Actual source code: pjd.c
slepc-3.13.4 2020-09-02
1: /*
2: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
3: SLEPc - Scalable Library for Eigenvalue Problem Computations
4: Copyright (c) 2002-2020, 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 polynomial eigensolver: "jd"
13: Method: Jacobi-Davidson
15: Algorithm:
17: Jacobi-Davidson for polynomial eigenvalue problems.
19: References:
21: [1] C. Campos and J.E. Roman, "A polynomial Jacobi-Davidson solver
22: with support for non-monomial bases and deflation", BIT Numer.
23: Math. (in press), 2019.
25: [2] G.L.G. Sleijpen et al., "Jacobi-Davidson type methods for
26: generalized eigenproblems and polynomial eigenproblems", BIT
27: 36(3):595-633, 1996.
29: [3] Feng-Nan Hwang, Zih-Hao Wei, Tsung-Ming Huang, Weichung Wang,
30: "A Parallel Additive Schwarz Preconditioned Jacobi-Davidson
31: Algorithm for Polynomial Eigenvalue Problems in Quantum Dot
32: Simulation", J. Comput. Phys. 229(8):2932-2947, 2010.
33: */
35: #include <slepc/private/pepimpl.h>
36: #include <slepcblaslapack.h>
38: static PetscBool cited = PETSC_FALSE;
39: static const char citation[] =
40: "@Article{slepc-slice-qep,\n"
41: " author = \"C. Campos and J. E. Roman\",\n"
42: " title = \"A polynomial {Jacobi-Davidson} solver with support for non-monomial bases and deflation\",\n"
43: " journal = \"{BIT} Numer. Math.\",\n"
44: " volume = \"IP\",\n"
45: " number = \"-\",\n"
46: " pages = \"1--24\",\n"
47: " year = \"2019,\"\n"
48: " doi = \"https://doi.org/10.1007/s10543-019-00778-z\"\n"
49: "}\n";
51: typedef struct {
52: PetscReal keep; /* restart parameter */
53: PetscReal fix; /* fix parameter */
54: PetscBool reusepc; /* flag indicating whether pc is rebuilt or not */
55: BV V; /* work basis vectors to store the search space */
56: BV W; /* work basis vectors to store the test space */
57: BV *TV; /* work basis vectors to store T*V (each TV[i] is the coefficient for \lambda^i of T*V for the extended T) */
58: BV *AX; /* work basis vectors to store A_i*X for locked eigenvectors */
59: BV N[2]; /* auxiliary work BVs */
60: BV X; /* locked eigenvectors */
61: PetscScalar *T; /* matrix of the invariant pair */
62: PetscScalar *Tj; /* matrix containing the powers of the invariant pair matrix */
63: PetscScalar *XpX; /* X^H*X */
64: PetscInt ld; /* leading dimension for Tj and XpX */
65: PC pcshell; /* preconditioner including basic precond+projector */
66: Mat Pshell; /* auxiliary shell matrix */
67: PetscInt nlock; /* number of locked vectors in the invariant pair */
68: Vec vtempl; /* reference nested vector */
69: PetscInt midx; /* minimality index */
70: PetscInt mmidx; /* maximum allowed minimality index */
71: PEPJDProjection proj; /* projection type (orthogonal, harmonic) */
72: } PEP_JD;
74: typedef struct {
75: PEP pep;
76: PC pc; /* basic preconditioner */
77: Vec Bp[2]; /* preconditioned residual of derivative polynomial, B\p */
78: Vec u[2]; /* Ritz vector */
79: PetscScalar gamma[2]; /* precomputed scalar u'*B\p */
80: PetscScalar theta;
81: PetscScalar *M;
82: PetscScalar *ps;
83: PetscInt ld;
84: Vec *work;
85: Mat PPr;
86: BV X;
87: PetscInt n;
88: } PEP_JD_PCSHELL;
90: typedef struct {
91: Mat Pr,Pi; /* matrix polynomial evaluated at theta */
92: PEP pep;
93: Vec *work;
94: PetscScalar theta[2];
95: } PEP_JD_MATSHELL;
97: /*
98: Duplicate and resize auxiliary basis
99: */
100: static PetscErrorCode PEPJDDuplicateBasis(PEP pep,BV *basis)
101: {
102: PetscErrorCode ierr;
103: PEP_JD *pjd = (PEP_JD*)pep->data;
104: PetscInt nloc,m;
105: BVType type;
106: BVOrthogType otype;
107: BVOrthogRefineType oref;
108: PetscReal oeta;
109: BVOrthogBlockType oblock;
112: if (pjd->ld>1) {
113: BVCreate(PetscObjectComm((PetscObject)pep),basis);
114: BVGetSizes(pep->V,&nloc,NULL,&m);
115: nloc += pjd->ld-1;
116: BVSetSizes(*basis,nloc,PETSC_DECIDE,m);
117: BVGetType(pep->V,&type);
118: BVSetType(*basis,type);
119: BVGetOrthogonalization(pep->V,&otype,&oref,&oeta,&oblock);
120: BVSetOrthogonalization(*basis,otype,oref,oeta,oblock);
121: PetscObjectStateIncrease((PetscObject)*basis);
122: } else {
123: BVDuplicate(pep->V,basis);
124: }
125: return(0);
126: }
128: PetscErrorCode PEPSetUp_JD(PEP pep)
129: {
131: PEP_JD *pjd = (PEP_JD*)pep->data;
132: PetscBool isprecond,flg;
133: PetscInt i;
136: pep->lineariz = PETSC_FALSE;
137: PEPSetDimensions_Default(pep,pep->nev,&pep->ncv,&pep->mpd);
138: if (pep->max_it==PETSC_DEFAULT) pep->max_it = PetscMax(100,2*pep->n/pep->ncv);
139: if (!pep->which) pep->which = PEP_TARGET_MAGNITUDE;
140: if (pep->which!=PEP_TARGET_MAGNITUDE && pep->which!=PEP_TARGET_REAL && pep->which!=PEP_TARGET_IMAGINARY) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"Wrong value of pep->which");
142: PetscObjectTypeCompare((PetscObject)pep->st,STPRECOND,&isprecond);
143: if (!isprecond) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"JD only works with PRECOND spectral transformation");
145: STGetTransform(pep->st,&flg);
146: if (flg) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"Solver requires the ST transformation flag unset, see STSetTransform()");
148: if (!pjd->mmidx) pjd->mmidx = pep->nmat-1;
149: pjd->mmidx = PetscMin(pjd->mmidx,pep->nmat-1);
150: if (!pjd->keep) pjd->keep = 0.5;
151: PEPBasisCoefficients(pep,pep->pbc);
152: PEPAllocateSolution(pep,0);
153: PEPSetWorkVecs(pep,5);
154: pjd->ld = pep->nev;
155: #if !defined (PETSC_USE_COMPLEX)
156: pjd->ld++;
157: #endif
158: PetscMalloc2(pep->nmat,&pjd->TV,pep->nmat,&pjd->AX);
159: for (i=0;i<pep->nmat;i++) {
160: PEPJDDuplicateBasis(pep,pjd->TV+i);
161: }
162: if (pjd->ld>1) {
163: PEPJDDuplicateBasis(pep,&pjd->V);
164: BVSetFromOptions(pjd->V);
165: for (i=0;i<pep->nmat;i++) {
166: BVDuplicateResize(pep->V,pjd->ld-1,pjd->AX+i);
167: }
168: BVDuplicateResize(pep->V,pjd->ld-1,pjd->N);
169: BVDuplicateResize(pep->V,pjd->ld-1,pjd->N+1);
170: pjd->X = pep->V;
171: PetscCalloc3((pjd->ld)*(pjd->ld),&pjd->XpX,pep->ncv*pep->ncv,&pjd->T,pjd->ld*pjd->ld*pep->nmat,&pjd->Tj);
172: } else pjd->V = pep->V;
173: if (pjd->proj==PEP_JD_PROJECTION_HARMONIC) { PEPJDDuplicateBasis(pep,&pjd->W); }
174: else pjd->W = pjd->V;
175: DSSetType(pep->ds,DSPEP);
176: DSPEPSetDegree(pep->ds,pep->nmat-1);
177: if (pep->basis!=PEP_BASIS_MONOMIAL) {
178: DSPEPSetCoefficients(pep->ds,pep->pbc);
179: }
180: DSAllocate(pep->ds,pep->ncv);
181: return(0);
182: }
184: /*
185: Updates columns (low to (high-1)) of TV[i]
186: */
187: static PetscErrorCode PEPJDUpdateTV(PEP pep,PetscInt low,PetscInt high,Vec *w)
188: {
190: PEP_JD *pjd = (PEP_JD*)pep->data;
191: PetscInt pp,col,i,nloc,nconv;
192: Vec v1,v2,t1,t2;
193: PetscScalar *array1,*array2,*x2,*xx,*N,*Np,*y2=NULL,zero=0.0,sone=1.0,*pT,fact,*psc;
194: PetscReal *cg,*ca,*cb;
195: PetscMPIInt rk,np;
196: PetscBLASInt n_,ld_,one=1;
197: Mat T;
198: BV pbv;
201: ca = pep->pbc; cb = ca+pep->nmat; cg = cb + pep->nmat;
202: nconv = pjd->nlock;
203: PetscMalloc5(nconv,&x2,nconv,&xx,nconv*nconv,&pT,nconv*nconv,&N,nconv*nconv,&Np);
204: MPI_Comm_rank(PetscObjectComm((PetscObject)pep),&rk);
205: MPI_Comm_size(PetscObjectComm((PetscObject)pep),&np);
206: BVGetSizes(pep->V,&nloc,NULL,NULL);
207: t1 = w[0];
208: t2 = w[1];
209: PetscBLASIntCast(pjd->nlock,&n_);
210: PetscBLASIntCast(pjd->ld,&ld_);
211: if (nconv){
212: for (i=0;i<nconv;i++) {
213: PetscArraycpy(pT+i*nconv,pjd->T+i*pep->ncv,nconv);
214: }
215: MatCreateSeqDense(PETSC_COMM_SELF,nconv,nconv,pT,&T);
216: }
217: for (col=low;col<high;col++) {
218: BVGetColumn(pjd->V,col,&v1);
219: VecGetArray(v1,&array1);
220: if (nconv>0) {
221: for (i=0;i<nconv;i++) x2[i] = array1[nloc+i]* PetscSqrtReal(np);
222: }
223: VecPlaceArray(t1,array1);
224: if (nconv) {
225: BVSetActiveColumns(pjd->N[0],0,nconv);
226: BVSetActiveColumns(pjd->N[1],0,nconv);
227: BVDotVec(pjd->X,t1,xx);
228: }
229: for (pp=pep->nmat-1;pp>=0;pp--) {
230: BVGetColumn(pjd->TV[pp],col,&v2);
231: VecGetArray(v2,&array2);
232: VecPlaceArray(t2,array2);
233: MatMult(pep->A[pp],t1,t2);
234: if (nconv) {
235: if (pp<pep->nmat-3) {
236: BVMult(pjd->N[0],1.0,-cg[pp+2],pjd->AX[pp+1],NULL);
237: MatShift(T,-cb[pp+1]);
238: BVMult(pjd->N[0],1.0/ca[pp],1.0/ca[pp],pjd->N[1],T);
239: pbv = pjd->N[0]; pjd->N[0] = pjd->N[1]; pjd->N[1] = pbv;
240: BVMultVec(pjd->N[1],1.0,1.0,t2,x2);
241: MatShift(T,cb[pp+1]);
242: } else if (pp==pep->nmat-3) {
243: BVCopy(pjd->AX[pp+2],pjd->N[0]);
244: BVScale(pjd->N[0],1/ca[pp+1]);
245: BVCopy(pjd->AX[pp+1],pjd->N[1]);
246: MatShift(T,-cb[pp+1]);
247: BVMult(pjd->N[1],1.0/ca[pp],1.0/ca[pp],pjd->N[0],T);
248: BVMultVec(pjd->N[1],1.0,1.0,t2,x2);
249: MatShift(T,cb[pp+1]);
250: } else if (pp==pep->nmat-2) {
251: BVMultVec(pjd->AX[pp+1],1.0/ca[pp],1.0,t2,x2);
252: }
253: if (pp<pjd->midx) {
254: y2 = array2+nloc;
255: PetscStackCallBLAS("BLASgemv",BLASgemv_("C",&n_,&n_,&sone,pjd->Tj+pjd->ld*pjd->ld*pp,&ld_,xx,&one,&zero,y2,&one));
256: if (pp<pjd->midx-2) {
257: fact = -cg[pp+2];
258: PetscStackCallBLAS("BLASgemm",BLASgemm_("C","N",&n_,&n_,&n_,&sone,pjd->Tj+(pp+1)*pjd->ld*pjd->ld,&ld_,pjd->XpX,&ld_,&fact,Np,&n_));
259: fact = 1/ca[pp];
260: MatShift(T,-cb[pp+1]);
261: PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&n_,&n_,&n_,&fact,N,&n_,pT,&n_,&fact,Np,&n_));
262: MatShift(T,cb[pp+1]);
263: psc = Np; Np = N; N = psc;
264: PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n_,&n_,&sone,N,&n_,x2,&one,&sone,y2,&one));
265: } else if (pp==pjd->midx-2) {
266: fact = 1/ca[pp];
267: PetscStackCallBLAS("BLASgemm",BLASgemm_("C","N",&n_,&n_,&n_,&fact,pjd->Tj+(pp+1)*pjd->ld*pjd->ld,&ld_,pjd->XpX,&ld_,&zero,N,&n_));
268: PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n_,&n_,&sone,N,&n_,x2,&one,&sone,y2,&one));
269: } else if (pp==pjd->midx-1) {
270: PetscArrayzero(Np,nconv*nconv);
271: }
272: }
273: for (i=0;i<nconv;i++) array2[nloc+i] /= PetscSqrtReal(np);
274: }
275: VecResetArray(t2);
276: VecRestoreArray(v2,&array2);
277: BVRestoreColumn(pjd->TV[pp],col,&v2);
278: }
279: VecResetArray(t1);
280: VecRestoreArray(v1,&array1);
281: BVRestoreColumn(pjd->V,col,&v1);
282: }
283: if (nconv) {MatDestroy(&T);}
284: PetscFree5(x2,xx,pT,N,Np);
285: return(0);
286: }
288: /*
289: RRQR of X. Xin*P=Xou*R. Rank of R is rk
290: */
291: static PetscErrorCode PEPJDOrthogonalize(PetscInt row,PetscInt col,PetscScalar *X,PetscInt ldx,PetscInt *rk,PetscInt *P,PetscScalar *R,PetscInt ldr)
292: {
294: PetscInt i,j,n,r;
295: PetscBLASInt row_,col_,ldx_,*p,lwork,info,n_;
296: PetscScalar *tau,*work;
297: PetscReal tol,*rwork;
300: PetscBLASIntCast(row,&row_);
301: PetscBLASIntCast(col,&col_);
302: PetscBLASIntCast(ldx,&ldx_);
303: n = PetscMin(row,col);
304: PetscBLASIntCast(n,&n_);
305: lwork = 3*col_+1;
306: PetscMalloc4(col,&p,n,&tau,lwork,&work,2*col,&rwork);
307: for (i=1;i<col;i++) p[i] = 0;
308: p[0] = 1;
310: /* rank revealing QR */
311: #if defined(PETSC_USE_COMPLEX)
312: PetscStackCallBLAS("LAPACKgeqp3",LAPACKgeqp3_(&row_,&col_,X,&ldx_,p,tau,work,&lwork,rwork,&info));
313: #else
314: PetscStackCallBLAS("LAPACKgeqp3",LAPACKgeqp3_(&row_,&col_,X,&ldx_,p,tau,work,&lwork,&info));
315: #endif
316: SlepcCheckLapackInfo("geqp3",info);
317: if (P) for (i=0;i<col;i++) P[i] = p[i]-1;
319: /* rank computation */
320: tol = PetscMax(row,col)*PETSC_MACHINE_EPSILON*PetscAbsScalar(X[0]);
321: r = 1;
322: for (i=1;i<n;i++) {
323: if (PetscAbsScalar(X[i+ldx*i])>tol) r++;
324: else break;
325: }
326: if (rk) *rk=r;
328: /* copy upper triangular matrix if requested */
329: if (R) {
330: for (i=0;i<r;i++) {
331: PetscArrayzero(R+i*ldr,r);
332: for (j=0;j<=i;j++) R[i*ldr+j] = X[i*ldx+j];
333: }
334: }
335: PetscStackCallBLAS("LAPACKorgqr",LAPACKorgqr_(&row_,&n_,&n_,X,&ldx_,tau,work,&lwork,&info));
336: SlepcCheckLapackInfo("orgqr",info);
337: PetscFree4(p,tau,work,rwork);
338: return(0);
339: }
341: /*
342: Application of extended preconditioner
343: */
344: static PetscErrorCode PEPJDExtendedPCApply(PC pc,Vec x,Vec y)
345: {
346: PetscInt i,j,nloc,n,ld=0;
347: PetscMPIInt np;
348: Vec tx,ty;
349: PEP_JD_PCSHELL *ctx;
350: PetscErrorCode ierr;
351: const PetscScalar *array1;
352: PetscScalar *x2=NULL,*t=NULL,*ps=NULL,*array2,zero=0.0,sone=1.0;
353: PetscBLASInt one=1,ld_,n_,ncv_;
354: PEP_JD *pjd=NULL;
357: MPI_Comm_size(PetscObjectComm((PetscObject)pc),&np);
358: PCShellGetContext(pc,(void**)&ctx);
359: n = ctx->n;
360: if (n) {
361: pjd = (PEP_JD*)ctx->pep->data;
362: ps = ctx->ps;
363: ld = pjd->ld;
364: PetscMalloc2(n,&x2,n,&t);
365: VecGetLocalSize(ctx->work[0],&nloc);
366: VecGetArrayRead(x,&array1);
367: for (i=0;i<n;i++) x2[i] = array1[nloc+i]* PetscSqrtReal(np);
368: VecRestoreArrayRead(x,&array1);
369: }
371: /* y = B\x apply PC */
372: tx = ctx->work[0];
373: ty = ctx->work[1];
374: VecGetArrayRead(x,&array1);
375: VecPlaceArray(tx,array1);
376: VecGetArray(y,&array2);
377: VecPlaceArray(ty,array2);
378: PCApply(ctx->pc,tx,ty);
379: if (n) {
380: PetscBLASIntCast(ld,&ld_);
381: PetscBLASIntCast(n,&n_);
382: for (i=0;i<n;i++) {
383: t[i] = 0.0;
384: for (j=0;j<n;j++) t[i] += ctx->M[i+j*ld]*x2[j];
385: }
386: if (pjd->midx==1) {
387: PetscBLASIntCast(ctx->pep->ncv,&ncv_);
388: for (i=0;i<n;i++) pjd->T[i*(1+ctx->pep->ncv)] -= ctx->theta;
389: PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n_,&n_,&sone,pjd->T,&ncv_,t,&one,&zero,x2,&one));
390: for (i=0;i<n;i++) pjd->T[i*(1+ctx->pep->ncv)] += ctx->theta;
391: for (i=0;i<n;i++) array2[nloc+i] = x2[i];
392: for (i=0;i<n;i++) x2[i] = -t[i];
393: } else {
394: for (i=0;i<n;i++) array2[nloc+i] = t[i];
395: PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n_,&n_,&sone,ps,&ld_,t,&one,&zero,x2,&one));
396: }
397: for (i=0;i<n;i++) array2[nloc+i] /= PetscSqrtReal(np);
398: BVSetActiveColumns(pjd->X,0,n);
399: BVMultVec(pjd->X,-1.0,1.0,ty,x2);
400: PetscFree2(x2,t);
401: }
402: VecResetArray(tx);
403: VecResetArray(ty);
404: VecRestoreArrayRead(x,&array1);
405: VecRestoreArray(y,&array2);
406: return(0);
407: }
409: /*
410: Application of shell preconditioner:
411: y = B\x - eta*B\p, with eta = (u'*B\x)/(u'*B\p)
412: */
413: static PetscErrorCode PCShellApply_PEPJD(PC pc,Vec x,Vec y)
414: {
416: PetscScalar rr,eta;
417: PEP_JD_PCSHELL *ctx;
418: PetscInt sz;
419: const Vec *xs,*ys;
420: #if !defined(PETSC_USE_COMPLEX)
421: PetscScalar rx,xr,xx;
422: #endif
425: PCShellGetContext(pc,(void**)&ctx);
426: VecCompGetSubVecs(x,&sz,&xs);
427: VecCompGetSubVecs(y,NULL,&ys);
428: /* y = B\x apply extended PC */
429: PEPJDExtendedPCApply(pc,xs[0],ys[0]);
430: #if !defined(PETSC_USE_COMPLEX)
431: if (sz==2) {
432: PEPJDExtendedPCApply(pc,xs[1],ys[1]);
433: }
434: #endif
436: /* Compute eta = u'*y / u'*Bp */
437: VecDot(ys[0],ctx->u[0],&rr);
438: eta = -rr*ctx->gamma[0];
439: #if !defined(PETSC_USE_COMPLEX)
440: if (sz==2) {
441: VecDot(ys[0],ctx->u[1],&xr);
442: VecDot(ys[1],ctx->u[0],&rx);
443: VecDot(ys[1],ctx->u[1],&xx);
444: eta += -ctx->gamma[0]*xx-ctx->gamma[1]*(-xr+rx);
445: }
446: #endif
447: eta /= ctx->gamma[0]*ctx->gamma[0]+ctx->gamma[1]*ctx->gamma[1];
449: /* y = y - eta*Bp */
450: VecAXPY(ys[0],eta,ctx->Bp[0]);
451: #if !defined(PETSC_USE_COMPLEX)
452: if (sz==2) {
453: VecAXPY(ys[1],eta,ctx->Bp[1]);
454: eta = -ctx->gamma[1]*(rr+xx)+ctx->gamma[0]*(-xr+rx);
455: eta /= ctx->gamma[0]*ctx->gamma[0]+ctx->gamma[1]*ctx->gamma[1];
456: VecAXPY(ys[0],eta,ctx->Bp[1]);
457: VecAXPY(ys[1],-eta,ctx->Bp[0]);
458: }
459: #endif
460: return(0);
461: }
463: static PetscErrorCode PEPJDCopyToExtendedVec(PEP pep,Vec v,PetscScalar *a,PetscInt na,PetscInt off,Vec vex,PetscBool back)
464: {
466: PetscMPIInt np,rk,count;
467: PetscScalar *array1,*array2;
468: PetscInt nloc;
471: MPI_Comm_rank(PetscObjectComm((PetscObject)pep),&rk);
472: MPI_Comm_size(PetscObjectComm((PetscObject)pep),&np);
473: BVGetSizes(pep->V,&nloc,NULL,NULL);
474: if (v) {
475: VecGetArray(v,&array1);
476: VecGetArray(vex,&array2);
477: if (back) {
478: PetscArraycpy(array1,array2,nloc);
479: } else {
480: PetscArraycpy(array2,array1,nloc);
481: }
482: VecRestoreArray(v,&array1);
483: VecRestoreArray(vex,&array2);
484: }
485: if (a) {
486: VecGetArray(vex,&array2);
487: if (back) {
488: PetscArraycpy(a,array2+nloc+off,na);
489: PetscMPIIntCast(na,&count);
490: MPI_Bcast(a,count,MPIU_SCALAR,np-1,PetscObjectComm((PetscObject)pep));
491: } else {
492: PetscArraycpy(array2+nloc+off,a,na);
493: PetscMPIIntCast(na,&count);
494: MPI_Bcast(array2+nloc+off,count,MPIU_SCALAR,np-1,PetscObjectComm((PetscObject)pep));
495: }
496: VecRestoreArray(vex,&array2);
497: }
498: return(0);
499: }
501: /* Computes Phi^hat(lambda) times a vector or its derivative (depends on beval)
502: if no vector is provided returns a matrix
503: */
504: static PetscErrorCode PEPJDEvaluateHatBasis(PEP pep,PetscInt n,PetscScalar *H,PetscInt ldh,PetscScalar *beval,PetscScalar *t,PetscInt idx,PetscScalar *qpp,PetscScalar *qp,PetscScalar *q)
505: {
507: PetscInt j,i;
508: PetscBLASInt n_,ldh_,one=1;
509: PetscReal *a,*b,*g;
510: PetscScalar sone=1.0,zero=0.0;
513: a = pep->pbc; b=a+pep->nmat; g=b+pep->nmat;
514: PetscBLASIntCast(n,&n_);
515: PetscBLASIntCast(ldh,&ldh_);
516: if (idx<1) {
517: PetscArrayzero(q,t?n:n*n);
518: } else if (idx==1) {
519: if (t) {for (j=0;j<n;j++) q[j] = t[j]*beval[idx-1]/a[0];}
520: else {
521: PetscArrayzero(q,n*n);
522: for (j=0;j<n;j++) q[(j+1)*n] = beval[idx-1]/a[0];
523: }
524: } else {
525: if (t) {
526: PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n_,&n_,&sone,H,&ldh_,qp,&one,&zero,q,&one));
527: for (j=0;j<n;j++) {
528: q[j] += beval[idx-1]*t[j]-b[idx-1]*qp[j]-g[idx-1]*qpp[j];
529: q[j] /= a[idx-1];
530: }
531: } else {
532: PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&n_,&n_,&n_,&sone,H,&ldh_,qp,&n_,&zero,q,&n_));
533: for (j=0;j<n;j++) {
534: q[j+n*j] += beval[idx-1];
535: for (i=0;i<n;i++) {
536: q[i+n*j] += -b[idx-1]*qp[j*n+i]-g[idx-1]*qpp[j*n+i];
537: q[i+n*j] /= a[idx-1];
538: }
539: }
540: }
541: }
542: return(0);
543: }
545: static PetscErrorCode PEPJDComputeResidual(PEP pep,PetscBool derivative,PetscInt sz,Vec *u,PetscScalar *theta,Vec *p,Vec *work)
546: {
547: PEP_JD *pjd = (PEP_JD*)pep->data;
549: PetscMPIInt rk,np,count;
550: Vec tu,tp,w;
551: PetscScalar *dval,*dvali,*array1,*array2,*x2=NULL,*y2,*qj=NULL,*tt=NULL,*xx=NULL,*xxi=NULL,sone=1.0;
552: PetscInt i,j,nconv,nloc;
553: PetscBLASInt n,ld,one=1;
554: #if !defined(PETSC_USE_COMPLEX)
555: Vec tui=NULL,tpi=NULL;
556: PetscScalar *x2i=NULL,*qji=NULL,*qq,*y2i,*arrayi1,*arrayi2;
557: #endif
560: nconv = pjd->nlock;
561: if (!nconv) {
562: PetscMalloc1(2*sz*pep->nmat,&dval);
563: } else {
564: PetscMalloc5(2*pep->nmat,&dval,2*nconv,&xx,nconv,&tt,sz*nconv,&x2,(sz==2?3:1)*nconv*pep->nmat,&qj);
565: MPI_Comm_rank(PetscObjectComm((PetscObject)pep),&rk);
566: MPI_Comm_size(PetscObjectComm((PetscObject)pep),&np);
567: BVGetSizes(pep->V,&nloc,NULL,NULL);
568: VecGetArray(u[0],&array1);
569: for (i=0;i<nconv;i++) x2[i] = array1[nloc+i]*PetscSqrtReal(np);
570: VecRestoreArray(u[0],&array1);
571: #if !defined(PETSC_USE_COMPLEX)
572: if (sz==2) {
573: x2i = x2+nconv;
574: VecGetArray(u[1],&arrayi1);
575: for (i=0;i<nconv;i++) x2i[i] = arrayi1[nloc+i]*PetscSqrtReal(np);
576: VecRestoreArray(u[1],&arrayi1);
577: }
578: #endif
579: }
580: dvali = dval+pep->nmat;
581: tu = work[0];
582: tp = work[1];
583: w = work[2];
584: VecGetArray(u[0],&array1);
585: VecPlaceArray(tu,array1);
586: VecGetArray(p[0],&array2);
587: VecPlaceArray(tp,array2);
588: VecSet(tp,0.0);
589: #if !defined(PETSC_USE_COMPLEX)
590: if (sz==2) {
591: tui = work[3];
592: tpi = work[4];
593: VecGetArray(u[1],&arrayi1);
594: VecPlaceArray(tui,arrayi1);
595: VecGetArray(p[1],&arrayi2);
596: VecPlaceArray(tpi,arrayi2);
597: VecSet(tpi,0.0);
598: }
599: #endif
600: if (derivative) {
601: PEPEvaluateBasisDerivative(pep,theta[0],theta[1],dval,dvali);
602: } else {
603: PEPEvaluateBasis(pep,theta[0],theta[1],dval,dvali);
604: }
605: for (i=derivative?1:0;i<pep->nmat;i++) {
606: MatMult(pep->A[i],tu,w);
607: VecAXPY(tp,dval[i],w);
608: #if !defined(PETSC_USE_COMPLEX)
609: if (sz==2) {
610: VecAXPY(tpi,dvali[i],w);
611: MatMult(pep->A[i],tui,w);
612: VecAXPY(tpi,dval[i],w);
613: VecAXPY(tp,-dvali[i],w);
614: }
615: #endif
616: }
617: if (nconv) {
618: for (i=0;i<pep->nmat;i++) {
619: PEPJDEvaluateHatBasis(pep,nconv,pjd->T,pep->ncv,dval,x2,i,i>1?qj+(i-2)*nconv:NULL,i>0?qj+(i-1)*nconv:NULL,qj+i*nconv);
620: }
621: #if !defined(PETSC_USE_COMPLEX)
622: if (sz==2) {
623: qji = qj+nconv*pep->nmat;
624: qq = qji+nconv*pep->nmat;
625: for (i=0;i<pep->nmat;i++) {
626: PEPJDEvaluateHatBasis(pep,nconv,pjd->T,pep->ncv,dvali,x2i,i,i>1?qji+(i-2)*nconv:NULL,i>0?qji+(i-1)*nconv:NULL,qji+i*nconv);
627: }
628: for (i=0;i<nconv*pep->nmat;i++) qj[i] -= qji[i];
629: for (i=0;i<pep->nmat;i++) {
630: PEPJDEvaluateHatBasis(pep,nconv,pjd->T,pep->ncv,dval,x2i,i,i>1?qji+(i-2)*nconv:NULL,i>0?qji+(i-1)*nconv:NULL,qji+i*nconv);
631: PEPJDEvaluateHatBasis(pep,nconv,pjd->T,pep->ncv,dvali,x2,i,i>1?qq+(i-2)*nconv:NULL,i>0?qq+(i-1)*nconv:NULL,qq+i*nconv);
632: }
633: for (i=0;i<nconv*pep->nmat;i++) qji[i] += qq[i];
634: for (i=derivative?2:1;i<pep->nmat;i++) {
635: BVMultVec(pjd->AX[i],1.0,1.0,tpi,qji+i*nconv);
636: }
637: }
638: #endif
639: for (i=derivative?2:1;i<pep->nmat;i++) {
640: BVMultVec(pjd->AX[i],1.0,1.0,tp,qj+i*nconv);
641: }
643: /* extended vector part */
644: BVSetActiveColumns(pjd->X,0,nconv);
645: BVDotVec(pjd->X,tu,xx);
646: xxi = xx+nconv;
647: #if !defined(PETSC_USE_COMPLEX)
648: if (sz==2) { BVDotVec(pjd->X,tui,xxi); }
649: #endif
650: if (sz==1) { PetscArrayzero(xxi,nconv); }
651: if (rk==np-1) {
652: PetscBLASIntCast(nconv,&n);
653: PetscBLASIntCast(pjd->ld,&ld);
654: y2 = array2+nloc;
655: PetscArrayzero(y2,nconv);
656: for (j=derivative?1:0;j<pjd->midx;j++) {
657: for (i=0;i<nconv;i++) tt[i] = dval[j]*xx[i]-dvali[j]*xxi[i];
658: PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n,&n,&sone,pjd->XpX,&ld,qj+j*nconv,&one,&sone,tt,&one));
659: PetscStackCallBLAS("BLASgemv",BLASgemv_("C",&n,&n,&sone,pjd->Tj+j*ld*ld,&ld,tt,&one,&sone,y2,&one));
660: }
661: for (i=0;i<nconv;i++) array2[nloc+i] /= PetscSqrtReal(np);
662: #if !defined(PETSC_USE_COMPLEX)
663: if (sz==2) {
664: y2i = arrayi2+nloc;
665: PetscArrayzero(y2i,nconv);
666: for (j=derivative?1:0;j<pjd->midx;j++) {
667: for (i=0;i<nconv;i++) tt[i] = dval[j]*xxi[i]+dvali[j]*xx[i];
668: PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n,&n,&sone,pjd->XpX,&ld,qji+j*nconv,&one,&sone,tt,&one));
669: PetscStackCallBLAS("BLASgemv",BLASgemv_("C",&n,&n,&sone,pjd->Tj+j*ld*ld,&ld,tt,&one,&sone,y2i,&one));
670: }
671: for (i=0;i<nconv;i++) arrayi2[nloc+i] /= PetscSqrtReal(np);
672: }
673: #endif
674: }
675: PetscMPIIntCast(nconv,&count);
676: MPI_Bcast(array2+nloc,count,MPIU_SCALAR,np-1,PetscObjectComm((PetscObject)pep));
677: #if !defined(PETSC_USE_COMPLEX)
678: if (sz==2) {
679: MPI_Bcast(arrayi2+nloc,count,MPIU_SCALAR,np-1,PetscObjectComm((PetscObject)pep));
680: }
681: #endif
682: }
683: if (nconv) {
684: PetscFree5(dval,xx,tt,x2,qj);
685: } else {
686: PetscFree(dval);
687: }
688: VecResetArray(tu);
689: VecRestoreArray(u[0],&array1);
690: VecResetArray(tp);
691: VecRestoreArray(p[0],&array2);
692: #if !defined(PETSC_USE_COMPLEX)
693: if (sz==2) {
694: VecResetArray(tui);
695: VecRestoreArray(u[1],&arrayi1);
696: VecResetArray(tpi);
697: VecRestoreArray(p[1],&arrayi2);
698: }
699: #endif
700: return(0);
701: }
703: static PetscErrorCode PEPJDProcessInitialSpace(PEP pep,Vec *w)
704: {
705: PEP_JD *pjd = (PEP_JD*)pep->data;
707: PetscScalar *tt,target[2];
708: Vec vg,wg;
709: PetscInt i;
710: PetscReal norm;
713: PetscMalloc1(pjd->ld-1,&tt);
714: if (pep->nini==0) {
715: BVSetRandomColumn(pjd->V,0);
716: for (i=0;i<pjd->ld-1;i++) tt[i] = 0.0;
717: BVGetColumn(pjd->V,0,&vg);
718: PEPJDCopyToExtendedVec(pep,NULL,tt,pjd->ld-1,0,vg,PETSC_FALSE);
719: BVRestoreColumn(pjd->V,0,&vg);
720: BVNormColumn(pjd->V,0,NORM_2,&norm);
721: BVScaleColumn(pjd->V,0,1.0/norm);
722: if (pjd->proj==PEP_JD_PROJECTION_HARMONIC) {
723: BVGetColumn(pjd->V,0,&vg);
724: BVGetColumn(pjd->W,0,&wg);
725: VecSet(wg,0.0);
726: target[0] = pep->target; target[1] = 0.0;
727: PEPJDComputeResidual(pep,PETSC_TRUE,1,&vg,target,&wg,w);
728: BVRestoreColumn(pjd->W,0,&wg);
729: BVRestoreColumn(pjd->V,0,&vg);
730: BVNormColumn(pjd->W,0,NORM_2,&norm);
731: BVScaleColumn(pjd->W,0,1.0/norm);
732: }
733: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Support for initial vectors not implemented yet");
734: PetscFree(tt);
735: return(0);
736: }
738: static PetscErrorCode MatMult_PEPJD(Mat P,Vec x,Vec y)
739: {
740: PetscErrorCode ierr;
741: PEP_JD_MATSHELL *matctx;
742: PEP_JD *pjd;
743: PetscInt i,j,nconv,nloc,nmat,ldt,ncv,sz;
744: Vec tx,ty;
745: const Vec *xs,*ys;
746: PetscScalar *array1,*array2,*x2=NULL,*y2,*tt=NULL,*xx=NULL,*xxi,theta[2],sone=1.0,*qj,*val,*vali=NULL;
747: PetscBLASInt n,ld,one=1;
748: PetscMPIInt np;
749: #if !defined(PETSC_USE_COMPLEX)
750: Vec txi=NULL,tyi=NULL;
751: PetscScalar *x2i=NULL,*qji=NULL,*qq,*y2i,*arrayi1,*arrayi2;
752: #endif
755: MPI_Comm_size(PetscObjectComm((PetscObject)P),&np);
756: MatShellGetContext(P,(void**)&matctx);
757: pjd = (PEP_JD*)(matctx->pep->data);
758: nconv = pjd->nlock;
759: nmat = matctx->pep->nmat;
760: ncv = matctx->pep->ncv;
761: ldt = pjd->ld;
762: VecCompGetSubVecs(x,&sz,&xs);
763: VecCompGetSubVecs(y,NULL,&ys);
764: theta[0] = matctx->theta[0];
765: theta[1] = (sz==2)?matctx->theta[1]:0.0;
766: if (nconv>0) {
767: PetscMalloc5(nconv,&tt,sz*nconv,&x2,(sz==2?3:1)*nconv*nmat,&qj,2*nconv,&xx,2*nmat,&val);
768: BVGetSizes(matctx->pep->V,&nloc,NULL,NULL);
769: VecGetArray(xs[0],&array1);
770: for (i=0;i<nconv;i++) x2[i] = array1[nloc+i]* PetscSqrtReal(np);
771: VecRestoreArray(xs[0],&array1);
772: #if !defined(PETSC_USE_COMPLEX)
773: if (sz==2) {
774: x2i = x2+nconv;
775: VecGetArray(xs[1],&arrayi1);
776: for (i=0;i<nconv;i++) x2i[i] = arrayi1[nloc+i]* PetscSqrtReal(np);
777: VecRestoreArray(xs[1],&arrayi1);
778: }
779: #endif
780: vali = val+nmat;
781: }
782: tx = matctx->work[0];
783: ty = matctx->work[1];
784: VecGetArray(xs[0],&array1);
785: VecPlaceArray(tx,array1);
786: VecGetArray(ys[0],&array2);
787: VecPlaceArray(ty,array2);
788: MatMult(matctx->Pr,tx,ty);
789: #if !defined(PETSC_USE_COMPLEX)
790: if (sz==2) {
791: txi = matctx->work[2];
792: tyi = matctx->work[3];
793: VecGetArray(xs[1],&arrayi1);
794: VecPlaceArray(txi,arrayi1);
795: VecGetArray(ys[1],&arrayi2);
796: VecPlaceArray(tyi,arrayi2);
797: MatMult(matctx->Pr,txi,tyi);
798: if (theta[1]!=0.0) {
799: MatMult(matctx->Pi,txi,matctx->work[4]);
800: VecAXPY(ty,-1.0,matctx->work[4]);
801: MatMult(matctx->Pi,tx,matctx->work[4]);
802: VecAXPY(tyi,1.0,matctx->work[4]);
803: }
804: }
805: #endif
806: if (nconv>0) {
807: PEPEvaluateBasis(matctx->pep,theta[0],theta[1],val,vali);
808: for (i=0;i<nmat;i++) {
809: PEPJDEvaluateHatBasis(matctx->pep,nconv,pjd->T,ncv,val,x2,i,i>1?qj+(i-2)*nconv:NULL,i>0?qj+(i-1)*nconv:NULL,qj+i*nconv);
810: }
811: #if !defined(PETSC_USE_COMPLEX)
812: if (sz==2) {
813: qji = qj+nconv*nmat;
814: qq = qji+nconv*nmat;
815: for (i=0;i<nmat;i++) {
816: PEPJDEvaluateHatBasis(matctx->pep,nconv,pjd->T,matctx->pep->ncv,vali,x2i,i,i>1?qji+(i-2)*nconv:NULL,i>0?qji+(i-1)*nconv:NULL,qji+i*nconv);
817: }
818: for (i=0;i<nconv*nmat;i++) qj[i] -= qji[i];
819: for (i=0;i<nmat;i++) {
820: PEPJDEvaluateHatBasis(matctx->pep,nconv,pjd->T,matctx->pep->ncv,val,x2i,i,i>1?qji+(i-2)*nconv:NULL,i>0?qji+(i-1)*nconv:NULL,qji+i*nconv);
821: PEPJDEvaluateHatBasis(matctx->pep,nconv,pjd->T,matctx->pep->ncv,vali,x2,i,i>1?qq+(i-2)*nconv:NULL,i>0?qq+(i-1)*nconv:NULL,qq+i*nconv);
822: }
823: for (i=0;i<nconv*nmat;i++) qji[i] += qq[i];
824: for (i=1;i<matctx->pep->nmat;i++) {
825: BVMultVec(pjd->AX[i],1.0,1.0,tyi,qji+i*nconv);
826: }
827: }
828: #endif
829: for (i=1;i<nmat;i++) {
830: BVMultVec(pjd->AX[i],1.0,1.0,ty,qj+i*nconv);
831: }
833: /* extended vector part */
834: BVSetActiveColumns(pjd->X,0,nconv);
835: BVDotVec(pjd->X,tx,xx);
836: xxi = xx+nconv;
837: #if !defined(PETSC_USE_COMPLEX)
838: if (sz==2) { BVDotVec(pjd->X,txi,xxi); }
839: #endif
840: if (sz==1) { PetscArrayzero(xxi,nconv); }
841: PetscBLASIntCast(pjd->nlock,&n);
842: PetscBLASIntCast(ldt,&ld);
843: y2 = array2+nloc;
844: PetscArrayzero(y2,nconv);
845: for (j=0;j<pjd->midx;j++) {
846: for (i=0;i<nconv;i++) tt[i] = val[j]*xx[i]-vali[j]*xxi[i];
847: PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n,&n,&sone,pjd->XpX,&ld,qj+j*nconv,&one,&sone,tt,&one));
848: PetscStackCallBLAS("BLASgemv",BLASgemv_("C",&n,&n,&sone,pjd->Tj+j*ld*ld,&ld,tt,&one,&sone,y2,&one));
849: }
850: #if !defined(PETSC_USE_COMPLEX)
851: if (sz==2) {
852: y2i = arrayi2+nloc;
853: PetscArrayzero(y2i,nconv);
854: for (j=0;j<pjd->midx;j++) {
855: for (i=0;i<nconv;i++) tt[i] = val[j]*xxi[i]+vali[j]*xx[i];
856: PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&n,&n,&sone,pjd->XpX,&ld,qji+j*nconv,&one,&sone,tt,&one));
857: PetscStackCallBLAS("BLASgemv",BLASgemv_("C",&n,&n,&sone,pjd->Tj+j*ld*ld,&ld,tt,&one,&sone,y2i,&one));
858: }
859: for (i=0;i<nconv;i++) arrayi2[nloc+i] /= PetscSqrtReal(np);
860: }
861: #endif
862: for (i=0;i<nconv;i++) array2[nloc+i] /= PetscSqrtReal(np);
863: PetscFree5(tt,x2,qj,xx,val);
864: }
865: VecResetArray(tx);
866: VecRestoreArray(xs[0],&array1);
867: VecResetArray(ty);
868: VecRestoreArray(ys[0],&array2);
869: #if !defined(PETSC_USE_COMPLEX)
870: if (sz==2) {
871: VecResetArray(txi);
872: VecRestoreArray(xs[1],&arrayi1);
873: VecResetArray(tyi);
874: VecRestoreArray(ys[1],&arrayi2);
875: }
876: #endif
877: return(0);
878: }
880: static PetscErrorCode MatCreateVecs_PEPJD(Mat A,Vec *right,Vec *left)
881: {
882: PetscErrorCode ierr;
883: PEP_JD_MATSHELL *matctx;
884: PEP_JD *pjd;
885: PetscInt kspsf=1,i;
886: Vec v[2];
889: MatShellGetContext(A,(void**)&matctx);
890: pjd = (PEP_JD*)(matctx->pep->data);
891: #if !defined (PETSC_USE_COMPLEX)
892: kspsf = 2;
893: #endif
894: for (i=0;i<kspsf;i++){
895: BVCreateVec(pjd->V,v+i);
896: }
897: if (right) {
898: VecCreateCompWithVecs(v,kspsf,pjd->vtempl,right);
899: }
900: if (left) {
901: VecCreateCompWithVecs(v,kspsf,pjd->vtempl,left);
902: }
903: for (i=0;i<kspsf;i++) {
904: VecDestroy(&v[i]);
905: }
906: return(0);
907: }
909: static PetscErrorCode PEPJDUpdateExtendedPC(PEP pep,PetscScalar theta)
910: {
912: PEP_JD *pjd = (PEP_JD*)pep->data;
913: PEP_JD_PCSHELL *pcctx;
914: PetscInt i,j,k,n=pjd->nlock,ld=pjd->ld,deg=pep->nmat-1;
915: PetscScalar *M,*ps,*work,*U,*V,*S,*Sp,*Spp,snone=-1.0,sone=1.0,zero=0.0,*val;
916: PetscReal tol,maxeig=0.0,*sg,*rwork;
917: PetscBLASInt n_,info,ld_,*p,lw_,rk=0;
920: if (n) {
921: PCShellGetContext(pjd->pcshell,(void**)&pcctx);
922: pcctx->theta = theta;
923: pcctx->n = n;
924: M = pcctx->M;
925: PetscBLASIntCast(n,&n_);
926: PetscBLASIntCast(ld,&ld_);
927: if (pjd->midx==1) {
928: PetscArraycpy(M,pjd->XpX,ld*ld);
929: PetscCalloc2(10*n,&work,n,&p);
930: } else {
931: ps = pcctx->ps;
932: PetscCalloc7(2*n*n,&U,3*n*n,&S,n,&sg,10*n,&work,5*n,&rwork,n,&p,deg+1,&val);
933: V = U+n*n;
934: /* pseudo-inverse */
935: for (j=0;j<n;j++) {
936: for (i=0;i<n;i++) S[n*j+i] = -pjd->T[pep->ncv*j+i];
937: S[n*j+j] += theta;
938: }
939: lw_ = 10*n_;
940: #if !defined (PETSC_USE_COMPLEX)
941: PetscStackCallBLAS("LAPACKgesvd",LAPACKgesvd_("S","S",&n_,&n_,S,&n_,sg,U,&n_,V,&n_,work,&lw_,&info));
942: #else
943: PetscStackCallBLAS("LAPACKgesvd",LAPACKgesvd_("S","S",&n_,&n_,S,&n_,sg,U,&n_,V,&n_,work,&lw_,rwork,&info));
944: #endif
945: SlepcCheckLapackInfo("gesvd",info);
946: for (i=0;i<n;i++) maxeig = PetscMax(maxeig,sg[i]);
947: tol = 10*PETSC_MACHINE_EPSILON*n*maxeig;
948: for (j=0;j<n;j++) {
949: if (sg[j]>tol) {
950: for (i=0;i<n;i++) U[j*n+i] /= sg[j];
951: rk++;
952: } else break;
953: }
954: PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&n_,&n_,&rk,&sone,U,&n_,V,&n_,&zero,ps,&ld_));
956: /* compute M */
957: PEPEvaluateBasis(pep,theta,0.0,val,NULL);
958: PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&n_,&n_,&n_,&snone,pjd->XpX,&ld_,ps,&ld_,&zero,M,&ld_));
959: PetscArrayzero(S,2*n*n);
960: Sp = S+n*n;
961: for (j=0;j<n;j++) S[j*(n+1)] = 1.0;
962: for (k=1;k<pjd->midx;k++) {
963: for (j=0;j<n;j++) for (i=0;i<n;i++) V[j*n+i] = S[j*n+i] - ps[j*ld+i]*val[k];
964: PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&n_,&n_,&n_,&sone,pjd->XpX,&ld_,V,&n_,&zero,U,&n_));
965: PetscStackCallBLAS("BLASgemm",BLASgemm_("C","N",&n_,&n_,&n_,&sone,pjd->Tj+k*ld*ld,&ld_,U,&n_,&sone,M,&ld_));
966: Spp = Sp; Sp = S;
967: PEPJDEvaluateHatBasis(pep,n,pjd->T,pep->ncv,val,NULL,k+1,Spp,Sp,S);
968: }
969: }
970: /* inverse */
971: PetscStackCallBLAS("LAPACKgetrf",LAPACKgetrf_(&n_,&n_,M,&ld_,p,&info));
972: SlepcCheckLapackInfo("getrf",info);
973: PetscStackCallBLAS("LAPACKgetri",LAPACKgetri_(&n_,M,&ld_,p,work,&n_,&info));
974: SlepcCheckLapackInfo("getri",info);
975: if (pjd->midx==1) {
976: PetscFree2(work,p);
977: } else {
978: PetscFree7(U,S,sg,work,rwork,p,val);
979: }
980: }
981: return(0);
982: }
984: static PetscErrorCode PEPJDMatSetUp(PEP pep,PetscInt sz,PetscScalar *theta)
985: {
986: PetscErrorCode ierr;
987: PEP_JD *pjd = (PEP_JD*)pep->data;
988: PEP_JD_MATSHELL *matctx;
989: PEP_JD_PCSHELL *pcctx;
990: MatStructure str;
991: PetscScalar *vals,*valsi;
992: PetscBool skipmat=PETSC_FALSE;
993: PetscInt i;
994: Mat Pr=NULL;
997: if (sz==2 && theta[1]==0.0) sz = 1;
998: MatShellGetContext(pjd->Pshell,(void**)&matctx);
999: PCShellGetContext(pjd->pcshell,(void**)&pcctx);
1000: if (matctx->Pr && matctx->theta[0]==theta[0] && ((!matctx->Pi && sz==1) || (sz==2 && matctx->theta[1]==theta[1]))) {
1001: if (pcctx->n == pjd->nlock) return(0);
1002: skipmat = PETSC_TRUE;
1003: }
1004: if (!skipmat) {
1005: PetscMalloc2(pep->nmat,&vals,pep->nmat,&valsi);
1006: STGetMatStructure(pep->st,&str);
1007: PEPEvaluateBasis(pep,theta[0],theta[1],vals,valsi);
1008: if (!matctx->Pr) {
1009: MatDuplicate(pep->A[0],MAT_COPY_VALUES,&matctx->Pr);
1010: } else {
1011: MatCopy(pep->A[0],matctx->Pr,str);
1012: }
1013: for (i=1;i<pep->nmat;i++) {
1014: MatAXPY(matctx->Pr,vals[i],pep->A[i],str);
1015: }
1016: if (!pjd->reusepc) {
1017: if (pcctx->PPr && sz==2) {
1018: MatCopy(matctx->Pr,pcctx->PPr,str);
1019: Pr = pcctx->PPr;
1020: } else Pr = matctx->Pr;
1021: }
1022: matctx->theta[0] = theta[0];
1023: #if !defined(PETSC_USE_COMPLEX)
1024: if (sz==2) {
1025: if (!matctx->Pi) {
1026: MatDuplicate(pep->A[0],MAT_COPY_VALUES,&matctx->Pi);
1027: } else {
1028: MatCopy(pep->A[1],matctx->Pi,str);
1029: }
1030: MatScale(matctx->Pi,valsi[1]);
1031: for (i=2;i<pep->nmat;i++) {
1032: MatAXPY(matctx->Pi,valsi[i],pep->A[i],str);
1033: }
1034: matctx->theta[1] = theta[1];
1035: }
1036: #endif
1037: PetscFree2(vals,valsi);
1038: }
1039: if (!pjd->reusepc) {
1040: if (!skipmat) {
1041: PCSetOperators(pcctx->pc,Pr,Pr);
1042: PCSetUp(pcctx->pc);
1043: }
1044: PEPJDUpdateExtendedPC(pep,theta[0]);
1045: }
1046: return(0);
1047: }
1049: static PetscErrorCode PEPJDCreateShellPC(PEP pep,Vec *ww)
1050: {
1051: PEP_JD *pjd = (PEP_JD*)pep->data;
1052: PEP_JD_PCSHELL *pcctx;
1053: PEP_JD_MATSHELL *matctx;
1054: KSP ksp;
1055: PetscInt nloc,mloc,kspsf=1;
1056: Vec v[2];
1057: PetscScalar target[2];
1058: PetscErrorCode ierr;
1059: Mat Pr;
1062: /* Create the reference vector */
1063: BVGetColumn(pjd->V,0,&v[0]);
1064: v[1] = v[0];
1065: #if !defined (PETSC_USE_COMPLEX)
1066: kspsf = 2;
1067: #endif
1068: VecCreateCompWithVecs(v,kspsf,NULL,&pjd->vtempl);
1069: BVRestoreColumn(pjd->V,0,&v[0]);
1070: PetscLogObjectParent((PetscObject)pep,(PetscObject)pjd->vtempl);
1072: /* Replace preconditioner with one containing projectors */
1073: PCCreate(PetscObjectComm((PetscObject)pep),&pjd->pcshell);
1074: PCSetType(pjd->pcshell,PCSHELL);
1075: PCShellSetName(pjd->pcshell,"PCPEPJD");
1076: PCShellSetApply(pjd->pcshell,PCShellApply_PEPJD);
1077: PetscNew(&pcctx);
1078: PCShellSetContext(pjd->pcshell,pcctx);
1079: STGetKSP(pep->st,&ksp);
1080: BVCreateVec(pjd->V,&pcctx->Bp[0]);
1081: VecDuplicate(pcctx->Bp[0],&pcctx->Bp[1]);
1082: KSPGetPC(ksp,&pcctx->pc);
1083: PetscObjectReference((PetscObject)pcctx->pc);
1084: MatGetLocalSize(pep->A[0],&mloc,&nloc);
1085: if (pjd->ld>1) {
1086: nloc += pjd->ld-1; mloc += pjd->ld-1;
1087: }
1088: PetscNew(&matctx);
1089: MatCreateShell(PetscObjectComm((PetscObject)pep),kspsf*nloc,kspsf*mloc,PETSC_DETERMINE,PETSC_DETERMINE,matctx,&pjd->Pshell);
1090: MatShellSetOperation(pjd->Pshell,MATOP_MULT,(void(*)(void))MatMult_PEPJD);
1091: MatShellSetOperation(pjd->Pshell,MATOP_CREATE_VECS,(void(*)(void))MatCreateVecs_PEPJD);
1092: matctx->pep = pep;
1093: target[0] = pep->target; target[1] = 0.0;
1094: PEPJDMatSetUp(pep,1,target);
1095: Pr = matctx->Pr;
1096: pcctx->PPr = NULL;
1097: #if !defined(PETSC_USE_COMPLEX)
1098: if (!pjd->reusepc) {
1099: MatDuplicate(matctx->Pr,MAT_COPY_VALUES,&pcctx->PPr);
1100: Pr = pcctx->PPr;
1101: }
1102: #endif
1103: PCSetOperators(pcctx->pc,Pr,Pr);
1104: PCSetErrorIfFailure(pcctx->pc,PETSC_TRUE);
1105: KSPSetPC(ksp,pjd->pcshell);
1106: if (pjd->reusepc) {
1107: PCSetReusePreconditioner(pcctx->pc,PETSC_TRUE);
1108: KSPSetReusePreconditioner(ksp,PETSC_TRUE);
1109: }
1110: KSPSetOperators(ksp,pjd->Pshell,pjd->Pshell);
1111: KSPSetUp(ksp);
1112: if (pjd->ld>1) {
1113: PetscMalloc2(pjd->ld*pjd->ld,&pcctx->M,pjd->ld*pjd->ld,&pcctx->ps);
1114: pcctx->pep = pep;
1115: }
1116: matctx->work = ww;
1117: pcctx->work = ww;
1118: return(0);
1119: }
1121: static PetscErrorCode PEPJDEigenvectors(PEP pep)
1122: {
1124: PEP_JD *pjd = (PEP_JD*)pep->data;
1125: PetscBLASInt ld,nconv,info,nc;
1126: PetscScalar *Z,*w;
1127: PetscReal *wr,norm;
1128: PetscInt i;
1129: Mat U;
1130: #if !defined(PETSC_USE_COMPLEX)
1131: Vec v,v1;
1132: #endif
1135: PetscMalloc3(pep->nconv*pep->nconv,&Z,3*pep->ncv,&wr,2*pep->ncv,&w);
1136: PetscBLASIntCast(pep->ncv,&ld);
1137: PetscBLASIntCast(pep->nconv,&nconv);
1138: #if !defined(PETSC_USE_COMPLEX)
1139: PetscStackCallBLAS("LAPACKtrevc",LAPACKtrevc_("R","A",NULL,&nconv,pjd->T,&ld,NULL,&nconv,Z,&nconv,&nconv,&nc,wr,&info));
1140: #else
1141: PetscStackCallBLAS("LAPACKtrevc",LAPACKtrevc_("R","A",NULL,&nconv,pjd->T,&ld,NULL,&nconv,Z,&nconv,&nconv,&nc,w,wr,&info));
1142: #endif
1143: SlepcCheckLapackInfo("trevc",info);
1144: MatCreateSeqDense(PETSC_COMM_SELF,nconv,nconv,Z,&U);
1145: BVSetActiveColumns(pjd->X,0,pep->nconv);
1146: BVMultInPlace(pjd->X,U,0,pep->nconv);
1147: for (i=0;i<pep->nconv;i++) {
1148: #if !defined(PETSC_USE_COMPLEX)
1149: if (pep->eigi[i]!=0.0) { /* first eigenvalue of a complex conjugate pair */
1150: BVGetColumn(pjd->X,i,&v);
1151: BVGetColumn(pjd->X,i+1,&v1);
1152: VecNormalizeComplex(v,v1,PETSC_TRUE,NULL);
1153: BVRestoreColumn(pjd->X,i,&v);
1154: BVRestoreColumn(pjd->X,i+1,&v1);
1155: i++;
1156: } else /* real eigenvalue */
1157: #endif
1158: {
1159: BVNormColumn(pjd->X,i,NORM_2,&norm);
1160: BVScaleColumn(pjd->X,i,1.0/norm);
1161: }
1162: }
1163: MatDestroy(&U);
1164: PetscFree3(Z,wr,w);
1165: return(0);
1166: }
1168: static PetscErrorCode PEPJDLockConverged(PEP pep,PetscInt *nv,PetscInt sz)
1169: {
1171: PEP_JD *pjd = (PEP_JD*)pep->data;
1172: PetscInt j,i,*P,ldds,rk=0,nvv=*nv;
1173: Vec v,x,w;
1174: PetscScalar *R,*r,*pX,target[2];
1175: Mat X;
1176: PetscBLASInt sz_,rk_,nv_,info;
1177: PetscMPIInt np;
1180: /* update AX and XpX */
1181: for (i=sz;i>0;i--) {
1182: BVGetColumn(pjd->X,pjd->nlock-i,&x);
1183: for (j=0;j<pep->nmat;j++) {
1184: BVGetColumn(pjd->AX[j],pjd->nlock-i,&v);
1185: MatMult(pep->A[j],x,v);
1186: BVRestoreColumn(pjd->AX[j],pjd->nlock-i,&v);
1187: BVSetActiveColumns(pjd->AX[j],0,pjd->nlock-i+1);
1188: }
1189: BVRestoreColumn(pjd->X,pjd->nlock-i,&x);
1190: BVDotColumn(pjd->X,(pjd->nlock-i),pjd->XpX+(pjd->nlock-i)*(pjd->ld));
1191: pjd->XpX[(pjd->nlock-i)*(1+pjd->ld)] = 1.0;
1192: for (j=0;j<pjd->nlock-i;j++) pjd->XpX[j*(pjd->ld)+pjd->nlock-i] = PetscConj(pjd->XpX[(pjd->nlock-i)*(pjd->ld)+j]);
1193: }
1195: /* minimality index */
1196: pjd->midx = PetscMin(pjd->mmidx,pjd->nlock);
1198: /* evaluate the polynomial basis in T */
1199: PetscArrayzero(pjd->Tj,pjd->ld*pjd->ld*pep->nmat);
1200: for (j=0;j<pep->nmat;j++) {
1201: PEPEvaluateBasisMat(pep,pjd->nlock,pjd->T,pep->ncv,j,(j>1)?pjd->Tj+(j-2)*pjd->ld*pjd->ld:NULL,pjd->ld,j?pjd->Tj+(j-1)*pjd->ld*pjd->ld:NULL,pjd->ld,pjd->Tj+j*pjd->ld*pjd->ld,pjd->ld);
1202: }
1204: /* Extend search space */
1205: MPI_Comm_size(PetscObjectComm((PetscObject)pep),&np);
1206: PetscCalloc3(nvv,&P,nvv*nvv,&R,nvv*sz,&r);
1207: DSGetLeadingDimension(pep->ds,&ldds);
1208: DSGetArray(pep->ds,DS_MAT_X,&pX);
1209: PEPJDOrthogonalize(nvv,nvv,pX,ldds,&rk,P,R,nvv);
1210: for (j=0;j<sz;j++) {
1211: for (i=0;i<rk;i++) r[i*sz+j] = PetscConj(R[nvv*i+j]*pep->eigr[P[i]]); /* first row scaled with permuted diagonal */
1212: }
1213: PetscBLASIntCast(rk,&rk_);
1214: PetscBLASIntCast(sz,&sz_);
1215: PetscBLASIntCast(nvv,&nv_);
1216: PetscStackCallBLAS("LAPACKtrtri",LAPACKtrtri_("U","N",&rk_,R,&nv_,&info));
1217: SlepcCheckLapackInfo("trtri",info);
1218: for (i=0;i<sz;i++) PetscStackCallBLAS("BLAStrmv",BLAStrmv_("U","C","N",&rk_,R,&nv_,r+i,&sz_));
1219: for (i=0;i<sz*rk;i++) r[i] = PetscConj(r[i])/PetscSqrtReal(np); /* revert */
1220: BVSetActiveColumns(pjd->V,0,nvv);
1221: rk -= sz;
1222: for (j=0;j<rk;j++) {
1223: PetscArraycpy(R+j*nvv,pX+(j+sz)*ldds,nvv);
1224: }
1225: DSRestoreArray(pep->ds,DS_MAT_X,&pX);
1226: MatCreateSeqDense(PETSC_COMM_SELF,nvv,rk,R,&X);
1227: BVMultInPlace(pjd->V,X,0,rk);
1228: MatDestroy(&X);
1229: BVSetActiveColumns(pjd->V,0,rk);
1230: for (j=0;j<rk;j++) {
1231: BVGetColumn(pjd->V,j,&v);
1232: PEPJDCopyToExtendedVec(pep,NULL,r+sz*(j+sz),sz,pjd->nlock-sz,v,PETSC_FALSE);
1233: BVRestoreColumn(pjd->V,j,&v);
1234: }
1235: BVOrthogonalize(pjd->V,NULL);
1237: if (pjd->proj==PEP_JD_PROJECTION_HARMONIC) {
1238: for (j=0;j<rk;j++) {
1239: /* W = P(target)*V */
1240: BVGetColumn(pjd->W,j,&w);
1241: BVGetColumn(pjd->V,j,&v);
1242: target[0] = pep->target; target[1] = 0.0;
1243: PEPJDComputeResidual(pep,PETSC_FALSE,1,&v,target,&w,pep->work);
1244: BVRestoreColumn(pjd->V,j,&v);
1245: BVRestoreColumn(pjd->W,j,&w);
1246: }
1247: BVSetActiveColumns(pjd->W,0,rk);
1248: BVOrthogonalize(pjd->W,NULL);
1249: }
1250: *nv = rk;
1251: PetscFree3(P,R,r);
1252: return(0);
1253: }
1255: PetscErrorCode PEPJDSystemSetUp(PEP pep,PetscInt sz,PetscScalar *theta,Vec *u,Vec *p,Vec *ww)
1256: {
1258: PEP_JD *pjd = (PEP_JD*)pep->data;
1259: PEP_JD_PCSHELL *pcctx;
1260: #if !defined(PETSC_USE_COMPLEX)
1261: PetscScalar s[2];
1262: #endif
1265: PCShellGetContext(pjd->pcshell,(void**)&pcctx);
1266: PEPJDMatSetUp(pep,sz,theta);
1267: pcctx->u[0] = u[0]; pcctx->u[1] = u[1];
1268: /* Compute r'. p is a work space vector */
1269: PEPJDComputeResidual(pep,PETSC_TRUE,sz,u,theta,p,ww);
1270: PEPJDExtendedPCApply(pjd->pcshell,p[0],pcctx->Bp[0]);
1271: VecDot(pcctx->Bp[0],u[0],pcctx->gamma);
1272: #if !defined(PETSC_USE_COMPLEX)
1273: if (sz==2) {
1274: PEPJDExtendedPCApply(pjd->pcshell,p[1],pcctx->Bp[1]);
1275: VecDot(pcctx->Bp[0],u[1],pcctx->gamma+1);
1276: VecMDot(pcctx->Bp[1],2,u,s);
1277: pcctx->gamma[0] += s[1];
1278: pcctx->gamma[1] = -pcctx->gamma[1]+s[0];
1279: }
1280: #endif
1281: if (sz==1) {
1282: VecZeroEntries(pcctx->Bp[1]);
1283: pcctx->gamma[1] = 0.0;
1284: }
1285: return(0);
1286: }
1288: PetscErrorCode PEPSolve_JD(PEP pep)
1289: {
1290: PetscErrorCode ierr;
1291: PEP_JD *pjd = (PEP_JD*)pep->data;
1292: PetscInt k,nv,nvc,ld,minv,dim,bupdated=0,sz=1,kspsf=1,idx,off,maxits,nloc;
1293: PetscMPIInt np,count;
1294: PetscScalar theta[2]={0.0,0.0},ritz[2]={0.0,0.0},*pX,*eig,*eigi,*array;
1295: PetscReal norm,*res,tol=0.0,rtol,abstol, dtol;
1296: PetscBool lindep,ini=PETSC_TRUE;
1297: Vec tc,t[2]={NULL,NULL},u[2]={NULL,NULL},p[2]={NULL,NULL};
1298: Vec rc,rr[2],r[2]={NULL,NULL},*ww=pep->work,v[2];
1299: Mat G,X,Y;
1300: KSP ksp;
1301: PEP_JD_PCSHELL *pcctx;
1302: PEP_JD_MATSHELL *matctx;
1303: #if !defined(PETSC_USE_COMPLEX)
1304: PetscReal norm1;
1305: #endif
1308: PetscCitationsRegister(citation,&cited);
1309: MPI_Comm_size(PetscObjectComm((PetscObject)pep),&np);
1310: BVGetSizes(pep->V,&nloc,NULL,NULL);
1311: DSGetLeadingDimension(pep->ds,&ld);
1312: PetscCalloc3(pep->ncv+pep->nev,&eig,pep->ncv+pep->nev,&eigi,pep->ncv+pep->nev,&res);
1313: pjd->nlock = 0;
1314: STGetKSP(pep->st,&ksp);
1315: KSPGetTolerances(ksp,&rtol,&abstol,&dtol,&maxits);
1316: #if !defined (PETSC_USE_COMPLEX)
1317: kspsf = 2;
1318: #endif
1319: PEPJDProcessInitialSpace(pep,ww);
1320: nv = (pep->nini)?pep->nini:1;
1322: /* Replace preconditioner with one containing projectors */
1323: PEPJDCreateShellPC(pep,ww);
1324: PCShellGetContext(pjd->pcshell,(void**)&pcctx);
1326: /* Create auxiliar vectors */
1327: BVCreateVec(pjd->V,&u[0]);
1328: VecDuplicate(u[0],&p[0]);
1329: VecDuplicate(u[0],&r[0]);
1330: #if !defined (PETSC_USE_COMPLEX)
1331: VecDuplicate(u[0],&u[1]);
1332: VecDuplicate(u[0],&p[1]);
1333: VecDuplicate(u[0],&r[1]);
1334: #endif
1336: /* Restart loop */
1337: while (pep->reason == PEP_CONVERGED_ITERATING) {
1338: pep->its++;
1339: DSSetDimensions(pep->ds,nv,0,0,0);
1340: BVSetActiveColumns(pjd->V,bupdated,nv);
1341: PEPJDUpdateTV(pep,bupdated,nv,ww);
1342: if (pjd->proj==PEP_JD_PROJECTION_HARMONIC) { BVSetActiveColumns(pjd->W,bupdated,nv); }
1343: for (k=0;k<pep->nmat;k++) {
1344: BVSetActiveColumns(pjd->TV[k],bupdated,nv);
1345: DSGetMat(pep->ds,DSMatExtra[k],&G);
1346: BVMatProject(pjd->TV[k],NULL,pjd->W,G);
1347: DSRestoreMat(pep->ds,DSMatExtra[k],&G);
1348: }
1349: BVSetActiveColumns(pjd->V,0,nv);
1350: BVSetActiveColumns(pjd->W,0,nv);
1352: /* Solve projected problem */
1353: DSSetState(pep->ds,DS_STATE_RAW);
1354: DSSolve(pep->ds,pep->eigr,pep->eigi);
1355: DSSort(pep->ds,pep->eigr,pep->eigi,NULL,NULL,NULL);
1356: DSSynchronize(pep->ds,pep->eigr,pep->eigi);
1357: idx = 0;
1358: do {
1359: ritz[0] = pep->eigr[idx];
1360: #if !defined(PETSC_USE_COMPLEX)
1361: ritz[1] = pep->eigi[idx];
1362: sz = (ritz[1]==0.0)?1:2;
1363: #endif
1364: /* Compute Ritz vector u=V*X(:,1) */
1365: DSGetArray(pep->ds,DS_MAT_X,&pX);
1366: BVSetActiveColumns(pjd->V,0,nv);
1367: BVMultVec(pjd->V,1.0,0.0,u[0],pX+idx*ld);
1368: #if !defined(PETSC_USE_COMPLEX)
1369: if (sz==2) {
1370: BVMultVec(pjd->V,1.0,0.0,u[1],pX+(idx+1)*ld);
1371: }
1372: #endif
1373: DSRestoreArray(pep->ds,DS_MAT_X,&pX);
1374: PEPJDComputeResidual(pep,PETSC_FALSE,sz,u,ritz,r,ww);
1375: /* Check convergence */
1376: VecNorm(r[0],NORM_2,&norm);
1377: #if !defined(PETSC_USE_COMPLEX)
1378: if (sz==2) {
1379: VecNorm(r[1],NORM_2,&norm1);
1380: norm = SlepcAbs(norm,norm1);
1381: }
1382: #endif
1383: (*pep->converged)(pep,ritz[0],ritz[1],norm,&pep->errest[pep->nconv],pep->convergedctx);
1384: if (sz==2) pep->errest[pep->nconv+1] = pep->errest[pep->nconv];
1385: if (ini) {
1386: tol = PetscMin(.1,pep->errest[pep->nconv]); ini = PETSC_FALSE;
1387: } else tol = PetscMin(pep->errest[pep->nconv],tol/2);
1388: (*pep->stopping)(pep,pep->its,pep->max_it,(pep->errest[pep->nconv]<pep->tol)?pep->nconv+sz:pep->nconv,pep->nev,&pep->reason,pep->stoppingctx);
1389: if (pep->errest[pep->nconv]<pep->tol) {
1390: /* Ritz pair converged */
1391: ini = PETSC_TRUE;
1392: minv = PetscMin(nv,(PetscInt)(pjd->keep*pep->ncv));
1393: if (pjd->ld>1) {
1394: BVGetColumn(pjd->X,pep->nconv,&v[0]);
1395: PEPJDCopyToExtendedVec(pep,v[0],pjd->T+pep->ncv*pep->nconv,pjd->ld-1,0,u[0],PETSC_TRUE);
1396: BVRestoreColumn(pjd->X,pep->nconv,&v[0]);
1397: BVSetActiveColumns(pjd->X,0,pep->nconv+1);
1398: BVNormColumn(pjd->X,pep->nconv,NORM_2,&norm);
1399: BVScaleColumn(pjd->X,pep->nconv,1.0/norm);
1400: for (k=0;k<pep->nconv;k++) pjd->T[pep->ncv*pep->nconv+k] *= PetscSqrtReal(np)/norm;
1401: pjd->T[(pep->ncv+1)*pep->nconv] = ritz[0];
1402: eig[pep->nconv] = ritz[0];
1403: idx++;
1404: #if !defined(PETSC_USE_COMPLEX)
1405: if (sz==2) {
1406: BVGetColumn(pjd->X,pep->nconv+1,&v[0]);
1407: PEPJDCopyToExtendedVec(pep,v[0],pjd->T+pep->ncv*(pep->nconv+1),pjd->ld-1,0,u[1],PETSC_TRUE);
1408: BVRestoreColumn(pjd->X,pep->nconv+1,&v[0]);
1409: BVSetActiveColumns(pjd->X,0,pep->nconv+2);
1410: BVNormColumn(pjd->X,pep->nconv+1,NORM_2,&norm1);
1411: BVScaleColumn(pjd->X,pep->nconv+1,1.0/norm1);
1412: for (k=0;k<pep->nconv;k++) pjd->T[pep->ncv*(pep->nconv+1)+k] *= PetscSqrtReal(np)/norm1;
1413: pjd->T[(pep->ncv+1)*(pep->nconv+1)] = ritz[0];
1414: pjd->T[(pep->ncv+1)*pep->nconv+1] = -ritz[1]*norm1/norm;
1415: pjd->T[(pep->ncv+1)*(pep->nconv+1)-1] = ritz[1]*norm/norm1;
1416: eig[pep->nconv+1] = ritz[0];
1417: eigi[pep->nconv] = ritz[1]; eigi[pep->nconv+1] = -ritz[1];
1418: idx++;
1419: }
1420: #endif
1421: } else {
1422: BVInsertVec(pep->V,pep->nconv,u[0]);
1423: }
1424: pep->nconv += sz;
1425: }
1426: } while (pep->errest[pep->nconv]<pep->tol && pep->nconv<nv);
1428: if (pep->reason==PEP_CONVERGED_ITERATING) {
1429: nvc = nv;
1430: if (idx) {
1431: pjd->nlock +=idx;
1432: PEPJDLockConverged(pep,&nv,idx);
1433: }
1434: if (nv+sz>=pep->ncv-1) {
1435: /* Basis full, force restart */
1436: minv = PetscMin(nv,(PetscInt)(pjd->keep*pep->ncv));
1437: DSGetDimensions(pep->ds,&dim,NULL,NULL,NULL,NULL);
1438: DSGetArray(pep->ds,DS_MAT_X,&pX);
1439: PEPJDOrthogonalize(dim,minv,pX,ld,&minv,NULL,NULL,ld);
1440: DSRestoreArray(pep->ds,DS_MAT_X,&pX);
1441: DSGetArray(pep->ds,DS_MAT_Y,&pX);
1442: PEPJDOrthogonalize(dim,minv,pX,ld,&minv,NULL,NULL,ld);
1443: DSRestoreArray(pep->ds,DS_MAT_Y,&pX);
1444: DSGetMat(pep->ds,DS_MAT_X,&X);
1445: BVMultInPlace(pjd->V,X,0,minv);
1446: if (pjd->proj==PEP_JD_PROJECTION_HARMONIC) {
1447: DSGetMat(pep->ds,DS_MAT_Y,&Y);
1448: BVMultInPlace(pjd->W,Y,pep->nconv,minv);
1449: DSRestoreMat(pep->ds,DS_MAT_Y,&Y);
1450: }
1451: MatDestroy(&X);
1452: nv = minv;
1453: bupdated = 0;
1454: } else {
1455: if (!idx && pep->errest[pep->nconv]<pjd->fix) {theta[0] = ritz[0]; theta[1] = ritz[1];}
1456: else {theta[0] = pep->target; theta[1] = 0.0;}
1457: /* Update system mat */
1458: PEPJDSystemSetUp(pep,sz,theta,u,p,ww);
1459: /* Solve correction equation to expand basis */
1460: BVGetColumn(pjd->V,nv,&t[0]);
1461: rr[0] = r[0];
1462: if (sz==2) {
1463: BVGetColumn(pjd->V,nv+1,&t[1]);
1464: rr[1] = r[1];
1465: } else {
1466: t[1] = NULL;
1467: rr[1] = NULL;
1468: }
1469: VecCreateCompWithVecs(t,kspsf,pjd->vtempl,&tc);
1470: VecCreateCompWithVecs(rr,kspsf,pjd->vtempl,&rc);
1471: VecCompSetSubVecs(pjd->vtempl,sz,NULL);
1472: tol = PetscMax(rtol,tol/2);
1473: KSPSetTolerances(ksp,tol,abstol,dtol,maxits);
1474: KSPSolve(ksp,rc,tc);
1475: VecDestroy(&tc);
1476: VecDestroy(&rc);
1477: VecGetArray(t[0],&array);
1478: PetscMPIIntCast(pep->nconv,&count);
1479: MPI_Bcast(array+nloc,count,MPIU_SCALAR,np-1,PetscObjectComm((PetscObject)pep));
1480: VecRestoreArray(t[0],&array);
1481: BVRestoreColumn(pjd->V,nv,&t[0]);
1482: BVOrthogonalizeColumn(pjd->V,nv,NULL,&norm,&lindep);
1483: if (lindep || norm==0.0) {
1484: if (sz==1) SETERRQ(PETSC_COMM_SELF,1,"Linearly dependent continuation vector");
1485: else off = 1;
1486: } else {
1487: off = 0;
1488: BVScaleColumn(pjd->V,nv,1.0/norm);
1489: }
1490: #if !defined(PETSC_USE_COMPLEX)
1491: if (sz==2) {
1492: VecGetArray(t[1],&array);
1493: MPI_Bcast(array+nloc,count,MPIU_SCALAR,np-1,PetscObjectComm((PetscObject)pep));
1494: VecRestoreArray(t[1],&array);
1495: BVRestoreColumn(pjd->V,nv+1,&t[1]);
1496: if (off) {
1497: BVCopyColumn(pjd->V,nv+1,nv);
1498: }
1499: BVOrthogonalizeColumn(pjd->V,nv+1-off,NULL,&norm,&lindep);
1500: if (lindep || norm==0.0) {
1501: if (off) SETERRQ(PETSC_COMM_SELF,1,"Linearly dependent continuation vector");
1502: else off = 1;
1503: } else {
1504: BVScaleColumn(pjd->V,nv+1-off,1.0/norm);
1505: }
1506: }
1507: #endif
1508: if (pjd->proj==PEP_JD_PROJECTION_HARMONIC) {
1509: BVInsertVec(pjd->W,nv,r[0]);
1510: if (sz==2 && !off) {
1511: BVInsertVec(pjd->W,nv+1,r[1]);
1512: }
1513: BVOrthogonalizeColumn(pjd->W,nv,NULL,&norm,&lindep);
1514: if (lindep || norm==0.0) SETERRQ(PETSC_COMM_SELF,1,"Linearly dependent continuation vector");
1515: BVScaleColumn(pjd->W,nv,1.0/norm);
1516: if (sz==2 && !off) {
1517: BVOrthogonalizeColumn(pjd->W,nv+1,NULL,&norm,&lindep);
1518: if (lindep || norm==0.0) SETERRQ(PETSC_COMM_SELF,1,"Linearly dependent continuation vector");
1519: BVScaleColumn(pjd->W,nv+1,1.0/norm);
1520: }
1521: }
1522: bupdated = idx?0:nv;
1523: nv += sz-off;
1524: }
1525: for (k=0;k<nvc;k++) {
1526: eig[pep->nconv-idx+k] = pep->eigr[k];
1527: #if !defined(PETSC_USE_COMPLEX)
1528: eigi[pep->nconv-idx+k] = pep->eigi[k];
1529: #endif
1530: }
1531: PEPMonitor(pep,pep->its,pep->nconv,eig,eigi,pep->errest,pep->nconv+1);
1532: }
1533: }
1534: if (pjd->ld>1) {
1535: for (k=0;k<pep->nconv;k++) {
1536: pep->eigr[k] = eig[k];
1537: pep->eigi[k] = eigi[k];
1538: }
1539: if (pep->nconv>0) { PEPJDEigenvectors(pep); }
1540: PetscFree2(pcctx->M,pcctx->ps);
1541: }
1542: VecDestroy(&u[0]);
1543: VecDestroy(&r[0]);
1544: VecDestroy(&p[0]);
1545: #if !defined (PETSC_USE_COMPLEX)
1546: VecDestroy(&u[1]);
1547: VecDestroy(&r[1]);
1548: VecDestroy(&p[1]);
1549: #endif
1550: KSPSetTolerances(ksp,rtol,abstol,dtol,maxits);
1551: KSPSetPC(ksp,pcctx->pc);
1552: VecDestroy(&pcctx->Bp[0]);
1553: VecDestroy(&pcctx->Bp[1]);
1554: MatShellGetContext(pjd->Pshell,(void**)&matctx);
1555: MatDestroy(&matctx->Pr);
1556: MatDestroy(&matctx->Pi);
1557: MatDestroy(&pjd->Pshell);
1558: MatDestroy(&pcctx->PPr);
1559: PCDestroy(&pcctx->pc);
1560: PetscFree(pcctx);
1561: PetscFree(matctx);
1562: PCDestroy(&pjd->pcshell);
1563: PetscFree3(eig,eigi,res);
1564: VecDestroy(&pjd->vtempl);
1565: return(0);
1566: }
1568: PetscErrorCode PEPJDSetRestart_JD(PEP pep,PetscReal keep)
1569: {
1570: PEP_JD *pjd = (PEP_JD*)pep->data;
1573: if (keep==PETSC_DEFAULT) pjd->keep = 0.5;
1574: else {
1575: if (keep<0.1 || keep>0.9) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"The keep argument must be in the range [0.1,0.9]");
1576: pjd->keep = keep;
1577: }
1578: return(0);
1579: }
1581: /*@
1582: PEPJDSetRestart - Sets the restart parameter for the Jacobi-Davidson
1583: method, in particular the proportion of basis vectors that must be kept
1584: after restart.
1586: Logically Collective on pep
1588: Input Parameters:
1589: + pep - the eigenproblem solver context
1590: - keep - the number of vectors to be kept at restart
1592: Options Database Key:
1593: . -pep_jd_restart - Sets the restart parameter
1595: Notes:
1596: Allowed values are in the range [0.1,0.9]. The default is 0.5.
1598: Level: advanced
1600: .seealso: PEPJDGetRestart()
1601: @*/
1602: PetscErrorCode PEPJDSetRestart(PEP pep,PetscReal keep)
1603: {
1609: PetscTryMethod(pep,"PEPJDSetRestart_C",(PEP,PetscReal),(pep,keep));
1610: return(0);
1611: }
1613: PetscErrorCode PEPJDGetRestart_JD(PEP pep,PetscReal *keep)
1614: {
1615: PEP_JD *pjd = (PEP_JD*)pep->data;
1618: *keep = pjd->keep;
1619: return(0);
1620: }
1622: /*@
1623: PEPJDGetRestart - Gets the restart parameter used in the Jacobi-Davidson method.
1625: Not Collective
1627: Input Parameter:
1628: . pep - the eigenproblem solver context
1630: Output Parameter:
1631: . keep - the restart parameter
1633: Level: advanced
1635: .seealso: PEPJDSetRestart()
1636: @*/
1637: PetscErrorCode PEPJDGetRestart(PEP pep,PetscReal *keep)
1638: {
1644: PetscUseMethod(pep,"PEPJDGetRestart_C",(PEP,PetscReal*),(pep,keep));
1645: return(0);
1646: }
1648: PetscErrorCode PEPJDSetFix_JD(PEP pep,PetscReal fix)
1649: {
1650: PEP_JD *pjd = (PEP_JD*)pep->data;
1653: if (fix == PETSC_DEFAULT || fix == PETSC_DECIDE) pjd->fix = 0.01;
1654: else {
1655: if (fix < 0.0) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"Invalid fix value");
1656: pjd->fix = fix;
1657: }
1658: return(0);
1659: }
1661: /*@
1662: PEPJDSetFix - Sets the threshold for changing the target in the correction
1663: equation.
1665: Logically Collective on pep
1667: Input Parameters:
1668: + pep - the eigenproblem solver context
1669: - fix - threshold for changing the target
1671: Options Database Key:
1672: . -pep_jd_fix - the fix value
1674: Note:
1675: The target in the correction equation is fixed at the first iterations.
1676: When the norm of the residual vector is lower than the fix value,
1677: the target is set to the corresponding eigenvalue.
1679: Level: advanced
1681: .seealso: PEPJDGetFix()
1682: @*/
1683: PetscErrorCode PEPJDSetFix(PEP pep,PetscReal fix)
1684: {
1690: PetscTryMethod(pep,"PEPJDSetFix_C",(PEP,PetscReal),(pep,fix));
1691: return(0);
1692: }
1694: PetscErrorCode PEPJDGetFix_JD(PEP pep,PetscReal *fix)
1695: {
1696: PEP_JD *pjd = (PEP_JD*)pep->data;
1699: *fix = pjd->fix;
1700: return(0);
1701: }
1703: /*@
1704: PEPJDGetFix - Returns the threshold for changing the target in the correction
1705: equation.
1707: Not Collective
1709: Input Parameter:
1710: . pep - the eigenproblem solver context
1712: Output Parameter:
1713: . fix - threshold for changing the target
1715: Note:
1716: The target in the correction equation is fixed at the first iterations.
1717: When the norm of the residual vector is lower than the fix value,
1718: the target is set to the corresponding eigenvalue.
1720: Level: advanced
1722: .seealso: PEPJDSetFix()
1723: @*/
1724: PetscErrorCode PEPJDGetFix(PEP pep,PetscReal *fix)
1725: {
1731: PetscUseMethod(pep,"PEPJDGetFix_C",(PEP,PetscReal*),(pep,fix));
1732: return(0);
1733: }
1735: PetscErrorCode PEPJDSetReusePreconditioner_JD(PEP pep,PetscBool reusepc)
1736: {
1737: PEP_JD *pjd = (PEP_JD*)pep->data;
1740: pjd->reusepc = reusepc;
1741: return(0);
1742: }
1744: /*@
1745: PEPJDSetReusePreconditioner - Sets a flag indicating whether the preconditioner
1746: must be reused or not.
1748: Logically Collective on pep
1750: Input Parameters:
1751: + pep - the eigenproblem solver context
1752: - reusepc - the reuse flag
1754: Options Database Key:
1755: . -pep_jd_reuse_preconditioner - the reuse flag
1757: Note:
1758: The default value is False. If set to True, the preconditioner is built
1759: only at the beginning, using the target value. Otherwise, it may be rebuilt
1760: (depending on the fix parameter) at each iteration from the Ritz value.
1762: Level: advanced
1764: .seealso: PEPJDGetReusePreconditioner(), PEPJDSetFix()
1765: @*/
1766: PetscErrorCode PEPJDSetReusePreconditioner(PEP pep,PetscBool reusepc)
1767: {
1773: PetscTryMethod(pep,"PEPJDSetReusePreconditioner_C",(PEP,PetscBool),(pep,reusepc));
1774: return(0);
1775: }
1777: PetscErrorCode PEPJDGetReusePreconditioner_JD(PEP pep,PetscBool *reusepc)
1778: {
1779: PEP_JD *pjd = (PEP_JD*)pep->data;
1782: *reusepc = pjd->reusepc;
1783: return(0);
1784: }
1786: /*@
1787: PEPJDGetReusePreconditioner - Returns the flag for reusing the preconditioner.
1789: Not Collective
1791: Input Parameter:
1792: . pep - the eigenproblem solver context
1794: Output Parameter:
1795: . reusepc - the reuse flag
1797: Level: advanced
1799: .seealso: PEPJDSetReusePreconditioner()
1800: @*/
1801: PetscErrorCode PEPJDGetReusePreconditioner(PEP pep,PetscBool *reusepc)
1802: {
1808: PetscUseMethod(pep,"PEPJDGetReusePreconditioner_C",(PEP,PetscBool*),(pep,reusepc));
1809: return(0);
1810: }
1812: PetscErrorCode PEPJDSetMinimalityIndex_JD(PEP pep,PetscInt mmidx)
1813: {
1814: PEP_JD *pjd = (PEP_JD*)pep->data;
1817: if (mmidx == PETSC_DEFAULT || mmidx == PETSC_DECIDE) pjd->mmidx = 1;
1818: else {
1819: if (mmidx < 1) SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"Invalid mmidx value");
1820: pjd->mmidx = mmidx;
1821: pep->state = PEP_STATE_INITIAL;
1822: }
1823: return(0);
1824: }
1826: /*@
1827: PEPJDSetMinimalityIndex - Sets the maximum allowed value for the minimality index.
1829: Logically Collective on pep
1831: Input Parameters:
1832: + pep - the eigenproblem solver context
1833: - mmidx - maximum minimality index
1835: Options Database Key:
1836: . -pep_jd_minimality_index - the minimality index value
1838: Note:
1839: The default value is equal to the degree of the polynomial. A smaller value
1840: can be used if the wanted eigenvectors are known to be linearly independent.
1842: Level: advanced
1844: .seealso: PEPJDGetMinimalityIndex()
1845: @*/
1846: PetscErrorCode PEPJDSetMinimalityIndex(PEP pep,PetscInt mmidx)
1847: {
1853: PetscTryMethod(pep,"PEPJDSetMinimalityIndex_C",(PEP,PetscInt),(pep,mmidx));
1854: return(0);
1855: }
1857: PetscErrorCode PEPJDGetMinimalityIndex_JD(PEP pep,PetscInt *mmidx)
1858: {
1859: PEP_JD *pjd = (PEP_JD*)pep->data;
1862: *mmidx = pjd->mmidx;
1863: return(0);
1864: }
1866: /*@
1867: PEPJDGetMinimalityIndex - Returns the maximum allowed value of the minimality
1868: index.
1870: Not Collective
1872: Input Parameter:
1873: . pep - the eigenproblem solver context
1875: Output Parameter:
1876: . mmidx - minimality index
1878: Level: advanced
1880: .seealso: PEPJDSetMinimalityIndex()
1881: @*/
1882: PetscErrorCode PEPJDGetMinimalityIndex(PEP pep,PetscInt *mmidx)
1883: {
1889: PetscUseMethod(pep,"PEPJDGetMinimalityIndex_C",(PEP,PetscInt*),(pep,mmidx));
1890: return(0);
1891: }
1893: PetscErrorCode PEPJDSetProjection_JD(PEP pep,PEPJDProjection proj)
1894: {
1895: PEP_JD *pjd = (PEP_JD*)pep->data;
1898: switch (proj) {
1899: case PEP_JD_PROJECTION_HARMONIC:
1900: case PEP_JD_PROJECTION_ORTHOGONAL:
1901: if (pjd->proj != proj) {
1902: pep->state = PEP_STATE_INITIAL;
1903: pjd->proj = proj;
1904: }
1905: break;
1906: default:
1907: SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"Invalid 'proj' value");
1908: }
1909: return(0);
1910: }
1912: /*@
1913: PEPJDSetProjection - Sets the type of projection to be used in the Jacobi-Davidson solver.
1915: Logically Collective on pep
1917: Input Parameters:
1918: + pep - the eigenproblem solver context
1919: - proj - the type of projection
1921: Options Database Key:
1922: . -pep_jd_projection - the projection type, either orthogonal or harmonic
1924: Level: advanced
1926: .seealso: PEPJDGetProjection()
1927: @*/
1928: PetscErrorCode PEPJDSetProjection(PEP pep,PEPJDProjection proj)
1929: {
1935: PetscTryMethod(pep,"PEPJDSetProjection_C",(PEP,PEPJDProjection),(pep,proj));
1936: return(0);
1937: }
1939: PetscErrorCode PEPJDGetProjection_JD(PEP pep,PEPJDProjection *proj)
1940: {
1941: PEP_JD *pjd = (PEP_JD*)pep->data;
1944: *proj = pjd->proj;
1945: return(0);
1946: }
1948: /*@
1949: PEPJDGetProjection - Returns the type of projection used by the Jacobi-Davidson solver.
1951: Not Collective
1953: Input Parameter:
1954: . pep - the eigenproblem solver context
1956: Output Parameter:
1957: . proj - the type of projection
1959: Level: advanced
1961: .seealso: PEPJDSetProjection()
1962: @*/
1963: PetscErrorCode PEPJDGetProjection(PEP pep,PEPJDProjection *proj)
1964: {
1970: PetscUseMethod(pep,"PEPJDGetProjection_C",(PEP,PEPJDProjection*),(pep,proj));
1971: return(0);
1972: }
1974: PetscErrorCode PEPSetFromOptions_JD(PetscOptionItems *PetscOptionsObject,PEP pep)
1975: {
1976: PetscErrorCode ierr;
1977: PetscBool flg,b1;
1978: PetscReal r1;
1979: PetscInt i1;
1980: PEPJDProjection proj;
1983: PetscOptionsHead(PetscOptionsObject,"PEP JD Options");
1985: PetscOptionsReal("-pep_jd_restart","Proportion of vectors kept after restart","PEPJDSetRestart",0.5,&r1,&flg);
1986: if (flg) { PEPJDSetRestart(pep,r1); }
1988: PetscOptionsReal("-pep_jd_fix","Tolerance for changing the target in the correction equation","PEPJDSetFix",0.01,&r1,&flg);
1989: if (flg) { PEPJDSetFix(pep,r1); }
1991: PetscOptionsBool("-pep_jd_reuse_preconditioner","Whether to reuse the preconditioner","PEPJDSetReusePreconditoiner",PETSC_FALSE,&b1,&flg);
1992: if (flg) { PEPJDSetReusePreconditioner(pep,b1); }
1994: PetscOptionsInt("-pep_jd_minimality_index","Maximum allowed minimality index","PEPJDSetMinimalityIndex",1,&i1,&flg);
1995: if (flg) { PEPJDSetMinimalityIndex(pep,i1); }
1997: PetscOptionsEnum("-pep_jd_projection","Type of projection","PEPJDSetProjection",PEPJDProjectionTypes,(PetscEnum)PEP_JD_PROJECTION_HARMONIC,(PetscEnum*)&proj,&flg);
1998: if (flg) { PEPJDSetProjection(pep,proj); }
2000: PetscOptionsTail();
2001: return(0);
2002: }
2004: PetscErrorCode PEPView_JD(PEP pep,PetscViewer viewer)
2005: {
2007: PEP_JD *pjd = (PEP_JD*)pep->data;
2008: PetscBool isascii;
2011: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii);
2012: if (isascii) {
2013: PetscViewerASCIIPrintf(viewer," %d%% of basis vectors kept after restart\n",(int)(100*pjd->keep));
2014: PetscViewerASCIIPrintf(viewer," threshold for changing the target in the correction equation (fix): %g\n",(double)pjd->fix);
2015: PetscViewerASCIIPrintf(viewer," projection type: %s\n",PEPJDProjectionTypes[pjd->proj]);
2016: PetscViewerASCIIPrintf(viewer," maximum allowed minimality index: %d\n",pjd->mmidx);
2017: if (pjd->reusepc) { PetscViewerASCIIPrintf(viewer," reusing the preconditioner\n"); }
2018: }
2019: return(0);
2020: }
2022: PetscErrorCode PEPSetDefaultST_JD(PEP pep)
2023: {
2025: KSP ksp;
2028: if (!((PetscObject)pep->st)->type_name) {
2029: STSetType(pep->st,STPRECOND);
2030: STPrecondSetKSPHasMat(pep->st,PETSC_TRUE);
2031: }
2032: STSetTransform(pep->st,PETSC_FALSE);
2033: STGetKSP(pep->st,&ksp);
2034: if (!((PetscObject)ksp)->type_name) {
2035: KSPSetType(ksp,KSPBCGSL);
2036: KSPSetTolerances(ksp,1e-5,PETSC_DEFAULT,PETSC_DEFAULT,100);
2037: }
2038: return(0);
2039: }
2041: PetscErrorCode PEPReset_JD(PEP pep)
2042: {
2044: PEP_JD *pjd = (PEP_JD*)pep->data;
2045: PetscInt i;
2048: for (i=0;i<pep->nmat;i++) {
2049: BVDestroy(pjd->TV+i);
2050: }
2051: if (pjd->proj==PEP_JD_PROJECTION_HARMONIC) { BVDestroy(&pjd->W); }
2052: if (pjd->ld>1) {
2053: BVDestroy(&pjd->V);
2054: for (i=0;i<pep->nmat;i++) {
2055: BVDestroy(pjd->AX+i);
2056: }
2057: BVDestroy(&pjd->N[0]);
2058: BVDestroy(&pjd->N[1]);
2059: PetscFree3(pjd->XpX,pjd->T,pjd->Tj);
2060: }
2061: PetscFree2(pjd->TV,pjd->AX);
2062: return(0);
2063: }
2065: PetscErrorCode PEPDestroy_JD(PEP pep)
2066: {
2070: PetscFree(pep->data);
2071: PetscObjectComposeFunction((PetscObject)pep,"PEPJDSetRestart_C",NULL);
2072: PetscObjectComposeFunction((PetscObject)pep,"PEPJDGetRestart_C",NULL);
2073: PetscObjectComposeFunction((PetscObject)pep,"PEPJDSetFix_C",NULL);
2074: PetscObjectComposeFunction((PetscObject)pep,"PEPJDGetFix_C",NULL);
2075: PetscObjectComposeFunction((PetscObject)pep,"PEPJDSetReusePreconditioner_C",NULL);
2076: PetscObjectComposeFunction((PetscObject)pep,"PEPJDGetReusePreconditioner_C",NULL);
2077: PetscObjectComposeFunction((PetscObject)pep,"PEPJDSetMinimalityIndex_C",NULL);
2078: PetscObjectComposeFunction((PetscObject)pep,"PEPJDGetMinimalityIndex_C",NULL);
2079: PetscObjectComposeFunction((PetscObject)pep,"PEPJDSetProjection_C",NULL);
2080: PetscObjectComposeFunction((PetscObject)pep,"PEPJDGetProjection_C",NULL);
2081: return(0);
2082: }
2084: SLEPC_EXTERN PetscErrorCode PEPCreate_JD(PEP pep)
2085: {
2086: PEP_JD *pjd;
2090: PetscNewLog(pep,&pjd);
2091: pep->data = (void*)pjd;
2093: pjd->fix = 0.01;
2094: pjd->mmidx = 0;
2096: pep->ops->solve = PEPSolve_JD;
2097: pep->ops->setup = PEPSetUp_JD;
2098: pep->ops->setfromoptions = PEPSetFromOptions_JD;
2099: pep->ops->destroy = PEPDestroy_JD;
2100: pep->ops->reset = PEPReset_JD;
2101: pep->ops->view = PEPView_JD;
2102: pep->ops->setdefaultst = PEPSetDefaultST_JD;
2104: PetscObjectComposeFunction((PetscObject)pep,"PEPJDSetRestart_C",PEPJDSetRestart_JD);
2105: PetscObjectComposeFunction((PetscObject)pep,"PEPJDGetRestart_C",PEPJDGetRestart_JD);
2106: PetscObjectComposeFunction((PetscObject)pep,"PEPJDSetFix_C",PEPJDSetFix_JD);
2107: PetscObjectComposeFunction((PetscObject)pep,"PEPJDGetFix_C",PEPJDGetFix_JD);
2108: PetscObjectComposeFunction((PetscObject)pep,"PEPJDSetReusePreconditioner_C",PEPJDSetReusePreconditioner_JD);
2109: PetscObjectComposeFunction((PetscObject)pep,"PEPJDGetReusePreconditioner_C",PEPJDGetReusePreconditioner_JD);
2110: PetscObjectComposeFunction((PetscObject)pep,"PEPJDSetMinimalityIndex_C",PEPJDSetMinimalityIndex_JD);
2111: PetscObjectComposeFunction((PetscObject)pep,"PEPJDGetMinimalityIndex_C",PEPJDGetMinimalityIndex_JD);
2112: PetscObjectComposeFunction((PetscObject)pep,"PEPJDSetProjection_C",PEPJDSetProjection_JD);
2113: PetscObjectComposeFunction((PetscObject)pep,"PEPJDGetProjection_C",PEPJDGetProjection_JD);
2114: return(0);
2115: }