Output Parameters:
880: + delta - threshold for numerical rank
881: - spur - spurious threshold (to discard spurious eigenpairs)
883: Level: advanced
885: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSSetThreshold()`
886: @*/
887: PetscErrorCode EPSCISSGetThreshold(EPS eps,PetscReal *delta,PetscReal *spur)
888: {
889: PetscFunctionBegin;
891: PetscUseMethod(eps,"EPSCISSGetThreshold_C",(EPS,PetscReal*,PetscReal*),(eps,delta,spur));
892: PetscFunctionReturn(PETSC_SUCCESS);
893: }
895: static PetscErrorCode EPSCISSSetRefinement_CISS(EPS eps,PetscInt inner,PetscInt blsize)
896: {
897: EPS_CISS *ctx = (EPS_CISS*)eps->data;
899: PetscFunctionBegin;
900: if (inner == PETSC_DETERMINE) {
901: ctx->refine_inner = 0;
902: } else if (inner != PETSC_CURRENT) {
903: PetscCheck(inner>=0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The refine inner argument must be >= 0");
904: ctx->refine_inner = inner;
905: }
906: if (blsize == PETSC_DETERMINE) {
907: ctx->refine_blocksize = 0;
908: } else if (blsize != PETSC_CURRENT) {
909: PetscCheck(blsize>=0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The refine blocksize argument must be >= 0");
910: ctx->refine_blocksize = blsize;
911: }
912: PetscFunctionReturn(PETSC_SUCCESS);
913: }
915: /*@
916: EPSCISSSetRefinement - Sets the values of various refinement parameters
917: in the CISS solver.
919: Logically Collective
921: Input Parameters:
922: + eps - the linear eigensolver context
923: . inner - number of iterative refinement iterations (inner loop)
924: - blsize - number of iterative refinement iterations (blocksize loop)
926: Options Database Keys:
927: + -eps_ciss_refine_inner inner - sets number of inner iterations
928: - -eps_ciss_refine_blocksize blsize - sets number of blocksize iterations
930: Notes:
931: `PETSC_CURRENT` can be used to preserve the current value of any of the
932: arguments, and `PETSC_DETERMINE` to set them to a default of 0 (no refinement).
934: For a detailed description of the parameters see {cite:p}`Mae16`.
936: Level: advanced
938: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSGetRefinement()`, `EPSCISSSetSizes()`, `EPSCISSSetThreshold()`
939: @*/
940: PetscErrorCode EPSCISSSetRefinement(EPS eps,PetscInt inner,PetscInt blsize)
941: {
942: PetscFunctionBegin;
946: PetscTryMethod(eps,"EPSCISSSetRefinement_C",(EPS,PetscInt,PetscInt),(eps,inner,blsize));
947: PetscFunctionReturn(PETSC_SUCCESS);
948: }
950: static PetscErrorCode EPSCISSGetRefinement_CISS(EPS eps,PetscInt *inner,PetscInt *blsize)
951: {
952: EPS_CISS *ctx = (EPS_CISS*)eps->data;
954: PetscFunctionBegin;
955: if (inner) *inner = ctx->refine_inner;
956: if (blsize) *blsize = ctx->refine_blocksize;
957: PetscFunctionReturn(PETSC_SUCCESS);
958: }
960: /*@
961: EPSCISSGetRefinement - Gets the values of various refinement parameters
962: in the CISS solver.
964: Not Collective
966: Input Parameter:
967: . eps - the linear eigensolver context
969: Output Parameters:
970: + inner - number of iterative refinement iterations (inner loop)
971: - blsize - number of iterative refinement iterations (blocksize loop)
973: Level: advanced
975: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSSetRefinement()`
976: @*/
977: PetscErrorCode EPSCISSGetRefinement(EPS eps, PetscInt *inner, PetscInt *blsize)
978: {
979: PetscFunctionBegin;
981: PetscUseMethod(eps,"EPSCISSGetRefinement_C",(EPS,PetscInt*,PetscInt*),(eps,inner,blsize));
982: PetscFunctionReturn(PETSC_SUCCESS);
983: }
985: static PetscErrorCode EPSCISSSetUseST_CISS(EPS eps,PetscBool usest)
986: {
987: EPS_CISS *ctx = (EPS_CISS*)eps->data;
989: PetscFunctionBegin;
990: ctx->usest = usest;
991: ctx->usest_set = PETSC_TRUE;
992: eps->state = EPS_STATE_INITIAL;
993: PetscFunctionReturn(PETSC_SUCCESS);
994: }
996: /*@
997: EPSCISSSetUseST - Sets a flag indicating that the CISS solver will
998: use the `ST` object for the linear solves.
1000: Logically Collective
1002: Input Parameters:
1003: + eps - the linear eigensolver context
1004: - usest - boolean flag to use the `ST` object or not
1006: Options Database Key:
1007: . -eps_ciss_usest (true|false) - whether the `ST` object will be used or not
1009: Note:
1010: When this option is set, the linear solves can be configured by
1011: setting options for the `KSP` object obtained with `STGetKSP()`.
1012: Otherwise, several `KSP` objects are created, which can be accessed
1013: with `EPSCISSGetKSPs()`.
1015: The default is to use the `ST`, unless several partitions have been
1016: specified, see `EPSCISSSetSizes()`.
1018: Level: advanced
1020: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSGetUseST()`, `EPSCISSSetSizes()`, `EPSCISSGetKSPs()`, `STGetKSP()`
1021: @*/
1022: PetscErrorCode EPSCISSSetUseST(EPS eps,PetscBool usest)
1023: {
1024: PetscFunctionBegin;
1027: PetscTryMethod(eps,"EPSCISSSetUseST_C",(EPS,PetscBool),(eps,usest));
1028: PetscFunctionReturn(PETSC_SUCCESS);
1029: }
1031: static PetscErrorCode EPSCISSGetUseST_CISS(EPS eps,PetscBool *usest)
1032: {
1033: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1035: PetscFunctionBegin;
1036: *usest = ctx->usest;
1037: PetscFunctionReturn(PETSC_SUCCESS);
1038: }
1040: /*@
1041: EPSCISSGetUseST - Gets the flag for using the `ST` object
1042: in the CISS solver.
1044: Not Collective
1046: Input Parameter:
1047: . eps - the linear eigensolver context
1049: Output Parameter:
1050: . usest - boolean flag indicating if the `ST` object is being used
1052: Level: advanced
1054: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSSetUseST()`
1055: @*/
1056: PetscErrorCode EPSCISSGetUseST(EPS eps,PetscBool *usest)
1057: {
1058: PetscFunctionBegin;
1060: PetscAssertPointer(usest,2);
1061: PetscUseMethod(eps,"EPSCISSGetUseST_C",(EPS,PetscBool*),(eps,usest));
1062: PetscFunctionReturn(PETSC_SUCCESS);
1063: }
1065: static PetscErrorCode EPSCISSSetQuadRule_CISS(EPS eps,EPSCISSQuadRule quad)
1066: {
1067: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1069: PetscFunctionBegin;
1070: if (ctx->quad != quad) {
1071: ctx->quad = quad;
1072: eps->state = EPS_STATE_INITIAL;
1073: }
1074: PetscFunctionReturn(PETSC_SUCCESS);
1075: }
1077: /*@
1078: EPSCISSSetQuadRule - Sets the quadrature rule used in the CISS solver.
1080: Logically Collective
1082: Input Parameters:
1083: + eps - the linear eigensolver context
1084: - quad - the quadrature rule, see `EPSCISSQuadRule` for possible values
1086: Options Database Key:
1087: . -eps_ciss_quadrule (trapezoidal|chebyshev) - sets the quadrature rule
1089: Notes:
1090: By default, the trapezoidal rule is used (`EPS_CISS_QUADRULE_TRAPEZOIDAL`).
1092: If the `chebyshev` option is specified (`EPS_CISS_QUADRULE_CHEBYSHEV`), then
1093: Chebyshev points are used as quadrature points.
1095: Level: advanced
1097: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSGetQuadRule()`, `EPSCISSQuadRule`
1098: @*/
1099: PetscErrorCode EPSCISSSetQuadRule(EPS eps,EPSCISSQuadRule quad)
1100: {
1101: PetscFunctionBegin;
1104: PetscTryMethod(eps,"EPSCISSSetQuadRule_C",(EPS,EPSCISSQuadRule),(eps,quad));
1105: PetscFunctionReturn(PETSC_SUCCESS);
1106: }
1108: static PetscErrorCode EPSCISSGetQuadRule_CISS(EPS eps,EPSCISSQuadRule *quad)
1109: {
1110: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1112: PetscFunctionBegin;
1113: *quad = ctx->quad;
1114: PetscFunctionReturn(PETSC_SUCCESS);
1115: }
1117: /*@
1118: EPSCISSGetQuadRule - Gets the quadrature rule used in the CISS solver.
1120: Not Collective
1122: Input Parameter:
1123: . eps - the linear eigensolver context
1125: Output Parameter:
1126: . quad - quadrature rule
1128: Level: advanced
1130: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSSetQuadRule()`, `EPSCISSQuadRule`
1131: @*/
1132: PetscErrorCode EPSCISSGetQuadRule(EPS eps,EPSCISSQuadRule *quad)
1133: {
1134: PetscFunctionBegin;
1136: PetscAssertPointer(quad,2);
1137: PetscUseMethod(eps,"EPSCISSGetQuadRule_C",(EPS,EPSCISSQuadRule*),(eps,quad));
1138: PetscFunctionReturn(PETSC_SUCCESS);
1139: }
1141: static PetscErrorCode EPSCISSSetExtraction_CISS(EPS eps,EPSCISSExtraction extraction)
1142: {
1143: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1145: PetscFunctionBegin;
1146: if (ctx->extraction != extraction) {
1147: ctx->extraction = extraction;
1148: eps->state = EPS_STATE_INITIAL;
1149: }
1150: PetscFunctionReturn(PETSC_SUCCESS);
1151: }
1153: /*@
1154: EPSCISSSetExtraction - Sets the extraction technique used in the CISS solver.
1156: Logically Collective
1158: Input Parameters:
1159: + eps - the linear eigensolver context
1160: - extraction - the extraction technique, see `EPSCISSExtraction` for possible values
1162: Options Database Key:
1163: . -eps_ciss_extraction (ritz|hankel) - sets the extraction technique
1165: Notes:
1166: By default, the Rayleigh-Ritz extraction is used (`EPS_CISS_EXTRACTION_RITZ`),
1167: see {cite:p}`Sak07`.
1169: If the `hankel` option is specified (`EPS_CISS_EXTRACTION_HANKEL`), then
1170: the block Hankel method is used for extracting eigenpairs {cite:p}`Sak03`.
1172: Level: advanced
1174: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSGetExtraction()`, `EPSCISSExtraction`
1175: @*/
1176: PetscErrorCode EPSCISSSetExtraction(EPS eps,EPSCISSExtraction extraction)
1177: {
1178: PetscFunctionBegin;
1181: PetscTryMethod(eps,"EPSCISSSetExtraction_C",(EPS,EPSCISSExtraction),(eps,extraction));
1182: PetscFunctionReturn(PETSC_SUCCESS);
1183: }
1185: static PetscErrorCode EPSCISSGetExtraction_CISS(EPS eps,EPSCISSExtraction *extraction)
1186: {
1187: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1189: PetscFunctionBegin;
1190: *extraction = ctx->extraction;
1191: PetscFunctionReturn(PETSC_SUCCESS);
1192: }
1194: /*@
1195: EPSCISSGetExtraction - Gets the extraction technique used in the CISS solver.
1197: Not Collective
1199: Input Parameter:
1200: . eps - the linear eigensolver context
1202: Output Parameter:
1203: . extraction - extraction technique
1205: Level: advanced
1207: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSSetExtraction()`, `EPSCISSExtraction`
1208: @*/
1209: PetscErrorCode EPSCISSGetExtraction(EPS eps,EPSCISSExtraction *extraction)
1210: {
1211: PetscFunctionBegin;
1213: PetscAssertPointer(extraction,2);
1214: PetscUseMethod(eps,"EPSCISSGetExtraction_C",(EPS,EPSCISSExtraction*),(eps,extraction));
1215: PetscFunctionReturn(PETSC_SUCCESS);
1216: }
1218: static PetscErrorCode EPSCISSGetKSPs_CISS(EPS eps,PetscInt *nsolve,KSP **ksp)
1219: {
1220: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1221: SlepcContourData contour;
1222: PetscInt i,nsplit;
1223: PC pc;
1224: MPI_Comm child;
1226: PetscFunctionBegin;
1227: if (!ctx->contour) { /* initialize contour data structure first */
1228: PetscCall(RGCanUseConjugates(eps->rg,ctx->isreal,&ctx->useconj));
1229: PetscCall(SlepcContourDataCreate(ctx->useconj?ctx->N/2:ctx->N,ctx->npart,(PetscObject)eps,&ctx->contour));
1230: }
1231: contour = ctx->contour;
1232: if (!contour->ksp) {
1233: PetscCall(PetscMalloc1(contour->npoints,&contour->ksp));
1234: PetscCall(EPSGetST(eps,&eps->st));
1235: PetscCall(STGetSplitPreconditionerInfo(eps->st,&nsplit,NULL));
1236: PetscCall(PetscSubcommGetChild(contour->subcomm,&child));
1237: for (i=0;i<contour->npoints;i++) {
1238: PetscCall(KSPCreate(child,&contour->ksp[i]));
1239: PetscCall(PetscObjectIncrementTabLevel((PetscObject)contour->ksp[i],(PetscObject)eps,1));
1240: PetscCall(KSPSetOptionsPrefix(contour->ksp[i],((PetscObject)eps)->prefix));
1241: PetscCall(KSPAppendOptionsPrefix(contour->ksp[i],"eps_ciss_"));
1242: PetscCall(PetscObjectSetOptions((PetscObject)contour->ksp[i],((PetscObject)eps)->options));
1243: PetscCall(KSPSetErrorIfNotConverged(contour->ksp[i],PETSC_TRUE));
1244: PetscCall(KSPSetTolerances(contour->ksp[i],SlepcDefaultTol(eps->tol),PETSC_CURRENT,PETSC_CURRENT,PETSC_CURRENT));
1245: PetscCall(KSPGetPC(contour->ksp[i],&pc));
1246: if (nsplit) {
1247: PetscCall(KSPSetType(contour->ksp[i],KSPBCGS));
1248: PetscCall(PCSetType(pc,PCBJACOBI));
1249: } else {
1250: PetscCall(KSPSetType(contour->ksp[i],KSPPREONLY));
1251: PetscCall(PCSetType(pc,PCLU));
1252: }
1253: }
1254: }
1255: if (nsolve) *nsolve = contour->npoints;
1256: if (ksp) *ksp = contour->ksp;
1257: PetscFunctionReturn(PETSC_SUCCESS);
1258: }
1260: /*@C
1261: EPSCISSGetKSPs - Retrieve the array of linear solver objects associated with
1262: the CISS solver.
1264: Not Collective
1266: Input Parameter:
1267: . eps - the linear eigensolver context
1269: Output Parameters:
1270: + nsolve - number of solver objects
1271: - ksp - array of linear solver object
1273: Note:
1274: The number of `KSP` solvers is equal to the number of integration points divided by
1275: the number of partitions, see `EPSCISSSetSizes()`. This value is halved in the case
1276: of real matrices with a region centered at the real axis.
1278: Level: advanced
1280: .seealso: [](ch:eps), `EPSCISS`, `EPSCISSSetSizes()`
1281: @*/
1282: PetscErrorCode EPSCISSGetKSPs(EPS eps,PetscInt *nsolve,KSP **ksp)
1283: {
1284: PetscFunctionBegin;
1286: PetscUseMethod(eps,"EPSCISSGetKSPs_C",(EPS,PetscInt*,KSP**),(eps,nsolve,ksp));
1287: PetscFunctionReturn(PETSC_SUCCESS);
1288: }
1290: static PetscErrorCode EPSReset_CISS(EPS eps)
1291: {
1292: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1294: PetscFunctionBegin;
1295: PetscCall(BVDestroy(&ctx->S));
1296: PetscCall(BVDestroy(&ctx->V));
1297: PetscCall(BVDestroy(&ctx->Y));
1298: if (!ctx->usest) PetscCall(SlepcContourDataReset(ctx->contour));
1299: PetscCall(BVDestroy(&ctx->pV));
1300: PetscFunctionReturn(PETSC_SUCCESS);
1301: }
1303: static PetscErrorCode EPSSetFromOptions_CISS(EPS eps,PetscOptionItems PetscOptionsObject)
1304: {
1305: PetscReal r3,r4;
1306: PetscInt i,i1,i2,i3,i4,i5,i6,i7;
1307: PetscBool b1,b2,flg,flg2,flg3,flg4,flg5,flg6;
1308: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1309: EPSCISSQuadRule quad;
1310: EPSCISSExtraction extraction;
1312: PetscFunctionBegin;
1313: PetscOptionsHeadBegin(PetscOptionsObject,"EPS CISS Options");
1315: PetscCall(EPSCISSGetSizes(eps,&i1,&i2,&i3,&i4,&i5,&b1));
1316: PetscCall(PetscOptionsInt("-eps_ciss_integration_points","Number of integration points","EPSCISSSetSizes",i1,&i1,&flg));
1317: PetscCall(PetscOptionsInt("-eps_ciss_blocksize","Block size","EPSCISSSetSizes",i2,&i2,&flg2));
1318: PetscCall(PetscOptionsInt("-eps_ciss_moments","Moment size","EPSCISSSetSizes",i3,&i3,&flg3));
1319: PetscCall(PetscOptionsInt("-eps_ciss_partitions","Number of partitions","EPSCISSSetSizes",i4,&i4,&flg4));
1320: PetscCall(PetscOptionsInt("-eps_ciss_maxblocksize","Maximum block size","EPSCISSSetSizes",i5,&i5,&flg5));
1321: PetscCall(PetscOptionsBool("-eps_ciss_realmats","True if A and B are real","EPSCISSSetSizes",b1,&b1,&flg6));
1322: if (flg || flg2 || flg3 || flg4 || flg5 || flg6) PetscCall(EPSCISSSetSizes(eps,i1,i2,i3,i4,i5,b1));
1324: PetscCall(EPSCISSGetThreshold(eps,&r3,&r4));
1325: PetscCall(PetscOptionsReal("-eps_ciss_delta","Threshold for numerical rank","EPSCISSSetThreshold",r3,&r3,&flg));
1326: PetscCall(PetscOptionsReal("-eps_ciss_spurious_threshold","Threshold for the spurious eigenpairs","EPSCISSSetThreshold",r4,&r4,&flg2));
1327: if (flg || flg2) PetscCall(EPSCISSSetThreshold(eps,r3,r4));
1329: PetscCall(EPSCISSGetRefinement(eps,&i6,&i7));
1330: PetscCall(PetscOptionsInt("-eps_ciss_refine_inner","Number of inner iterative refinement iterations","EPSCISSSetRefinement",i6,&i6,&flg));
1331: PetscCall(PetscOptionsInt("-eps_ciss_refine_blocksize","Number of blocksize iterative refinement iterations","EPSCISSSetRefinement",i7,&i7,&flg2));
1332: if (flg || flg2) PetscCall(EPSCISSSetRefinement(eps,i6,i7));
1334: PetscCall(EPSCISSGetUseST(eps,&b2));
1335: PetscCall(PetscOptionsBool("-eps_ciss_usest","Use ST for linear solves","EPSCISSSetUseST",b2,&b2,&flg));
1336: if (flg) PetscCall(EPSCISSSetUseST(eps,b2));
1338: PetscCall(PetscOptionsEnum("-eps_ciss_quadrule","Quadrature rule","EPSCISSSetQuadRule",EPSCISSQuadRules,(PetscEnum)ctx->quad,(PetscEnum*)&quad,&flg));
1339: if (flg) PetscCall(EPSCISSSetQuadRule(eps,quad));
1341: PetscCall(PetscOptionsEnum("-eps_ciss_extraction","Extraction technique","EPSCISSSetExtraction",EPSCISSExtractions,(PetscEnum)ctx->extraction,(PetscEnum*)&extraction,&flg));
1342: if (flg) PetscCall(EPSCISSSetExtraction(eps,extraction));
1344: PetscOptionsHeadEnd();
1346: if (!eps->rg) PetscCall(EPSGetRG(eps,&eps->rg));
1347: PetscCall(RGSetFromOptions(eps->rg)); /* this is necessary here to set useconj */
1348: if (!ctx->contour || !ctx->contour->ksp) PetscCall(EPSCISSGetKSPs(eps,NULL,NULL));
1349: PetscAssert(ctx->contour && ctx->contour->ksp,PetscObjectComm((PetscObject)eps),PETSC_ERR_PLIB,"Something went wrong with EPSCISSGetKSPs()");
1350: for (i=0;i<ctx->contour->npoints;i++) PetscCall(KSPSetFromOptions(ctx->contour->ksp[i]));
1351: PetscCall(PetscSubcommSetFromOptions(ctx->contour->subcomm));
1352: PetscFunctionReturn(PETSC_SUCCESS);
1353: }
1355: static PetscErrorCode EPSDestroy_CISS(EPS eps)
1356: {
1357: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1359: PetscFunctionBegin;
1360: PetscCall(SlepcContourDataDestroy(&ctx->contour));
1361: PetscCall(PetscFree4(ctx->weight,ctx->omega,ctx->pp,ctx->sigma));
1362: PetscCall(PetscFree(eps->data));
1363: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetSizes_C",NULL));
1364: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetSizes_C",NULL));
1365: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetThreshold_C",NULL));
1366: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetThreshold_C",NULL));
1367: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetRefinement_C",NULL));
1368: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetRefinement_C",NULL));
1369: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetUseST_C",NULL));
1370: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetUseST_C",NULL));
1371: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetQuadRule_C",NULL));
1372: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetQuadRule_C",NULL));
1373: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetExtraction_C",NULL));
1374: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetExtraction_C",NULL));
1375: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetKSPs_C",NULL));
1376: PetscFunctionReturn(PETSC_SUCCESS);
1377: }
1379: static PetscErrorCode EPSView_CISS(EPS eps,PetscViewer viewer)
1380: {
1381: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1382: PetscBool isascii;
1383: PetscViewer sviewer;
1385: PetscFunctionBegin;
1386: PetscCall(PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii));
1387: if (isascii) {
1388: PetscCall(PetscViewerASCIIPrintf(viewer," sizes { integration points: %" PetscInt_FMT ", block size: %" PetscInt_FMT ", moment size: %" PetscInt_FMT ", partitions: %" PetscInt_FMT ", maximum block size: %" PetscInt_FMT " }\n",ctx->N,ctx->L,ctx->M,ctx->npart,ctx->L_max));
1389: if (ctx->isreal) PetscCall(PetscViewerASCIIPrintf(viewer," exploiting symmetry of integration points\n"));
1390: PetscCall(PetscViewerASCIIPrintf(viewer," threshold { delta: %g, spurious threshold: %g }\n",(double)ctx->delta,(double)ctx->spurious_threshold));
1391: PetscCall(PetscViewerASCIIPrintf(viewer," iterative refinement { inner: %" PetscInt_FMT ", blocksize: %" PetscInt_FMT " }\n",ctx->refine_inner, ctx->refine_blocksize));
1392: PetscCall(PetscViewerASCIIPrintf(viewer," extraction: %s\n",EPSCISSExtractions[ctx->extraction]));
1393: PetscCall(PetscViewerASCIIPrintf(viewer," quadrature rule: %s\n",EPSCISSQuadRules[ctx->quad]));
1394: if (ctx->usest) PetscCall(PetscViewerASCIIPrintf(viewer," using ST for linear solves\n"));
1395: else {
1396: if (!ctx->contour || !ctx->contour->ksp) PetscCall(EPSCISSGetKSPs(eps,NULL,NULL));
1397: PetscAssert(ctx->contour && ctx->contour->ksp,PetscObjectComm((PetscObject)eps),PETSC_ERR_PLIB,"Something went wrong with EPSCISSGetKSPs()");
1398: PetscCall(PetscViewerASCIIPushTab(viewer));
1399: if (ctx->npart>1 && ctx->contour->subcomm) {
1400: PetscCall(PetscViewerGetSubViewer(viewer,ctx->contour->subcomm->child,&sviewer));
1401: if (!ctx->contour->subcomm->color) PetscCall(KSPView(ctx->contour->ksp[0],sviewer));
1402: PetscCall(PetscViewerFlush(sviewer));
1403: PetscCall(PetscViewerRestoreSubViewer(viewer,ctx->contour->subcomm->child,&sviewer));
1404: /* extra call needed because of the two calls to PetscViewerASCIIPushSynchronized() in PetscViewerGetSubViewer() */
1405: PetscCall(PetscViewerASCIIPopSynchronized(viewer));
1406: } else PetscCall(KSPView(ctx->contour->ksp[0],viewer));
1407: PetscCall(PetscViewerASCIIPopTab(viewer));
1408: }
1409: }
1410: PetscFunctionReturn(PETSC_SUCCESS);
1411: }
1413: static PetscErrorCode EPSSetDefaultST_CISS(EPS eps)
1414: {
1415: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1416: PetscBool usest = ctx->usest;
1417: KSP ksp;
1418: PC pc;
1420: PetscFunctionBegin;
1421: if (!((PetscObject)eps->st)->type_name) {
1422: if (!ctx->usest_set) usest = (ctx->npart>1)? PETSC_FALSE: PETSC_TRUE;
1423: if (usest) PetscCall(STSetType(eps->st,STSINVERT));
1424: else {
1425: /* we are not going to use ST, so avoid factorizing the matrix */
1426: PetscCall(STSetType(eps->st,STSHIFT));
1427: if (eps->isgeneralized) {
1428: PetscCall(STGetKSP(eps->st,&ksp));
1429: PetscCall(KSPGetPC(ksp,&pc));
1430: PetscCall(PCSetType(pc,PCNONE));
1431: }
1432: }
1433: }
1434: PetscFunctionReturn(PETSC_SUCCESS);
1435: }
1437: /*MC
1438: EPSCISS - EPSCISS = "ciss" - A contour integral eigensolver based on the
1439: Sakurai-Sugiura scheme.
1441: Notes:
1442: This solver is based on the numerical contour integration idea
1443: proposed initially by {cite:t}`Sak03` and improved later by adding
1444: a Rayleigh-Ritz projection step {cite:p}`Sak07`.
1446: Contour integral methods are able to compute all eigenvalues
1447: lying inside a region of the complex plane. Use `EPSGetRG()` to
1448: specify the region. However, the computational cost is usually high
1449: because multiple linear systems must be solved. For this, we can
1450: use the `KSP` object inside `ST`, or several independent `KSP`s,
1451: see `EPSCISSSetUseST()`.
1453: Details of the implementation in SLEPc can be found in {cite:p}`Mae16`.
1455: Level: beginner
1457: .seealso: [](ch:eps), `EPS`, `EPSType`, `EPSSetType()`, `EPSGetRG()`
1458: M*/
1459: SLEPC_EXTERN PetscErrorCode EPSCreate_CISS(EPS eps)
1460: {
1461: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1463: PetscFunctionBegin;
1464: PetscCall(PetscNew(&ctx));
1465: eps->data = ctx;
1467: eps->useds = PETSC_TRUE;
1468: eps->categ = EPS_CATEGORY_CONTOUR;
1470: eps->ops->solve = EPSSolve_CISS;
1471: eps->ops->setup = EPSSetUp_CISS;
1472: eps->ops->setupsort = EPSSetUpSort_CISS;
1473: eps->ops->setfromoptions = EPSSetFromOptions_CISS;
1474: eps->ops->destroy = EPSDestroy_CISS;
1475: eps->ops->reset = EPSReset_CISS;
1476: eps->ops->view = EPSView_CISS;
1477: eps->ops->computevectors = EPSComputeVectors_CISS;
1478: eps->ops->setdefaultst = EPSSetDefaultST_CISS;
1480: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetSizes_C",EPSCISSSetSizes_CISS));
1481: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetSizes_C",EPSCISSGetSizes_CISS));
1482: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetThreshold_C",EPSCISSSetThreshold_CISS));
1483: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetThreshold_C",EPSCISSGetThreshold_CISS));
1484: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetRefinement_C",EPSCISSSetRefinement_CISS));
1485: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetRefinement_C",EPSCISSGetRefinement_CISS));
1486: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetUseST_C",EPSCISSSetUseST_CISS));
1487: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetUseST_C",EPSCISSGetUseST_CISS));
1488: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetQuadRule_C",EPSCISSSetQuadRule_CISS));
1489: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetQuadRule_C",EPSCISSGetQuadRule_CISS));
1490: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetExtraction_C",EPSCISSSetExtraction_CISS));
1491: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetExtraction_C",EPSCISSGetExtraction_CISS));
1492: PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetKSPs_C",EPSCISSGetKSPs_CISS));
1494: /* set default values of parameters */
1495: ctx->N = 32;
1496: ctx->L = 16;
1497: ctx->M = ctx->N/4;
1498: ctx->delta = SLEPC_DEFAULT_TOL*1e-4;
1499: ctx->L_max = 64;
1500: ctx->spurious_threshold = PetscSqrtReal(SLEPC_DEFAULT_TOL);
1501: ctx->usest = PETSC_TRUE;
1502: ctx->usest_set = PETSC_FALSE;
1503: ctx->isreal = PETSC_FALSE;
1504: ctx->refine_inner = 0;
1505: ctx->refine_blocksize = 0;
1506: ctx->npart = 1;
1507: ctx->quad = (EPSCISSQuadRule)0;
1508: ctx->extraction = EPS_CISS_EXTRACTION_RITZ;
1509: PetscFunctionReturn(PETSC_SUCCESS);
1510: }