Actual source code: ciss.c
slepc-3.11.2 2019-07-30
1: /*
2: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
3: SLEPc - Scalable Library for Eigenvalue Problem Computations
4: Copyright (c) 2002-2019, 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> /*I "slepceps.h" I*/
34: #include <slepcblaslapack.h>
36: typedef struct {
37: /* parameters */
38: PetscInt N; /* number of integration points (32) */
39: PetscInt L; /* block size (16) */
40: PetscInt M; /* moment degree (N/4 = 4) */
41: PetscReal delta; /* threshold of singular value (1e-12) */
42: PetscInt L_max; /* maximum number of columns of the source matrix V */
43: PetscReal spurious_threshold; /* discard spurious eigenpairs */
44: PetscBool isreal; /* A and B are real */
45: PetscInt npart; /* number of partitions */
46: PetscInt refine_inner;
47: PetscInt refine_blocksize;
48: /* private data */
49: PetscReal *sigma; /* threshold for numerical rank */
50: PetscInt subcomm_id;
51: PetscInt num_solve_point;
52: PetscScalar *weight;
53: PetscScalar *omega;
54: PetscScalar *pp;
55: BV V;
56: BV S;
57: BV pV;
58: BV Y;
59: Vec xsub;
60: Vec xdup;
61: KSP *ksp; /* ksp array for storing factorizations at integration points */
62: PetscBool useconj;
63: PetscReal est_eig;
64: VecScatter scatterin;
65: Mat pA,pB;
66: PetscSubcomm subcomm;
67: PetscBool usest;
68: PetscBool usest_set; /* whether the user set the usest flag or not */
69: EPSCISSQuadRule quad;
70: EPSCISSExtraction extraction;
71: } EPS_CISS;
73: /* destroy KSP objects when the number of solve points changes */
74: PETSC_STATIC_INLINE PetscErrorCode EPSCISSResetSolvers(EPS eps)
75: {
77: PetscInt i;
78: EPS_CISS *ctx = (EPS_CISS*)eps->data;
81: if (ctx->ksp) {
82: for (i=0;i<ctx->num_solve_point;i++) {
83: KSPDestroy(&ctx->ksp[i]);
84: }
85: PetscFree(ctx->ksp);
86: }
87: return(0);
88: }
90: /* clean PetscSubcomm object when the number of partitions changes */
91: PETSC_STATIC_INLINE PetscErrorCode EPSCISSResetSubcomm(EPS eps)
92: {
94: EPS_CISS *ctx = (EPS_CISS*)eps->data;
97: EPSCISSResetSolvers(eps);
98: PetscSubcommDestroy(&ctx->subcomm);
99: return(0);
100: }
102: /* determine whether half of integration points can be avoided (use its conjugates);
103: depends on isreal and the center of the region */
104: PETSC_STATIC_INLINE PetscErrorCode EPSCISSSetUseConj(EPS eps,PetscBool *useconj)
105: {
107: PetscScalar center;
108: PetscReal c,d;
109: PetscBool isellipse,isinterval;
110: #if defined(PETSC_USE_COMPLEX)
111: EPS_CISS *ctx = (EPS_CISS*)eps->data;
112: #endif
115: *useconj = PETSC_FALSE;
116: PetscObjectTypeCompare((PetscObject)eps->rg,RGELLIPSE,&isellipse);
117: if (isellipse) {
118: RGEllipseGetParameters(eps->rg,¢er,NULL,NULL);
119: #if defined(PETSC_USE_COMPLEX)
120: *useconj = (ctx->isreal && PetscImaginaryPart(center) == 0.0)? PETSC_TRUE: PETSC_FALSE;
121: #endif
122: } else {
123: PetscObjectTypeCompare((PetscObject)eps->rg,RGINTERVAL,&isinterval);
124: if (isinterval) {
125: RGIntervalGetEndpoints(eps->rg,NULL,NULL,&c,&d);
126: #if defined(PETSC_USE_COMPLEX)
127: *useconj = (ctx->isreal && c==d)? PETSC_TRUE: PETSC_FALSE;
128: #endif
129: }
130: }
131: return(0);
132: }
134: /* create PetscSubcomm object and determine num_solve_point (depends on npart, N, useconj) */
135: PETSC_STATIC_INLINE PetscErrorCode EPSCISSSetUpSubComm(EPS eps,PetscInt *num_solve_point)
136: {
138: EPS_CISS *ctx = (EPS_CISS*)eps->data;
139: PetscInt N = ctx->N;
142: PetscSubcommCreate(PetscObjectComm((PetscObject)eps),&ctx->subcomm);
143: PetscSubcommSetNumber(ctx->subcomm,ctx->npart);
144: PetscSubcommSetType(ctx->subcomm,PETSC_SUBCOMM_INTERLACED);
145: PetscLogObjectMemory((PetscObject)eps,sizeof(PetscSubcomm));
146: ctx->subcomm_id = ctx->subcomm->color;
147: EPSCISSSetUseConj(eps,&ctx->useconj);
148: if (ctx->useconj) N = N/2;
149: *num_solve_point = N / ctx->npart;
150: if (N%ctx->npart > ctx->subcomm_id) (*num_solve_point)++;
151: return(0);
152: }
154: static PetscErrorCode CISSRedundantMat(EPS eps)
155: {
157: EPS_CISS *ctx = (EPS_CISS*)eps->data;
158: Mat A,B;
159: PetscInt nmat;
162: STGetNumMatrices(eps->st,&nmat);
163: if (ctx->subcomm->n != 1) {
164: STGetMatrix(eps->st,0,&A);
165: MatDestroy(&ctx->pA);
166: MatCreateRedundantMatrix(A,ctx->subcomm->n,PetscSubcommChild(ctx->subcomm),MAT_INITIAL_MATRIX,&ctx->pA);
167: if (nmat>1) {
168: STGetMatrix(eps->st,1,&B);
169: MatDestroy(&ctx->pB);
170: MatCreateRedundantMatrix(B,ctx->subcomm->n,PetscSubcommChild(ctx->subcomm),MAT_INITIAL_MATRIX,&ctx->pB);
171: } else ctx->pB = NULL;
172: } else {
173: ctx->pA = NULL;
174: ctx->pB = NULL;
175: }
176: return(0);
177: }
179: static PetscErrorCode CISSScatterVec(EPS eps)
180: {
182: EPS_CISS *ctx = (EPS_CISS*)eps->data;
183: IS is1,is2;
184: Vec v0;
185: PetscInt i,j,k,mstart,mend,mlocal;
186: PetscInt *idx1,*idx2,mloc_sub;
189: VecDestroy(&ctx->xsub);
190: MatCreateVecs(ctx->pA,&ctx->xsub,NULL);
192: VecDestroy(&ctx->xdup);
193: MatGetLocalSize(ctx->pA,&mloc_sub,NULL);
194: VecCreateMPI(PetscSubcommContiguousParent(ctx->subcomm),mloc_sub,PETSC_DECIDE,&ctx->xdup);
196: VecScatterDestroy(&ctx->scatterin);
197: BVGetColumn(ctx->V,0,&v0);
198: VecGetOwnershipRange(v0,&mstart,&mend);
199: mlocal = mend - mstart;
200: PetscMalloc2(ctx->subcomm->n*mlocal,&idx1,ctx->subcomm->n*mlocal,&idx2);
201: j = 0;
202: for (k=0;k<ctx->subcomm->n;k++) {
203: for (i=mstart;i<mend;i++) {
204: idx1[j] = i;
205: idx2[j++] = i + eps->n*k;
206: }
207: }
208: ISCreateGeneral(PetscObjectComm((PetscObject)eps),ctx->subcomm->n*mlocal,idx1,PETSC_COPY_VALUES,&is1);
209: ISCreateGeneral(PetscObjectComm((PetscObject)eps),ctx->subcomm->n*mlocal,idx2,PETSC_COPY_VALUES,&is2);
210: VecScatterCreate(v0,is1,ctx->xdup,is2,&ctx->scatterin);
211: ISDestroy(&is1);
212: ISDestroy(&is2);
213: PetscFree2(idx1,idx2);
214: BVRestoreColumn(ctx->V,0,&v0);
215: return(0);
216: }
218: static PetscErrorCode SetPathParameter(EPS eps)
219: {
221: EPS_CISS *ctx = (EPS_CISS*)eps->data;
222: PetscInt i,j;
223: PetscScalar center=0.0,tmp,tmp2,*omegai;
224: PetscReal theta,radius=1.0,vscale,a,b,c,d,max_w=0.0,rgscale;
225: #if defined(PETSC_USE_COMPLEX)
226: PetscReal start_ang,end_ang;
227: #endif
228: PetscBool isring=PETSC_FALSE,isellipse=PETSC_FALSE,isinterval=PETSC_FALSE;
231: PetscObjectTypeCompare((PetscObject)eps->rg,RGELLIPSE,&isellipse);
232: PetscObjectTypeCompare((PetscObject)eps->rg,RGRING,&isring);
233: PetscObjectTypeCompare((PetscObject)eps->rg,RGINTERVAL,&isinterval);
234: RGGetScale(eps->rg,&rgscale);
235: PetscMalloc1(ctx->N+1l,&omegai);
236: RGComputeContour(eps->rg,ctx->N,ctx->omega,omegai);
237: if (isellipse) {
238: RGEllipseGetParameters(eps->rg,¢er,&radius,&vscale);
239: for (i=0;i<ctx->N;i++) {
240: #if defined(PETSC_USE_COMPLEX)
241: theta = 2.0*PETSC_PI*(i+0.5)/ctx->N;
242: ctx->pp[i] = PetscCosReal(theta)+vscale*PetscSinReal(theta)*PETSC_i;
243: ctx->weight[i] = rgscale*radius*(vscale*PetscCosReal(theta)+PetscSinReal(theta)*PETSC_i)/(PetscReal)ctx->N;
244: #else
245: theta = (PETSC_PI/ctx->N)*(i+0.5);
246: ctx->pp[i] = PetscCosReal(theta);
247: ctx->weight[i] = PetscCosReal((ctx->N-1)*theta)/ctx->N;
248: ctx->omega[i] = rgscale*(center + radius*ctx->pp[i]);
249: #endif
250: }
251: } else if (ctx->quad == EPS_CISS_QUADRULE_CHEBYSHEV) {
252: for (i=0;i<ctx->N;i++) {
253: theta = (PETSC_PI/ctx->N)*(i+0.5);
254: ctx->pp[i] = PetscCosReal(theta);
255: ctx->weight[i] = PetscCosReal((ctx->N-1)*theta)/ctx->N;
256: }
257: if (isinterval) {
258: RGIntervalGetEndpoints(eps->rg,&a,&b,&c,&d);
259: if ((c!=d || c!=0.0) && (a!=b || a!=0.0)) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Endpoints of the imaginary axis or the real axis must be both zero");
260: for (i=0;i<ctx->N;i++) {
261: if (c==d) ctx->omega[i] = ((b-a)*(ctx->pp[i]+1.0)/2.0+a)*rgscale;
262: if (a==b) {
263: #if defined(PETSC_USE_COMPLEX)
264: ctx->omega[i] = ((d-c)*(ctx->pp[i]+1.0)/2.0+c)*rgscale*PETSC_i;
265: #else
266: SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Integration points on a vertical line require complex arithmetic");
267: #endif
268: }
269: }
270: }
271: if (isring) { /* only supported in complex scalars */
272: #if defined(PETSC_USE_COMPLEX)
273: RGRingGetParameters(eps->rg,¢er,&radius,&vscale,&start_ang,&end_ang,NULL);
274: for (i=0;i<ctx->N;i++) {
275: theta = (start_ang*2.0+(end_ang-start_ang)*(PetscRealPart(ctx->pp[i])+1.0))*PETSC_PI;
276: ctx->omega[i] = rgscale*(center + radius*(PetscCosReal(theta)+PETSC_i*vscale*PetscSinReal(theta)));
277: }
278: #endif
279: }
280: } else {
281: if (isinterval) {
282: RGIntervalGetEndpoints(eps->rg,&a,&b,&c,&d);
283: center = rgscale*((b+a)/2.0+(d+c)/2.0*PETSC_PI);
284: radius = PetscSqrtReal(PetscPowRealInt(rgscale*(b-a)/2.0,2)+PetscPowRealInt(rgscale*(d-c)/2.0,2));
285: } else if (isring) {
286: RGRingGetParameters(eps->rg,¢er,&radius,NULL,NULL,NULL,NULL);
287: center *= rgscale;
288: radius *= rgscale;
289: }
290: for (i=0;i<ctx->N;i++) {
291: ctx->pp[i] = (ctx->omega[i]-center)/radius;
292: tmp = 1; tmp2 = 1;
293: for (j=0;j<ctx->N;j++) {
294: tmp *= ctx->omega[j];
295: if (i != j) tmp2 *= ctx->omega[j]-ctx->omega[i];
296: }
297: ctx->weight[i] = tmp/tmp2;
298: max_w = PetscMax(PetscAbsScalar(ctx->weight[i]),max_w);
299: }
300: for (i=0;i<ctx->N;i++) ctx->weight[i] /= (PetscScalar)max_w;
301: }
302: PetscFree(omegai);
303: return(0);
304: }
306: static PetscErrorCode CISSVecSetRandom(BV V,PetscInt i0,PetscInt i1)
307: {
309: PetscInt i,j,nlocal;
310: PetscScalar *vdata;
311: Vec x;
314: BVGetSizes(V,&nlocal,NULL,NULL);
315: for (i=i0;i<i1;i++) {
316: BVSetRandomColumn(V,i);
317: BVGetColumn(V,i,&x);
318: VecGetArray(x,&vdata);
319: for (j=0;j<nlocal;j++) {
320: vdata[j] = PetscRealPart(vdata[j]);
321: if (PetscRealPart(vdata[j]) < 0.5) vdata[j] = -1.0;
322: else vdata[j] = 1.0;
323: }
324: VecRestoreArray(x,&vdata);
325: BVRestoreColumn(V,i,&x);
326: }
327: return(0);
328: }
330: static PetscErrorCode VecScatterVecs(EPS eps,BV Vin,PetscInt n)
331: {
332: PetscErrorCode ierr;
333: EPS_CISS *ctx = (EPS_CISS*)eps->data;
334: PetscInt i;
335: Vec vi,pvi;
336: const PetscScalar *array;
339: for (i=0;i<n;i++) {
340: BVGetColumn(Vin,i,&vi);
341: VecScatterBegin(ctx->scatterin,vi,ctx->xdup,INSERT_VALUES,SCATTER_FORWARD);
342: VecScatterEnd(ctx->scatterin,vi,ctx->xdup,INSERT_VALUES,SCATTER_FORWARD);
343: BVRestoreColumn(Vin,i,&vi);
344: VecGetArrayRead(ctx->xdup,&array);
345: VecPlaceArray(ctx->xsub,array);
346: BVGetColumn(ctx->pV,i,&pvi);
347: VecCopy(ctx->xsub,pvi);
348: BVRestoreColumn(ctx->pV,i,&pvi);
349: VecResetArray(ctx->xsub);
350: VecRestoreArrayRead(ctx->xdup,&array);
351: }
352: return(0);
353: }
355: static PetscErrorCode SolveLinearSystem(EPS eps,Mat A,Mat B,BV V,PetscInt L_start,PetscInt L_end,PetscBool initksp)
356: {
358: EPS_CISS *ctx = (EPS_CISS*)eps->data;
359: PetscInt i,j,p_id;
360: Mat Fz,kspMat;
361: Vec Bvj,vj,yj;
362: KSP ksp;
365: if (!ctx->ksp) { EPSCISSGetKSPs(eps,&ctx->num_solve_point,&ctx->ksp); }
366: BVCreateVec(V,&Bvj);
367: if (ctx->usest) {
368: MatDuplicate(A,MAT_DO_NOT_COPY_VALUES,&Fz);
369: }
370: for (i=0;i<ctx->num_solve_point;i++) {
371: p_id = i*ctx->subcomm->n + ctx->subcomm_id;
372: if (!ctx->usest && initksp) {
373: MatDuplicate(A,MAT_COPY_VALUES,&kspMat);
374: if (B) {
375: MatAXPY(kspMat,-ctx->omega[p_id],B,DIFFERENT_NONZERO_PATTERN);
376: } else {
377: MatShift(kspMat,-ctx->omega[p_id]);
378: }
379: KSPSetOperators(ctx->ksp[i],kspMat,kspMat);
380: MatDestroy(&kspMat);
381: } else if (ctx->usest) {
382: STSetShift(eps->st,ctx->omega[p_id]);
383: STGetKSP(eps->st,&ksp);
384: }
385: for (j=L_start;j<L_end;j++) {
386: BVGetColumn(V,j,&vj);
387: BVGetColumn(ctx->Y,i*ctx->L_max+j,&yj);
388: if (B) {
389: MatMult(B,vj,Bvj);
390: if (ctx->usest) {
391: KSPSolve(ksp,Bvj,yj);
392: } else {
393: KSPSolve(ctx->ksp[i],Bvj,yj);
394: }
395: } else {
396: if (ctx->usest) {
397: KSPSolve(ksp,vj,yj);
398: } else {
399: KSPSolve(ctx->ksp[i],vj,yj);
400: }
401: }
402: BVRestoreColumn(V,j,&vj);
403: BVRestoreColumn(ctx->Y,i*ctx->L_max+j,&yj);
404: }
405: if (ctx->usest && i<ctx->num_solve_point-1) { KSPReset(ksp); }
406: }
407: if (ctx->usest) { MatDestroy(&Fz); }
408: VecDestroy(&Bvj);
409: return(0);
410: }
412: #if defined(PETSC_USE_COMPLEX)
413: static PetscErrorCode EstimateNumberEigs(EPS eps,PetscInt *L_add)
414: {
416: EPS_CISS *ctx = (EPS_CISS*)eps->data;
417: PetscInt i,j,p_id;
418: PetscScalar tmp,m = 1,sum = 0.0;
419: PetscReal eta;
420: Vec v,vtemp,vj,yj;
423: BVGetColumn(ctx->Y,0,&yj);
424: VecDuplicate(yj,&v);
425: BVRestoreColumn(ctx->Y,0,&yj);
426: BVCreateVec(ctx->V,&vtemp);
427: for (j=0;j<ctx->L;j++) {
428: VecSet(v,0);
429: for (i=0;i<ctx->num_solve_point; i++) {
430: p_id = i*ctx->subcomm->n + ctx->subcomm_id;
431: BVSetActiveColumns(ctx->Y,i*ctx->L_max+j,i*ctx->L_max+j+1);
432: BVMultVec(ctx->Y,ctx->weight[p_id],1,v,&m);
433: }
434: BVGetColumn(ctx->V,j,&vj);
435: if (ctx->pA) {
436: VecSet(vtemp,0);
437: VecScatterBegin(ctx->scatterin,v,vtemp,ADD_VALUES,SCATTER_REVERSE);
438: VecScatterEnd(ctx->scatterin,v,vtemp,ADD_VALUES,SCATTER_REVERSE);
439: VecDot(vj,vtemp,&tmp);
440: } else {
441: VecDot(vj,v,&tmp);
442: }
443: BVRestoreColumn(ctx->V,j,&vj);
444: if (ctx->useconj) sum += PetscRealPart(tmp)*2;
445: else sum += tmp;
446: }
447: ctx->est_eig = PetscAbsScalar(sum/(PetscReal)ctx->L);
448: eta = PetscPowReal(10.0,-PetscLog10Real(eps->tol)/ctx->N);
449: PetscInfo1(eps,"Estimation_#Eig %f\n",(double)ctx->est_eig);
450: *L_add = (PetscInt)PetscCeilReal((ctx->est_eig*eta)/ctx->M) - ctx->L;
451: if (*L_add < 0) *L_add = 0;
452: if (*L_add>ctx->L_max-ctx->L) {
453: PetscInfo(eps,"Number of eigenvalues around the contour path may be too large\n");
454: *L_add = ctx->L_max-ctx->L;
455: }
456: VecDestroy(&v);
457: VecDestroy(&vtemp);
458: return(0);
459: }
460: #endif
462: static PetscErrorCode CalcMu(EPS eps,PetscScalar *Mu)
463: {
465: PetscMPIInt sub_size,len;
466: PetscInt i,j,k,s;
467: PetscScalar *m,*temp,*temp2,*ppk,alp;
468: EPS_CISS *ctx = (EPS_CISS*)eps->data;
469: Mat M;
472: MPI_Comm_size(PetscSubcommChild(ctx->subcomm),&sub_size);
473: PetscMalloc3(ctx->num_solve_point*ctx->L*(ctx->L+1),&temp,2*ctx->M*ctx->L*ctx->L,&temp2,ctx->num_solve_point,&ppk);
474: MatCreateSeqDense(PETSC_COMM_SELF,ctx->L,ctx->L_max*ctx->num_solve_point,NULL,&M);
475: for (i=0;i<2*ctx->M*ctx->L*ctx->L;i++) temp2[i] = 0;
476: BVSetActiveColumns(ctx->Y,0,ctx->L_max*ctx->num_solve_point);
477: if (ctx->pA) {
478: BVSetActiveColumns(ctx->pV,0,ctx->L);
479: BVDot(ctx->Y,ctx->pV,M);
480: } else {
481: BVSetActiveColumns(ctx->V,0,ctx->L);
482: BVDot(ctx->Y,ctx->V,M);
483: }
484: MatDenseGetArray(M,&m);
485: for (i=0;i<ctx->num_solve_point;i++) {
486: for (j=0;j<ctx->L;j++) {
487: for (k=0;k<ctx->L;k++) {
488: temp[k+j*ctx->L+i*ctx->L*ctx->L]=m[k+j*ctx->L+i*ctx->L*ctx->L_max];
489: }
490: }
491: }
492: MatDenseRestoreArray(M,&m);
493: for (i=0;i<ctx->num_solve_point;i++) ppk[i] = 1;
494: for (k=0;k<2*ctx->M;k++) {
495: for (j=0;j<ctx->L;j++) {
496: for (i=0;i<ctx->num_solve_point;i++) {
497: alp = ppk[i]*ctx->weight[i*ctx->subcomm->n + ctx->subcomm_id];
498: for (s=0;s<ctx->L;s++) {
499: if (ctx->useconj) temp2[s+(j+k*ctx->L)*ctx->L] += PetscRealPart(alp*temp[s+(j+i*ctx->L)*ctx->L])*2;
500: else temp2[s+(j+k*ctx->L)*ctx->L] += alp*temp[s+(j+i*ctx->L)*ctx->L];
501: }
502: }
503: }
504: for (i=0;i<ctx->num_solve_point;i++)
505: ppk[i] *= ctx->pp[i*ctx->subcomm->n + ctx->subcomm_id];
506: }
507: for (i=0;i<2*ctx->M*ctx->L*ctx->L;i++) temp2[i] /= sub_size;
508: PetscMPIIntCast(2*ctx->M*ctx->L*ctx->L,&len);
509: MPI_Allreduce(temp2,Mu,len,MPIU_SCALAR,MPIU_SUM,PetscObjectComm((PetscObject)eps));
510: PetscFree3(temp,temp2,ppk);
511: MatDestroy(&M);
512: return(0);
513: }
515: static PetscErrorCode BlockHankel(EPS eps,PetscScalar *Mu,PetscInt s,PetscScalar *H)
516: {
517: EPS_CISS *ctx = (EPS_CISS*)eps->data;
518: PetscInt i,j,k,L=ctx->L,M=ctx->M;
521: for (k=0;k<L*M;k++)
522: for (j=0;j<M;j++)
523: for (i=0;i<L;i++)
524: H[j*L+i+k*L*M] = Mu[i+k*L+(j+s)*L*L];
525: return(0);
526: }
528: static PetscErrorCode SVD_H0(EPS eps,PetscScalar *S,PetscInt *K)
529: {
530: #if defined(PETSC_MISSING_LAPACK_GESVD)
532: SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GESVD - Lapack routine is unavailable");
533: #else
535: EPS_CISS *ctx = (EPS_CISS*)eps->data;
536: PetscInt i,ml=ctx->L*ctx->M;
537: PetscBLASInt m,n,lda,ldu,ldvt,lwork,info;
538: PetscScalar *work;
539: #if defined(PETSC_USE_COMPLEX)
540: PetscReal *rwork;
541: #endif
544: PetscMalloc1(5*ml,&work);
545: #if defined(PETSC_USE_COMPLEX)
546: PetscMalloc1(5*ml,&rwork);
547: #endif
548: PetscBLASIntCast(ml,&m);
549: n = m; lda = m; ldu = m; ldvt = m; lwork = 5*m;
550: PetscFPTrapPush(PETSC_FP_TRAP_OFF);
551: #if defined(PETSC_USE_COMPLEX)
552: PetscStackCallBLAS("LAPACKgesvd",LAPACKgesvd_("N","N",&m,&n,S,&lda,ctx->sigma,NULL,&ldu,NULL,&ldvt,work,&lwork,rwork,&info));
553: #else
554: PetscStackCallBLAS("LAPACKgesvd",LAPACKgesvd_("N","N",&m,&n,S,&lda,ctx->sigma,NULL,&ldu,NULL,&ldvt,work,&lwork,&info));
555: #endif
556: SlepcCheckLapackInfo("gesvd",info);
557: PetscFPTrapPop();
558: (*K) = 0;
559: for (i=0;i<ml;i++) {
560: if (ctx->sigma[i]/PetscMax(ctx->sigma[0],1)>ctx->delta) (*K)++;
561: }
562: PetscFree(work);
563: #if defined(PETSC_USE_COMPLEX)
564: PetscFree(rwork);
565: #endif
566: return(0);
567: #endif
568: }
570: static PetscErrorCode ConstructS(EPS eps)
571: {
573: EPS_CISS *ctx = (EPS_CISS*)eps->data;
574: PetscInt i,j,k,vec_local_size,p_id;
575: Vec v,sj,yj;
576: PetscScalar *ppk, *v_data, m = 1;
579: BVGetSizes(ctx->Y,&vec_local_size,NULL,NULL);
580: PetscMalloc1(ctx->num_solve_point,&ppk);
581: for (i=0;i<ctx->num_solve_point;i++) ppk[i] = 1;
582: BVGetColumn(ctx->Y,0,&yj);
583: VecDuplicate(yj,&v);
584: BVRestoreColumn(ctx->Y,0,&yj);
585: for (k=0;k<ctx->M;k++) {
586: for (j=0;j<ctx->L;j++) {
587: VecSet(v,0);
588: for (i=0;i<ctx->num_solve_point;i++) {
589: p_id = i*ctx->subcomm->n + ctx->subcomm_id;
590: BVSetActiveColumns(ctx->Y,i*ctx->L_max+j,i*ctx->L_max+j+1);
591: BVMultVec(ctx->Y,ppk[i]*ctx->weight[p_id],1.0,v,&m);
592: }
593: if (ctx->useconj) {
594: VecGetArray(v,&v_data);
595: for (i=0;i<vec_local_size;i++) v_data[i] = PetscRealPart(v_data[i])*2;
596: VecRestoreArray(v,&v_data);
597: }
598: BVGetColumn(ctx->S,k*ctx->L+j,&sj);
599: if (ctx->pA) {
600: VecSet(sj,0);
601: VecScatterBegin(ctx->scatterin,v,sj,ADD_VALUES,SCATTER_REVERSE);
602: VecScatterEnd(ctx->scatterin,v,sj,ADD_VALUES,SCATTER_REVERSE);
603: } else {
604: VecCopy(v,sj);
605: }
606: BVRestoreColumn(ctx->S,k*ctx->L+j,&sj);
607: }
608: for (i=0;i<ctx->num_solve_point;i++) {
609: p_id = i*ctx->subcomm->n + ctx->subcomm_id;
610: ppk[i] *= ctx->pp[p_id];
611: }
612: }
613: PetscFree(ppk);
614: VecDestroy(&v);
615: return(0);
616: }
618: static PetscErrorCode SVD_S(BV S,PetscInt ml,PetscReal delta,PetscReal *sigma,PetscInt *K)
619: {
620: #if defined(PETSC_MISSING_LAPACK_GESVD)
622: SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GESVD - Lapack routine is unavailable");
623: #else
625: PetscInt i,j,k,local_size;
626: PetscMPIInt len;
627: PetscScalar *work,*temp,*B,*tempB,*s_data,*Q1,*Q2,*temp2,alpha=1,beta=0;
628: PetscBLASInt l,m,n,lda,ldu,ldvt,lwork,info,ldb,ldc;
629: #if defined(PETSC_USE_COMPLEX)
630: PetscReal *rwork;
631: #endif
634: BVGetSizes(S,&local_size,NULL,NULL);
635: BVGetArray(S,&s_data);
636: PetscMalloc7(ml*ml,&temp,ml*ml,&temp2,local_size*ml,&Q1,local_size*ml,&Q2,ml*ml,&B,ml*ml,&tempB,5*ml,&work);
637: PetscMemzero(B,ml*ml*sizeof(PetscScalar));
638: #if defined(PETSC_USE_COMPLEX)
639: PetscMalloc1(5*ml,&rwork);
640: #endif
641: PetscFPTrapPush(PETSC_FP_TRAP_OFF);
643: for (i=0;i<ml;i++) B[i*ml+i]=1;
645: for (k=0;k<2;k++) {
646: PetscBLASIntCast(local_size,&m);
647: PetscBLASIntCast(ml,&l);
648: n = l; lda = m; ldb = m; ldc = l;
649: if (k == 0) {
650: PetscStackCallBLAS("BLASgemm",BLASgemm_("C","N",&l,&n,&m,&alpha,s_data,&lda,s_data,&ldb,&beta,temp,&ldc));
651: } else if ((k%2)==1) {
652: PetscStackCallBLAS("BLASgemm",BLASgemm_("C","N",&l,&n,&m,&alpha,Q1,&lda,Q1,&ldb,&beta,temp,&ldc));
653: } else {
654: PetscStackCallBLAS("BLASgemm",BLASgemm_("C","N",&l,&n,&m,&alpha,Q2,&lda,Q2,&ldb,&beta,temp,&ldc));
655: }
656: PetscMemzero(temp2,ml*ml*sizeof(PetscScalar));
657: PetscMPIIntCast(ml*ml,&len);
658: MPI_Allreduce(temp,temp2,len,MPIU_SCALAR,MPIU_SUM,PetscObjectComm((PetscObject)S));
660: PetscBLASIntCast(ml,&m);
661: n = m; lda = m; lwork = 5*m, ldu = 1; ldvt = 1;
662: #if defined(PETSC_USE_COMPLEX)
663: PetscStackCallBLAS("LAPACKgesvd",LAPACKgesvd_("O","N",&m,&n,temp2,&lda,sigma,NULL,&ldu,NULL,&ldvt,work,&lwork,rwork,&info));
664: #else
665: PetscStackCallBLAS("LAPACKgesvd",LAPACKgesvd_("O","N",&m,&n,temp2,&lda,sigma,NULL,&ldu,NULL,&ldvt,work,&lwork,&info));
666: #endif
667: SlepcCheckLapackInfo("gesvd",info);
669: PetscBLASIntCast(local_size,&l);
670: PetscBLASIntCast(ml,&n);
671: m = n; lda = l; ldb = m; ldc = l;
672: if (k==0) {
673: PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&l,&n,&m,&alpha,s_data,&lda,temp2,&ldb,&beta,Q1,&ldc));
674: } else if ((k%2)==1) {
675: PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&l,&n,&m,&alpha,Q1,&lda,temp2,&ldb,&beta,Q2,&ldc));
676: } else {
677: PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&l,&n,&m,&alpha,Q2,&lda,temp2,&ldb,&beta,Q1,&ldc));
678: }
680: PetscBLASIntCast(ml,&l);
681: m = l; n = l; lda = l; ldb = m; ldc = l;
682: PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&l,&n,&m,&alpha,B,&lda,temp2,&ldb,&beta,tempB,&ldc));
683: for (i=0;i<ml;i++) {
684: sigma[i] = sqrt(sigma[i]);
685: for (j=0;j<local_size;j++) {
686: if ((k%2)==1) Q2[j+i*local_size]/=sigma[i];
687: else Q1[j+i*local_size]/=sigma[i];
688: }
689: for (j=0;j<ml;j++) {
690: B[j+i*ml]=tempB[j+i*ml]*sigma[i];
691: }
692: }
693: }
695: PetscBLASIntCast(ml,&m);
696: n = m; lda = m; ldu=1; ldvt=1;
697: #if defined(PETSC_USE_COMPLEX)
698: PetscStackCallBLAS("LAPACKgesvd",LAPACKgesvd_("N","O",&m,&n,B,&lda,sigma,NULL,&ldu,NULL,&ldvt,work,&lwork,rwork,&info));
699: #else
700: PetscStackCallBLAS("LAPACKgesvd",LAPACKgesvd_("N","O",&m,&n,B,&lda,sigma,NULL,&ldu,NULL,&ldvt,work,&lwork,&info));
701: #endif
702: SlepcCheckLapackInfo("gesvd",info);
704: PetscBLASIntCast(local_size,&l);
705: PetscBLASIntCast(ml,&n);
706: m = n; lda = l; ldb = m; ldc = l;
707: if ((k%2)==1) {
708: PetscStackCallBLAS("BLASgemm",BLASgemm_("N","T",&l,&n,&m,&alpha,Q1,&lda,B,&ldb,&beta,s_data,&ldc));
709: } else {
710: PetscStackCallBLAS("BLASgemm",BLASgemm_("N","T",&l,&n,&m,&alpha,Q2,&lda,B,&ldb,&beta,s_data,&ldc));
711: }
713: PetscFPTrapPop();
714: BVRestoreArray(S,&s_data);
716: (*K) = 0;
717: for (i=0;i<ml;i++) {
718: if (sigma[i]/PetscMax(sigma[0],1)>delta) (*K)++;
719: }
720: PetscFree7(temp,temp2,Q1,Q2,B,tempB,work);
721: #if defined(PETSC_USE_COMPLEX)
722: PetscFree(rwork);
723: #endif
724: return(0);
725: #endif
726: }
728: static PetscErrorCode isGhost(EPS eps,PetscInt ld,PetscInt nv,PetscBool *fl)
729: {
731: EPS_CISS *ctx = (EPS_CISS*)eps->data;
732: PetscInt i,j;
733: PetscScalar *pX;
734: PetscReal *tau,s1,s2,tau_max=0.0;
737: PetscMalloc1(nv,&tau);
738: DSVectors(eps->ds,DS_MAT_X,NULL,NULL);
739: DSGetArray(eps->ds,DS_MAT_X,&pX);
741: for (i=0;i<nv;i++) {
742: s1 = 0;
743: s2 = 0;
744: for (j=0;j<nv;j++) {
745: s1 += PetscAbsScalar(PetscPowScalarInt(pX[i*ld+j],2));
746: s2 += PetscPowRealInt(PetscAbsScalar(pX[i*ld+j]),2)/ctx->sigma[j];
747: }
748: tau[i] = s1/s2;
749: tau_max = PetscMax(tau_max,tau[i]);
750: }
751: DSRestoreArray(eps->ds,DS_MAT_X,&pX);
752: for (i=0;i<nv;i++) {
753: tau[i] /= tau_max;
754: }
755: for (i=0;i<nv;i++) {
756: if (tau[i]>=ctx->spurious_threshold) fl[i] = PETSC_TRUE;
757: else fl[i] = PETSC_FALSE;
758: }
759: PetscFree(tau);
760: return(0);
761: }
763: static PetscErrorCode rescale_eig(EPS eps,PetscInt nv)
764: {
766: EPS_CISS *ctx = (EPS_CISS*)eps->data;
767: PetscInt i;
768: PetscScalar center;
769: PetscReal radius,a,b,c,d,rgscale;
770: #if defined(PETSC_USE_COMPLEX)
771: PetscReal start_ang,end_ang,vscale,theta;
772: #endif
773: PetscBool isring,isellipse,isinterval;
776: PetscObjectTypeCompare((PetscObject)eps->rg,RGELLIPSE,&isellipse);
777: PetscObjectTypeCompare((PetscObject)eps->rg,RGRING,&isring);
778: PetscObjectTypeCompare((PetscObject)eps->rg,RGINTERVAL,&isinterval);
779: RGGetScale(eps->rg,&rgscale);
780: if (isinterval) {
781: RGIntervalGetEndpoints(eps->rg,NULL,NULL,&c,&d);
782: if (c==d) {
783: for (i=0;i<nv;i++) {
784: #if defined(PETSC_USE_COMPLEX)
785: eps->eigr[i] = PetscRealPart(eps->eigr[i]);
786: #else
787: eps->eigi[i] = 0;
788: #endif
789: }
790: }
791: }
792: if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {
793: if (isellipse) {
794: RGEllipseGetParameters(eps->rg,¢er,&radius,NULL);
795: for (i=0;i<nv;i++) eps->eigr[i] = rgscale*(center + radius*eps->eigr[i]);
796: } else if (isinterval) {
797: RGIntervalGetEndpoints(eps->rg,&a,&b,&c,&d);
798: if (ctx->quad == EPS_CISS_QUADRULE_CHEBYSHEV) {
799: for (i=0;i<nv;i++) {
800: if (c==d) eps->eigr[i] = ((b-a)*(eps->eigr[i]+1.0)/2.0+a)*rgscale;
801: if (a==b) {
802: #if defined(PETSC_USE_COMPLEX)
803: eps->eigr[i] = ((d-c)*(eps->eigr[i]+1.0)/2.0+c)*rgscale*PETSC_i;
804: #else
805: SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Integration points on a vertical line require complex arithmetic");
806: #endif
807: }
808: }
809: } else {
810: center = (b+a)/2.0+(d+c)/2.0*PETSC_PI;
811: radius = PetscSqrtReal(PetscPowRealInt((b-a)/2.0,2)+PetscPowRealInt((d-c)/2.0,2));
812: for (i=0;i<nv;i++) eps->eigr[i] = center + radius*eps->eigr[i];
813: }
814: } else if (isring) { /* only supported in complex scalars */
815: #if defined(PETSC_USE_COMPLEX)
816: RGRingGetParameters(eps->rg,¢er,&radius,&vscale,&start_ang,&end_ang,NULL);
817: if (ctx->quad == EPS_CISS_QUADRULE_CHEBYSHEV) {
818: for (i=0;i<nv;i++) {
819: theta = (start_ang*2.0+(end_ang-start_ang)*(PetscRealPart(eps->eigr[i])+1.0))*PETSC_PI;
820: eps->eigr[i] = rgscale*center + (rgscale*radius+PetscImaginaryPart(eps->eigr[i]))*(PetscCosReal(theta)+PETSC_i*vscale*PetscSinReal(theta));
821: }
822: } else {
823: for (i=0;i<nv;i++) eps->eigr[i] = rgscale*(center + radius*eps->eigr[i]);
824: }
825: #endif
826: }
827: }
828: return(0);
829: }
831: PetscErrorCode EPSSetUp_CISS(EPS eps)
832: {
834: EPS_CISS *ctx = (EPS_CISS*)eps->data;
835: PetscBool issinvert,istrivial,isring,isellipse,isinterval,flg,useconj;
836: PetscReal c,d;
837: Mat A;
840: if (!eps->ncv) {
841: eps->ncv = ctx->L_max*ctx->M;
842: if (eps->ncv>eps->n) {
843: eps->ncv = eps->n;
844: ctx->L_max = eps->ncv/ctx->M;
845: if (!ctx->L_max) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Cannot adjust solver parameters, try setting a smaller value of M (moment size)");
846: }
847: } else {
848: EPSSetDimensions_Default(eps,eps->nev,&eps->ncv,&eps->mpd);
849: ctx->L_max = eps->ncv/ctx->M;
850: if (!ctx->L_max) {
851: ctx->L_max = 1;
852: eps->ncv = ctx->L_max*ctx->M;
853: }
854: }
855: ctx->L = PetscMin(ctx->L,ctx->L_max);
856: if (!eps->max_it) eps->max_it = 1;
857: if (!eps->mpd) eps->mpd = eps->ncv;
858: if (!eps->which) eps->which = EPS_ALL;
859: if (!eps->extraction) { EPSSetExtraction(eps,EPS_RITZ); }
860: else if (eps->extraction!=EPS_RITZ) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Unsupported extraction type");
861: if (eps->arbitrary) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Arbitrary selection of eigenpairs not supported in this solver");
862: if (eps->stopping!=EPSStoppingBasic) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"This solver does not support user-defined stopping test");
864: /* check region */
865: RGIsTrivial(eps->rg,&istrivial);
866: if (istrivial) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"CISS requires a nontrivial region, e.g. -rg_type ellipse ...");
867: RGGetComplement(eps->rg,&flg);
868: if (flg) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"A region with complement flag set is not allowed");
869: PetscObjectTypeCompare((PetscObject)eps->rg,RGELLIPSE,&isellipse);
870: PetscObjectTypeCompare((PetscObject)eps->rg,RGRING,&isring);
871: PetscObjectTypeCompare((PetscObject)eps->rg,RGINTERVAL,&isinterval);
872: if (!isellipse && !isring && !isinterval) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Currently only implemented for interval, elliptic or ring regions");
873: /* if useconj has changed, then reset subcomm data */
874: EPSCISSSetUseConj(eps,&useconj);
875: if (useconj!=ctx->useconj) { EPSCISSResetSubcomm(eps); }
877: #if !defined(PETSC_USE_COMPLEX)
878: if (isring) {
879: SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Ring region only supported for complex scalars");
880: }
881: #endif
882: if (isinterval) {
883: RGIntervalGetEndpoints(eps->rg,NULL,NULL,&c,&d);
884: #if !defined(PETSC_USE_COMPLEX)
885: if (c!=d || c!=0.0) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"In real scalars, endpoints of the imaginary axis must be both zero");
886: #endif
887: if (!ctx->quad && c==d) ctx->quad = EPS_CISS_QUADRULE_CHEBYSHEV;
888: }
889: if (!ctx->quad) ctx->quad = EPS_CISS_QUADRULE_TRAPEZOIDAL;
891: /* create split comm */
892: if (!ctx->subcomm) { EPSCISSSetUpSubComm(eps,&ctx->num_solve_point); }
894: EPSAllocateSolution(eps,0);
895: if (ctx->weight) { PetscFree4(ctx->weight,ctx->omega,ctx->pp,ctx->sigma); }
896: PetscMalloc4(ctx->N,&ctx->weight,ctx->N+1,&ctx->omega,ctx->N,&ctx->pp,ctx->L_max*ctx->M,&ctx->sigma);
897: PetscLogObjectMemory((PetscObject)eps,3*ctx->N*sizeof(PetscScalar)+ctx->L_max*ctx->N*sizeof(PetscReal));
899: /* allocate basis vectors */
900: BVDestroy(&ctx->S);
901: BVDuplicateResize(eps->V,ctx->L_max*ctx->M,&ctx->S);
902: PetscLogObjectParent((PetscObject)eps,(PetscObject)ctx->S);
903: BVDestroy(&ctx->V);
904: BVDuplicateResize(eps->V,ctx->L_max,&ctx->V);
905: PetscLogObjectParent((PetscObject)eps,(PetscObject)ctx->V);
907: STGetMatrix(eps->st,0,&A);
908: PetscObjectTypeCompare((PetscObject)A,MATSHELL,&flg);
909: if (flg) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"Matrix type shell is not supported in this solver");
911: if (!ctx->usest_set) ctx->usest = (ctx->npart>1)? PETSC_FALSE: PETSC_TRUE;
912: if (ctx->usest && ctx->npart>1) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"The usest flag is not supported when partitions > 1");
914: CISSRedundantMat(eps);
915: if (ctx->pA) {
916: CISSScatterVec(eps);
917: BVDestroy(&ctx->pV);
918: BVCreate(PetscObjectComm((PetscObject)ctx->xsub),&ctx->pV);
919: BVSetSizesFromVec(ctx->pV,ctx->xsub,eps->n);
920: BVSetFromOptions(ctx->pV);
921: BVResize(ctx->pV,ctx->L_max,PETSC_FALSE);
922: PetscLogObjectParent((PetscObject)eps,(PetscObject)ctx->pV);
923: }
925: if (ctx->usest) {
926: PetscObjectTypeCompare((PetscObject)eps->st,STSINVERT,&issinvert);
927: if (!issinvert) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"If the usest flag is set, you must select the STSINVERT spectral transformation");
928: }
930: BVDestroy(&ctx->Y);
931: if (ctx->pA) {
932: BVCreate(PetscObjectComm((PetscObject)ctx->xsub),&ctx->Y);
933: BVSetSizesFromVec(ctx->Y,ctx->xsub,eps->n);
934: BVSetFromOptions(ctx->Y);
935: BVResize(ctx->Y,ctx->num_solve_point*ctx->L_max,PETSC_FALSE);
936: } else {
937: BVDuplicateResize(eps->V,ctx->num_solve_point*ctx->L_max,&ctx->Y);
938: }
939: PetscLogObjectParent((PetscObject)eps,(PetscObject)ctx->Y);
941: if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {
942: DSSetType(eps->ds,DSGNHEP);
943: } else if (eps->isgeneralized) {
944: if (eps->ishermitian && eps->ispositive) {
945: DSSetType(eps->ds,DSGHEP);
946: } else {
947: DSSetType(eps->ds,DSGNHEP);
948: }
949: } else {
950: if (eps->ishermitian) {
951: DSSetType(eps->ds,DSHEP);
952: } else {
953: DSSetType(eps->ds,DSNHEP);
954: }
955: }
956: DSAllocate(eps->ds,eps->ncv);
957: EPSSetWorkVecs(eps,2);
959: #if !defined(PETSC_USE_COMPLEX)
960: if (!eps->ishermitian) { PetscInfo(eps,"Warning: complex eigenvalues are not calculated exactly without --with-scalar-type=complex in PETSc\n"); }
961: #endif
962: return(0);
963: }
965: PetscErrorCode EPSSolve_CISS(EPS eps)
966: {
968: EPS_CISS *ctx = (EPS_CISS*)eps->data;
969: Mat A,B,X,M,pA,pB;
970: PetscInt i,j,ld,nmat,L_add=0,nv=0,L_base=ctx->L,inner,nlocal,*inside;
971: PetscScalar *Mu,*H0,*H1=NULL,*rr,*temp;
972: PetscReal error,max_error;
973: PetscBool *fl1;
974: Vec si,w[3];
975: SlepcSC sc;
976: PetscRandom rand;
977: #if defined(PETSC_USE_COMPLEX)
978: PetscBool isellipse;
979: #endif
982: w[0] = eps->work[0];
983: w[1] = NULL;
984: w[2] = eps->work[1];
985: /* override SC settings */
986: DSGetSlepcSC(eps->ds,&sc);
987: sc->comparison = SlepcCompareLargestMagnitude;
988: sc->comparisonctx = NULL;
989: sc->map = NULL;
990: sc->mapobj = NULL;
991: VecGetLocalSize(w[0],&nlocal);
992: DSGetLeadingDimension(eps->ds,&ld);
993: STGetNumMatrices(eps->st,&nmat);
994: STGetMatrix(eps->st,0,&A);
995: if (nmat>1) { STGetMatrix(eps->st,1,&B); }
996: else B = NULL;
997: SetPathParameter(eps);
998: CISSVecSetRandom(ctx->V,0,ctx->L);
999: BVGetRandomContext(ctx->V,&rand);
1001: if (ctx->pA) {
1002: VecScatterVecs(eps,ctx->V,ctx->L);
1003: SolveLinearSystem(eps,ctx->pA,ctx->pB,ctx->pV,0,ctx->L,PETSC_TRUE);
1004: } else {
1005: SolveLinearSystem(eps,A,B,ctx->V,0,ctx->L,PETSC_TRUE);
1006: }
1007: #if defined(PETSC_USE_COMPLEX)
1008: PetscObjectTypeCompare((PetscObject)eps->rg,RGELLIPSE,&isellipse);
1009: if (isellipse) {
1010: EstimateNumberEigs(eps,&L_add);
1011: } else {
1012: L_add = 0;
1013: }
1014: #else
1015: L_add = 0;
1016: #endif
1017: if (L_add>0) {
1018: PetscInfo2(eps,"Changing L %D -> %D by Estimate #Eig\n",ctx->L,ctx->L+L_add);
1019: CISSVecSetRandom(ctx->V,ctx->L,ctx->L+L_add);
1020: if (ctx->pA) {
1021: VecScatterVecs(eps,ctx->V,ctx->L+L_add);
1022: SolveLinearSystem(eps,ctx->pA,ctx->pB,ctx->pV,ctx->L,ctx->L+L_add,PETSC_FALSE);
1023: } else {
1024: SolveLinearSystem(eps,A,B,ctx->V,ctx->L,ctx->L+L_add,PETSC_FALSE);
1025: }
1026: ctx->L += L_add;
1027: }
1028: PetscMalloc2(ctx->L*ctx->L*ctx->M*2,&Mu,ctx->L*ctx->M*ctx->L*ctx->M,&H0);
1029: for (i=0;i<ctx->refine_blocksize;i++) {
1030: CalcMu(eps,Mu);
1031: BlockHankel(eps,Mu,0,H0);
1032: SVD_H0(eps,H0,&nv);
1033: if (ctx->sigma[0]<=ctx->delta || nv < ctx->L*ctx->M || ctx->L == ctx->L_max) break;
1034: L_add = L_base;
1035: if (ctx->L+L_add>ctx->L_max) L_add = ctx->L_max-ctx->L;
1036: PetscInfo2(eps,"Changing L %D -> %D by SVD(H0)\n",ctx->L,ctx->L+L_add);
1037: CISSVecSetRandom(ctx->V,ctx->L,ctx->L+L_add);
1038: if (ctx->pA) {
1039: VecScatterVecs(eps,ctx->V,ctx->L+L_add);
1040: SolveLinearSystem(eps,ctx->pA,ctx->pB,ctx->pV,ctx->L,ctx->L+L_add,PETSC_FALSE);
1041: } else {
1042: SolveLinearSystem(eps,A,B,ctx->V,ctx->L,ctx->L+L_add,PETSC_FALSE);
1043: }
1044: ctx->L += L_add;
1045: }
1046: if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {
1047: PetscMalloc1(ctx->L*ctx->M*ctx->L*ctx->M,&H1);
1048: }
1050: while (eps->reason == EPS_CONVERGED_ITERATING) {
1051: eps->its++;
1052: for (inner=0;inner<=ctx->refine_inner;inner++) {
1053: if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {
1054: CalcMu(eps,Mu);
1055: BlockHankel(eps,Mu,0,H0);
1056: SVD_H0(eps,H0,&nv);
1057: break;
1058: } else {
1059: ConstructS(eps);
1060: BVSetActiveColumns(ctx->S,0,ctx->L);
1061: BVCopy(ctx->S,ctx->V);
1062: SVD_S(ctx->S,ctx->L*ctx->M,ctx->delta,ctx->sigma,&nv);
1063: if (ctx->sigma[0]>ctx->delta && nv==ctx->L*ctx->M && inner!=ctx->refine_inner) {
1064: if (ctx->pA) {
1065: VecScatterVecs(eps,ctx->V,ctx->L);
1066: SolveLinearSystem(eps,ctx->pA,ctx->pB,ctx->pV,0,ctx->L,PETSC_FALSE);
1067: } else {
1068: SolveLinearSystem(eps,A,B,ctx->V,0,ctx->L,PETSC_FALSE);
1069: }
1070: } else break;
1071: }
1072: }
1073: eps->nconv = 0;
1074: if (nv == 0) eps->reason = EPS_CONVERGED_TOL;
1075: else {
1076: DSSetDimensions(eps->ds,nv,0,0,0);
1077: DSSetState(eps->ds,DS_STATE_RAW);
1079: if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {
1080: BlockHankel(eps,Mu,0,H0);
1081: BlockHankel(eps,Mu,1,H1);
1082: DSGetArray(eps->ds,DS_MAT_A,&temp);
1083: for (j=0;j<nv;j++) {
1084: for (i=0;i<nv;i++) {
1085: temp[i+j*ld] = H1[i+j*ctx->L*ctx->M];
1086: }
1087: }
1088: DSRestoreArray(eps->ds,DS_MAT_A,&temp);
1089: DSGetArray(eps->ds,DS_MAT_B,&temp);
1090: for (j=0;j<nv;j++) {
1091: for (i=0;i<nv;i++) {
1092: temp[i+j*ld] = H0[i+j*ctx->L*ctx->M];
1093: }
1094: }
1095: DSRestoreArray(eps->ds,DS_MAT_B,&temp);
1096: } else {
1097: BVSetActiveColumns(ctx->S,0,nv);
1098: DSGetMat(eps->ds,DS_MAT_A,&pA);
1099: MatZeroEntries(pA);
1100: BVMatProject(ctx->S,A,ctx->S,pA);
1101: DSRestoreMat(eps->ds,DS_MAT_A,&pA);
1102: if (B) {
1103: DSGetMat(eps->ds,DS_MAT_B,&pB);
1104: MatZeroEntries(pB);
1105: BVMatProject(ctx->S,B,ctx->S,pB);
1106: DSRestoreMat(eps->ds,DS_MAT_B,&pB);
1107: }
1108: }
1110: DSSolve(eps->ds,eps->eigr,eps->eigi);
1111: DSSynchronize(eps->ds,eps->eigr,eps->eigi);
1113: PetscMalloc3(nv,&fl1,nv,&inside,nv,&rr);
1114: rescale_eig(eps,nv);
1115: isGhost(eps,ld,nv,fl1);
1116: RGCheckInside(eps->rg,nv,eps->eigr,eps->eigi,inside);
1117: for (i=0;i<nv;i++) {
1118: if (fl1[i] && inside[i]>=0) {
1119: rr[i] = 1.0;
1120: eps->nconv++;
1121: } else rr[i] = 0.0;
1122: }
1123: DSSort(eps->ds,eps->eigr,eps->eigi,rr,NULL,&eps->nconv);
1124: DSSynchronize(eps->ds,eps->eigr,eps->eigi);
1125: rescale_eig(eps,nv);
1126: PetscFree3(fl1,inside,rr);
1127: BVSetActiveColumns(eps->V,0,nv);
1128: if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {
1129: ConstructS(eps);
1130: BVSetActiveColumns(ctx->S,0,ctx->L);
1131: BVCopy(ctx->S,ctx->V);
1132: BVSetActiveColumns(ctx->S,0,nv);
1133: }
1134: BVCopy(ctx->S,eps->V);
1136: DSVectors(eps->ds,DS_MAT_X,NULL,NULL);
1137: DSGetMat(eps->ds,DS_MAT_X,&X);
1138: BVMultInPlace(ctx->S,X,0,eps->nconv);
1139: if (eps->ishermitian) {
1140: BVMultInPlace(eps->V,X,0,eps->nconv);
1141: }
1142: MatDestroy(&X);
1143: max_error = 0.0;
1144: for (i=0;i<eps->nconv;i++) {
1145: BVGetColumn(ctx->S,i,&si);
1146: EPSComputeResidualNorm_Private(eps,PETSC_FALSE,eps->eigr[i],eps->eigi[i],si,NULL,w,&error);
1147: (*eps->converged)(eps,eps->eigr[i],eps->eigi[i],error,&error,eps->convergedctx);
1148: BVRestoreColumn(ctx->S,i,&si);
1149: max_error = PetscMax(max_error,error);
1150: }
1152: if (max_error <= eps->tol) eps->reason = EPS_CONVERGED_TOL;
1153: else if (eps->its >= eps->max_it) eps->reason = EPS_DIVERGED_ITS;
1154: else {
1155: if (eps->nconv > ctx->L) {
1156: MatCreateSeqDense(PETSC_COMM_SELF,eps->nconv,ctx->L,NULL,&M);
1157: MatDenseGetArray(M,&temp);
1158: for (i=0;i<ctx->L*eps->nconv;i++) {
1159: PetscRandomGetValue(rand,&temp[i]);
1160: temp[i] = PetscRealPart(temp[i]);
1161: }
1162: MatDenseRestoreArray(M,&temp);
1163: BVSetActiveColumns(ctx->S,0,eps->nconv);
1164: BVMultInPlace(ctx->S,M,0,ctx->L);
1165: MatDestroy(&M);
1166: BVSetActiveColumns(ctx->S,0,ctx->L);
1167: BVCopy(ctx->S,ctx->V);
1168: }
1169: if (ctx->pA) {
1170: VecScatterVecs(eps,ctx->V,ctx->L);
1171: SolveLinearSystem(eps,ctx->pA,ctx->pB,ctx->pV,0,ctx->L,PETSC_FALSE);
1172: } else {
1173: SolveLinearSystem(eps,A,B,ctx->V,0,ctx->L,PETSC_FALSE);
1174: }
1175: }
1176: }
1177: }
1178: if (ctx->extraction == EPS_CISS_EXTRACTION_HANKEL) {
1179: PetscFree(H1);
1180: }
1181: PetscFree2(Mu,H0);
1182: return(0);
1183: }
1185: static PetscErrorCode EPSCISSSetSizes_CISS(EPS eps,PetscInt ip,PetscInt bs,PetscInt ms,PetscInt npart,PetscInt bsmax,PetscBool realmats)
1186: {
1188: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1189: PetscInt oN,onpart;
1192: oN = ctx->N;
1193: if (ip == PETSC_DECIDE || ip == PETSC_DEFAULT) {
1194: if (ctx->N!=32) { ctx->N =32; ctx->M = ctx->N/4; }
1195: } else {
1196: if (ip<1) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The ip argument must be > 0");
1197: if (ip%2) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The ip argument must be an even number");
1198: if (ctx->N!=ip) { ctx->N = ip; ctx->M = ctx->N/4; }
1199: }
1200: if (bs == PETSC_DECIDE || bs == PETSC_DEFAULT) {
1201: ctx->L = 16;
1202: } else {
1203: if (bs<1) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The bs argument must be > 0");
1204: ctx->L = bs;
1205: }
1206: if (ms == PETSC_DECIDE || ms == PETSC_DEFAULT) {
1207: ctx->M = ctx->N/4;
1208: } else {
1209: if (ms<1) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The ms argument must be > 0");
1210: if (ms>ctx->N) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The ms argument must be less than or equal to the number of integration points");
1211: ctx->M = ms;
1212: }
1213: onpart = ctx->npart;
1214: if (npart == PETSC_DECIDE || npart == PETSC_DEFAULT) {
1215: ctx->npart = 1;
1216: } else {
1217: if (npart<1) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The npart argument must be > 0");
1218: ctx->npart = npart;
1219: }
1220: if (bsmax == PETSC_DECIDE || bsmax == PETSC_DEFAULT) {
1221: ctx->L_max = 64;
1222: } else {
1223: if (bsmax<1) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The bsmax argument must be > 0");
1224: ctx->L_max = PetscMax(bsmax,ctx->L);
1225: }
1226: if (onpart != ctx->npart || oN != ctx->N || realmats != ctx->isreal) { EPSCISSResetSubcomm(eps); }
1227: ctx->isreal = realmats;
1228: eps->state = EPS_STATE_INITIAL;
1229: return(0);
1230: }
1232: /*@
1233: EPSCISSSetSizes - Sets the values of various size parameters in the CISS solver.
1235: Logically Collective on EPS
1237: Input Parameters:
1238: + eps - the eigenproblem solver context
1239: . ip - number of integration points
1240: . bs - block size
1241: . ms - moment size
1242: . npart - number of partitions when splitting the communicator
1243: . bsmax - max block size
1244: - realmats - A and B are real
1246: Options Database Keys:
1247: + -eps_ciss_integration_points - Sets the number of integration points
1248: . -eps_ciss_blocksize - Sets the block size
1249: . -eps_ciss_moments - Sets the moment size
1250: . -eps_ciss_partitions - Sets the number of partitions
1251: . -eps_ciss_maxblocksize - Sets the maximum block size
1252: - -eps_ciss_realmats - A and B are real
1254: Note:
1255: The default number of partitions is 1. This means the internal KSP object is shared
1256: among all processes of the EPS communicator. Otherwise, the communicator is split
1257: into npart communicators, so that npart KSP solves proceed simultaneously.
1259: Level: advanced
1261: .seealso: EPSCISSGetSizes()
1262: @*/
1263: PetscErrorCode EPSCISSSetSizes(EPS eps,PetscInt ip,PetscInt bs,PetscInt ms,PetscInt npart,PetscInt bsmax,PetscBool realmats)
1264: {
1275: PetscTryMethod(eps,"EPSCISSSetSizes_C",(EPS,PetscInt,PetscInt,PetscInt,PetscInt,PetscInt,PetscBool),(eps,ip,bs,ms,npart,bsmax,realmats));
1276: return(0);
1277: }
1279: static PetscErrorCode EPSCISSGetSizes_CISS(EPS eps,PetscInt *ip,PetscInt *bs,PetscInt *ms,PetscInt *npart,PetscInt *bsmax,PetscBool *realmats)
1280: {
1281: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1284: if (ip) *ip = ctx->N;
1285: if (bs) *bs = ctx->L;
1286: if (ms) *ms = ctx->M;
1287: if (npart) *npart = ctx->npart;
1288: if (bsmax) *bsmax = ctx->L_max;
1289: if (realmats) *realmats = ctx->isreal;
1290: return(0);
1291: }
1293: /*@
1294: EPSCISSGetSizes - Gets the values of various size parameters in the CISS solver.
1296: Not Collective
1298: Input Parameter:
1299: . eps - the eigenproblem solver context
1301: Output Parameters:
1302: + ip - number of integration points
1303: . bs - block size
1304: . ms - moment size
1305: . npart - number of partitions when splitting the communicator
1306: . bsmax - max block size
1307: - realmats - A and B are real
1309: Level: advanced
1311: .seealso: EPSCISSSetSizes()
1312: @*/
1313: PetscErrorCode EPSCISSGetSizes(EPS eps,PetscInt *ip,PetscInt *bs,PetscInt *ms,PetscInt *npart,PetscInt *bsmax,PetscBool *realmats)
1314: {
1319: PetscUseMethod(eps,"EPSCISSGetSizes_C",(EPS,PetscInt*,PetscInt*,PetscInt*,PetscInt*,PetscInt*,PetscBool*),(eps,ip,bs,ms,npart,bsmax,realmats));
1320: return(0);
1321: }
1323: static PetscErrorCode EPSCISSSetThreshold_CISS(EPS eps,PetscReal delta,PetscReal spur)
1324: {
1325: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1328: if (delta == PETSC_DEFAULT) {
1329: ctx->delta = 1e-12;
1330: } else {
1331: if (delta<=0.0) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The delta argument must be > 0.0");
1332: ctx->delta = delta;
1333: }
1334: if (spur == PETSC_DEFAULT) {
1335: ctx->spurious_threshold = 1e-4;
1336: } else {
1337: if (spur<=0.0) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The spurious threshold argument must be > 0.0");
1338: ctx->spurious_threshold = spur;
1339: }
1340: return(0);
1341: }
1343: /*@
1344: EPSCISSSetThreshold - Sets the values of various threshold parameters in
1345: the CISS solver.
1347: Logically Collective on EPS
1349: Input Parameters:
1350: + eps - the eigenproblem solver context
1351: . delta - threshold for numerical rank
1352: - spur - spurious threshold (to discard spurious eigenpairs)
1354: Options Database Keys:
1355: + -eps_ciss_delta - Sets the delta
1356: - -eps_ciss_spurious_threshold - Sets the spurious threshold
1358: Level: advanced
1360: .seealso: EPSCISSGetThreshold()
1361: @*/
1362: PetscErrorCode EPSCISSSetThreshold(EPS eps,PetscReal delta,PetscReal spur)
1363: {
1370: PetscTryMethod(eps,"EPSCISSSetThreshold_C",(EPS,PetscReal,PetscReal),(eps,delta,spur));
1371: return(0);
1372: }
1374: static PetscErrorCode EPSCISSGetThreshold_CISS(EPS eps,PetscReal *delta,PetscReal *spur)
1375: {
1376: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1379: if (delta) *delta = ctx->delta;
1380: if (spur) *spur = ctx->spurious_threshold;
1381: return(0);
1382: }
1384: /*@
1385: EPSCISSGetThreshold - Gets the values of various threshold parameters
1386: in the CISS solver.
1388: Not Collective
1390: Input Parameter:
1391: . eps - the eigenproblem solver context
1393: Output Parameters:
1394: + delta - threshold for numerical rank
1395: - spur - spurious threshold (to discard spurious eigenpairs)
1397: Level: advanced
1399: .seealso: EPSCISSSetThreshold()
1400: @*/
1401: PetscErrorCode EPSCISSGetThreshold(EPS eps,PetscReal *delta,PetscReal *spur)
1402: {
1407: PetscUseMethod(eps,"EPSCISSGetThreshold_C",(EPS,PetscReal*,PetscReal*),(eps,delta,spur));
1408: return(0);
1409: }
1411: static PetscErrorCode EPSCISSSetRefinement_CISS(EPS eps,PetscInt inner,PetscInt blsize)
1412: {
1413: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1416: if (inner == PETSC_DEFAULT) {
1417: ctx->refine_inner = 0;
1418: } else {
1419: if (inner<0) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The refine inner argument must be >= 0");
1420: ctx->refine_inner = inner;
1421: }
1422: if (blsize == PETSC_DEFAULT) {
1423: ctx->refine_blocksize = 0;
1424: } else {
1425: if (blsize<0) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The refine blocksize argument must be >= 0");
1426: ctx->refine_blocksize = blsize;
1427: }
1428: return(0);
1429: }
1431: /*@
1432: EPSCISSSetRefinement - Sets the values of various refinement parameters
1433: in the CISS solver.
1435: Logically Collective on EPS
1437: Input Parameters:
1438: + eps - the eigenproblem solver context
1439: . inner - number of iterative refinement iterations (inner loop)
1440: - blsize - number of iterative refinement iterations (blocksize loop)
1442: Options Database Keys:
1443: + -eps_ciss_refine_inner - Sets number of inner iterations
1444: - -eps_ciss_refine_blocksize - Sets number of blocksize iterations
1446: Level: advanced
1448: .seealso: EPSCISSGetRefinement()
1449: @*/
1450: PetscErrorCode EPSCISSSetRefinement(EPS eps,PetscInt inner,PetscInt blsize)
1451: {
1458: PetscTryMethod(eps,"EPSCISSSetRefinement_C",(EPS,PetscInt,PetscInt),(eps,inner,blsize));
1459: return(0);
1460: }
1462: static PetscErrorCode EPSCISSGetRefinement_CISS(EPS eps,PetscInt *inner,PetscInt *blsize)
1463: {
1464: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1467: if (inner) *inner = ctx->refine_inner;
1468: if (blsize) *blsize = ctx->refine_blocksize;
1469: return(0);
1470: }
1472: /*@
1473: EPSCISSGetRefinement - Gets the values of various refinement parameters
1474: in the CISS solver.
1476: Not Collective
1478: Input Parameter:
1479: . eps - the eigenproblem solver context
1481: Output Parameters:
1482: + inner - number of iterative refinement iterations (inner loop)
1483: - blsize - number of iterative refinement iterations (blocksize loop)
1485: Level: advanced
1487: .seealso: EPSCISSSetRefinement()
1488: @*/
1489: PetscErrorCode EPSCISSGetRefinement(EPS eps, PetscInt *inner, PetscInt *blsize)
1490: {
1495: PetscUseMethod(eps,"EPSCISSGetRefinement_C",(EPS,PetscInt*,PetscInt*),(eps,inner,blsize));
1496: return(0);
1497: }
1499: static PetscErrorCode EPSCISSSetUseST_CISS(EPS eps,PetscBool usest)
1500: {
1501: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1504: ctx->usest = usest;
1505: ctx->usest_set = PETSC_TRUE;
1506: eps->state = EPS_STATE_INITIAL;
1507: return(0);
1508: }
1510: /*@
1511: EPSCISSSetUseST - Sets a flag indicating that the CISS solver will
1512: use the ST object for the linear solves.
1514: Logically Collective on EPS
1516: Input Parameters:
1517: + eps - the eigenproblem solver context
1518: - usest - boolean flag to use the ST object or not
1520: Options Database Keys:
1521: . -eps_ciss_usest <bool> - whether the ST object will be used or not
1523: Level: advanced
1525: .seealso: EPSCISSGetUseST()
1526: @*/
1527: PetscErrorCode EPSCISSSetUseST(EPS eps,PetscBool usest)
1528: {
1534: PetscTryMethod(eps,"EPSCISSSetUseST_C",(EPS,PetscBool),(eps,usest));
1535: return(0);
1536: }
1538: static PetscErrorCode EPSCISSGetUseST_CISS(EPS eps,PetscBool *usest)
1539: {
1540: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1543: *usest = ctx->usest;
1544: return(0);
1545: }
1547: /*@
1548: EPSCISSGetUseST - Gets the flag for using the ST object
1549: in the CISS solver.
1551: Not Collective
1553: Input Parameter:
1554: . eps - the eigenproblem solver context
1556: Output Parameters:
1557: . usest - boolean flag indicating if the ST object is being used
1559: Level: advanced
1561: .seealso: EPSCISSSetUseST()
1562: @*/
1563: PetscErrorCode EPSCISSGetUseST(EPS eps,PetscBool *usest)
1564: {
1570: PetscUseMethod(eps,"EPSCISSGetUseST_C",(EPS,PetscBool*),(eps,usest));
1571: return(0);
1572: }
1574: static PetscErrorCode EPSCISSSetQuadRule_CISS(EPS eps,EPSCISSQuadRule quad)
1575: {
1576: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1579: ctx->quad = quad;
1580: return(0);
1581: }
1583: /*@
1584: EPSCISSSetQuadRule - Sets the quadrature rule used in the CISS solver.
1586: Logically Collective on EPS
1588: Input Parameters:
1589: + eps - the eigenproblem solver context
1590: - quad - the quadrature rule
1592: Options Database Key:
1593: . -eps_ciss_quadrule - Sets the quadrature rule (either 'trapezoidal' or
1594: 'chebyshev')
1596: Notes:
1597: By default, the trapezoidal rule is used (EPS_CISS_QUADRULE_TRAPEZOIDAL).
1599: If the 'chebyshev' option is specified (EPS_CISS_QUADRULE_CHEBYSHEV), then
1600: Chebyshev points are used as quadrature points.
1602: Level: advanced
1604: .seealso: EPSCISSGetQuadRule(), EPSCISSQuadRule
1605: @*/
1606: PetscErrorCode EPSCISSSetQuadRule(EPS eps,EPSCISSQuadRule quad)
1607: {
1613: PetscTryMethod(eps,"EPSCISSSetQuadRule_C",(EPS,EPSCISSQuadRule),(eps,quad));
1614: return(0);
1615: }
1617: static PetscErrorCode EPSCISSGetQuadRule_CISS(EPS eps,EPSCISSQuadRule *quad)
1618: {
1619: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1622: *quad = ctx->quad;
1623: return(0);
1624: }
1626: /*@
1627: EPSCISSGetQuadRule - Gets the quadrature rule used in the CISS solver.
1629: Not Collective
1631: Input Parameter:
1632: . eps - the eigenproblem solver context
1634: Output Parameters:
1635: . quad - quadrature rule
1637: Level: advanced
1639: .seealso: EPSCISSSetQuadRule() EPSCISSQuadRule
1640: @*/
1641: PetscErrorCode EPSCISSGetQuadRule(EPS eps, EPSCISSQuadRule *quad)
1642: {
1648: PetscUseMethod(eps,"EPSCISSGetQuadRule_C",(EPS,EPSCISSQuadRule*),(eps,quad));
1649: return(0);
1650: }
1652: static PetscErrorCode EPSCISSSetExtraction_CISS(EPS eps,EPSCISSExtraction extraction)
1653: {
1654: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1657: ctx->extraction = extraction;
1658: return(0);
1659: }
1661: /*@
1662: EPSCISSSetExtraction - Sets the extraction technique used in the CISS solver.
1664: Logically Collective on EPS
1666: Input Parameters:
1667: + eps - the eigenproblem solver context
1668: - extraction - the extraction technique
1670: Options Database Key:
1671: . -eps_ciss_extraction - Sets the extraction technique (either 'ritz' or
1672: 'hankel')
1674: Notes:
1675: By default, the Rayleigh-Ritz extraction is used (EPS_CISS_EXTRACTION_RITZ).
1677: If the 'hankel' option is specified (EPS_CISS_EXTRACTION_HANKEL), then
1678: the Block Hankel method is used for extracting eigenpairs.
1680: Level: advanced
1682: .seealso: EPSCISSGetExtraction(), EPSCISSExtraction
1683: @*/
1684: PetscErrorCode EPSCISSSetExtraction(EPS eps,EPSCISSExtraction extraction)
1685: {
1691: PetscTryMethod(eps,"EPSCISSSetExtraction_C",(EPS,EPSCISSExtraction),(eps,extraction));
1692: return(0);
1693: }
1695: static PetscErrorCode EPSCISSGetExtraction_CISS(EPS eps,EPSCISSExtraction *extraction)
1696: {
1697: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1700: *extraction = ctx->extraction;
1701: return(0);
1702: }
1704: /*@
1705: EPSCISSGetExtraction - Gets the extraction technique used in the CISS solver.
1707: Not Collective
1709: Input Parameter:
1710: . eps - the eigenproblem solver context
1712: Output Parameters:
1713: + extraction - extraction technique
1715: Level: advanced
1717: .seealso: EPSCISSSetExtraction() EPSCISSExtraction
1718: @*/
1719: PetscErrorCode EPSCISSGetExtraction(EPS eps,EPSCISSExtraction *extraction)
1720: {
1726: PetscUseMethod(eps,"EPSCISSGetExtraction_C",(EPS,EPSCISSExtraction*),(eps,extraction));
1727: return(0);
1728: }
1730: static PetscErrorCode EPSCISSGetKSPs_CISS(EPS eps,PetscInt *nsolve,KSP **ksp)
1731: {
1733: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1734: PetscInt i;
1735: PC pc;
1738: if (!ctx->ksp) {
1739: if (!ctx->subcomm) { /* initialize subcomm first */
1740: EPSCISSSetUseConj(eps,&ctx->useconj);
1741: EPSCISSSetUpSubComm(eps,&ctx->num_solve_point);
1742: }
1743: PetscMalloc1(ctx->num_solve_point,&ctx->ksp);
1744: for (i=0;i<ctx->num_solve_point;i++) {
1745: KSPCreate(PetscSubcommChild(ctx->subcomm),&ctx->ksp[i]);
1746: PetscObjectIncrementTabLevel((PetscObject)ctx->ksp[i],(PetscObject)eps,1);
1747: KSPSetOptionsPrefix(ctx->ksp[i],((PetscObject)eps)->prefix);
1748: KSPAppendOptionsPrefix(ctx->ksp[i],"eps_ciss_");
1749: PetscLogObjectParent((PetscObject)eps,(PetscObject)ctx->ksp[i]);
1750: PetscObjectSetOptions((PetscObject)ctx->ksp[i],((PetscObject)eps)->options);
1751: KSPSetErrorIfNotConverged(ctx->ksp[i],PETSC_TRUE);
1752: KSPSetTolerances(ctx->ksp[i],SLEPC_DEFAULT_TOL,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);
1753: KSPGetPC(ctx->ksp[i],&pc);
1754: KSPSetType(ctx->ksp[i],KSPPREONLY);
1755: PCSetType(pc,PCLU);
1756: }
1757: }
1758: if (nsolve) *nsolve = ctx->num_solve_point;
1759: if (ksp) *ksp = ctx->ksp;
1760: return(0);
1761: }
1763: /*@C
1764: EPSCISSGetKSPs - Retrieve the array of linear solver objects associated with
1765: the CISS solver.
1767: Not Collective
1769: Input Parameter:
1770: . eps - the eigenproblem solver solver
1772: Output Parameters:
1773: + nsolve - number of solver objects
1774: - ksp - array of linear solver object
1776: Notes:
1777: The number of KSP solvers is equal to the number of integration points divided by
1778: the number of partitions. This value is halved in the case of real matrices with
1779: a region centered at the real axis.
1781: Level: advanced
1783: .seealso: EPSCISSSetSizes()
1784: @*/
1785: PetscErrorCode EPSCISSGetKSPs(EPS eps,PetscInt *nsolve,KSP **ksp)
1786: {
1791: PetscUseMethod(eps,"EPSCISSGetKSPs_C",(EPS,PetscInt*,KSP**),(eps,nsolve,ksp));
1792: return(0);
1793: }
1795: PetscErrorCode EPSReset_CISS(EPS eps)
1796: {
1798: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1799: PetscInt i;
1802: BVDestroy(&ctx->S);
1803: BVDestroy(&ctx->V);
1804: BVDestroy(&ctx->Y);
1805: if (!ctx->usest) {
1806: for (i=0;i<ctx->num_solve_point;i++) {
1807: KSPReset(ctx->ksp[i]);
1808: }
1809: }
1810: VecScatterDestroy(&ctx->scatterin);
1811: VecDestroy(&ctx->xsub);
1812: VecDestroy(&ctx->xdup);
1813: if (ctx->pA) {
1814: MatDestroy(&ctx->pA);
1815: MatDestroy(&ctx->pB);
1816: BVDestroy(&ctx->pV);
1817: }
1818: return(0);
1819: }
1821: PetscErrorCode EPSSetFromOptions_CISS(PetscOptionItems *PetscOptionsObject,EPS eps)
1822: {
1823: PetscErrorCode ierr;
1824: PetscReal r3,r4;
1825: PetscInt i,i1,i2,i3,i4,i5,i6,i7;
1826: PetscBool b1,b2,flg;
1827: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1828: EPSCISSQuadRule quad;
1829: EPSCISSExtraction extraction;
1832: PetscOptionsHead(PetscOptionsObject,"EPS CISS Options");
1834: EPSCISSGetSizes(eps,&i1,&i2,&i3,&i4,&i5,&b1);
1835: PetscOptionsInt("-eps_ciss_integration_points","Number of integration points","EPSCISSSetSizes",i1,&i1,NULL);
1836: PetscOptionsInt("-eps_ciss_blocksize","Block size","EPSCISSSetSizes",i2,&i2,NULL);
1837: PetscOptionsInt("-eps_ciss_moments","Moment size","EPSCISSSetSizes",i3,&i3,NULL);
1838: PetscOptionsInt("-eps_ciss_partitions","Number of partitions","EPSCISSSetSizes",i4,&i4,NULL);
1839: PetscOptionsInt("-eps_ciss_maxblocksize","Maximum block size","EPSCISSSetSizes",i5,&i5,NULL);
1840: PetscOptionsBool("-eps_ciss_realmats","True if A and B are real","EPSCISSSetSizes",b1,&b1,NULL);
1841: EPSCISSSetSizes(eps,i1,i2,i3,i4,i5,b1);
1843: EPSCISSGetThreshold(eps,&r3,&r4);
1844: PetscOptionsReal("-eps_ciss_delta","Threshold for numerical rank","EPSCISSSetThreshold",r3,&r3,NULL);
1845: PetscOptionsReal("-eps_ciss_spurious_threshold","Threshold for the spurious eigenpairs","EPSCISSSetThreshold",r4,&r4,NULL);
1846: EPSCISSSetThreshold(eps,r3,r4);
1848: EPSCISSGetRefinement(eps,&i6,&i7);
1849: PetscOptionsInt("-eps_ciss_refine_inner","Number of inner iterative refinement iterations","EPSCISSSetRefinement",i6,&i6,NULL);
1850: PetscOptionsInt("-eps_ciss_refine_blocksize","Number of blocksize iterative refinement iterations","EPSCISSSetRefinement",i7,&i7,NULL);
1851: EPSCISSSetRefinement(eps,i6,i7);
1853: EPSCISSGetUseST(eps,&b2);
1854: PetscOptionsBool("-eps_ciss_usest","Use ST for linear solves","EPSCISSSetUseST",b2,&b2,&flg);
1855: if (flg) { EPSCISSSetUseST(eps,b2); }
1857: PetscOptionsEnum("-eps_ciss_quadrule","Quadrature rule","EPSCISSSetQuadRule",EPSCISSQuadRules,(PetscEnum)ctx->quad,(PetscEnum*)&quad,&flg);
1858: if (flg) { EPSCISSSetQuadRule(eps,quad); }
1860: PetscOptionsEnum("-eps_ciss_extraction","Extraction technique","EPSCISSSetExtraction",EPSCISSExtractions,(PetscEnum)ctx->extraction,(PetscEnum*)&extraction,&flg);
1861: if (flg) { EPSCISSSetExtraction(eps,extraction); }
1863: PetscOptionsTail();
1865: if (!eps->rg) { EPSGetRG(eps,&eps->rg); }
1866: RGSetFromOptions(eps->rg); /* this is necessary here to set useconj */
1867: if (!ctx->ksp) { EPSCISSGetKSPs(eps,&ctx->num_solve_point,&ctx->ksp); }
1868: for (i=0;i<ctx->num_solve_point;i++) {
1869: KSPSetFromOptions(ctx->ksp[i]);
1870: }
1871: PetscSubcommSetFromOptions(ctx->subcomm);
1872: return(0);
1873: }
1875: PetscErrorCode EPSDestroy_CISS(EPS eps)
1876: {
1878: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1881: EPSCISSResetSubcomm(eps);
1882: PetscFree4(ctx->weight,ctx->omega,ctx->pp,ctx->sigma);
1883: PetscFree(eps->data);
1884: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetSizes_C",NULL);
1885: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetSizes_C",NULL);
1886: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetThreshold_C",NULL);
1887: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetThreshold_C",NULL);
1888: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetRefinement_C",NULL);
1889: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetRefinement_C",NULL);
1890: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetUseST_C",NULL);
1891: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetUseST_C",NULL);
1892: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetQuadRule_C",NULL);
1893: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetQuadRule_C",NULL);
1894: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetExtraction_C",NULL);
1895: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetExtraction_C",NULL);
1896: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetKSPs_C",NULL);
1897: return(0);
1898: }
1900: PetscErrorCode EPSView_CISS(EPS eps,PetscViewer viewer)
1901: {
1903: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1904: PetscBool isascii;
1907: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii);
1908: if (isascii) {
1909: PetscViewerASCIIPrintf(viewer," sizes { integration points: %D, block size: %D, moment size: %D, partitions: %D, maximum block size: %D }\n",ctx->N,ctx->L,ctx->M,ctx->npart,ctx->L_max);
1910: if (ctx->isreal) {
1911: PetscViewerASCIIPrintf(viewer," exploiting symmetry of integration points\n");
1912: }
1913: PetscViewerASCIIPrintf(viewer," threshold { delta: %g, spurious threshold: %g }\n",(double)ctx->delta,(double)ctx->spurious_threshold);
1914: PetscViewerASCIIPrintf(viewer," iterative refinement { inner: %D, blocksize: %D }\n",ctx->refine_inner, ctx->refine_blocksize);
1915: PetscViewerASCIIPrintf(viewer," extraction: %s\n",EPSCISSExtractions[ctx->extraction]);
1916: PetscViewerASCIIPrintf(viewer," quadrature rule: %s\n",EPSCISSQuadRules[ctx->quad]);
1917: if (ctx->usest) {
1918: PetscViewerASCIIPrintf(viewer," using ST for linear solves\n");
1919: } else {
1920: if (!ctx->ksp) { EPSCISSGetKSPs(eps,&ctx->num_solve_point,&ctx->ksp); }
1921: PetscViewerASCIIPushTab(viewer);
1922: KSPView(ctx->ksp[0],viewer);
1923: PetscViewerASCIIPopTab(viewer);
1924: }
1925: }
1926: return(0);
1927: }
1929: PetscErrorCode EPSSetDefaultST_CISS(EPS eps)
1930: {
1932: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1933: PetscBool usest = ctx->usest;
1936: if (!((PetscObject)eps->st)->type_name) {
1937: if (!ctx->usest_set) usest = (ctx->npart>1)? PETSC_FALSE: PETSC_TRUE;
1938: if (usest) {
1939: STSetType(eps->st,STSINVERT);
1940: } else {
1941: /* we are not going to use ST, so avoid factorizing the matrix */
1942: STSetType(eps->st,STSHIFT);
1943: }
1944: }
1945: return(0);
1946: }
1948: SLEPC_EXTERN PetscErrorCode EPSCreate_CISS(EPS eps)
1949: {
1951: EPS_CISS *ctx = (EPS_CISS*)eps->data;
1954: PetscNewLog(eps,&ctx);
1955: eps->data = ctx;
1957: eps->useds = PETSC_TRUE;
1958: eps->categ = EPS_CATEGORY_CONTOUR;
1960: eps->ops->solve = EPSSolve_CISS;
1961: eps->ops->setup = EPSSetUp_CISS;
1962: eps->ops->setfromoptions = EPSSetFromOptions_CISS;
1963: eps->ops->destroy = EPSDestroy_CISS;
1964: eps->ops->reset = EPSReset_CISS;
1965: eps->ops->view = EPSView_CISS;
1966: eps->ops->computevectors = EPSComputeVectors_Schur;
1967: eps->ops->setdefaultst = EPSSetDefaultST_CISS;
1969: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetSizes_C",EPSCISSSetSizes_CISS);
1970: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetSizes_C",EPSCISSGetSizes_CISS);
1971: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetThreshold_C",EPSCISSSetThreshold_CISS);
1972: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetThreshold_C",EPSCISSGetThreshold_CISS);
1973: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetRefinement_C",EPSCISSSetRefinement_CISS);
1974: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetRefinement_C",EPSCISSGetRefinement_CISS);
1975: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetUseST_C",EPSCISSSetUseST_CISS);
1976: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetUseST_C",EPSCISSGetUseST_CISS);
1977: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetQuadRule_C",EPSCISSSetQuadRule_CISS);
1978: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetQuadRule_C",EPSCISSGetQuadRule_CISS);
1979: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSSetExtraction_C",EPSCISSSetExtraction_CISS);
1980: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetExtraction_C",EPSCISSGetExtraction_CISS);
1981: PetscObjectComposeFunction((PetscObject)eps,"EPSCISSGetKSPs_C",EPSCISSGetKSPs_CISS);
1982: /* set default values of parameters */
1983: ctx->N = 32;
1984: ctx->L = 16;
1985: ctx->M = ctx->N/4;
1986: ctx->delta = 1e-12;
1987: ctx->L_max = 64;
1988: ctx->spurious_threshold = 1e-4;
1989: ctx->usest = PETSC_TRUE;
1990: ctx->usest_set = PETSC_FALSE;
1991: ctx->isreal = PETSC_FALSE;
1992: ctx->refine_inner = 0;
1993: ctx->refine_blocksize = 0;
1994: ctx->npart = 1;
1995: ctx->quad = (EPSCISSQuadRule)0;
1996: ctx->extraction = EPS_CISS_EXTRACTION_RITZ;
1997: return(0);
1998: }