Actual source code: bddcschurs.c

petsc-3.13.6 2020-09-29
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  1:  #include <../src/ksp/pc/impls/bddc/bddc.h>
  2:  #include <../src/ksp/pc/impls/bddc/bddcprivate.h>
  3:  #include <../src/mat/impls/dense/seq/dense.h>
  4:  #include <petscblaslapack.h>

  6: PETSC_STATIC_INLINE PetscErrorCode PCBDDCAdjGetNextLayer_Private(PetscInt*,PetscInt,PetscBT,PetscInt*,PetscInt*,PetscInt*);
  7: static PetscErrorCode PCBDDCComputeExplicitSchur(Mat,PetscBool,MatReuse,Mat*);
  8: static PetscErrorCode PCBDDCReuseSolvers_Interior(PC,Vec,Vec);
  9: static PetscErrorCode PCBDDCReuseSolvers_Correction(PC,Vec,Vec);

 11: /* if v2 is not present, correction is done in-place */
 12: PetscErrorCode PCBDDCReuseSolversBenignAdapt(PCBDDCReuseSolvers ctx, Vec v, Vec v2, PetscBool sol, PetscBool full)
 13: {
 14:   PetscScalar    *array;
 15:   PetscScalar    *array2;

 19:   if (!ctx->benign_n) return(0);
 20:   if (sol && full) {
 21:     PetscInt n_I,size_schur;

 23:     /* get sizes */
 24:     MatGetSize(ctx->benign_csAIB,&size_schur,NULL);
 25:     VecGetSize(v,&n_I);
 26:     n_I = n_I - size_schur;
 27:     /* get schur sol from array */
 28:     VecGetArray(v,&array);
 29:     VecPlaceArray(ctx->benign_dummy_schur_vec,array+n_I);
 30:     VecRestoreArray(v,&array);
 31:     /* apply interior sol correction */
 32:     MatMultTranspose(ctx->benign_csAIB,ctx->benign_dummy_schur_vec,ctx->benign_corr_work);
 33:     VecResetArray(ctx->benign_dummy_schur_vec);
 34:     MatMultAdd(ctx->benign_AIIm1ones,ctx->benign_corr_work,v,v);
 35:   }
 36:   if (v2) {
 37:     PetscInt nl;

 39:     VecGetArrayRead(v,(const PetscScalar**)&array);
 40:     VecGetLocalSize(v2,&nl);
 41:     VecGetArray(v2,&array2);
 42:     PetscArraycpy(array2,array,nl);
 43:   } else {
 44:     VecGetArray(v,&array);
 45:     array2 = array;
 46:   }
 47:   if (!sol) { /* change rhs */
 48:     PetscInt n;
 49:     for (n=0;n<ctx->benign_n;n++) {
 50:       PetscScalar    sum = 0.;
 51:       const PetscInt *cols;
 52:       PetscInt       nz,i;

 54:       ISGetLocalSize(ctx->benign_zerodiag_subs[n],&nz);
 55:       ISGetIndices(ctx->benign_zerodiag_subs[n],&cols);
 56:       for (i=0;i<nz-1;i++) sum += array[cols[i]];
 57: #if defined(PETSC_USE_COMPLEX)
 58:       sum = -(PetscRealPart(sum)/nz + PETSC_i*(PetscImaginaryPart(sum)/nz));
 59: #else
 60:       sum = -sum/nz;
 61: #endif
 62:       for (i=0;i<nz-1;i++) array2[cols[i]] += sum;
 63:       ctx->benign_save_vals[n] = array2[cols[nz-1]];
 64:       array2[cols[nz-1]] = sum;
 65:       ISRestoreIndices(ctx->benign_zerodiag_subs[n],&cols);
 66:     }
 67:   } else {
 68:     PetscInt n;
 69:     for (n=0;n<ctx->benign_n;n++) {
 70:       PetscScalar    sum = 0.;
 71:       const PetscInt *cols;
 72:       PetscInt       nz,i;
 73:       ISGetLocalSize(ctx->benign_zerodiag_subs[n],&nz);
 74:       ISGetIndices(ctx->benign_zerodiag_subs[n],&cols);
 75:       for (i=0;i<nz-1;i++) sum += array[cols[i]];
 76: #if defined(PETSC_USE_COMPLEX)
 77:       sum = -(PetscRealPart(sum)/nz + PETSC_i*(PetscImaginaryPart(sum)/nz));
 78: #else
 79:       sum = -sum/nz;
 80: #endif
 81:       for (i=0;i<nz-1;i++) array2[cols[i]] += sum;
 82:       array2[cols[nz-1]] = ctx->benign_save_vals[n];
 83:       ISRestoreIndices(ctx->benign_zerodiag_subs[n],&cols);
 84:     }
 85:   }
 86:   if (v2) {
 87:     VecRestoreArrayRead(v,(const PetscScalar**)&array);
 88:     VecRestoreArray(v2,&array2);
 89:   } else {
 90:     VecRestoreArray(v,&array);
 91:   }
 92:   if (!sol && full) {
 93:     Vec      usedv;
 94:     PetscInt n_I,size_schur;

 96:     /* get sizes */
 97:     MatGetSize(ctx->benign_csAIB,&size_schur,NULL);
 98:     VecGetSize(v,&n_I);
 99:     n_I = n_I - size_schur;
100:     /* compute schur rhs correction */
101:     if (v2) {
102:       usedv = v2;
103:     } else {
104:       usedv = v;
105:     }
106:     /* apply schur rhs correction */
107:     MatMultTranspose(ctx->benign_AIIm1ones,usedv,ctx->benign_corr_work);
108:     VecGetArrayRead(usedv,(const PetscScalar**)&array);
109:     VecPlaceArray(ctx->benign_dummy_schur_vec,array+n_I);
110:     VecRestoreArrayRead(usedv,(const PetscScalar**)&array);
111:     MatMultAdd(ctx->benign_csAIB,ctx->benign_corr_work,ctx->benign_dummy_schur_vec,ctx->benign_dummy_schur_vec);
112:     VecResetArray(ctx->benign_dummy_schur_vec);
113:   }
114:   return(0);
115: }

117: static PetscErrorCode PCBDDCReuseSolvers_Solve_Private(PC pc, Vec rhs, Vec sol, PetscBool transpose, PetscBool full)
118: {
119:   PCBDDCReuseSolvers ctx;
120:   PetscBool          copy = PETSC_FALSE;
121:   PetscErrorCode     ierr;

124:   PCShellGetContext(pc,(void **)&ctx);
125:   if (full) {
126: #if defined(PETSC_HAVE_MUMPS)
127:     MatMumpsSetIcntl(ctx->F,26,-1);
128: #endif
129: #if defined(PETSC_HAVE_MKL_PARDISO)
130:     MatMkl_PardisoSetCntl(ctx->F,70,0);
131: #endif
132:     copy = ctx->has_vertices;
133:   } else { /* interior solver */
134: #if defined(PETSC_HAVE_MUMPS)
135:     MatMumpsSetIcntl(ctx->F,26,0);
136: #endif
137: #if defined(PETSC_HAVE_MKL_PARDISO)
138:     MatMkl_PardisoSetCntl(ctx->F,70,1);
139: #endif
140:     copy = PETSC_TRUE;
141:   }
142:   /* copy rhs into factored matrix workspace */
143:   if (copy) {
144:     PetscInt    n;
145:     PetscScalar *array,*array_solver;

147:     VecGetLocalSize(rhs,&n);
148:     VecGetArrayRead(rhs,(const PetscScalar**)&array);
149:     VecGetArray(ctx->rhs,&array_solver);
150:     PetscArraycpy(array_solver,array,n);
151:     VecRestoreArray(ctx->rhs,&array_solver);
152:     VecRestoreArrayRead(rhs,(const PetscScalar**)&array);

154:     PCBDDCReuseSolversBenignAdapt(ctx,ctx->rhs,NULL,PETSC_FALSE,full);
155:     if (transpose) {
156:       MatSolveTranspose(ctx->F,ctx->rhs,ctx->sol);
157:     } else {
158:       MatSolve(ctx->F,ctx->rhs,ctx->sol);
159:     }
160:     PCBDDCReuseSolversBenignAdapt(ctx,ctx->sol,NULL,PETSC_TRUE,full);

162:     /* get back data to caller worskpace */
163:     VecGetArrayRead(ctx->sol,(const PetscScalar**)&array_solver);
164:     VecGetArray(sol,&array);
165:     PetscArraycpy(array,array_solver,n);
166:     VecRestoreArray(sol,&array);
167:     VecRestoreArrayRead(ctx->sol,(const PetscScalar**)&array_solver);
168:   } else {
169:     if (ctx->benign_n) {
170:       PCBDDCReuseSolversBenignAdapt(ctx,rhs,ctx->rhs,PETSC_FALSE,full);
171:       if (transpose) {
172:         MatSolveTranspose(ctx->F,ctx->rhs,sol);
173:       } else {
174:         MatSolve(ctx->F,ctx->rhs,sol);
175:       }
176:       PCBDDCReuseSolversBenignAdapt(ctx,sol,NULL,PETSC_TRUE,full);
177:     } else {
178:       if (transpose) {
179:         MatSolveTranspose(ctx->F,rhs,sol);
180:       } else {
181:         MatSolve(ctx->F,rhs,sol);
182:       }
183:     }
184:   }
185:   /* restore defaults */
186: #if defined(PETSC_HAVE_MUMPS)
187:   MatMumpsSetIcntl(ctx->F,26,-1);
188: #endif
189: #if defined(PETSC_HAVE_MKL_PARDISO)
190:   MatMkl_PardisoSetCntl(ctx->F,70,0);
191: #endif
192:   return(0);
193: }

195: static PetscErrorCode PCBDDCReuseSolvers_Correction(PC pc, Vec rhs, Vec sol)
196: {
197:   PetscErrorCode   ierr;

200:   PCBDDCReuseSolvers_Solve_Private(pc,rhs,sol,PETSC_FALSE,PETSC_TRUE);
201:   return(0);
202: }

204: static PetscErrorCode PCBDDCReuseSolvers_CorrectionTranspose(PC pc, Vec rhs, Vec sol)
205: {
206:   PetscErrorCode   ierr;

209:   PCBDDCReuseSolvers_Solve_Private(pc,rhs,sol,PETSC_TRUE,PETSC_TRUE);
210:   return(0);
211: }

213: static PetscErrorCode PCBDDCReuseSolvers_Interior(PC pc, Vec rhs, Vec sol)
214: {
215:   PetscErrorCode   ierr;

218:   PCBDDCReuseSolvers_Solve_Private(pc,rhs,sol,PETSC_FALSE,PETSC_FALSE);
219:   return(0);
220: }

222: static PetscErrorCode PCBDDCReuseSolvers_InteriorTranspose(PC pc, Vec rhs, Vec sol)
223: {
224:   PetscErrorCode   ierr;

227:   PCBDDCReuseSolvers_Solve_Private(pc,rhs,sol,PETSC_TRUE,PETSC_FALSE);
228:   return(0);
229: }

231: static PetscErrorCode PCBDDCReuseSolvers_View(PC pc, PetscViewer viewer)
232: {
233:   PCBDDCReuseSolvers ctx;
234:   PetscBool          iascii;
235:   PetscErrorCode     ierr;

238:   PCShellGetContext(pc,(void **)&ctx);
239:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
240:   if (iascii) {
241:     PetscViewerPushFormat(viewer,PETSC_VIEWER_ASCII_INFO);
242:   }
243:   MatView(ctx->F,viewer);
244:   if (iascii) {
245:     PetscViewerPopFormat(viewer);
246:   }
247:   return(0);
248: }

250: static PetscErrorCode PCBDDCReuseSolversReset(PCBDDCReuseSolvers reuse)
251: {
252:   PetscInt       i;

256:   MatDestroy(&reuse->F);
257:   VecDestroy(&reuse->sol);
258:   VecDestroy(&reuse->rhs);
259:   PCDestroy(&reuse->interior_solver);
260:   PCDestroy(&reuse->correction_solver);
261:   ISDestroy(&reuse->is_R);
262:   ISDestroy(&reuse->is_B);
263:   VecScatterDestroy(&reuse->correction_scatter_B);
264:   VecDestroy(&reuse->sol_B);
265:   VecDestroy(&reuse->rhs_B);
266:   for (i=0;i<reuse->benign_n;i++) {
267:     ISDestroy(&reuse->benign_zerodiag_subs[i]);
268:   }
269:   PetscFree(reuse->benign_zerodiag_subs);
270:   PetscFree(reuse->benign_save_vals);
271:   MatDestroy(&reuse->benign_csAIB);
272:   MatDestroy(&reuse->benign_AIIm1ones);
273:   VecDestroy(&reuse->benign_corr_work);
274:   VecDestroy(&reuse->benign_dummy_schur_vec);
275:   return(0);
276: }

278: static PetscErrorCode PCBDDCComputeExplicitSchur(Mat M, PetscBool issym, MatReuse reuse, Mat *S)
279: {
280:   Mat            B, C, D, Bd, Cd, AinvBd;
281:   KSP            ksp;
282:   PC             pc;
283:   PetscBool      isLU, isILU, isCHOL, Bdense, Cdense;
284:   PetscReal      fill = 2.0;
285:   PetscInt       n_I;
286:   PetscMPIInt    size;

290:   MPI_Comm_size(PetscObjectComm((PetscObject)M),&size);
291:   if (size != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not for parallel matrices");
292:   if (reuse == MAT_REUSE_MATRIX) {
293:     PetscBool Sdense;

295:     PetscObjectTypeCompare((PetscObject)*S, MATSEQDENSE, &Sdense);
296:     if (!Sdense) SETERRQ(PetscObjectComm((PetscObject)M),PETSC_ERR_SUP,"S should dense");
297:   }
298:   MatSchurComplementGetSubMatrices(M, NULL, NULL, &B, &C, &D);
299:   MatSchurComplementGetKSP(M, &ksp);
300:   KSPGetPC(ksp, &pc);
301:   PetscObjectTypeCompare((PetscObject) pc, PCLU, &isLU);
302:   PetscObjectTypeCompare((PetscObject) pc, PCILU, &isILU);
303:   PetscObjectTypeCompare((PetscObject) pc, PCCHOLESKY, &isCHOL);
304:   PetscObjectTypeCompare((PetscObject) B, MATSEQDENSE, &Bdense);
305:   PetscObjectTypeCompare((PetscObject) C, MATSEQDENSE, &Cdense);
306:   MatGetSize(B,&n_I,NULL);
307:   if (n_I) {
308:     if (!Bdense) {
309:       MatConvert(B, MATSEQDENSE, MAT_INITIAL_MATRIX, &Bd);
310:     } else {
311:       Bd = B;
312:     }

314:     if (isLU || isILU || isCHOL) {
315:       Mat fact;
316:       KSPSetUp(ksp);
317:       PCFactorGetMatrix(pc, &fact);
318:       MatDuplicate(Bd, MAT_DO_NOT_COPY_VALUES, &AinvBd);
319:       MatMatSolve(fact, Bd, AinvBd);
320:     } else {
321:       PetscBool ex = PETSC_TRUE;

323:       if (ex) {
324:         Mat Ainvd;

326:         PCComputeOperator(pc, MATDENSE, &Ainvd);
327:         MatMatMult(Ainvd, Bd, MAT_INITIAL_MATRIX, fill, &AinvBd);
328:         MatDestroy(&Ainvd);
329:       } else {
330:         Vec         sol,rhs;
331:         PetscScalar *arrayrhs,*arraysol;
332:         PetscInt    i,nrhs,n;

334:         MatDuplicate(Bd, MAT_DO_NOT_COPY_VALUES, &AinvBd);
335:         MatGetSize(Bd,&n,&nrhs);
336:         MatDenseGetArray(Bd,&arrayrhs);
337:         MatDenseGetArray(AinvBd,&arraysol);
338:         KSPGetSolution(ksp,&sol);
339:         KSPGetRhs(ksp,&rhs);
340:         for (i=0;i<nrhs;i++) {
341:           VecPlaceArray(rhs,arrayrhs+i*n);
342:           VecPlaceArray(sol,arraysol+i*n);
343:           KSPSolve(ksp,rhs,sol);
344:           VecResetArray(rhs);
345:           VecResetArray(sol);
346:         }
347:         MatDenseRestoreArray(Bd,&arrayrhs);
348:         MatDenseRestoreArray(AinvBd,&arrayrhs);
349:       }
350:     }
351:     if (!Bdense & !issym) {
352:       MatDestroy(&Bd);
353:     }

355:     if (!issym) {
356:       if (!Cdense) {
357:         MatConvert(C, MATSEQDENSE, MAT_INITIAL_MATRIX, &Cd);
358:       } else {
359:         Cd = C;
360:       }
361:       MatMatMult(Cd, AinvBd, reuse, fill, S);
362:       if (!Cdense) {
363:         MatDestroy(&Cd);
364:       }
365:     } else {
366:       MatTransposeMatMult(Bd, AinvBd, reuse, fill, S);
367:       if (!Bdense) {
368:         MatDestroy(&Bd);
369:       }
370:     }
371:     MatDestroy(&AinvBd);
372:   }

374:   if (D) {
375:     Mat       Dd;
376:     PetscBool Ddense;

378:     PetscObjectTypeCompare((PetscObject)D,MATSEQDENSE,&Ddense);
379:     if (!Ddense) {
380:       MatConvert(D, MATSEQDENSE, MAT_INITIAL_MATRIX, &Dd);
381:     } else {
382:       Dd = D;
383:     }
384:     if (n_I) {
385:       MatAYPX(*S,-1.0,Dd,SAME_NONZERO_PATTERN);
386:     } else {
387:       if (reuse == MAT_INITIAL_MATRIX) {
388:         MatDuplicate(Dd,MAT_COPY_VALUES,S);
389:       } else {
390:         MatCopy(Dd,*S,SAME_NONZERO_PATTERN);
391:       }
392:     }
393:     if (!Ddense) {
394:       MatDestroy(&Dd);
395:     }
396:   } else {
397:     MatScale(*S,-1.0);
398:   }
399:   return(0);
400: }

402: PetscErrorCode PCBDDCSubSchursSetUp(PCBDDCSubSchurs sub_schurs, Mat Ain, Mat Sin, PetscBool exact_schur, PetscInt xadj[], PetscInt adjncy[], PetscInt nlayers, Vec scaling, PetscBool compute_Stilda, PetscBool reuse_solvers, PetscBool benign_trick, PetscInt benign_n, PetscInt benign_p0_lidx[], IS benign_zerodiag_subs[], Mat change, IS change_primal)
403: {
404:   Mat                    F,A_II,A_IB,A_BI,A_BB,AE_II;
405:   Mat                    S_all;
406:   Vec                    gstash,lstash;
407:   VecScatter             sstash;
408:   IS                     is_I,is_I_layer;
409:   IS                     all_subsets,all_subsets_mult,all_subsets_n;
410:   PetscScalar            *stasharray,*Bwork;
411:   PetscInt               *nnz,*all_local_idx_N;
412:   PetscInt               *auxnum1,*auxnum2;
413:   PetscInt               i,subset_size,max_subset_size;
414:   PetscInt               n_B,extra,local_size,global_size;
415:   PetscInt               local_stash_size;
416:   PetscBLASInt           B_N,B_ierr,B_lwork,*pivots;
417:   MPI_Comm               comm_n;
418:   PetscBool              deluxe = PETSC_TRUE;
419:   PetscBool              use_potr = PETSC_FALSE, use_sytr = PETSC_FALSE;
420:   PetscViewer            matl_dbg_viewer = NULL;
421:   PetscErrorCode         ierr;

424:   MatDestroy(&sub_schurs->A);
425:   MatDestroy(&sub_schurs->S);
426:   if (Ain) {
427:     PetscObjectReference((PetscObject)Ain);
428:     sub_schurs->A = Ain;
429:   }

431:   PetscObjectReference((PetscObject)Sin);
432:   sub_schurs->S = Sin;
433:   if (sub_schurs->schur_explicit) {
434:     sub_schurs->schur_explicit = (PetscBool)(!!sub_schurs->A);
435:   }

437:   /* preliminary checks */
438:   if (!sub_schurs->schur_explicit && compute_Stilda) SETERRQ(PetscObjectComm((PetscObject)sub_schurs->l2gmap),PETSC_ERR_SUP,"Adaptive selection of constraints requires MUMPS and/or MKL_PARDISO");

440:   if (benign_trick) sub_schurs->is_posdef = PETSC_FALSE;

442:   /* debug (MATLAB) */
443:   if (sub_schurs->debug) {
444:     PetscMPIInt size,rank;
445:     PetscInt    nr,*print_schurs_ranks,print_schurs = PETSC_FALSE;
446:     PetscBool   flg;

448:     MPI_Comm_size(PetscObjectComm((PetscObject)sub_schurs->l2gmap),&size);
449:     MPI_Comm_rank(PetscObjectComm((PetscObject)sub_schurs->l2gmap),&rank);
450:     nr   = size;
451:     PetscMalloc1(nr,&print_schurs_ranks);
452:     PetscOptionsBegin(PetscObjectComm((PetscObject)sub_schurs->l2gmap),sub_schurs->prefix,"BDDC sub_schurs options","PC");
453:     PetscOptionsIntArray("-sub_schurs_debug_ranks","Ranks to debug (all if the option is not used)",NULL,print_schurs_ranks,&nr,&flg);
454:     if (!flg) print_schurs = PETSC_TRUE;
455:     else {
456:       print_schurs = PETSC_FALSE;
457:       for (i=0;i<nr;i++) if (print_schurs_ranks[i] == (PetscInt)rank) { print_schurs = PETSC_TRUE; break; }
458:     }
459:     PetscOptionsEnd();
460:     PetscFree(print_schurs_ranks);
461:     if (print_schurs) {
462:       char filename[256];

464:       PetscSNPrintf(filename,sizeof(filename),"sub_schurs_Schur_r%d.m",PetscGlobalRank);
465:       PetscViewerASCIIOpen(PETSC_COMM_SELF,filename,&matl_dbg_viewer);
466:       PetscViewerPushFormat(matl_dbg_viewer,PETSC_VIEWER_ASCII_MATLAB);
467:     }
468:   }


471:   /* restrict work on active processes */
472:   if (sub_schurs->restrict_comm) {
473:     PetscSubcomm subcomm;
474:     PetscMPIInt  color,rank;

476:     color = 0;
477:     if (!sub_schurs->n_subs) color = 1; /* this can happen if we are in a multilevel case or if the subdomain is disconnected */
478:     MPI_Comm_rank(PetscObjectComm((PetscObject)sub_schurs->l2gmap),&rank);
479:     PetscSubcommCreate(PetscObjectComm((PetscObject)sub_schurs->l2gmap),&subcomm);
480:     PetscSubcommSetNumber(subcomm,2);
481:     PetscSubcommSetTypeGeneral(subcomm,color,rank);
482:     PetscCommDuplicate(PetscSubcommChild(subcomm),&comm_n,NULL);
483:     PetscSubcommDestroy(&subcomm);
484:     if (!sub_schurs->n_subs) {
485:       PetscCommDestroy(&comm_n);
486:       return(0);
487:     }
488:   } else {
489:     PetscCommDuplicate(PetscObjectComm((PetscObject)sub_schurs->l2gmap),&comm_n,NULL);
490:   }

492:   /* get Schur complement matrices */
493:   if (!sub_schurs->schur_explicit) {
494:     Mat       tA_IB,tA_BI,tA_BB;
495:     PetscBool isseqsbaij;
496:     MatSchurComplementGetSubMatrices(sub_schurs->S,&A_II,NULL,&tA_IB,&tA_BI,&tA_BB);
497:     PetscObjectTypeCompare((PetscObject)tA_BB,MATSEQSBAIJ,&isseqsbaij);
498:     if (isseqsbaij) {
499:       MatConvert(tA_BB,MATSEQAIJ,MAT_INITIAL_MATRIX,&A_BB);
500:       MatConvert(tA_IB,MATSEQAIJ,MAT_INITIAL_MATRIX,&A_IB);
501:       MatConvert(tA_BI,MATSEQAIJ,MAT_INITIAL_MATRIX,&A_BI);
502:     } else {
503:       PetscObjectReference((PetscObject)tA_BB);
504:       A_BB = tA_BB;
505:       PetscObjectReference((PetscObject)tA_IB);
506:       A_IB = tA_IB;
507:       PetscObjectReference((PetscObject)tA_BI);
508:       A_BI = tA_BI;
509:     }
510:   } else {
511:     A_II = NULL;
512:     A_IB = NULL;
513:     A_BI = NULL;
514:     A_BB = NULL;
515:   }
516:   S_all = NULL;

518:   /* determine interior problems */
519:   ISGetLocalSize(sub_schurs->is_I,&i);
520:   if (nlayers >= 0 && i) { /* Interior problems can be different from the original one */
521:     PetscBT                touched;
522:     const PetscInt*        idx_B;
523:     PetscInt               n_I,n_B,n_local_dofs,n_prev_added,j,layer,*local_numbering;

525:     if (!xadj) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Cannot request layering without adjacency");
526:     /* get sizes */
527:     ISGetLocalSize(sub_schurs->is_I,&n_I);
528:     ISGetLocalSize(sub_schurs->is_B,&n_B);

530:     PetscMalloc1(n_I+n_B,&local_numbering);
531:     PetscBTCreate(n_I+n_B,&touched);
532:     PetscBTMemzero(n_I+n_B,touched);

534:     /* all boundary dofs must be skipped when adding layers */
535:     ISGetIndices(sub_schurs->is_B,&idx_B);
536:     for (j=0;j<n_B;j++) {
537:       PetscBTSet(touched,idx_B[j]);
538:     }
539:     PetscArraycpy(local_numbering,idx_B,n_B);
540:     ISRestoreIndices(sub_schurs->is_B,&idx_B);

542:     /* add prescribed number of layers of dofs */
543:     n_local_dofs = n_B;
544:     n_prev_added = n_B;
545:     for (layer=0;layer<nlayers;layer++) {
546:       PetscInt n_added;
547:       if (n_local_dofs == n_I+n_B) break;
548:       if (n_local_dofs > n_I+n_B) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Error querying layer %D. Out of bound access (%D > %D)",layer,n_local_dofs,n_I+n_B);
549:       PCBDDCAdjGetNextLayer_Private(local_numbering+n_local_dofs,n_prev_added,touched,xadj,adjncy,&n_added);
550:       n_prev_added = n_added;
551:       n_local_dofs += n_added;
552:       if (!n_added) break;
553:     }
554:     PetscBTDestroy(&touched);

556:     /* IS for I layer dofs in original numbering */
557:     ISCreateGeneral(PetscObjectComm((PetscObject)sub_schurs->is_I),n_local_dofs-n_B,local_numbering+n_B,PETSC_COPY_VALUES,&is_I_layer);
558:     PetscFree(local_numbering);
559:     ISSort(is_I_layer);
560:     /* IS for I layer dofs in I numbering */
561:     if (!sub_schurs->schur_explicit) {
562:       ISLocalToGlobalMapping ItoNmap;
563:       ISLocalToGlobalMappingCreateIS(sub_schurs->is_I,&ItoNmap);
564:       ISGlobalToLocalMappingApplyIS(ItoNmap,IS_GTOLM_DROP,is_I_layer,&is_I);
565:       ISLocalToGlobalMappingDestroy(&ItoNmap);

567:       /* II block */
568:       MatCreateSubMatrix(A_II,is_I,is_I,MAT_INITIAL_MATRIX,&AE_II);
569:     }
570:   } else {
571:     PetscInt n_I;

573:     /* IS for I dofs in original numbering */
574:     PetscObjectReference((PetscObject)sub_schurs->is_I);
575:     is_I_layer = sub_schurs->is_I;

577:     /* IS for I dofs in I numbering (strided 1) */
578:     if (!sub_schurs->schur_explicit) {
579:       ISGetSize(sub_schurs->is_I,&n_I);
580:       ISCreateStride(PetscObjectComm((PetscObject)sub_schurs->is_I),n_I,0,1,&is_I);

582:       /* II block is the same */
583:       PetscObjectReference((PetscObject)A_II);
584:       AE_II = A_II;
585:     }
586:   }

588:   /* Get info on subset sizes and sum of all subsets sizes */
589:   max_subset_size = 0;
590:   local_size = 0;
591:   for (i=0;i<sub_schurs->n_subs;i++) {
592:     ISGetLocalSize(sub_schurs->is_subs[i],&subset_size);
593:     max_subset_size = PetscMax(subset_size,max_subset_size);
594:     local_size += subset_size;
595:   }

597:   /* Work arrays for local indices */
598:   extra = 0;
599:   ISGetLocalSize(sub_schurs->is_B,&n_B);
600:   if (sub_schurs->schur_explicit && is_I_layer) {
601:     ISGetLocalSize(is_I_layer,&extra);
602:   }
603:   PetscMalloc1(n_B+extra,&all_local_idx_N);
604:   if (extra) {
605:     const PetscInt *idxs;
606:     ISGetIndices(is_I_layer,&idxs);
607:     PetscArraycpy(all_local_idx_N,idxs,extra);
608:     ISRestoreIndices(is_I_layer,&idxs);
609:   }
610:   PetscMalloc1(sub_schurs->n_subs,&auxnum1);
611:   PetscMalloc1(sub_schurs->n_subs,&auxnum2);

613:   /* Get local indices in local numbering */
614:   local_size = 0;
615:   local_stash_size = 0;
616:   for (i=0;i<sub_schurs->n_subs;i++) {
617:     const PetscInt *idxs;

619:     ISGetLocalSize(sub_schurs->is_subs[i],&subset_size);
620:     ISGetIndices(sub_schurs->is_subs[i],&idxs);
621:     /* start (smallest in global ordering) and multiplicity */
622:     auxnum1[i] = idxs[0];
623:     auxnum2[i] = subset_size*subset_size;
624:     /* subset indices in local numbering */
625:     PetscArraycpy(all_local_idx_N+local_size+extra,idxs,subset_size);
626:     ISRestoreIndices(sub_schurs->is_subs[i],&idxs);
627:     local_size += subset_size;
628:     local_stash_size += subset_size*subset_size;
629:   }

631:   /* allocate extra workspace needed only for GETRI or SYTRF */
632:   use_potr = use_sytr = PETSC_FALSE;
633:   if (benign_trick || (sub_schurs->is_hermitian && sub_schurs->is_posdef)) {
634:     use_potr = PETSC_TRUE;
635:   } else if (sub_schurs->is_symmetric) {
636:     use_sytr = PETSC_TRUE;
637:   }
638:   if (local_size && !use_potr) {
639:     PetscScalar  lwork,dummyscalar = 0.;
640:     PetscBLASInt dummyint = 0;

642:     B_lwork = -1;
643:     PetscBLASIntCast(local_size,&B_N);
644:     PetscFPTrapPush(PETSC_FP_TRAP_OFF);
645:     if (use_sytr) {
646:       PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_("L",&B_N,&dummyscalar,&B_N,&dummyint,&lwork,&B_lwork,&B_ierr));
647:       if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in query to SYTRF Lapack routine %d",(int)B_ierr);
648:     } else {
649:       PetscStackCallBLAS("LAPACKgetri",LAPACKgetri_(&B_N,&dummyscalar,&B_N,&dummyint,&lwork,&B_lwork,&B_ierr));
650:       if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in query to GETRI Lapack routine %d",(int)B_ierr);
651:     }
652:     PetscFPTrapPop();
653:     PetscBLASIntCast((PetscInt)PetscRealPart(lwork),&B_lwork);
654:     PetscMalloc2(B_lwork,&Bwork,B_N,&pivots);
655:   } else {
656:     Bwork = NULL;
657:     pivots = NULL;
658:   }

660:   /* prepare data for summing up properly schurs on subsets */
661:   ISCreateGeneral(comm_n,sub_schurs->n_subs,auxnum1,PETSC_OWN_POINTER,&all_subsets_n);
662:   ISLocalToGlobalMappingApplyIS(sub_schurs->l2gmap,all_subsets_n,&all_subsets);
663:   ISDestroy(&all_subsets_n);
664:   ISCreateGeneral(comm_n,sub_schurs->n_subs,auxnum2,PETSC_OWN_POINTER,&all_subsets_mult);
665:   ISRenumber(all_subsets,all_subsets_mult,&global_size,&all_subsets_n);
666:   ISDestroy(&all_subsets);
667:   ISDestroy(&all_subsets_mult);
668:   ISGetLocalSize(all_subsets_n,&i);
669:   if (i != local_stash_size) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Invalid size of new subset! %D != %D",i,local_stash_size);
670:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,local_stash_size,NULL,&lstash);
671:   VecCreateMPI(comm_n,PETSC_DECIDE,global_size,&gstash);
672:   VecScatterCreate(lstash,NULL,gstash,all_subsets_n,&sstash);
673:   ISDestroy(&all_subsets_n);

675:   /* subset indices in local boundary numbering */
676:   if (!sub_schurs->is_Ej_all) {
677:     PetscInt *all_local_idx_B;

679:     PetscMalloc1(local_size,&all_local_idx_B);
680:     ISGlobalToLocalMappingApply(sub_schurs->BtoNmap,IS_GTOLM_DROP,local_size,all_local_idx_N+extra,&subset_size,all_local_idx_B);
681:     if (subset_size != local_size) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Error in sub_schurs serial (BtoNmap)! %D != %D",subset_size,local_size);
682:     ISCreateGeneral(PETSC_COMM_SELF,local_size,all_local_idx_B,PETSC_OWN_POINTER,&sub_schurs->is_Ej_all);
683:   }

685:   if (change) {
686:     ISLocalToGlobalMapping BtoS;
687:     IS                     change_primal_B;
688:     IS                     change_primal_all;

690:     if (sub_schurs->change_primal_sub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"This should not happen");
691:     if (sub_schurs->change) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"This should not happen");
692:     PetscMalloc1(sub_schurs->n_subs,&sub_schurs->change_primal_sub);
693:     for (i=0;i<sub_schurs->n_subs;i++) {
694:       ISLocalToGlobalMapping NtoS;
695:       ISLocalToGlobalMappingCreateIS(sub_schurs->is_subs[i],&NtoS);
696:       ISGlobalToLocalMappingApplyIS(NtoS,IS_GTOLM_DROP,change_primal,&sub_schurs->change_primal_sub[i]);
697:       ISLocalToGlobalMappingDestroy(&NtoS);
698:     }
699:     ISGlobalToLocalMappingApplyIS(sub_schurs->BtoNmap,IS_GTOLM_DROP,change_primal,&change_primal_B);
700:     ISLocalToGlobalMappingCreateIS(sub_schurs->is_Ej_all,&BtoS);
701:     ISGlobalToLocalMappingApplyIS(BtoS,IS_GTOLM_DROP,change_primal_B,&change_primal_all);
702:     ISLocalToGlobalMappingDestroy(&BtoS);
703:     ISDestroy(&change_primal_B);
704:     PetscMalloc1(sub_schurs->n_subs,&sub_schurs->change);
705:     for (i=0;i<sub_schurs->n_subs;i++) {
706:       Mat change_sub;

708:       ISGetLocalSize(sub_schurs->is_subs[i],&subset_size);
709:       KSPCreate(PETSC_COMM_SELF,&sub_schurs->change[i]);
710:       KSPSetType(sub_schurs->change[i],KSPPREONLY);
711:       if (!sub_schurs->change_with_qr) {
712:         MatCreateSubMatrix(change,sub_schurs->is_subs[i],sub_schurs->is_subs[i],MAT_INITIAL_MATRIX,&change_sub);
713:       } else {
714:         Mat change_subt;
715:         MatCreateSubMatrix(change,sub_schurs->is_subs[i],sub_schurs->is_subs[i],MAT_INITIAL_MATRIX,&change_subt);
716:         MatConvert(change_subt,MATSEQDENSE,MAT_INITIAL_MATRIX,&change_sub);
717:         MatDestroy(&change_subt);
718:       }
719:       KSPSetOperators(sub_schurs->change[i],change_sub,change_sub);
720:       MatDestroy(&change_sub);
721:       KSPSetOptionsPrefix(sub_schurs->change[i],sub_schurs->prefix);
722:       KSPAppendOptionsPrefix(sub_schurs->change[i],"sub_schurs_change_");
723:     }
724:     ISDestroy(&change_primal_all);
725:   }

727:   /* Local matrix of all local Schur on subsets (transposed) */
728:   if (!sub_schurs->S_Ej_all) {
729:     Mat         T;
730:     PetscScalar *v;
731:     PetscInt    *ii,*jj;
732:     PetscInt    cum,i,j,k;

734:     /* MatSeqAIJSetPreallocation + MatSetValues is slow for these kind of matrices (may have large blocks)
735:        Allocate properly a representative matrix and duplicate */
736:     PetscMalloc3(local_size+1,&ii,local_stash_size,&jj,local_stash_size,&v);
737:     ii[0] = 0;
738:     cum   = 0;
739:     for (i=0;i<sub_schurs->n_subs;i++) {
740:       ISGetLocalSize(sub_schurs->is_subs[i],&subset_size);
741:       for (j=0;j<subset_size;j++) {
742:         const PetscInt row = cum+j;
743:         PetscInt col = cum;

745:         ii[row+1] = ii[row] + subset_size;
746:         for (k=ii[row];k<ii[row+1];k++) {
747:           jj[k] = col;
748:           col++;
749:         }
750:       }
751:       cum += subset_size;
752:     }
753:     MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,local_size,local_size,ii,jj,v,&T);
754:     MatDuplicate(T,MAT_DO_NOT_COPY_VALUES,&sub_schurs->S_Ej_all);
755:     MatDestroy(&T);
756:     PetscFree3(ii,jj,v);
757:   }
758:   /* matrices for deluxe scaling and adaptive selection */
759:   if (compute_Stilda) {
760:     if (!sub_schurs->sum_S_Ej_tilda_all) {
761:       MatDuplicate(sub_schurs->S_Ej_all,MAT_DO_NOT_COPY_VALUES,&sub_schurs->sum_S_Ej_tilda_all);
762:     }
763:     if (!sub_schurs->sum_S_Ej_inv_all && deluxe) {
764:       MatDuplicate(sub_schurs->S_Ej_all,MAT_DO_NOT_COPY_VALUES,&sub_schurs->sum_S_Ej_inv_all);
765:     }
766:   }

768:   /* Compute Schur complements explicitly */
769:   F = NULL;
770:   if (!sub_schurs->schur_explicit) {
771:     /* this code branch is used when MatFactor with Schur complement support is not present or when explicitly requested;
772:        it is not efficient, unless the economic version of the scaling is used */
773:     Mat         S_Ej_expl;
774:     PetscScalar *work;
775:     PetscInt    j,*dummy_idx;
776:     PetscBool   Sdense;

778:     PetscMalloc2(max_subset_size,&dummy_idx,max_subset_size*max_subset_size,&work);
779:     local_size = 0;
780:     for (i=0;i<sub_schurs->n_subs;i++) {
781:       IS  is_subset_B;
782:       Mat AE_EE,AE_IE,AE_EI,S_Ej;

784:       /* subsets in original and boundary numbering */
785:       ISGlobalToLocalMappingApplyIS(sub_schurs->BtoNmap,IS_GTOLM_DROP,sub_schurs->is_subs[i],&is_subset_B);
786:       /* EE block */
787:       MatCreateSubMatrix(A_BB,is_subset_B,is_subset_B,MAT_INITIAL_MATRIX,&AE_EE);
788:       /* IE block */
789:       MatCreateSubMatrix(A_IB,is_I,is_subset_B,MAT_INITIAL_MATRIX,&AE_IE);
790:       /* EI block */
791:       if (sub_schurs->is_symmetric) {
792:         MatCreateTranspose(AE_IE,&AE_EI);
793:       } else if (sub_schurs->is_hermitian) {
794:         MatCreateHermitianTranspose(AE_IE,&AE_EI);
795:       } else {
796:         MatCreateSubMatrix(A_BI,is_subset_B,is_I,MAT_INITIAL_MATRIX,&AE_EI);
797:       }
798:       ISDestroy(&is_subset_B);
799:       MatCreateSchurComplement(AE_II,AE_II,AE_IE,AE_EI,AE_EE,&S_Ej);
800:       MatDestroy(&AE_EE);
801:       MatDestroy(&AE_IE);
802:       MatDestroy(&AE_EI);
803:       if (AE_II == A_II) { /* we can reuse the same ksp */
804:         KSP ksp;
805:         MatSchurComplementGetKSP(sub_schurs->S,&ksp);
806:         MatSchurComplementSetKSP(S_Ej,ksp);
807:       } else { /* build new ksp object which inherits ksp and pc types from the original one */
808:         KSP       origksp,schurksp;
809:         PC        origpc,schurpc;
810:         KSPType   ksp_type;
811:         PetscInt  n_internal;
812:         PetscBool ispcnone;

814:         MatSchurComplementGetKSP(sub_schurs->S,&origksp);
815:         MatSchurComplementGetKSP(S_Ej,&schurksp);
816:         KSPGetType(origksp,&ksp_type);
817:         KSPSetType(schurksp,ksp_type);
818:         KSPGetPC(schurksp,&schurpc);
819:         KSPGetPC(origksp,&origpc);
820:         PetscObjectTypeCompare((PetscObject)origpc,PCNONE,&ispcnone);
821:         if (!ispcnone) {
822:           PCType pc_type;
823:           PCGetType(origpc,&pc_type);
824:           PCSetType(schurpc,pc_type);
825:         } else {
826:           PCSetType(schurpc,PCLU);
827:         }
828:         ISGetSize(is_I,&n_internal);
829:         if (!n_internal) { /* UMFPACK gives error with 0 sized problems */
830:           MatSolverType solver = NULL;
831:           PCFactorGetMatSolverType(origpc,(MatSolverType*)&solver);
832:           if (solver) {
833:             PCFactorSetMatSolverType(schurpc,solver);
834:           }
835:         }
836:         KSPSetUp(schurksp);
837:       }
838:       ISGetLocalSize(sub_schurs->is_subs[i],&subset_size);
839:       MatCreateSeqDense(PETSC_COMM_SELF,subset_size,subset_size,work,&S_Ej_expl);
840:       PCBDDCComputeExplicitSchur(S_Ej,sub_schurs->is_symmetric,MAT_REUSE_MATRIX,&S_Ej_expl);
841:       PetscObjectTypeCompare((PetscObject)S_Ej_expl,MATSEQDENSE,&Sdense);
842:       if (Sdense) {
843:         for (j=0;j<subset_size;j++) {
844:           dummy_idx[j]=local_size+j;
845:         }
846:         MatSetValues(sub_schurs->S_Ej_all,subset_size,dummy_idx,subset_size,dummy_idx,work,INSERT_VALUES);
847:       } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not yet implemented for sparse matrices");
848:       MatDestroy(&S_Ej);
849:       MatDestroy(&S_Ej_expl);
850:       local_size += subset_size;
851:     }
852:     PetscFree2(dummy_idx,work);
853:     /* free */
854:     ISDestroy(&is_I);
855:     MatDestroy(&AE_II);
856:     PetscFree(all_local_idx_N);
857:   } else {
858:     Mat               A,cs_AIB_mat = NULL,benign_AIIm1_ones_mat = NULL;
859:     Vec               Dall = NULL;
860:     IS                is_A_all,*is_p_r = NULL;
861:     MatType           Stype;
862:     PetscScalar       *work,*S_data,*schur_factor,infty = PETSC_MAX_REAL;
863:     PetscScalar       *SEj_arr = NULL,*SEjinv_arr = NULL;
864:     const PetscScalar *rS_data;
865:     PetscInt          n,n_I,size_schur,size_active_schur,cum,cum2;
866:     PetscBool         economic,solver_S,S_lower_triangular = PETSC_FALSE;
867:     PetscBool         schur_has_vertices,factor_workaround;
868:     PetscBool         use_cholesky;
869: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
870:     PetscBool         oldpin;
871: #endif

873:     /* get sizes */
874:     n_I = 0;
875:     if (is_I_layer) {
876:       ISGetLocalSize(is_I_layer,&n_I);
877:     }
878:     economic = PETSC_FALSE;
879:     ISGetLocalSize(sub_schurs->is_I,&cum);
880:     if (cum != n_I) economic = PETSC_TRUE;
881:     MatGetLocalSize(sub_schurs->A,&n,NULL);
882:     size_active_schur = local_size;

884:     /* import scaling vector (wrong formulation if we have 3D edges) */
885:     if (scaling && compute_Stilda) {
886:       const PetscScalar *array;
887:       PetscScalar       *array2;
888:       const PetscInt    *idxs;
889:       PetscInt          i;

891:       ISGetIndices(sub_schurs->is_Ej_all,&idxs);
892:       VecCreateSeq(PETSC_COMM_SELF,size_active_schur,&Dall);
893:       VecGetArrayRead(scaling,&array);
894:       VecGetArray(Dall,&array2);
895:       for (i=0;i<size_active_schur;i++) array2[i] = array[idxs[i]];
896:       VecRestoreArray(Dall,&array2);
897:       VecRestoreArrayRead(scaling,&array);
898:       ISRestoreIndices(sub_schurs->is_Ej_all,&idxs);
899:       deluxe = PETSC_FALSE;
900:     }

902:     /* size active schurs does not count any dirichlet or vertex dof on the interface */
903:     factor_workaround = PETSC_FALSE;
904:     schur_has_vertices = PETSC_FALSE;
905:     cum = n_I+size_active_schur;
906:     if (sub_schurs->is_dir) {
907:       const PetscInt* idxs;
908:       PetscInt        n_dir;

910:       ISGetLocalSize(sub_schurs->is_dir,&n_dir);
911:       ISGetIndices(sub_schurs->is_dir,&idxs);
912:       PetscArraycpy(all_local_idx_N+cum,idxs,n_dir);
913:       ISRestoreIndices(sub_schurs->is_dir,&idxs);
914:       cum += n_dir;
915:       factor_workaround = PETSC_TRUE;
916:     }
917:     /* include the primal vertices in the Schur complement */
918:     if (exact_schur && sub_schurs->is_vertices && (compute_Stilda || benign_n)) {
919:       PetscInt n_v;

921:       ISGetLocalSize(sub_schurs->is_vertices,&n_v);
922:       if (n_v) {
923:         const PetscInt* idxs;

925:         ISGetIndices(sub_schurs->is_vertices,&idxs);
926:         PetscArraycpy(all_local_idx_N+cum,idxs,n_v);
927:         ISRestoreIndices(sub_schurs->is_vertices,&idxs);
928:         cum += n_v;
929:         factor_workaround = PETSC_TRUE;
930:         schur_has_vertices = PETSC_TRUE;
931:       }
932:     }
933:     size_schur = cum - n_I;
934:     ISCreateGeneral(PETSC_COMM_SELF,cum,all_local_idx_N,PETSC_OWN_POINTER,&is_A_all);
935: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
936:     oldpin = sub_schurs->A->boundtocpu;
937:     MatBindToCPU(sub_schurs->A,PETSC_TRUE);
938: #endif
939:     if (cum == n) {
940:       ISSetPermutation(is_A_all);
941:       MatPermute(sub_schurs->A,is_A_all,is_A_all,&A);
942:     } else {
943:       MatCreateSubMatrix(sub_schurs->A,is_A_all,is_A_all,MAT_INITIAL_MATRIX,&A);
944:     }
945: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
946:     MatBindToCPU(sub_schurs->A,oldpin);
947: #endif
948:     MatSetOptionsPrefix(A,sub_schurs->prefix);
949:     MatAppendOptionsPrefix(A,"sub_schurs_");

951:     /* if we actually change the basis for the pressures, LDL^T factors will use a lot of memory
952:        this is a workaround */
953:     if (benign_n) {
954:       Vec                    v,benign_AIIm1_ones;
955:       ISLocalToGlobalMapping N_to_reor;
956:       IS                     is_p0,is_p0_p;
957:       PetscScalar            *cs_AIB,*AIIm1_data;
958:       PetscInt               sizeA;

960:       ISLocalToGlobalMappingCreateIS(is_A_all,&N_to_reor);
961:       ISCreateGeneral(PETSC_COMM_SELF,benign_n,benign_p0_lidx,PETSC_COPY_VALUES,&is_p0);
962:       ISGlobalToLocalMappingApplyIS(N_to_reor,IS_GTOLM_DROP,is_p0,&is_p0_p);
963:       ISDestroy(&is_p0);
964:       MatCreateVecs(A,&v,&benign_AIIm1_ones);
965:       VecGetSize(v,&sizeA);
966:       MatCreateSeqDense(PETSC_COMM_SELF,sizeA,benign_n,NULL,&benign_AIIm1_ones_mat);
967:       MatCreateSeqDense(PETSC_COMM_SELF,size_schur,benign_n,NULL,&cs_AIB_mat);
968:       MatDenseGetArray(cs_AIB_mat,&cs_AIB);
969:       MatDenseGetArray(benign_AIIm1_ones_mat,&AIIm1_data);
970:       PetscMalloc1(benign_n,&is_p_r);
971:       /* compute colsum of A_IB restricted to pressures */
972:       for (i=0;i<benign_n;i++) {
973:         const PetscScalar *array;
974:         const PetscInt    *idxs;
975:         PetscInt          j,nz;

977:         ISGlobalToLocalMappingApplyIS(N_to_reor,IS_GTOLM_DROP,benign_zerodiag_subs[i],&is_p_r[i]);
978:         ISGetLocalSize(is_p_r[i],&nz);
979:         ISGetIndices(is_p_r[i],&idxs);
980:         for (j=0;j<nz;j++) AIIm1_data[idxs[j]+sizeA*i] = 1.;
981:         ISRestoreIndices(is_p_r[i],&idxs);
982:         VecPlaceArray(benign_AIIm1_ones,AIIm1_data+sizeA*i);
983:         MatMult(A,benign_AIIm1_ones,v);
984:         VecResetArray(benign_AIIm1_ones);
985:         VecGetArrayRead(v,&array);
986:         for (j=0;j<size_schur;j++) {
987: #if defined(PETSC_USE_COMPLEX)
988:           cs_AIB[i*size_schur + j] = (PetscRealPart(array[j+n_I])/nz + PETSC_i*(PetscImaginaryPart(array[j+n_I])/nz));
989: #else
990:           cs_AIB[i*size_schur + j] = array[j+n_I]/nz;
991: #endif
992:         }
993:         VecRestoreArrayRead(v,&array);
994:       }
995:       MatDenseRestoreArray(cs_AIB_mat,&cs_AIB);
996:       MatDenseRestoreArray(benign_AIIm1_ones_mat,&AIIm1_data);
997:       VecDestroy(&v);
998:       VecDestroy(&benign_AIIm1_ones);
999:       MatSetOption(A,MAT_KEEP_NONZERO_PATTERN,PETSC_FALSE);
1000:       MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
1001:       MatSetOption(A,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);
1002:       MatZeroRowsColumnsIS(A,is_p0_p,1.0,NULL,NULL);
1003:       ISDestroy(&is_p0_p);
1004:       ISLocalToGlobalMappingDestroy(&N_to_reor);
1005:     }
1006:     MatSetOption(A,MAT_SYMMETRIC,sub_schurs->is_symmetric);
1007:     MatSetOption(A,MAT_HERMITIAN,sub_schurs->is_hermitian);
1008:     MatSetOption(A,MAT_SPD,sub_schurs->is_posdef);

1010:     /* for complexes, symmetric and hermitian at the same time implies null imaginary part */
1011:     use_cholesky = (PetscBool)((use_potr || use_sytr) && sub_schurs->is_hermitian && sub_schurs->is_symmetric);

1013:     /* when using the benign subspace trick, the local Schur complements are SPD */
1014:     if (benign_trick) sub_schurs->is_posdef = PETSC_TRUE;

1016:     if (n_I) {
1017:       IS        is_schur;
1018:       char      stype[64];
1019:       PetscBool gpu = PETSC_FALSE;

1021:       if (use_cholesky) {
1022:         MatGetFactor(A,sub_schurs->mat_solver_type,MAT_FACTOR_CHOLESKY,&F);
1023:       } else {
1024:         MatGetFactor(A,sub_schurs->mat_solver_type,MAT_FACTOR_LU,&F);
1025:       }
1026:       MatSetErrorIfFailure(A,PETSC_TRUE);

1028:       /* subsets ordered last */
1029:       ISCreateStride(PETSC_COMM_SELF,size_schur,n_I,1,&is_schur);
1030:       MatFactorSetSchurIS(F,is_schur);
1031:       ISDestroy(&is_schur);

1033:       /* factorization step */
1034:       if (use_cholesky) {
1035:         MatCholeskyFactorSymbolic(F,A,NULL,NULL);
1036: #if defined(PETSC_HAVE_MUMPS) /* be sure that icntl 19 is not set by command line */
1037:         MatMumpsSetIcntl(F,19,2);
1038: #endif
1039:         MatCholeskyFactorNumeric(F,A,NULL);
1040:         S_lower_triangular = PETSC_TRUE;
1041:       } else {
1042:         MatLUFactorSymbolic(F,A,NULL,NULL,NULL);
1043: #if defined(PETSC_HAVE_MUMPS) /* be sure that icntl 19 is not set by command line */
1044:         MatMumpsSetIcntl(F,19,3);
1045: #endif
1046:         MatLUFactorNumeric(F,A,NULL);
1047:       }
1048:       MatViewFromOptions(F,(PetscObject)A,"-mat_factor_view");

1050:       if (matl_dbg_viewer) {
1051:         Mat S;
1052:         IS  is;

1054:         PetscObjectSetName((PetscObject)A,"A");
1055:         MatView(A,matl_dbg_viewer);
1056:         MatFactorCreateSchurComplement(F,&S,NULL);
1057:         PetscObjectSetName((PetscObject)S,"S");
1058:         MatView(S,matl_dbg_viewer);
1059:         MatDestroy(&S);
1060:         ISCreateStride(PETSC_COMM_SELF,n_I,0,1,&is);
1061:         PetscObjectSetName((PetscObject)is,"I");
1062:         ISView(is,matl_dbg_viewer);
1063:         ISDestroy(&is);
1064:         ISCreateStride(PETSC_COMM_SELF,size_schur,n_I,1,&is);
1065:         PetscObjectSetName((PetscObject)is,"B");
1066:         ISView(is,matl_dbg_viewer);
1067:         ISDestroy(&is);
1068:         PetscObjectSetName((PetscObject)is_A_all,"IA");
1069:         ISView(is_A_all,matl_dbg_viewer);
1070:       }

1072:       /* get explicit Schur Complement computed during numeric factorization */
1073:       MatFactorGetSchurComplement(F,&S_all,NULL);
1074:       PetscStrncpy(stype,MATSEQDENSE,sizeof(stype));
1075: #if defined(PETSC_HAVE_CUDA)
1076:       PetscObjectTypeCompareAny((PetscObject)A,&gpu,MATSEQAIJVIENNACL,MATSEQAIJCUSPARSE,"");
1077: #endif
1078:       if (gpu) {
1079:         PetscStrncpy(stype,MATSEQDENSECUDA,sizeof(stype));
1080:       }
1081:       PetscOptionsGetString(NULL,sub_schurs->prefix,"-sub_schurs_schur_mat_type",stype,sizeof(stype),NULL);
1082:       MatConvert(S_all,stype,MAT_INPLACE_MATRIX,&S_all);
1083:       MatSetOption(S_all,MAT_SPD,sub_schurs->is_posdef);
1084:       MatSetOption(S_all,MAT_HERMITIAN,sub_schurs->is_hermitian);
1085:       MatGetType(S_all,&Stype);

1087:       /* we can reuse the solvers if we are not using the economic version */
1088:       reuse_solvers = (PetscBool)(reuse_solvers && !economic);
1089:       factor_workaround = (PetscBool)(reuse_solvers && factor_workaround);
1090:       if (!sub_schurs->is_posdef && factor_workaround && compute_Stilda && size_active_schur)
1091:         reuse_solvers = factor_workaround = PETSC_FALSE;

1093:       solver_S = PETSC_TRUE;

1095:       /* update the Schur complement with the change of basis on the pressures */
1096:       if (benign_n) {
1097:         const PetscScalar *cs_AIB;
1098:         PetscScalar       *S_data,*AIIm1_data;
1099:         Mat               S2 = NULL,S3 = NULL; /* dbg */
1100:         PetscScalar       *S2_data,*S3_data; /* dbg */
1101:         Vec               v,benign_AIIm1_ones;
1102:         PetscInt          sizeA;

1104:         MatDenseGetArray(S_all,&S_data);
1105:         MatCreateVecs(A,&v,&benign_AIIm1_ones);
1106:         VecGetSize(v,&sizeA);
1107: #if defined(PETSC_HAVE_MUMPS)
1108:         MatMumpsSetIcntl(F,26,0);
1109: #endif
1110: #if defined(PETSC_HAVE_MKL_PARDISO)
1111:         MatMkl_PardisoSetCntl(F,70,1);
1112: #endif
1113:         MatDenseGetArrayRead(cs_AIB_mat,&cs_AIB);
1114:         MatDenseGetArray(benign_AIIm1_ones_mat,&AIIm1_data);
1115:         if (matl_dbg_viewer) {
1116:           MatDuplicate(S_all,MAT_DO_NOT_COPY_VALUES,&S2);
1117:           MatDuplicate(S_all,MAT_DO_NOT_COPY_VALUES,&S3);
1118:           MatDenseGetArray(S2,&S2_data);
1119:           MatDenseGetArray(S3,&S3_data);
1120:         }
1121:         for (i=0;i<benign_n;i++) {
1122:           PetscScalar    *array,sum = 0.,one = 1.,*sums;
1123:           const PetscInt *idxs;
1124:           PetscInt       k,j,nz;
1125:           PetscBLASInt   B_k,B_n;

1127:           PetscCalloc1(benign_n,&sums);
1128:           VecPlaceArray(benign_AIIm1_ones,AIIm1_data+sizeA*i);
1129:           VecCopy(benign_AIIm1_ones,v);
1130:           MatSolve(F,v,benign_AIIm1_ones);
1131:           MatMult(A,benign_AIIm1_ones,v);
1132:           VecResetArray(benign_AIIm1_ones);
1133:           /* p0 dofs (eliminated) are excluded from the sums */
1134:           for (k=0;k<benign_n;k++) {
1135:             ISGetLocalSize(is_p_r[k],&nz);
1136:             ISGetIndices(is_p_r[k],&idxs);
1137:             for (j=0;j<nz-1;j++) sums[k] -= AIIm1_data[idxs[j]+sizeA*i];
1138:             ISRestoreIndices(is_p_r[k],&idxs);
1139:           }
1140:           VecGetArrayRead(v,(const PetscScalar**)&array);
1141:           if (matl_dbg_viewer) {
1142:             Vec  vv;
1143:             char name[16];

1145:             VecCreateSeqWithArray(PETSC_COMM_SELF,1,size_schur,array+n_I,&vv);
1146:             PetscSNPrintf(name,sizeof(name),"Pvs%D",i);
1147:             PetscObjectSetName((PetscObject)vv,name);
1148:             VecView(vv,matl_dbg_viewer);
1149:           }
1150:           /* perform sparse rank updates on symmetric Schur (TODO: move outside of the loop?) */
1151:           /* cs_AIB already scaled by 1./nz */
1152:           B_k = 1;
1153:           for (k=0;k<benign_n;k++) {
1154:             sum  = sums[k];
1155:             PetscBLASIntCast(size_schur,&B_n);

1157:             if (PetscAbsScalar(sum) == 0.0) continue;
1158:             if (k == i) {
1159:               PetscStackCallBLAS("BLASsyrk",BLASsyrk_("L","N",&B_n,&B_k,&sum,cs_AIB+i*size_schur,&B_n,&one,S_data,&B_n));
1160:               if (matl_dbg_viewer) {
1161:                 PetscStackCallBLAS("BLASsyrk",BLASsyrk_("L","N",&B_n,&B_k,&sum,cs_AIB+i*size_schur,&B_n,&one,S3_data,&B_n));
1162:               }
1163:             } else { /* XXX Is it correct to use symmetric rank-2 update with half of the sum? */
1164:               sum /= 2.0;
1165:               PetscStackCallBLAS("BLASsyr2k",BLASsyr2k_("L","N",&B_n,&B_k,&sum,cs_AIB+k*size_schur,&B_n,cs_AIB+i*size_schur,&B_n,&one,S_data,&B_n));
1166:               if (matl_dbg_viewer) {
1167:                 PetscStackCallBLAS("BLASsyr2k",BLASsyr2k_("L","N",&B_n,&B_k,&sum,cs_AIB+k*size_schur,&B_n,cs_AIB+i*size_schur,&B_n,&one,S3_data,&B_n));
1168:               }
1169:             }
1170:           }
1171:           sum  = 1.;
1172:           PetscStackCallBLAS("BLASsyr2k",BLASsyr2k_("L","N",&B_n,&B_k,&sum,array+n_I,&B_n,cs_AIB+i*size_schur,&B_n,&one,S_data,&B_n));
1173:           if (matl_dbg_viewer) {
1174:             PetscStackCallBLAS("BLASsyr2k",BLASsyr2k_("L","N",&B_n,&B_k,&sum,array+n_I,&B_n,cs_AIB+i*size_schur,&B_n,&one,S2_data,&B_n));
1175:           }
1176:           VecRestoreArrayRead(v,(const PetscScalar**)&array);
1177:           /* set p0 entry of AIIm1_ones to zero */
1178:           ISGetLocalSize(is_p_r[i],&nz);
1179:           ISGetIndices(is_p_r[i],&idxs);
1180:           for (j=0;j<benign_n;j++) AIIm1_data[idxs[nz-1]+sizeA*j] = 0.;
1181:           ISRestoreIndices(is_p_r[i],&idxs);
1182:           PetscFree(sums);
1183:         }
1184:         VecDestroy(&benign_AIIm1_ones);
1185:         if (matl_dbg_viewer) {
1186:           MatDenseRestoreArray(S2,&S2_data);
1187:           MatDenseRestoreArray(S3,&S3_data);
1188:         }
1189:         if (!S_lower_triangular) { /* I need to expand the upper triangular data (column oriented) */
1190:           PetscInt k,j;
1191:           for (k=0;k<size_schur;k++) {
1192:             for (j=k;j<size_schur;j++) {
1193:               S_data[j*size_schur+k] = PetscConj(S_data[k*size_schur+j]);
1194:             }
1195:           }
1196:         }

1198:         /* restore defaults */
1199: #if defined(PETSC_HAVE_MUMPS)
1200:         MatMumpsSetIcntl(F,26,-1);
1201: #endif
1202: #if defined(PETSC_HAVE_MKL_PARDISO)
1203:         MatMkl_PardisoSetCntl(F,70,0);
1204: #endif
1205:         MatDenseRestoreArrayRead(cs_AIB_mat,&cs_AIB);
1206:         MatDenseRestoreArray(benign_AIIm1_ones_mat,&AIIm1_data);
1207:         VecDestroy(&v);
1208:         MatDenseRestoreArray(S_all,&S_data);
1209:         if (matl_dbg_viewer) {
1210:           Mat S;

1212:           MatFactorRestoreSchurComplement(F,&S_all,MAT_FACTOR_SCHUR_UNFACTORED);
1213:           MatFactorCreateSchurComplement(F,&S,NULL);
1214:           PetscObjectSetName((PetscObject)S,"Sb");
1215:           MatView(S,matl_dbg_viewer);
1216:           MatDestroy(&S);
1217:           PetscObjectSetName((PetscObject)S2,"S2P");
1218:           MatView(S2,matl_dbg_viewer);
1219:           PetscObjectSetName((PetscObject)S3,"S3P");
1220:           MatView(S3,matl_dbg_viewer);
1221:           PetscObjectSetName((PetscObject)cs_AIB_mat,"cs");
1222:           MatView(cs_AIB_mat,matl_dbg_viewer);
1223:           MatFactorGetSchurComplement(F,&S_all,NULL);
1224:         }
1225:         MatDestroy(&S2);
1226:         MatDestroy(&S3);
1227:       }
1228:       if (!reuse_solvers) {
1229:         for (i=0;i<benign_n;i++) {
1230:           ISDestroy(&is_p_r[i]);
1231:         }
1232:         PetscFree(is_p_r);
1233:         MatDestroy(&cs_AIB_mat);
1234:         MatDestroy(&benign_AIIm1_ones_mat);
1235:       }
1236:     } else { /* we can't use MatFactor when size_schur == size_of_the_problem */
1237:       MatConvert(A,MATSEQDENSE,MAT_INITIAL_MATRIX,&S_all);
1238:       MatGetType(S_all,&Stype);
1239:       reuse_solvers = PETSC_FALSE; /* TODO: why we can't reuse the solvers here? */
1240:       factor_workaround = PETSC_FALSE;
1241:       solver_S = PETSC_FALSE;
1242:     }

1244:     if (reuse_solvers) {
1245:       Mat                A_II,Afake;
1246:       Vec                vec1_B;
1247:       PCBDDCReuseSolvers msolv_ctx;
1248:       PetscInt           n_R;

1250:       if (sub_schurs->reuse_solver) {
1251:         PCBDDCReuseSolversReset(sub_schurs->reuse_solver);
1252:       } else {
1253:         PetscNew(&sub_schurs->reuse_solver);
1254:       }
1255:       msolv_ctx = sub_schurs->reuse_solver;
1256:       MatSchurComplementGetSubMatrices(sub_schurs->S,&A_II,NULL,NULL,NULL,NULL);
1257:       PetscObjectReference((PetscObject)F);
1258:       msolv_ctx->F = F;
1259:       MatCreateVecs(F,&msolv_ctx->sol,NULL);
1260:       /* currently PETSc has no support for MatSolve(F,x,x), so cheat and let rhs and sol share the same memory */
1261:       {
1262:         PetscScalar *array;
1263:         PetscInt    n;

1265:         VecGetLocalSize(msolv_ctx->sol,&n);
1266:         VecGetArray(msolv_ctx->sol,&array);
1267:         VecCreateSeqWithArray(PetscObjectComm((PetscObject)msolv_ctx->sol),1,n,array,&msolv_ctx->rhs);
1268:         VecRestoreArray(msolv_ctx->sol,&array);
1269:       }
1270:       msolv_ctx->has_vertices = schur_has_vertices;

1272:       /* interior solver */
1273:       PCCreate(PetscObjectComm((PetscObject)A_II),&msolv_ctx->interior_solver);
1274:       PCSetOperators(msolv_ctx->interior_solver,A_II,A_II);
1275:       PCSetType(msolv_ctx->interior_solver,PCSHELL);
1276:       PCShellSetName(msolv_ctx->interior_solver,"Interior solver (w/o Schur factorization)");
1277:       PCShellSetContext(msolv_ctx->interior_solver,msolv_ctx);
1278:       PCShellSetView(msolv_ctx->interior_solver,PCBDDCReuseSolvers_View);
1279:       PCShellSetApply(msolv_ctx->interior_solver,PCBDDCReuseSolvers_Interior);
1280:       PCShellSetApplyTranspose(msolv_ctx->interior_solver,PCBDDCReuseSolvers_InteriorTranspose);

1282:       /* correction solver */
1283:       PCCreate(PetscObjectComm((PetscObject)A_II),&msolv_ctx->correction_solver);
1284:       PCSetType(msolv_ctx->correction_solver,PCSHELL);
1285:       PCShellSetName(msolv_ctx->correction_solver,"Correction solver (with Schur factorization)");
1286:       PCShellSetContext(msolv_ctx->correction_solver,msolv_ctx);
1287:       PCShellSetView(msolv_ctx->interior_solver,PCBDDCReuseSolvers_View);
1288:       PCShellSetApply(msolv_ctx->correction_solver,PCBDDCReuseSolvers_Correction);
1289:       PCShellSetApplyTranspose(msolv_ctx->correction_solver,PCBDDCReuseSolvers_CorrectionTranspose);

1291:       /* scatter and vecs for Schur complement solver */
1292:       MatCreateVecs(S_all,&msolv_ctx->sol_B,&msolv_ctx->rhs_B);
1293:       MatCreateVecs(sub_schurs->S,&vec1_B,NULL);
1294:       if (!schur_has_vertices) {
1295:         ISGlobalToLocalMappingApplyIS(sub_schurs->BtoNmap,IS_GTOLM_DROP,is_A_all,&msolv_ctx->is_B);
1296:         VecScatterCreate(vec1_B,msolv_ctx->is_B,msolv_ctx->sol_B,NULL,&msolv_ctx->correction_scatter_B);
1297:         PetscObjectReference((PetscObject)is_A_all);
1298:         msolv_ctx->is_R = is_A_all;
1299:       } else {
1300:         IS              is_B_all;
1301:         const PetscInt* idxs;
1302:         PetscInt        dual,n_v,n;

1304:         ISGetLocalSize(sub_schurs->is_vertices,&n_v);
1305:         dual = size_schur - n_v;
1306:         ISGetLocalSize(is_A_all,&n);
1307:         ISGetIndices(is_A_all,&idxs);
1308:         ISCreateGeneral(PetscObjectComm((PetscObject)is_A_all),dual,idxs+n_I,PETSC_COPY_VALUES,&is_B_all);
1309:         ISGlobalToLocalMappingApplyIS(sub_schurs->BtoNmap,IS_GTOLM_DROP,is_B_all,&msolv_ctx->is_B);
1310:         ISDestroy(&is_B_all);
1311:         ISCreateStride(PetscObjectComm((PetscObject)is_A_all),dual,0,1,&is_B_all);
1312:         VecScatterCreate(vec1_B,msolv_ctx->is_B,msolv_ctx->sol_B,is_B_all,&msolv_ctx->correction_scatter_B);
1313:         ISDestroy(&is_B_all);
1314:         ISCreateGeneral(PetscObjectComm((PetscObject)is_A_all),n-n_v,idxs,PETSC_COPY_VALUES,&msolv_ctx->is_R);
1315:         ISRestoreIndices(is_A_all,&idxs);
1316:       }
1317:       ISGetLocalSize(msolv_ctx->is_R,&n_R);
1318:       MatCreateSeqAIJ(PETSC_COMM_SELF,n_R,n_R,0,NULL,&Afake);
1319:       MatAssemblyBegin(Afake,MAT_FINAL_ASSEMBLY);
1320:       MatAssemblyEnd(Afake,MAT_FINAL_ASSEMBLY);
1321:       PCSetOperators(msolv_ctx->correction_solver,Afake,Afake);
1322:       MatDestroy(&Afake);
1323:       VecDestroy(&vec1_B);

1325:       /* communicate benign info to solver context */
1326:       if (benign_n) {
1327:         PetscScalar *array;

1329:         msolv_ctx->benign_n = benign_n;
1330:         msolv_ctx->benign_zerodiag_subs = is_p_r;
1331:         PetscMalloc1(benign_n,&msolv_ctx->benign_save_vals);
1332:         msolv_ctx->benign_csAIB = cs_AIB_mat;
1333:         MatCreateVecs(cs_AIB_mat,&msolv_ctx->benign_corr_work,NULL);
1334:         VecGetArray(msolv_ctx->benign_corr_work,&array);
1335:         VecCreateSeqWithArray(PETSC_COMM_SELF,1,size_schur,array,&msolv_ctx->benign_dummy_schur_vec);
1336:         VecRestoreArray(msolv_ctx->benign_corr_work,&array);
1337:         msolv_ctx->benign_AIIm1ones = benign_AIIm1_ones_mat;
1338:       }
1339:     } else {
1340:       if (sub_schurs->reuse_solver) {
1341:         PCBDDCReuseSolversReset(sub_schurs->reuse_solver);
1342:       }
1343:       PetscFree(sub_schurs->reuse_solver);
1344:     }
1345:     MatDestroy(&A);
1346:     ISDestroy(&is_A_all);

1348:     /* Work arrays */
1349:     PetscMalloc1(max_subset_size*max_subset_size,&work);

1351:     /* S_Ej_all */
1352:     cum = cum2 = 0;
1353:     MatDenseGetArrayRead(S_all,&rS_data);
1354:     MatSeqAIJGetArray(sub_schurs->S_Ej_all,&SEj_arr);
1355:     if (compute_Stilda) {
1356:       MatSeqAIJGetArray(sub_schurs->sum_S_Ej_inv_all,&SEjinv_arr);
1357:     }
1358:     for (i=0;i<sub_schurs->n_subs;i++) {
1359:       PetscInt j;

1361:       /* get S_E */
1362:       ISGetLocalSize(sub_schurs->is_subs[i],&subset_size);
1363:       if (S_lower_triangular) { /* I need to expand the upper triangular data (column oriented) */
1364:         PetscInt k;
1365:         for (k=0;k<subset_size;k++) {
1366:           for (j=k;j<subset_size;j++) {
1367:             work[k*subset_size+j] = rS_data[cum2+k*size_schur+j];
1368:             work[j*subset_size+k] = PetscConj(rS_data[cum2+k*size_schur+j]);
1369:           }
1370:         }
1371:       } else { /* just copy to workspace */
1372:         PetscInt k;
1373:         for (k=0;k<subset_size;k++) {
1374:           for (j=0;j<subset_size;j++) {
1375:             work[k*subset_size+j] = rS_data[cum2+k*size_schur+j];
1376:           }
1377:         }
1378:       }
1379:       /* insert S_E values */
1380:       if (sub_schurs->change) {
1381:         Mat change_sub,SEj,T;

1383:         /* change basis */
1384:         KSPGetOperators(sub_schurs->change[i],&change_sub,NULL);
1385:         MatCreateSeqDense(PETSC_COMM_SELF,subset_size,subset_size,work,&SEj);
1386:         if (!sub_schurs->change_with_qr) { /* currently there's no support for PtAP with P SeqAIJ */
1387:           Mat T2;
1388:           MatTransposeMatMult(change_sub,SEj,MAT_INITIAL_MATRIX,1.0,&T2);
1389:           MatMatMult(T2,change_sub,MAT_INITIAL_MATRIX,1.0,&T);
1390:           MatConvert(T,MATSEQDENSE,MAT_INPLACE_MATRIX,&T);
1391:           MatDestroy(&T2);
1392:         } else {
1393:           MatPtAP(SEj,change_sub,MAT_INITIAL_MATRIX,1.0,&T);
1394:         }
1395:         MatCopy(T,SEj,SAME_NONZERO_PATTERN);
1396:         MatDestroy(&T);
1397:         MatZeroRowsColumnsIS(SEj,sub_schurs->change_primal_sub[i],1.0,NULL,NULL);
1398:         MatDestroy(&SEj);
1399:       }
1400:       if (deluxe) {
1401:         PetscArraycpy(SEj_arr,work,subset_size*subset_size);
1402:         /* if adaptivity is requested, invert S_E blocks */
1403:         if (compute_Stilda) {
1404:           Mat               M;
1405:           const PetscScalar *vals;
1406:           PetscBool         isdense,isdensecuda;

1408:           MatCreateSeqDense(PETSC_COMM_SELF,subset_size,subset_size,work,&M);
1409:           MatSetOption(M,MAT_SPD,sub_schurs->is_posdef);
1410:           MatSetOption(M,MAT_HERMITIAN,sub_schurs->is_hermitian);
1411:           if (!PetscBTLookup(sub_schurs->is_edge,i)) {
1412:             MatSetType(M,Stype);
1413:           }
1414:           PetscObjectTypeCompare((PetscObject)M,MATSEQDENSE,&isdense);
1415:           PetscObjectTypeCompare((PetscObject)M,MATSEQDENSECUDA,&isdensecuda);
1416:           if (use_cholesky) {
1417:             MatCholeskyFactor(M,NULL,NULL);
1418:           } else {
1419:             MatLUFactor(M,NULL,NULL,NULL);
1420:           }
1421:           if (isdense) {
1422:             MatSeqDenseInvertFactors_Private(M);
1423: #if defined(PETSC_HAVE_CUDA)
1424:           } else if (isdensecuda) {
1425:             MatSeqDenseCUDAInvertFactors_Private(M);
1426: #endif
1427:           } else SETERRQ1(PetscObjectComm((PetscObject)M),PETSC_ERR_SUP,"Not implemented for type %s",Stype);
1428:           MatDenseGetArrayRead(M,&vals);
1429:           PetscArraycpy(SEjinv_arr,vals,subset_size*subset_size);
1430:           MatDenseRestoreArrayRead(M,&vals);
1431:           MatDestroy(&M);
1432:         }
1433:       } else if (compute_Stilda) { /* not using deluxe */
1434:         Mat         SEj;
1435:         Vec         D;
1436:         PetscScalar *array;

1438:         MatCreateSeqDense(PETSC_COMM_SELF,subset_size,subset_size,work,&SEj);
1439:         VecGetArray(Dall,&array);
1440:         VecCreateSeqWithArray(PETSC_COMM_SELF,1,subset_size,array+cum,&D);
1441:         VecRestoreArray(Dall,&array);
1442:         VecShift(D,-1.);
1443:         MatDiagonalScale(SEj,D,D);
1444:         MatDestroy(&SEj);
1445:         VecDestroy(&D);
1446:         PetscArraycpy(SEj_arr,work,subset_size*subset_size);
1447:       }
1448:       cum += subset_size;
1449:       cum2 += subset_size*(size_schur + 1);
1450:       SEj_arr += subset_size*subset_size;
1451:       if (SEjinv_arr) SEjinv_arr += subset_size*subset_size;
1452:     }
1453:     MatDenseRestoreArrayRead(S_all,&rS_data);
1454:     MatSeqAIJRestoreArray(sub_schurs->S_Ej_all,&SEj_arr);
1455:     if (compute_Stilda) {
1456:       MatSeqAIJRestoreArray(sub_schurs->sum_S_Ej_inv_all,&SEjinv_arr);
1457:     }
1458:     if (solver_S) {
1459:       MatFactorRestoreSchurComplement(F,&S_all,MAT_FACTOR_SCHUR_UNFACTORED);
1460:     }

1462:     /* may prevent from unneeded copies, since MUMPS or MKL_Pardiso always use CPU memory
1463:        however, preliminary tests indicate using GPUs is still faster in the solve phase */
1464: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
1465:     if (reuse_solvers) {
1466:       Mat                  St;
1467:       MatFactorSchurStatus st;
1468:       PetscBool            flg = PETSC_FALSE;

1470:       PetscOptionsGetBool(NULL,sub_schurs->prefix,"-sub_schurs_schur_pin_to_cpu",&flg,NULL);
1471:       MatFactorGetSchurComplement(F,&St,&st);
1472:       MatBindToCPU(St,flg);
1473:       MatFactorRestoreSchurComplement(F,&St,st);
1474:     }
1475: #endif

1477:     schur_factor = NULL;
1478:     if (compute_Stilda && size_active_schur) {

1480:       MatSeqAIJGetArray(sub_schurs->sum_S_Ej_tilda_all,&SEjinv_arr);
1481:       if (sub_schurs->n_subs == 1 && size_schur == size_active_schur && deluxe) { /* we already computed the inverse */
1482:         PetscArraycpy(SEjinv_arr,work,size_schur*size_schur);
1483:       } else {
1484:         Mat S_all_inv=NULL;

1486:         if (solver_S) {
1487:           /* for adaptive selection we need S^-1; for solver reusage we need S_\Delta\Delta^-1.
1488:              The latter is not the principal subminor for S^-1. However, the factors can be reused since S_\Delta\Delta is the leading principal submatrix of S */
1489:           if (factor_workaround) {/* invert without calling MatFactorInvertSchurComplement, since we are hacking */
1490:             PetscScalar *data;
1491:             PetscInt     nd = 0;

1493:             if (!use_potr) {
1494:               SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Factor update not yet implemented for non SPD matrices");
1495:             }
1496:             MatFactorGetSchurComplement(F,&S_all_inv,NULL);
1497:             MatDenseGetArray(S_all_inv,&data);
1498:             if (sub_schurs->is_dir) { /* dirichlet dofs could have different scalings */
1499:               ISGetLocalSize(sub_schurs->is_dir,&nd);
1500:             }

1502:             /* factor and invert activedofs and vertices (dirichlet dofs does not contribute) */
1503:             if (schur_has_vertices) {
1504:               Mat          M;
1505:               PetscScalar *tdata;
1506:               PetscInt     nv = 0, news;

1508:               ISGetLocalSize(sub_schurs->is_vertices,&nv);
1509:               news = size_active_schur + nv;
1510:               PetscCalloc1(news*news,&tdata);
1511:               for (i=0;i<size_active_schur;i++) {
1512:                 PetscArraycpy(tdata+i*(news+1),data+i*(size_schur+1),size_active_schur-i);
1513:                 PetscArraycpy(tdata+i*(news+1)+size_active_schur-i,data+i*size_schur+size_active_schur+nd,nv);
1514:               }
1515:               for (i=0;i<nv;i++) {
1516:                 PetscInt k = i+size_active_schur;
1517:                 PetscArraycpy(tdata+k*(news+1),data+(k+nd)*(size_schur+1),nv-i);
1518:               }

1520:               MatCreateSeqDense(PETSC_COMM_SELF,news,news,tdata,&M);
1521:               MatSetOption(M,MAT_SPD,PETSC_TRUE);
1522:               MatCholeskyFactor(M,NULL,NULL);
1523:               /* save the factors */
1524:               cum = 0;
1525:               PetscMalloc1((size_active_schur*(size_active_schur +1))/2+nd,&schur_factor);
1526:               for (i=0;i<size_active_schur;i++) {
1527:                 PetscArraycpy(schur_factor+cum,tdata+i*(news+1),size_active_schur-i);
1528:                 cum += size_active_schur - i;
1529:               }
1530:               for (i=0;i<nd;i++) schur_factor[cum+i] = PetscSqrtReal(PetscRealPart(data[(i+size_active_schur)*(size_schur+1)]));
1531:               MatSeqDenseInvertFactors_Private(M);
1532:               /* move back just the active dofs to the Schur complement */
1533:               for (i=0;i<size_active_schur;i++) {
1534:                 PetscArraycpy(data+i*size_schur,tdata+i*news,size_active_schur);
1535:               }
1536:               PetscFree(tdata);
1537:               MatDestroy(&M);
1538:             } else { /* we can factorize and invert just the activedofs */
1539:               Mat         M;
1540:               PetscScalar *aux;

1542:               PetscMalloc1(nd,&aux);
1543:               for (i=0;i<nd;i++) aux[i] = 1.0/data[(i+size_active_schur)*(size_schur+1)];
1544:               MatCreateSeqDense(PETSC_COMM_SELF,size_active_schur,size_active_schur,data,&M);
1545:               MatSeqDenseSetLDA(M,size_schur);
1546:               MatSetOption(M,MAT_SPD,PETSC_TRUE);
1547:               MatCholeskyFactor(M,NULL,NULL);
1548:               MatSeqDenseInvertFactors_Private(M);
1549:               MatDestroy(&M);
1550:               MatCreateSeqDense(PETSC_COMM_SELF,size_schur,nd,data+size_active_schur*size_schur,&M);
1551:               MatZeroEntries(M);
1552:               MatDestroy(&M);
1553:               MatCreateSeqDense(PETSC_COMM_SELF,nd,size_schur,data+size_active_schur,&M);
1554:               MatSeqDenseSetLDA(M,size_schur);
1555:               MatZeroEntries(M);
1556:               MatDestroy(&M);
1557:               for (i=0;i<nd;i++) data[(i+size_active_schur)*(size_schur+1)] = aux[i];
1558:               PetscFree(aux);
1559:             }
1560:             MatDenseRestoreArray(S_all_inv,&data);
1561:           } else { /* use MatFactor calls to invert S */
1562:             MatFactorInvertSchurComplement(F);
1563:             MatFactorGetSchurComplement(F,&S_all_inv,NULL);
1564:           }
1565:         } else { /* we need to invert explicitly since we are not using MatFactor for S */
1566:           PetscObjectReference((PetscObject)S_all);
1567:           S_all_inv = S_all;
1568:           MatDenseGetArray(S_all_inv,&S_data);
1569:           PetscBLASIntCast(size_schur,&B_N);
1570:           PetscFPTrapPush(PETSC_FP_TRAP_OFF);
1571:           if (use_potr) {
1572:             PetscStackCallBLAS("LAPACKpotrf",LAPACKpotrf_("L",&B_N,S_data,&B_N,&B_ierr));
1573:             if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRF Lapack routine %d",(int)B_ierr);
1574:             PetscStackCallBLAS("LAPACKpotri",LAPACKpotri_("L",&B_N,S_data,&B_N,&B_ierr));
1575:             if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRI Lapack routine %d",(int)B_ierr);
1576:           } else if (use_sytr) {
1577:             PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_("L",&B_N,S_data,&B_N,pivots,Bwork,&B_lwork,&B_ierr));
1578:             if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRF Lapack routine %d",(int)B_ierr);
1579:             PetscStackCallBLAS("LAPACKsytri",LAPACKsytri_("L",&B_N,S_data,&B_N,pivots,Bwork,&B_ierr));
1580:             if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRI Lapack routine %d",(int)B_ierr);
1581:           } else {
1582:             PetscStackCallBLAS("LAPACKgetrf",LAPACKgetrf_(&B_N,&B_N,S_data,&B_N,pivots,&B_ierr));
1583:             if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRF Lapack routine %d",(int)B_ierr);
1584:             PetscStackCallBLAS("LAPACKgetri",LAPACKgetri_(&B_N,S_data,&B_N,pivots,Bwork,&B_lwork,&B_ierr));
1585:             if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRI Lapack routine %d",(int)B_ierr);
1586:           }
1587:           PetscLogFlops(1.0*size_schur*size_schur*size_schur);
1588:           PetscFPTrapPop();
1589:           MatDenseRestoreArray(S_all_inv,&S_data);
1590:         }
1591:         /* S_Ej_tilda_all */
1592:         cum = cum2 = 0;
1593:         MatDenseGetArrayRead(S_all_inv,&rS_data);
1594:         for (i=0;i<sub_schurs->n_subs;i++) {
1595:           PetscInt j;

1597:           ISGetLocalSize(sub_schurs->is_subs[i],&subset_size);
1598:           /* get (St^-1)_E */
1599:           /* Unless we are changing the variables, I don't need to expand to upper triangular since St^-1
1600:              will be properly accessed later during adaptive selection */
1601:           if (S_lower_triangular) {
1602:             PetscInt k;
1603:             if (sub_schurs->change) {
1604:               for (k=0;k<subset_size;k++) {
1605:                 for (j=k;j<subset_size;j++) {
1606:                   work[k*subset_size+j] = rS_data[cum2+k*size_schur+j];
1607:                   work[j*subset_size+k] = work[k*subset_size+j];
1608:                 }
1609:               }
1610:             } else {
1611:               for (k=0;k<subset_size;k++) {
1612:                 for (j=k;j<subset_size;j++) {
1613:                   work[k*subset_size+j] = rS_data[cum2+k*size_schur+j];
1614:                 }
1615:               }
1616:             }
1617:           } else {
1618:             PetscInt k;
1619:             for (k=0;k<subset_size;k++) {
1620:               for (j=0;j<subset_size;j++) {
1621:                 work[k*subset_size+j] = rS_data[cum2+k*size_schur+j];
1622:               }
1623:             }
1624:           }
1625:           if (sub_schurs->change) {
1626:             Mat change_sub,SEj,T;

1628:             /* change basis */
1629:             KSPGetOperators(sub_schurs->change[i],&change_sub,NULL);
1630:             MatCreateSeqDense(PETSC_COMM_SELF,subset_size,subset_size,work,&SEj);
1631:             if (!sub_schurs->change_with_qr) { /* currently there's no support for PtAP with P SeqAIJ */
1632:               Mat T2;
1633:               MatTransposeMatMult(change_sub,SEj,MAT_INITIAL_MATRIX,1.0,&T2);
1634:               MatMatMult(T2,change_sub,MAT_INITIAL_MATRIX,1.0,&T);
1635:               MatDestroy(&T2);
1636:               MatConvert(T,MATSEQDENSE,MAT_INPLACE_MATRIX,&T);
1637:             } else {
1638:               MatPtAP(SEj,change_sub,MAT_INITIAL_MATRIX,1.0,&T);
1639:             }
1640:             MatCopy(T,SEj,SAME_NONZERO_PATTERN);
1641:             MatDestroy(&T);
1642:             /* set diagonal entry to a very large value to pick the basis we are eliminating as the first eigenvectors with adaptive selection */
1643:             MatZeroRowsColumnsIS(SEj,sub_schurs->change_primal_sub[i],1./PETSC_SMALL,NULL,NULL);
1644:             MatDestroy(&SEj);
1645:           }
1646:           PetscArraycpy(SEjinv_arr,work,subset_size*subset_size);
1647:           cum += subset_size;
1648:           cum2 += subset_size*(size_schur + 1);
1649:           SEjinv_arr += subset_size*subset_size;
1650:         }
1651:         MatDenseRestoreArrayRead(S_all_inv,&rS_data);
1652:         if (solver_S) {
1653:           if (schur_has_vertices) {
1654:             MatFactorRestoreSchurComplement(F,&S_all_inv,MAT_FACTOR_SCHUR_FACTORED);
1655:           } else {
1656:             MatFactorRestoreSchurComplement(F,&S_all_inv,MAT_FACTOR_SCHUR_INVERTED);
1657:           }
1658:         }
1659:         MatDestroy(&S_all_inv);
1660:       }
1661:       MatSeqAIJRestoreArray(sub_schurs->sum_S_Ej_tilda_all,&SEjinv_arr);

1663:       /* move back factors if needed */
1664:       if (schur_has_vertices) {
1665:         Mat      S_tmp;
1666:         PetscInt nd = 0;

1668:         if (!solver_S) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"This should not happen");
1669:         MatFactorGetSchurComplement(F,&S_tmp,NULL);
1670:         if (use_potr) {
1671:           PetscScalar *data;

1673:           MatDenseGetArray(S_tmp,&data);
1674:           PetscArrayzero(data,size_schur*size_schur);

1676:           if (S_lower_triangular) {
1677:             cum = 0;
1678:             for (i=0;i<size_active_schur;i++) {
1679:               PetscArraycpy(data+i*(size_schur+1),schur_factor+cum,size_active_schur-i);
1680:               cum += size_active_schur-i;
1681:             }
1682:           } else {
1683:             PetscArraycpy(data,schur_factor,size_schur*size_schur);
1684:           }
1685:           if (sub_schurs->is_dir) {
1686:             ISGetLocalSize(sub_schurs->is_dir,&nd);
1687:             for (i=0;i<nd;i++) {
1688:               data[(i+size_active_schur)*(size_schur+1)] = schur_factor[cum+i];
1689:             }
1690:           }
1691:           /* workaround: since I cannot modify the matrices used inside the solvers for the forward and backward substitutions,
1692:              set the diagonal entry of the Schur factor to a very large value */
1693:           for (i=size_active_schur+nd;i<size_schur;i++) {
1694:             data[i*(size_schur+1)] = infty;
1695:           }
1696:           MatDenseRestoreArray(S_tmp,&data);
1697:         } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Factor update not yet implemented for non SPD matrices");
1698:         MatFactorRestoreSchurComplement(F,&S_tmp,MAT_FACTOR_SCHUR_FACTORED);
1699:       }
1700:     } else if (factor_workaround) { /* we need to eliminate any unneeded coupling */
1701:       PetscScalar *data;
1702:       PetscInt    nd = 0;

1704:       if (sub_schurs->is_dir) { /* dirichlet dofs could have different scalings */
1705:         ISGetLocalSize(sub_schurs->is_dir,&nd);
1706:       }
1707:       MatFactorGetSchurComplement(F,&S_all,NULL);
1708:       MatDenseGetArray(S_all,&data);
1709:       for (i=0;i<size_active_schur;i++) {
1710:         PetscArrayzero(data+i*size_schur+size_active_schur,size_schur-size_active_schur);
1711:       }
1712:       for (i=size_active_schur+nd;i<size_schur;i++) {
1713:         PetscArrayzero(data+i*size_schur+size_active_schur,size_schur-size_active_schur);
1714:         data[i*(size_schur+1)] = infty;
1715:       }
1716:       MatDenseRestoreArray(S_all,&data);
1717:       MatFactorRestoreSchurComplement(F,&S_all,MAT_FACTOR_SCHUR_UNFACTORED);
1718:     }
1719:     PetscFree(work);
1720:     PetscFree(schur_factor);
1721:     VecDestroy(&Dall);
1722:   }
1723:   ISDestroy(&is_I_layer);
1724:   MatDestroy(&S_all);
1725:   MatDestroy(&A_BB);
1726:   MatDestroy(&A_IB);
1727:   MatDestroy(&A_BI);
1728:   MatDestroy(&F);

1730:   PetscMalloc1(sub_schurs->n_subs,&nnz);
1731:   for (i=0;i<sub_schurs->n_subs;i++) {
1732:     ISGetLocalSize(sub_schurs->is_subs[i],&nnz[i]);
1733:   }
1734:   ISCreateGeneral(PETSC_COMM_SELF,sub_schurs->n_subs,nnz,PETSC_OWN_POINTER,&is_I_layer);
1735:   MatSetVariableBlockSizes(sub_schurs->S_Ej_all,sub_schurs->n_subs,nnz);
1736:   MatAssemblyBegin(sub_schurs->S_Ej_all,MAT_FINAL_ASSEMBLY);
1737:   MatAssemblyEnd(sub_schurs->S_Ej_all,MAT_FINAL_ASSEMBLY);
1738:   if (compute_Stilda) {
1739:     MatSetVariableBlockSizes(sub_schurs->sum_S_Ej_tilda_all,sub_schurs->n_subs,nnz);
1740:     MatAssemblyBegin(sub_schurs->sum_S_Ej_tilda_all,MAT_FINAL_ASSEMBLY);
1741:     MatAssemblyEnd(sub_schurs->sum_S_Ej_tilda_all,MAT_FINAL_ASSEMBLY);
1742:     if (deluxe) {
1743:       MatSetVariableBlockSizes(sub_schurs->sum_S_Ej_inv_all,sub_schurs->n_subs,nnz);
1744:       MatAssemblyBegin(sub_schurs->sum_S_Ej_inv_all,MAT_FINAL_ASSEMBLY);
1745:       MatAssemblyEnd(sub_schurs->sum_S_Ej_inv_all,MAT_FINAL_ASSEMBLY);
1746:     }
1747:   }
1748:   ISDestroy(&is_I_layer);

1750:   /* Get local part of (\sum_j S_Ej) */
1751:   if (!sub_schurs->sum_S_Ej_all) {
1752:     MatDuplicate(sub_schurs->S_Ej_all,MAT_DO_NOT_COPY_VALUES,&sub_schurs->sum_S_Ej_all);
1753:   }
1754:   VecSet(gstash,0.0);
1755:   MatSeqAIJGetArray(sub_schurs->S_Ej_all,&stasharray);
1756:   VecPlaceArray(lstash,stasharray);
1757:   VecScatterBegin(sstash,lstash,gstash,ADD_VALUES,SCATTER_FORWARD);
1758:   VecScatterEnd(sstash,lstash,gstash,ADD_VALUES,SCATTER_FORWARD);
1759:   MatSeqAIJRestoreArray(sub_schurs->S_Ej_all,&stasharray);
1760:   VecResetArray(lstash);
1761:   MatSeqAIJGetArray(sub_schurs->sum_S_Ej_all,&stasharray);
1762:   VecPlaceArray(lstash,stasharray);
1763:   VecScatterBegin(sstash,gstash,lstash,INSERT_VALUES,SCATTER_REVERSE);
1764:   VecScatterEnd(sstash,gstash,lstash,INSERT_VALUES,SCATTER_REVERSE);
1765:   MatSeqAIJRestoreArray(sub_schurs->sum_S_Ej_all,&stasharray);
1766:   VecResetArray(lstash);

1768:   /* Get local part of (\sum_j S^-1_Ej) (\sum_j St^-1_Ej) */
1769:   if (compute_Stilda) {
1770:     VecSet(gstash,0.0);
1771:     MatSeqAIJGetArray(sub_schurs->sum_S_Ej_tilda_all,&stasharray);
1772:     VecPlaceArray(lstash,stasharray);
1773:     VecScatterBegin(sstash,lstash,gstash,ADD_VALUES,SCATTER_FORWARD);
1774:     VecScatterEnd(sstash,lstash,gstash,ADD_VALUES,SCATTER_FORWARD);
1775:     VecScatterBegin(sstash,gstash,lstash,INSERT_VALUES,SCATTER_REVERSE);
1776:     VecScatterEnd(sstash,gstash,lstash,INSERT_VALUES,SCATTER_REVERSE);
1777:     MatSeqAIJRestoreArray(sub_schurs->sum_S_Ej_tilda_all,&stasharray);
1778:     VecResetArray(lstash);
1779:     if (deluxe) {
1780:       VecSet(gstash,0.0);
1781:       MatSeqAIJGetArray(sub_schurs->sum_S_Ej_inv_all,&stasharray);
1782:       VecPlaceArray(lstash,stasharray);
1783:       VecScatterBegin(sstash,lstash,gstash,ADD_VALUES,SCATTER_FORWARD);
1784:       VecScatterEnd(sstash,lstash,gstash,ADD_VALUES,SCATTER_FORWARD);
1785:       VecScatterBegin(sstash,gstash,lstash,INSERT_VALUES,SCATTER_REVERSE);
1786:       VecScatterEnd(sstash,gstash,lstash,INSERT_VALUES,SCATTER_REVERSE);
1787:       MatSeqAIJRestoreArray(sub_schurs->sum_S_Ej_inv_all,&stasharray);
1788:       VecResetArray(lstash);
1789:     } else {
1790:       PetscScalar *array;
1791:       PetscInt    cum;

1793:       MatSeqAIJGetArray(sub_schurs->sum_S_Ej_tilda_all,&array);
1794:       cum = 0;
1795:       for (i=0;i<sub_schurs->n_subs;i++) {
1796:         ISGetLocalSize(sub_schurs->is_subs[i],&subset_size);
1797:         PetscBLASIntCast(subset_size,&B_N);
1798:         PetscFPTrapPush(PETSC_FP_TRAP_OFF);
1799:         if (use_potr) {
1800:           PetscStackCallBLAS("LAPACKpotrf",LAPACKpotrf_("L",&B_N,array+cum,&B_N,&B_ierr));
1801:           if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRF Lapack routine %d",(int)B_ierr);
1802:           PetscStackCallBLAS("LAPACKpotri",LAPACKpotri_("L",&B_N,array+cum,&B_N,&B_ierr));
1803:           if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRI Lapack routine %d",(int)B_ierr);
1804:         } else if (use_sytr) {
1805:           PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_("L",&B_N,array+cum,&B_N,pivots,Bwork,&B_lwork,&B_ierr));
1806:           if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRF Lapack routine %d",(int)B_ierr);
1807:           PetscStackCallBLAS("LAPACKsytri",LAPACKsytri_("L",&B_N,array+cum,&B_N,pivots,Bwork,&B_ierr));
1808:           if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRI Lapack routine %d",(int)B_ierr);
1809:         } else {
1810:           PetscStackCallBLAS("LAPACKgetrf",LAPACKgetrf_(&B_N,&B_N,array+cum,&B_N,pivots,&B_ierr));
1811:           if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRF Lapack routine %d",(int)B_ierr);
1812:           PetscStackCallBLAS("LAPACKgetri",LAPACKgetri_(&B_N,array+cum,&B_N,pivots,Bwork,&B_lwork,&B_ierr));
1813:           if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRI Lapack routine %d",(int)B_ierr);
1814:         }
1815:         PetscLogFlops(1.0*subset_size*subset_size*subset_size);
1816:         PetscFPTrapPop();
1817:         cum += subset_size*subset_size;
1818:       }
1819:       MatSeqAIJRestoreArray(sub_schurs->sum_S_Ej_tilda_all,&array);
1820:       PetscObjectReference((PetscObject)sub_schurs->sum_S_Ej_all);
1821:       MatDestroy(&sub_schurs->sum_S_Ej_inv_all);
1822:       sub_schurs->sum_S_Ej_inv_all = sub_schurs->sum_S_Ej_all;
1823:     }
1824:   }
1825:   VecDestroy(&lstash);
1826:   VecDestroy(&gstash);
1827:   VecScatterDestroy(&sstash);

1829:   if (matl_dbg_viewer) {
1830:     PetscInt cum;

1832:     if (sub_schurs->S_Ej_all) {
1833:       PetscObjectSetName((PetscObject)sub_schurs->S_Ej_all,"SE");
1834:       MatView(sub_schurs->S_Ej_all,matl_dbg_viewer);
1835:     }
1836:     if (sub_schurs->sum_S_Ej_all) {
1837:       PetscObjectSetName((PetscObject)sub_schurs->sum_S_Ej_all,"SSE");
1838:       MatView(sub_schurs->sum_S_Ej_all,matl_dbg_viewer);
1839:     }
1840:     if (sub_schurs->sum_S_Ej_inv_all) {
1841:       PetscObjectSetName((PetscObject)sub_schurs->sum_S_Ej_inv_all,"SSEm");
1842:       MatView(sub_schurs->sum_S_Ej_inv_all,matl_dbg_viewer);
1843:     }
1844:     if (sub_schurs->sum_S_Ej_tilda_all) {
1845:       PetscObjectSetName((PetscObject)sub_schurs->sum_S_Ej_tilda_all,"SSEt");
1846:       MatView(sub_schurs->sum_S_Ej_tilda_all,matl_dbg_viewer);
1847:     }
1848:     for (i=0,cum=0;i<sub_schurs->n_subs;i++) {
1849:       IS   is;
1850:       char name[16];

1852:       PetscSNPrintf(name,sizeof(name),"IE%D",i);
1853:       ISGetLocalSize(sub_schurs->is_subs[i],&subset_size);
1854:       ISCreateStride(PETSC_COMM_SELF,subset_size,cum,1,&is);
1855:       PetscObjectSetName((PetscObject)is,name);
1856:       ISView(is,matl_dbg_viewer);
1857:       ISDestroy(&is);
1858:       cum += subset_size;
1859:     }
1860:   }

1862:   /* free workspace */
1863:   PetscViewerDestroy(&matl_dbg_viewer);
1864:   PetscFree2(Bwork,pivots);
1865:   PetscCommDestroy(&comm_n);
1866:   return(0);
1867: }

1869: PetscErrorCode PCBDDCSubSchursInit(PCBDDCSubSchurs sub_schurs, const char* prefix, IS is_I, IS is_B, PCBDDCGraph graph, ISLocalToGlobalMapping BtoNmap, PetscBool copycc)
1870: {
1871:   IS              *faces,*edges,*all_cc,vertices;
1872:   PetscInt        i,n_faces,n_edges,n_all_cc;
1873:   PetscBool       is_sorted,ispardiso,ismumps;
1874:   PetscErrorCode  ierr;

1877:   ISSorted(is_I,&is_sorted);
1878:   if (!is_sorted) SETERRQ(PetscObjectComm((PetscObject)is_I),PETSC_ERR_PLIB,"IS for I dofs should be shorted");
1879:   ISSorted(is_B,&is_sorted);
1880:   if (!is_sorted) SETERRQ(PetscObjectComm((PetscObject)is_B),PETSC_ERR_PLIB,"IS for B dofs should be shorted");

1882:   /* reset any previous data */
1883:   PCBDDCSubSchursReset(sub_schurs);

1885:   /* get index sets for faces and edges (already sorted by global ordering) */
1886:   PCBDDCGraphGetCandidatesIS(graph,&n_faces,&faces,&n_edges,&edges,&vertices);
1887:   n_all_cc = n_faces+n_edges;
1888:   PetscBTCreate(n_all_cc,&sub_schurs->is_edge);
1889:   PetscMalloc1(n_all_cc,&all_cc);
1890:   for (i=0;i<n_faces;i++) {
1891:     if (copycc) {
1892:       ISDuplicate(faces[i],&all_cc[i]);
1893:     } else {
1894:       PetscObjectReference((PetscObject)faces[i]);
1895:       all_cc[i] = faces[i];
1896:     }
1897:   }
1898:   for (i=0;i<n_edges;i++) {
1899:     if (copycc) {
1900:       ISDuplicate(edges[i],&all_cc[n_faces+i]);
1901:     } else {
1902:       PetscObjectReference((PetscObject)edges[i]);
1903:       all_cc[n_faces+i] = edges[i];
1904:     }
1905:     PetscBTSet(sub_schurs->is_edge,n_faces+i);
1906:   }
1907:   PetscObjectReference((PetscObject)vertices);
1908:   sub_schurs->is_vertices = vertices;
1909:   PCBDDCGraphRestoreCandidatesIS(graph,&n_faces,&faces,&n_edges,&edges,&vertices);
1910:   sub_schurs->is_dir = NULL;
1911:   PCBDDCGraphGetDirichletDofsB(graph,&sub_schurs->is_dir);

1913:   /* Determine if MatFactor can be used */
1914:   PetscStrallocpy(prefix,&sub_schurs->prefix);
1915: #if defined(PETSC_HAVE_MUMPS)
1916:   PetscStrncpy(sub_schurs->mat_solver_type,MATSOLVERMUMPS,64);
1917: #elif defined(PETSC_HAVE_MKL_PARDISO)
1918:   PetscStrncpy(sub_schurs->mat_solver_type,MATSOLVERMKL_PARDISO,64);
1919: #else
1920:   PetscStrncpy(sub_schurs->mat_solver_type,MATSOLVERPETSC,64);
1921: #endif
1922: #if defined(PETSC_USE_COMPLEX)
1923:   sub_schurs->is_hermitian  = PETSC_FALSE; /* Hermitian Cholesky is not supported by PETSc and external packages */
1924: #else
1925:   sub_schurs->is_hermitian  = PETSC_TRUE;
1926: #endif
1927:   sub_schurs->is_posdef     = PETSC_TRUE;
1928:   sub_schurs->is_symmetric  = PETSC_TRUE;
1929:   sub_schurs->debug         = PETSC_FALSE;
1930:   sub_schurs->restrict_comm = PETSC_FALSE;
1931:   PetscOptionsBegin(PetscObjectComm((PetscObject)graph->l2gmap),sub_schurs->prefix,"BDDC sub_schurs options","PC");
1932:   PetscOptionsString("-sub_schurs_mat_solver_type","Specific direct solver to use",NULL,sub_schurs->mat_solver_type,sub_schurs->mat_solver_type,64,NULL);
1933:   PetscOptionsBool("-sub_schurs_symmetric","Symmetric problem",NULL,sub_schurs->is_symmetric,&sub_schurs->is_symmetric,NULL);
1934:   PetscOptionsBool("-sub_schurs_hermitian","Hermitian problem",NULL,sub_schurs->is_hermitian,&sub_schurs->is_hermitian,NULL);
1935:   PetscOptionsBool("-sub_schurs_posdef","Positive definite problem",NULL,sub_schurs->is_posdef,&sub_schurs->is_posdef,NULL);
1936:   PetscOptionsBool("-sub_schurs_restrictcomm","Restrict communicator on active processes only",NULL,sub_schurs->restrict_comm,&sub_schurs->restrict_comm,NULL);
1937:   PetscOptionsBool("-sub_schurs_debug","Debug output",NULL,sub_schurs->debug,&sub_schurs->debug,NULL);
1938:   PetscOptionsEnd();
1939:   PetscStrcmp(sub_schurs->mat_solver_type,MATSOLVERMUMPS,&ismumps);
1940:   PetscStrcmp(sub_schurs->mat_solver_type,MATSOLVERMKL_PARDISO,&ispardiso);
1941:   sub_schurs->schur_explicit = (PetscBool)(ispardiso || ismumps);

1943:   /* for reals, symmetric and hermitian are synonims */
1944: #if !defined(PETSC_USE_COMPLEX)
1945:   sub_schurs->is_symmetric = (PetscBool)(sub_schurs->is_symmetric && sub_schurs->is_hermitian);
1946:   sub_schurs->is_hermitian = sub_schurs->is_symmetric;
1947: #endif

1949:   PetscObjectReference((PetscObject)is_I);
1950:   sub_schurs->is_I = is_I;
1951:   PetscObjectReference((PetscObject)is_B);
1952:   sub_schurs->is_B = is_B;
1953:   PetscObjectReference((PetscObject)graph->l2gmap);
1954:   sub_schurs->l2gmap = graph->l2gmap;
1955:   PetscObjectReference((PetscObject)BtoNmap);
1956:   sub_schurs->BtoNmap = BtoNmap;
1957:   sub_schurs->n_subs = n_all_cc;
1958:   sub_schurs->is_subs = all_cc;
1959:   sub_schurs->S_Ej_all = NULL;
1960:   sub_schurs->sum_S_Ej_all = NULL;
1961:   sub_schurs->sum_S_Ej_inv_all = NULL;
1962:   sub_schurs->sum_S_Ej_tilda_all = NULL;
1963:   sub_schurs->is_Ej_all = NULL;
1964:   return(0);
1965: }

1967: PetscErrorCode PCBDDCSubSchursCreate(PCBDDCSubSchurs *sub_schurs)
1968: {
1969:   PCBDDCSubSchurs schurs_ctx;
1970:   PetscErrorCode  ierr;

1973:   PetscNew(&schurs_ctx);
1974:   schurs_ctx->n_subs = 0;
1975:   *sub_schurs = schurs_ctx;
1976:   return(0);
1977: }

1979: PetscErrorCode PCBDDCSubSchursReset(PCBDDCSubSchurs sub_schurs)
1980: {
1981:   PetscInt       i;

1985:   if (!sub_schurs) return(0);
1986:   PetscFree(sub_schurs->prefix);
1987:   MatDestroy(&sub_schurs->A);
1988:   MatDestroy(&sub_schurs->S);
1989:   ISDestroy(&sub_schurs->is_I);
1990:   ISDestroy(&sub_schurs->is_B);
1991:   ISLocalToGlobalMappingDestroy(&sub_schurs->l2gmap);
1992:   ISLocalToGlobalMappingDestroy(&sub_schurs->BtoNmap);
1993:   MatDestroy(&sub_schurs->S_Ej_all);
1994:   MatDestroy(&sub_schurs->sum_S_Ej_all);
1995:   MatDestroy(&sub_schurs->sum_S_Ej_inv_all);
1996:   MatDestroy(&sub_schurs->sum_S_Ej_tilda_all);
1997:   ISDestroy(&sub_schurs->is_Ej_all);
1998:   ISDestroy(&sub_schurs->is_vertices);
1999:   ISDestroy(&sub_schurs->is_dir);
2000:   PetscBTDestroy(&sub_schurs->is_edge);
2001:   for (i=0;i<sub_schurs->n_subs;i++) {
2002:     ISDestroy(&sub_schurs->is_subs[i]);
2003:   }
2004:   if (sub_schurs->n_subs) {
2005:     PetscFree(sub_schurs->is_subs);
2006:   }
2007:   if (sub_schurs->reuse_solver) {
2008:     PCBDDCReuseSolversReset(sub_schurs->reuse_solver);
2009:   }
2010:   PetscFree(sub_schurs->reuse_solver);
2011:   if (sub_schurs->change) {
2012:     for (i=0;i<sub_schurs->n_subs;i++) {
2013:       KSPDestroy(&sub_schurs->change[i]);
2014:       ISDestroy(&sub_schurs->change_primal_sub[i]);
2015:     }
2016:   }
2017:   PetscFree(sub_schurs->change);
2018:   PetscFree(sub_schurs->change_primal_sub);
2019:   sub_schurs->n_subs = 0;
2020:   return(0);
2021: }

2023: PetscErrorCode PCBDDCSubSchursDestroy(PCBDDCSubSchurs* sub_schurs)
2024: {

2028:   PCBDDCSubSchursReset(*sub_schurs);
2029:   PetscFree(*sub_schurs);
2030:   return(0);
2031: }

2033: PETSC_STATIC_INLINE PetscErrorCode PCBDDCAdjGetNextLayer_Private(PetscInt* queue_tip,PetscInt n_prev,PetscBT touched,PetscInt* xadj,PetscInt* adjncy,PetscInt* n_added)
2034: {
2035:   PetscInt       i,j,n;

2039:   n = 0;
2040:   for (i=-n_prev;i<0;i++) {
2041:     PetscInt start_dof = queue_tip[i];
2042:     for (j=xadj[start_dof];j<xadj[start_dof+1];j++) {
2043:       PetscInt dof = adjncy[j];
2044:       if (!PetscBTLookup(touched,dof)) {
2045:         PetscBTSet(touched,dof);
2046:         queue_tip[n] = dof;
2047:         n++;
2048:       }
2049:     }
2050:   }
2051:   *n_added = n;
2052:   return(0);
2053: }