Actual source code: bddcschurs.c
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,&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,&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;
422: PetscBool flg;
425: MatDestroy(&sub_schurs->A);
426: MatDestroy(&sub_schurs->S);
427: if (Ain) {
428: PetscObjectReference((PetscObject)Ain);
429: sub_schurs->A = Ain;
430: }
432: PetscObjectReference((PetscObject)Sin);
433: sub_schurs->S = Sin;
434: if (sub_schurs->schur_explicit) {
435: sub_schurs->schur_explicit = (PetscBool)(!!sub_schurs->A);
436: }
438: /* preliminary checks */
439: 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");
441: if (benign_trick) sub_schurs->is_posdef = PETSC_FALSE;
443: /* debug (MATLAB) */
444: if (sub_schurs->debug) {
445: PetscMPIInt size,rank;
446: PetscInt nr,*print_schurs_ranks,print_schurs = PETSC_FALSE;
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: }
470: /* restrict work on active processes */
471: if (sub_schurs->restrict_comm) {
472: PetscSubcomm subcomm;
473: PetscMPIInt color,rank;
475: color = 0;
476: if (!sub_schurs->n_subs) color = 1; /* this can happen if we are in a multilevel case or if the subdomain is disconnected */
477: MPI_Comm_rank(PetscObjectComm((PetscObject)sub_schurs->l2gmap),&rank);
478: PetscSubcommCreate(PetscObjectComm((PetscObject)sub_schurs->l2gmap),&subcomm);
479: PetscSubcommSetNumber(subcomm,2);
480: PetscSubcommSetTypeGeneral(subcomm,color,rank);
481: PetscCommDuplicate(PetscSubcommChild(subcomm),&comm_n,NULL);
482: PetscSubcommDestroy(&subcomm);
483: if (!sub_schurs->n_subs) {
484: PetscCommDestroy(&comm_n);
485: return(0);
486: }
487: } else {
488: PetscCommDuplicate(PetscObjectComm((PetscObject)sub_schurs->l2gmap),&comm_n,NULL);
489: }
491: /* get Schur complement matrices */
492: if (!sub_schurs->schur_explicit) {
493: Mat tA_IB,tA_BI,tA_BB;
494: PetscBool isseqsbaij;
495: MatSchurComplementGetSubMatrices(sub_schurs->S,&A_II,NULL,&tA_IB,&tA_BI,&tA_BB);
496: PetscObjectTypeCompare((PetscObject)tA_BB,MATSEQSBAIJ,&isseqsbaij);
497: if (isseqsbaij) {
498: MatConvert(tA_BB,MATSEQAIJ,MAT_INITIAL_MATRIX,&A_BB);
499: MatConvert(tA_IB,MATSEQAIJ,MAT_INITIAL_MATRIX,&A_IB);
500: MatConvert(tA_BI,MATSEQAIJ,MAT_INITIAL_MATRIX,&A_BI);
501: } else {
502: PetscObjectReference((PetscObject)tA_BB);
503: A_BB = tA_BB;
504: PetscObjectReference((PetscObject)tA_IB);
505: A_IB = tA_IB;
506: PetscObjectReference((PetscObject)tA_BI);
507: A_BI = tA_BI;
508: }
509: } else {
510: A_II = NULL;
511: A_IB = NULL;
512: A_BI = NULL;
513: A_BB = NULL;
514: }
515: S_all = NULL;
517: /* determine interior problems */
518: ISGetLocalSize(sub_schurs->is_I,&i);
519: if (nlayers >= 0 && i) { /* Interior problems can be different from the original one */
520: PetscBT touched;
521: const PetscInt* idx_B;
522: PetscInt n_I,n_B,n_local_dofs,n_prev_added,j,layer,*local_numbering;
524: if (!xadj) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Cannot request layering without adjacency");
525: /* get sizes */
526: ISGetLocalSize(sub_schurs->is_I,&n_I);
527: ISGetLocalSize(sub_schurs->is_B,&n_B);
529: PetscMalloc1(n_I+n_B,&local_numbering);
530: PetscBTCreate(n_I+n_B,&touched);
531: PetscBTMemzero(n_I+n_B,touched);
533: /* all boundary dofs must be skipped when adding layers */
534: ISGetIndices(sub_schurs->is_B,&idx_B);
535: for (j=0;j<n_B;j++) {
536: PetscBTSet(touched,idx_B[j]);
537: }
538: PetscArraycpy(local_numbering,idx_B,n_B);
539: ISRestoreIndices(sub_schurs->is_B,&idx_B);
541: /* add prescribed number of layers of dofs */
542: n_local_dofs = n_B;
543: n_prev_added = n_B;
544: for (layer=0;layer<nlayers;layer++) {
545: PetscInt n_added;
546: if (n_local_dofs == n_I+n_B) break;
547: 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);
548: PCBDDCAdjGetNextLayer_Private(local_numbering+n_local_dofs,n_prev_added,touched,xadj,adjncy,&n_added);
549: n_prev_added = n_added;
550: n_local_dofs += n_added;
551: if (!n_added) break;
552: }
553: PetscBTDestroy(&touched);
555: /* IS for I layer dofs in original numbering */
556: ISCreateGeneral(PetscObjectComm((PetscObject)sub_schurs->is_I),n_local_dofs-n_B,local_numbering+n_B,PETSC_COPY_VALUES,&is_I_layer);
557: PetscFree(local_numbering);
558: ISSort(is_I_layer);
559: /* IS for I layer dofs in I numbering */
560: if (!sub_schurs->schur_explicit) {
561: ISLocalToGlobalMapping ItoNmap;
562: ISLocalToGlobalMappingCreateIS(sub_schurs->is_I,&ItoNmap);
563: ISGlobalToLocalMappingApplyIS(ItoNmap,IS_GTOLM_DROP,is_I_layer,&is_I);
564: ISLocalToGlobalMappingDestroy(&ItoNmap);
566: /* II block */
567: MatCreateSubMatrix(A_II,is_I,is_I,MAT_INITIAL_MATRIX,&AE_II);
568: }
569: } else {
570: PetscInt n_I;
572: /* IS for I dofs in original numbering */
573: PetscObjectReference((PetscObject)sub_schurs->is_I);
574: is_I_layer = sub_schurs->is_I;
576: /* IS for I dofs in I numbering (strided 1) */
577: if (!sub_schurs->schur_explicit) {
578: ISGetSize(sub_schurs->is_I,&n_I);
579: ISCreateStride(PetscObjectComm((PetscObject)sub_schurs->is_I),n_I,0,1,&is_I);
581: /* II block is the same */
582: PetscObjectReference((PetscObject)A_II);
583: AE_II = A_II;
584: }
585: }
587: /* Get info on subset sizes and sum of all subsets sizes */
588: max_subset_size = 0;
589: local_size = 0;
590: for (i=0;i<sub_schurs->n_subs;i++) {
591: ISGetLocalSize(sub_schurs->is_subs[i],&subset_size);
592: max_subset_size = PetscMax(subset_size,max_subset_size);
593: local_size += subset_size;
594: }
596: /* Work arrays for local indices */
597: extra = 0;
598: ISGetLocalSize(sub_schurs->is_B,&n_B);
599: if (sub_schurs->schur_explicit && is_I_layer) {
600: ISGetLocalSize(is_I_layer,&extra);
601: }
602: PetscMalloc1(n_B+extra,&all_local_idx_N);
603: if (extra) {
604: const PetscInt *idxs;
605: ISGetIndices(is_I_layer,&idxs);
606: PetscArraycpy(all_local_idx_N,idxs,extra);
607: ISRestoreIndices(is_I_layer,&idxs);
608: }
609: PetscMalloc1(sub_schurs->n_subs,&auxnum1);
610: PetscMalloc1(sub_schurs->n_subs,&auxnum2);
612: /* Get local indices in local numbering */
613: local_size = 0;
614: local_stash_size = 0;
615: for (i=0;i<sub_schurs->n_subs;i++) {
616: const PetscInt *idxs;
618: ISGetLocalSize(sub_schurs->is_subs[i],&subset_size);
619: ISGetIndices(sub_schurs->is_subs[i],&idxs);
620: /* start (smallest in global ordering) and multiplicity */
621: auxnum1[i] = idxs[0];
622: auxnum2[i] = subset_size*subset_size;
623: /* subset indices in local numbering */
624: PetscArraycpy(all_local_idx_N+local_size+extra,idxs,subset_size);
625: ISRestoreIndices(sub_schurs->is_subs[i],&idxs);
626: local_size += subset_size;
627: local_stash_size += subset_size*subset_size;
628: }
630: /* allocate extra workspace needed only for GETRI or SYTRF */
631: use_potr = use_sytr = PETSC_FALSE;
632: if (benign_trick || (sub_schurs->is_hermitian && sub_schurs->is_posdef)) {
633: use_potr = PETSC_TRUE;
634: } else if (sub_schurs->is_symmetric) {
635: use_sytr = PETSC_TRUE;
636: }
637: if (local_size && !use_potr) {
638: PetscScalar lwork,dummyscalar = 0.;
639: PetscBLASInt dummyint = 0;
641: B_lwork = -1;
642: PetscBLASIntCast(local_size,&B_N);
643: PetscFPTrapPush(PETSC_FP_TRAP_OFF);
644: if (use_sytr) {
645: PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_("L",&B_N,&dummyscalar,&B_N,&dummyint,&lwork,&B_lwork,&B_ierr));
646: if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in query to SYTRF Lapack routine %d",(int)B_ierr);
647: } else {
648: PetscStackCallBLAS("LAPACKgetri",LAPACKgetri_(&B_N,&dummyscalar,&B_N,&dummyint,&lwork,&B_lwork,&B_ierr));
649: if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in query to GETRI Lapack routine %d",(int)B_ierr);
650: }
651: PetscFPTrapPop();
652: PetscBLASIntCast((PetscInt)PetscRealPart(lwork),&B_lwork);
653: PetscMalloc2(B_lwork,&Bwork,B_N,&pivots);
654: } else {
655: Bwork = NULL;
656: pivots = NULL;
657: }
659: /* prepare data for summing up properly schurs on subsets */
660: ISCreateGeneral(comm_n,sub_schurs->n_subs,auxnum1,PETSC_OWN_POINTER,&all_subsets_n);
661: ISLocalToGlobalMappingApplyIS(sub_schurs->l2gmap,all_subsets_n,&all_subsets);
662: ISDestroy(&all_subsets_n);
663: ISCreateGeneral(comm_n,sub_schurs->n_subs,auxnum2,PETSC_OWN_POINTER,&all_subsets_mult);
664: ISRenumber(all_subsets,all_subsets_mult,&global_size,&all_subsets_n);
665: ISDestroy(&all_subsets);
666: ISDestroy(&all_subsets_mult);
667: ISGetLocalSize(all_subsets_n,&i);
668: if (i != local_stash_size) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Invalid size of new subset! %D != %D",i,local_stash_size);
669: VecCreateSeqWithArray(PETSC_COMM_SELF,1,local_stash_size,NULL,&lstash);
670: VecCreateMPI(comm_n,PETSC_DECIDE,global_size,&gstash);
671: VecScatterCreate(lstash,NULL,gstash,all_subsets_n,&sstash);
672: ISDestroy(&all_subsets_n);
674: /* subset indices in local boundary numbering */
675: if (!sub_schurs->is_Ej_all) {
676: PetscInt *all_local_idx_B;
678: PetscMalloc1(local_size,&all_local_idx_B);
679: ISGlobalToLocalMappingApply(sub_schurs->BtoNmap,IS_GTOLM_DROP,local_size,all_local_idx_N+extra,&subset_size,all_local_idx_B);
680: if (subset_size != local_size) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Error in sub_schurs serial (BtoNmap)! %D != %D",subset_size,local_size);
681: ISCreateGeneral(PETSC_COMM_SELF,local_size,all_local_idx_B,PETSC_OWN_POINTER,&sub_schurs->is_Ej_all);
682: }
684: if (change) {
685: ISLocalToGlobalMapping BtoS;
686: IS change_primal_B;
687: IS change_primal_all;
689: if (sub_schurs->change_primal_sub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"This should not happen");
690: if (sub_schurs->change) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"This should not happen");
691: PetscMalloc1(sub_schurs->n_subs,&sub_schurs->change_primal_sub);
692: for (i=0;i<sub_schurs->n_subs;i++) {
693: ISLocalToGlobalMapping NtoS;
694: ISLocalToGlobalMappingCreateIS(sub_schurs->is_subs[i],&NtoS);
695: ISGlobalToLocalMappingApplyIS(NtoS,IS_GTOLM_DROP,change_primal,&sub_schurs->change_primal_sub[i]);
696: ISLocalToGlobalMappingDestroy(&NtoS);
697: }
698: ISGlobalToLocalMappingApplyIS(sub_schurs->BtoNmap,IS_GTOLM_DROP,change_primal,&change_primal_B);
699: ISLocalToGlobalMappingCreateIS(sub_schurs->is_Ej_all,&BtoS);
700: ISGlobalToLocalMappingApplyIS(BtoS,IS_GTOLM_DROP,change_primal_B,&change_primal_all);
701: ISLocalToGlobalMappingDestroy(&BtoS);
702: ISDestroy(&change_primal_B);
703: PetscMalloc1(sub_schurs->n_subs,&sub_schurs->change);
704: for (i=0;i<sub_schurs->n_subs;i++) {
705: Mat change_sub;
707: ISGetLocalSize(sub_schurs->is_subs[i],&subset_size);
708: KSPCreate(PETSC_COMM_SELF,&sub_schurs->change[i]);
709: KSPSetType(sub_schurs->change[i],KSPPREONLY);
710: if (!sub_schurs->change_with_qr) {
711: MatCreateSubMatrix(change,sub_schurs->is_subs[i],sub_schurs->is_subs[i],MAT_INITIAL_MATRIX,&change_sub);
712: } else {
713: Mat change_subt;
714: MatCreateSubMatrix(change,sub_schurs->is_subs[i],sub_schurs->is_subs[i],MAT_INITIAL_MATRIX,&change_subt);
715: MatConvert(change_subt,MATSEQDENSE,MAT_INITIAL_MATRIX,&change_sub);
716: MatDestroy(&change_subt);
717: }
718: KSPSetOperators(sub_schurs->change[i],change_sub,change_sub);
719: MatDestroy(&change_sub);
720: KSPSetOptionsPrefix(sub_schurs->change[i],sub_schurs->prefix);
721: KSPAppendOptionsPrefix(sub_schurs->change[i],"sub_schurs_change_");
722: }
723: ISDestroy(&change_primal_all);
724: }
726: /* Local matrix of all local Schur on subsets (transposed) */
727: if (!sub_schurs->S_Ej_all) {
728: Mat T;
729: PetscScalar *v;
730: PetscInt *ii,*jj;
731: PetscInt cum,i,j,k;
733: /* MatSeqAIJSetPreallocation + MatSetValues is slow for these kind of matrices (may have large blocks)
734: Allocate properly a representative matrix and duplicate */
735: PetscMalloc3(local_size+1,&ii,local_stash_size,&jj,local_stash_size,&v);
736: ii[0] = 0;
737: cum = 0;
738: for (i=0;i<sub_schurs->n_subs;i++) {
739: ISGetLocalSize(sub_schurs->is_subs[i],&subset_size);
740: for (j=0;j<subset_size;j++) {
741: const PetscInt row = cum+j;
742: PetscInt col = cum;
744: ii[row+1] = ii[row] + subset_size;
745: for (k=ii[row];k<ii[row+1];k++) {
746: jj[k] = col;
747: col++;
748: }
749: }
750: cum += subset_size;
751: }
752: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,local_size,local_size,ii,jj,v,&T);
753: MatDuplicate(T,MAT_DO_NOT_COPY_VALUES,&sub_schurs->S_Ej_all);
754: MatDestroy(&T);
755: PetscFree3(ii,jj,v);
756: }
757: /* matrices for deluxe scaling and adaptive selection */
758: if (compute_Stilda) {
759: if (!sub_schurs->sum_S_Ej_tilda_all) {
760: MatDuplicate(sub_schurs->S_Ej_all,MAT_DO_NOT_COPY_VALUES,&sub_schurs->sum_S_Ej_tilda_all);
761: }
762: if (!sub_schurs->sum_S_Ej_inv_all && deluxe) {
763: MatDuplicate(sub_schurs->S_Ej_all,MAT_DO_NOT_COPY_VALUES,&sub_schurs->sum_S_Ej_inv_all);
764: }
765: }
767: /* Compute Schur complements explicitly */
768: F = NULL;
769: if (!sub_schurs->schur_explicit) {
770: /* this code branch is used when MatFactor with Schur complement support is not present or when explicitly requested;
771: it is not efficient, unless the economic version of the scaling is used */
772: Mat S_Ej_expl;
773: PetscScalar *work;
774: PetscInt j,*dummy_idx;
775: PetscBool Sdense;
777: PetscMalloc2(max_subset_size,&dummy_idx,max_subset_size*max_subset_size,&work);
778: local_size = 0;
779: for (i=0;i<sub_schurs->n_subs;i++) {
780: IS is_subset_B;
781: Mat AE_EE,AE_IE,AE_EI,S_Ej;
783: /* subsets in original and boundary numbering */
784: ISGlobalToLocalMappingApplyIS(sub_schurs->BtoNmap,IS_GTOLM_DROP,sub_schurs->is_subs[i],&is_subset_B);
785: /* EE block */
786: MatCreateSubMatrix(A_BB,is_subset_B,is_subset_B,MAT_INITIAL_MATRIX,&AE_EE);
787: /* IE block */
788: MatCreateSubMatrix(A_IB,is_I,is_subset_B,MAT_INITIAL_MATRIX,&AE_IE);
789: /* EI block */
790: if (sub_schurs->is_symmetric) {
791: MatCreateTranspose(AE_IE,&AE_EI);
792: } else if (sub_schurs->is_hermitian) {
793: MatCreateHermitianTranspose(AE_IE,&AE_EI);
794: } else {
795: MatCreateSubMatrix(A_BI,is_subset_B,is_I,MAT_INITIAL_MATRIX,&AE_EI);
796: }
797: ISDestroy(&is_subset_B);
798: MatCreateSchurComplement(AE_II,AE_II,AE_IE,AE_EI,AE_EE,&S_Ej);
799: MatDestroy(&AE_EE);
800: MatDestroy(&AE_IE);
801: MatDestroy(&AE_EI);
802: if (AE_II == A_II) { /* we can reuse the same ksp */
803: KSP ksp;
804: MatSchurComplementGetKSP(sub_schurs->S,&ksp);
805: MatSchurComplementSetKSP(S_Ej,ksp);
806: } else { /* build new ksp object which inherits ksp and pc types from the original one */
807: KSP origksp,schurksp;
808: PC origpc,schurpc;
809: KSPType ksp_type;
810: PetscInt n_internal;
811: PetscBool ispcnone;
813: MatSchurComplementGetKSP(sub_schurs->S,&origksp);
814: MatSchurComplementGetKSP(S_Ej,&schurksp);
815: KSPGetType(origksp,&ksp_type);
816: KSPSetType(schurksp,ksp_type);
817: KSPGetPC(schurksp,&schurpc);
818: KSPGetPC(origksp,&origpc);
819: PetscObjectTypeCompare((PetscObject)origpc,PCNONE,&ispcnone);
820: if (!ispcnone) {
821: PCType pc_type;
822: PCGetType(origpc,&pc_type);
823: PCSetType(schurpc,pc_type);
824: } else {
825: PCSetType(schurpc,PCLU);
826: }
827: ISGetSize(is_I,&n_internal);
828: if (!n_internal) { /* UMFPACK gives error with 0 sized problems */
829: MatSolverType solver = NULL;
830: PCFactorGetMatSolverType(origpc,(MatSolverType*)&solver);
831: if (solver) {
832: PCFactorSetMatSolverType(schurpc,solver);
833: }
834: }
835: KSPSetUp(schurksp);
836: }
837: ISGetLocalSize(sub_schurs->is_subs[i],&subset_size);
838: MatCreateSeqDense(PETSC_COMM_SELF,subset_size,subset_size,work,&S_Ej_expl);
839: PCBDDCComputeExplicitSchur(S_Ej,sub_schurs->is_symmetric,MAT_REUSE_MATRIX,&S_Ej_expl);
840: PetscObjectTypeCompare((PetscObject)S_Ej_expl,MATSEQDENSE,&Sdense);
841: if (Sdense) {
842: for (j=0;j<subset_size;j++) {
843: dummy_idx[j]=local_size+j;
844: }
845: MatSetValues(sub_schurs->S_Ej_all,subset_size,dummy_idx,subset_size,dummy_idx,work,INSERT_VALUES);
846: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not yet implemented for sparse matrices");
847: MatDestroy(&S_Ej);
848: MatDestroy(&S_Ej_expl);
849: local_size += subset_size;
850: }
851: PetscFree2(dummy_idx,work);
852: /* free */
853: ISDestroy(&is_I);
854: MatDestroy(&AE_II);
855: PetscFree(all_local_idx_N);
856: } else {
857: Mat A,cs_AIB_mat = NULL,benign_AIIm1_ones_mat = NULL;
858: Vec Dall = NULL;
859: IS is_A_all,*is_p_r = NULL;
860: MatType Stype;
861: PetscScalar *work,*S_data,*schur_factor,infty = PETSC_MAX_REAL;
862: PetscScalar *SEj_arr = NULL,*SEjinv_arr = NULL;
863: const PetscScalar *rS_data;
864: PetscInt n,n_I,size_schur,size_active_schur,cum,cum2;
865: PetscBool economic,solver_S,S_lower_triangular = PETSC_FALSE;
866: PetscBool schur_has_vertices,factor_workaround;
867: PetscBool use_cholesky;
868: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
869: PetscBool oldpin;
870: #endif
872: /* get sizes */
873: n_I = 0;
874: if (is_I_layer) {
875: ISGetLocalSize(is_I_layer,&n_I);
876: }
877: economic = PETSC_FALSE;
878: ISGetLocalSize(sub_schurs->is_I,&cum);
879: if (cum != n_I) economic = PETSC_TRUE;
880: MatGetLocalSize(sub_schurs->A,&n,NULL);
881: size_active_schur = local_size;
883: /* import scaling vector (wrong formulation if we have 3D edges) */
884: if (scaling && compute_Stilda) {
885: const PetscScalar *array;
886: PetscScalar *array2;
887: const PetscInt *idxs;
888: PetscInt i;
890: ISGetIndices(sub_schurs->is_Ej_all,&idxs);
891: VecCreateSeq(PETSC_COMM_SELF,size_active_schur,&Dall);
892: VecGetArrayRead(scaling,&array);
893: VecGetArray(Dall,&array2);
894: for (i=0;i<size_active_schur;i++) array2[i] = array[idxs[i]];
895: VecRestoreArray(Dall,&array2);
896: VecRestoreArrayRead(scaling,&array);
897: ISRestoreIndices(sub_schurs->is_Ej_all,&idxs);
898: deluxe = PETSC_FALSE;
899: }
901: /* size active schurs does not count any dirichlet or vertex dof on the interface */
902: factor_workaround = PETSC_FALSE;
903: schur_has_vertices = PETSC_FALSE;
904: cum = n_I+size_active_schur;
905: if (sub_schurs->is_dir) {
906: const PetscInt* idxs;
907: PetscInt n_dir;
909: ISGetLocalSize(sub_schurs->is_dir,&n_dir);
910: ISGetIndices(sub_schurs->is_dir,&idxs);
911: PetscArraycpy(all_local_idx_N+cum,idxs,n_dir);
912: ISRestoreIndices(sub_schurs->is_dir,&idxs);
913: cum += n_dir;
914: factor_workaround = PETSC_TRUE;
915: }
916: /* include the primal vertices in the Schur complement */
917: if (exact_schur && sub_schurs->is_vertices && (compute_Stilda || benign_n)) {
918: PetscInt n_v;
920: ISGetLocalSize(sub_schurs->is_vertices,&n_v);
921: if (n_v) {
922: const PetscInt* idxs;
924: ISGetIndices(sub_schurs->is_vertices,&idxs);
925: PetscArraycpy(all_local_idx_N+cum,idxs,n_v);
926: ISRestoreIndices(sub_schurs->is_vertices,&idxs);
927: cum += n_v;
928: factor_workaround = PETSC_TRUE;
929: schur_has_vertices = PETSC_TRUE;
930: }
931: }
932: size_schur = cum - n_I;
933: ISCreateGeneral(PETSC_COMM_SELF,cum,all_local_idx_N,PETSC_OWN_POINTER,&is_A_all);
934: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
935: oldpin = sub_schurs->A->boundtocpu;
936: MatBindToCPU(sub_schurs->A,PETSC_TRUE);
937: #endif
938: if (cum == n) {
939: ISSetPermutation(is_A_all);
940: MatPermute(sub_schurs->A,is_A_all,is_A_all,&A);
941: } else {
942: MatCreateSubMatrix(sub_schurs->A,is_A_all,is_A_all,MAT_INITIAL_MATRIX,&A);
943: }
944: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
945: MatBindToCPU(sub_schurs->A,oldpin);
946: #endif
947: MatSetOptionsPrefix(A,sub_schurs->prefix);
948: MatAppendOptionsPrefix(A,"sub_schurs_");
950: /* if we actually change the basis for the pressures, LDL^T factors will use a lot of memory
951: this is a workaround */
952: if (benign_n) {
953: Vec v,benign_AIIm1_ones;
954: ISLocalToGlobalMapping N_to_reor;
955: IS is_p0,is_p0_p;
956: PetscScalar *cs_AIB,*AIIm1_data;
957: PetscInt sizeA;
959: ISLocalToGlobalMappingCreateIS(is_A_all,&N_to_reor);
960: ISCreateGeneral(PETSC_COMM_SELF,benign_n,benign_p0_lidx,PETSC_COPY_VALUES,&is_p0);
961: ISGlobalToLocalMappingApplyIS(N_to_reor,IS_GTOLM_DROP,is_p0,&is_p0_p);
962: ISDestroy(&is_p0);
963: MatCreateVecs(A,&v,&benign_AIIm1_ones);
964: VecGetSize(v,&sizeA);
965: MatCreateSeqDense(PETSC_COMM_SELF,sizeA,benign_n,NULL,&benign_AIIm1_ones_mat);
966: MatCreateSeqDense(PETSC_COMM_SELF,size_schur,benign_n,NULL,&cs_AIB_mat);
967: MatDenseGetArray(cs_AIB_mat,&cs_AIB);
968: MatDenseGetArray(benign_AIIm1_ones_mat,&AIIm1_data);
969: PetscMalloc1(benign_n,&is_p_r);
970: /* compute colsum of A_IB restricted to pressures */
971: for (i=0;i<benign_n;i++) {
972: const PetscScalar *array;
973: const PetscInt *idxs;
974: PetscInt j,nz;
976: ISGlobalToLocalMappingApplyIS(N_to_reor,IS_GTOLM_DROP,benign_zerodiag_subs[i],&is_p_r[i]);
977: ISGetLocalSize(is_p_r[i],&nz);
978: ISGetIndices(is_p_r[i],&idxs);
979: for (j=0;j<nz;j++) AIIm1_data[idxs[j]+sizeA*i] = 1.;
980: ISRestoreIndices(is_p_r[i],&idxs);
981: VecPlaceArray(benign_AIIm1_ones,AIIm1_data+sizeA*i);
982: MatMult(A,benign_AIIm1_ones,v);
983: VecResetArray(benign_AIIm1_ones);
984: VecGetArrayRead(v,&array);
985: for (j=0;j<size_schur;j++) {
986: #if defined(PETSC_USE_COMPLEX)
987: cs_AIB[i*size_schur + j] = (PetscRealPart(array[j+n_I])/nz + PETSC_i*(PetscImaginaryPart(array[j+n_I])/nz));
988: #else
989: cs_AIB[i*size_schur + j] = array[j+n_I]/nz;
990: #endif
991: }
992: VecRestoreArrayRead(v,&array);
993: }
994: MatDenseRestoreArray(cs_AIB_mat,&cs_AIB);
995: MatDenseRestoreArray(benign_AIIm1_ones_mat,&AIIm1_data);
996: VecDestroy(&v);
997: VecDestroy(&benign_AIIm1_ones);
998: MatSetOption(A,MAT_KEEP_NONZERO_PATTERN,PETSC_FALSE);
999: MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
1000: MatSetOption(A,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);
1001: MatZeroRowsColumnsIS(A,is_p0_p,1.0,NULL,NULL);
1002: ISDestroy(&is_p0_p);
1003: ISLocalToGlobalMappingDestroy(&N_to_reor);
1004: }
1005: MatSetOption(A,MAT_SYMMETRIC,sub_schurs->is_symmetric);
1006: MatSetOption(A,MAT_HERMITIAN,sub_schurs->is_hermitian);
1007: MatSetOption(A,MAT_SPD,sub_schurs->is_posdef);
1009: /* for complexes, symmetric and hermitian at the same time implies null imaginary part */
1010: use_cholesky = (PetscBool)((use_potr || use_sytr) && sub_schurs->is_hermitian && sub_schurs->is_symmetric);
1012: /* when using the benign subspace trick, the local Schur complements are SPD */
1013: /* MKL_PARDISO does not handle well the computation of a Schur complement from a symmetric indefinite factorization
1014: Use LU and adapt pivoting perturbation (still, solution is not as accurate as with using MUMPS) */
1015: if (benign_trick) {
1016: sub_schurs->is_posdef = PETSC_TRUE;
1017: PetscStrcmp(sub_schurs->mat_solver_type,MATSOLVERMKL_PARDISO,&flg);
1018: if (flg) use_cholesky = PETSC_FALSE;
1019: }
1021: if (n_I) {
1022: IS is_schur;
1023: char stype[64];
1024: PetscBool gpu = PETSC_FALSE;
1026: if (use_cholesky) {
1027: MatGetFactor(A,sub_schurs->mat_solver_type,MAT_FACTOR_CHOLESKY,&F);
1028: } else {
1029: MatGetFactor(A,sub_schurs->mat_solver_type,MAT_FACTOR_LU,&F);
1030: }
1031: MatSetErrorIfFailure(A,PETSC_TRUE);
1032: #if defined(PETSC_HAVE_MKL_PARDISO)
1033: if (benign_trick) { MatMkl_PardisoSetCntl(F,10,10); }
1034: #endif
1035: /* subsets ordered last */
1036: ISCreateStride(PETSC_COMM_SELF,size_schur,n_I,1,&is_schur);
1037: MatFactorSetSchurIS(F,is_schur);
1038: ISDestroy(&is_schur);
1040: /* factorization step */
1041: if (use_cholesky) {
1042: MatCholeskyFactorSymbolic(F,A,NULL,NULL);
1043: #if defined(PETSC_HAVE_MUMPS) /* be sure that icntl 19 is not set by command line */
1044: MatMumpsSetIcntl(F,19,2);
1045: #endif
1046: MatCholeskyFactorNumeric(F,A,NULL);
1047: S_lower_triangular = PETSC_TRUE;
1048: } else {
1049: MatLUFactorSymbolic(F,A,NULL,NULL,NULL);
1050: #if defined(PETSC_HAVE_MUMPS) /* be sure that icntl 19 is not set by command line */
1051: MatMumpsSetIcntl(F,19,3);
1052: #endif
1053: MatLUFactorNumeric(F,A,NULL);
1054: }
1055: MatViewFromOptions(F,(PetscObject)A,"-mat_factor_view");
1057: if (matl_dbg_viewer) {
1058: Mat S;
1059: IS is;
1061: PetscObjectSetName((PetscObject)A,"A");
1062: MatView(A,matl_dbg_viewer);
1063: MatFactorCreateSchurComplement(F,&S,NULL);
1064: PetscObjectSetName((PetscObject)S,"S");
1065: MatView(S,matl_dbg_viewer);
1066: MatDestroy(&S);
1067: ISCreateStride(PETSC_COMM_SELF,n_I,0,1,&is);
1068: PetscObjectSetName((PetscObject)is,"I");
1069: ISView(is,matl_dbg_viewer);
1070: ISDestroy(&is);
1071: ISCreateStride(PETSC_COMM_SELF,size_schur,n_I,1,&is);
1072: PetscObjectSetName((PetscObject)is,"B");
1073: ISView(is,matl_dbg_viewer);
1074: ISDestroy(&is);
1075: PetscObjectSetName((PetscObject)is_A_all,"IA");
1076: ISView(is_A_all,matl_dbg_viewer);
1077: }
1079: /* get explicit Schur Complement computed during numeric factorization */
1080: MatFactorGetSchurComplement(F,&S_all,NULL);
1081: PetscStrncpy(stype,MATSEQDENSE,sizeof(stype));
1082: #if defined(PETSC_HAVE_CUDA)
1083: PetscObjectTypeCompareAny((PetscObject)A,&gpu,MATSEQAIJVIENNACL,MATSEQAIJCUSPARSE,"");
1084: #endif
1085: if (gpu) {
1086: PetscStrncpy(stype,MATSEQDENSECUDA,sizeof(stype));
1087: }
1088: PetscOptionsGetString(NULL,sub_schurs->prefix,"-sub_schurs_schur_mat_type",stype,sizeof(stype),NULL);
1089: MatConvert(S_all,stype,MAT_INPLACE_MATRIX,&S_all);
1090: MatSetOption(S_all,MAT_SPD,sub_schurs->is_posdef);
1091: MatSetOption(S_all,MAT_HERMITIAN,sub_schurs->is_hermitian);
1092: MatGetType(S_all,&Stype);
1094: /* we can reuse the solvers if we are not using the economic version */
1095: reuse_solvers = (PetscBool)(reuse_solvers && !economic);
1096: factor_workaround = (PetscBool)(reuse_solvers && factor_workaround);
1097: if (!sub_schurs->is_posdef && factor_workaround && compute_Stilda && size_active_schur)
1098: reuse_solvers = factor_workaround = PETSC_FALSE;
1100: solver_S = PETSC_TRUE;
1102: /* update the Schur complement with the change of basis on the pressures */
1103: if (benign_n) {
1104: const PetscScalar *cs_AIB;
1105: PetscScalar *S_data,*AIIm1_data;
1106: Mat S2 = NULL,S3 = NULL; /* dbg */
1107: PetscScalar *S2_data,*S3_data; /* dbg */
1108: Vec v,benign_AIIm1_ones;
1109: PetscInt sizeA;
1111: MatDenseGetArray(S_all,&S_data);
1112: MatCreateVecs(A,&v,&benign_AIIm1_ones);
1113: VecGetSize(v,&sizeA);
1114: #if defined(PETSC_HAVE_MUMPS)
1115: MatMumpsSetIcntl(F,26,0);
1116: #endif
1117: #if defined(PETSC_HAVE_MKL_PARDISO)
1118: MatMkl_PardisoSetCntl(F,70,1);
1119: #endif
1120: MatDenseGetArrayRead(cs_AIB_mat,&cs_AIB);
1121: MatDenseGetArray(benign_AIIm1_ones_mat,&AIIm1_data);
1122: if (matl_dbg_viewer) {
1123: MatDuplicate(S_all,MAT_DO_NOT_COPY_VALUES,&S2);
1124: MatDuplicate(S_all,MAT_DO_NOT_COPY_VALUES,&S3);
1125: MatDenseGetArray(S2,&S2_data);
1126: MatDenseGetArray(S3,&S3_data);
1127: }
1128: for (i=0;i<benign_n;i++) {
1129: PetscScalar *array,sum = 0.,one = 1.,*sums;
1130: const PetscInt *idxs;
1131: PetscInt k,j,nz;
1132: PetscBLASInt B_k,B_n;
1134: PetscCalloc1(benign_n,&sums);
1135: VecPlaceArray(benign_AIIm1_ones,AIIm1_data+sizeA*i);
1136: VecCopy(benign_AIIm1_ones,v);
1137: MatSolve(F,v,benign_AIIm1_ones);
1138: MatMult(A,benign_AIIm1_ones,v);
1139: VecResetArray(benign_AIIm1_ones);
1140: /* p0 dofs (eliminated) are excluded from the sums */
1141: for (k=0;k<benign_n;k++) {
1142: ISGetLocalSize(is_p_r[k],&nz);
1143: ISGetIndices(is_p_r[k],&idxs);
1144: for (j=0;j<nz-1;j++) sums[k] -= AIIm1_data[idxs[j]+sizeA*i];
1145: ISRestoreIndices(is_p_r[k],&idxs);
1146: }
1147: VecGetArrayRead(v,(const PetscScalar**)&array);
1148: if (matl_dbg_viewer) {
1149: Vec vv;
1150: char name[16];
1152: VecCreateSeqWithArray(PETSC_COMM_SELF,1,size_schur,array+n_I,&vv);
1153: PetscSNPrintf(name,sizeof(name),"Pvs%D",i);
1154: PetscObjectSetName((PetscObject)vv,name);
1155: VecView(vv,matl_dbg_viewer);
1156: }
1157: /* perform sparse rank updates on symmetric Schur (TODO: move outside of the loop?) */
1158: /* cs_AIB already scaled by 1./nz */
1159: B_k = 1;
1160: for (k=0;k<benign_n;k++) {
1161: sum = sums[k];
1162: PetscBLASIntCast(size_schur,&B_n);
1164: if (PetscAbsScalar(sum) == 0.0) continue;
1165: if (k == i) {
1166: PetscStackCallBLAS("BLASsyrk",BLASsyrk_("L","N",&B_n,&B_k,&sum,cs_AIB+i*size_schur,&B_n,&one,S_data,&B_n));
1167: if (matl_dbg_viewer) {
1168: PetscStackCallBLAS("BLASsyrk",BLASsyrk_("L","N",&B_n,&B_k,&sum,cs_AIB+i*size_schur,&B_n,&one,S3_data,&B_n));
1169: }
1170: } else { /* XXX Is it correct to use symmetric rank-2 update with half of the sum? */
1171: sum /= 2.0;
1172: 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));
1173: if (matl_dbg_viewer) {
1174: 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));
1175: }
1176: }
1177: }
1178: sum = 1.;
1179: 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));
1180: if (matl_dbg_viewer) {
1181: 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));
1182: }
1183: VecRestoreArrayRead(v,(const PetscScalar**)&array);
1184: /* set p0 entry of AIIm1_ones to zero */
1185: ISGetLocalSize(is_p_r[i],&nz);
1186: ISGetIndices(is_p_r[i],&idxs);
1187: for (j=0;j<benign_n;j++) AIIm1_data[idxs[nz-1]+sizeA*j] = 0.;
1188: ISRestoreIndices(is_p_r[i],&idxs);
1189: PetscFree(sums);
1190: }
1191: VecDestroy(&benign_AIIm1_ones);
1192: if (matl_dbg_viewer) {
1193: MatDenseRestoreArray(S2,&S2_data);
1194: MatDenseRestoreArray(S3,&S3_data);
1195: }
1196: if (!S_lower_triangular) { /* I need to expand the upper triangular data (column oriented) */
1197: PetscInt k,j;
1198: for (k=0;k<size_schur;k++) {
1199: for (j=k;j<size_schur;j++) {
1200: S_data[j*size_schur+k] = PetscConj(S_data[k*size_schur+j]);
1201: }
1202: }
1203: }
1205: /* restore defaults */
1206: #if defined(PETSC_HAVE_MUMPS)
1207: MatMumpsSetIcntl(F,26,-1);
1208: #endif
1209: #if defined(PETSC_HAVE_MKL_PARDISO)
1210: MatMkl_PardisoSetCntl(F,70,0);
1211: #endif
1212: MatDenseRestoreArrayRead(cs_AIB_mat,&cs_AIB);
1213: MatDenseRestoreArray(benign_AIIm1_ones_mat,&AIIm1_data);
1214: VecDestroy(&v);
1215: MatDenseRestoreArray(S_all,&S_data);
1216: if (matl_dbg_viewer) {
1217: Mat S;
1219: MatFactorRestoreSchurComplement(F,&S_all,MAT_FACTOR_SCHUR_UNFACTORED);
1220: MatFactorCreateSchurComplement(F,&S,NULL);
1221: PetscObjectSetName((PetscObject)S,"Sb");
1222: MatView(S,matl_dbg_viewer);
1223: MatDestroy(&S);
1224: PetscObjectSetName((PetscObject)S2,"S2P");
1225: MatView(S2,matl_dbg_viewer);
1226: PetscObjectSetName((PetscObject)S3,"S3P");
1227: MatView(S3,matl_dbg_viewer);
1228: PetscObjectSetName((PetscObject)cs_AIB_mat,"cs");
1229: MatView(cs_AIB_mat,matl_dbg_viewer);
1230: MatFactorGetSchurComplement(F,&S_all,NULL);
1231: }
1232: MatDestroy(&S2);
1233: MatDestroy(&S3);
1234: }
1235: if (!reuse_solvers) {
1236: for (i=0;i<benign_n;i++) {
1237: ISDestroy(&is_p_r[i]);
1238: }
1239: PetscFree(is_p_r);
1240: MatDestroy(&cs_AIB_mat);
1241: MatDestroy(&benign_AIIm1_ones_mat);
1242: }
1243: } else { /* we can't use MatFactor when size_schur == size_of_the_problem */
1244: MatConvert(A,MATSEQDENSE,MAT_INITIAL_MATRIX,&S_all);
1245: MatGetType(S_all,&Stype);
1246: reuse_solvers = PETSC_FALSE; /* TODO: why we can't reuse the solvers here? */
1247: factor_workaround = PETSC_FALSE;
1248: solver_S = PETSC_FALSE;
1249: }
1251: if (reuse_solvers) {
1252: Mat A_II,Afake;
1253: Vec vec1_B;
1254: PCBDDCReuseSolvers msolv_ctx;
1255: PetscInt n_R;
1257: if (sub_schurs->reuse_solver) {
1258: PCBDDCReuseSolversReset(sub_schurs->reuse_solver);
1259: } else {
1260: PetscNew(&sub_schurs->reuse_solver);
1261: }
1262: msolv_ctx = sub_schurs->reuse_solver;
1263: MatSchurComplementGetSubMatrices(sub_schurs->S,&A_II,NULL,NULL,NULL,NULL);
1264: PetscObjectReference((PetscObject)F);
1265: msolv_ctx->F = F;
1266: MatCreateVecs(F,&msolv_ctx->sol,NULL);
1267: /* currently PETSc has no support for MatSolve(F,x,x), so cheat and let rhs and sol share the same memory */
1268: {
1269: PetscScalar *array;
1270: PetscInt n;
1272: VecGetLocalSize(msolv_ctx->sol,&n);
1273: VecGetArray(msolv_ctx->sol,&array);
1274: VecCreateSeqWithArray(PetscObjectComm((PetscObject)msolv_ctx->sol),1,n,array,&msolv_ctx->rhs);
1275: VecRestoreArray(msolv_ctx->sol,&array);
1276: }
1277: msolv_ctx->has_vertices = schur_has_vertices;
1279: /* interior solver */
1280: PCCreate(PetscObjectComm((PetscObject)A_II),&msolv_ctx->interior_solver);
1281: PCSetOperators(msolv_ctx->interior_solver,A_II,A_II);
1282: PCSetType(msolv_ctx->interior_solver,PCSHELL);
1283: PCShellSetName(msolv_ctx->interior_solver,"Interior solver (w/o Schur factorization)");
1284: PCShellSetContext(msolv_ctx->interior_solver,msolv_ctx);
1285: PCShellSetView(msolv_ctx->interior_solver,PCBDDCReuseSolvers_View);
1286: PCShellSetApply(msolv_ctx->interior_solver,PCBDDCReuseSolvers_Interior);
1287: PCShellSetApplyTranspose(msolv_ctx->interior_solver,PCBDDCReuseSolvers_InteriorTranspose);
1289: /* correction solver */
1290: PCCreate(PetscObjectComm((PetscObject)A_II),&msolv_ctx->correction_solver);
1291: PCSetType(msolv_ctx->correction_solver,PCSHELL);
1292: PCShellSetName(msolv_ctx->correction_solver,"Correction solver (with Schur factorization)");
1293: PCShellSetContext(msolv_ctx->correction_solver,msolv_ctx);
1294: PCShellSetView(msolv_ctx->interior_solver,PCBDDCReuseSolvers_View);
1295: PCShellSetApply(msolv_ctx->correction_solver,PCBDDCReuseSolvers_Correction);
1296: PCShellSetApplyTranspose(msolv_ctx->correction_solver,PCBDDCReuseSolvers_CorrectionTranspose);
1298: /* scatter and vecs for Schur complement solver */
1299: MatCreateVecs(S_all,&msolv_ctx->sol_B,&msolv_ctx->rhs_B);
1300: MatCreateVecs(sub_schurs->S,&vec1_B,NULL);
1301: if (!schur_has_vertices) {
1302: ISGlobalToLocalMappingApplyIS(sub_schurs->BtoNmap,IS_GTOLM_DROP,is_A_all,&msolv_ctx->is_B);
1303: VecScatterCreate(vec1_B,msolv_ctx->is_B,msolv_ctx->sol_B,NULL,&msolv_ctx->correction_scatter_B);
1304: PetscObjectReference((PetscObject)is_A_all);
1305: msolv_ctx->is_R = is_A_all;
1306: } else {
1307: IS is_B_all;
1308: const PetscInt* idxs;
1309: PetscInt dual,n_v,n;
1311: ISGetLocalSize(sub_schurs->is_vertices,&n_v);
1312: dual = size_schur - n_v;
1313: ISGetLocalSize(is_A_all,&n);
1314: ISGetIndices(is_A_all,&idxs);
1315: ISCreateGeneral(PetscObjectComm((PetscObject)is_A_all),dual,idxs+n_I,PETSC_COPY_VALUES,&is_B_all);
1316: ISGlobalToLocalMappingApplyIS(sub_schurs->BtoNmap,IS_GTOLM_DROP,is_B_all,&msolv_ctx->is_B);
1317: ISDestroy(&is_B_all);
1318: ISCreateStride(PetscObjectComm((PetscObject)is_A_all),dual,0,1,&is_B_all);
1319: VecScatterCreate(vec1_B,msolv_ctx->is_B,msolv_ctx->sol_B,is_B_all,&msolv_ctx->correction_scatter_B);
1320: ISDestroy(&is_B_all);
1321: ISCreateGeneral(PetscObjectComm((PetscObject)is_A_all),n-n_v,idxs,PETSC_COPY_VALUES,&msolv_ctx->is_R);
1322: ISRestoreIndices(is_A_all,&idxs);
1323: }
1324: ISGetLocalSize(msolv_ctx->is_R,&n_R);
1325: MatCreateSeqAIJ(PETSC_COMM_SELF,n_R,n_R,0,NULL,&Afake);
1326: MatAssemblyBegin(Afake,MAT_FINAL_ASSEMBLY);
1327: MatAssemblyEnd(Afake,MAT_FINAL_ASSEMBLY);
1328: PCSetOperators(msolv_ctx->correction_solver,Afake,Afake);
1329: MatDestroy(&Afake);
1330: VecDestroy(&vec1_B);
1332: /* communicate benign info to solver context */
1333: if (benign_n) {
1334: PetscScalar *array;
1336: msolv_ctx->benign_n = benign_n;
1337: msolv_ctx->benign_zerodiag_subs = is_p_r;
1338: PetscMalloc1(benign_n,&msolv_ctx->benign_save_vals);
1339: msolv_ctx->benign_csAIB = cs_AIB_mat;
1340: MatCreateVecs(cs_AIB_mat,&msolv_ctx->benign_corr_work,NULL);
1341: VecGetArray(msolv_ctx->benign_corr_work,&array);
1342: VecCreateSeqWithArray(PETSC_COMM_SELF,1,size_schur,array,&msolv_ctx->benign_dummy_schur_vec);
1343: VecRestoreArray(msolv_ctx->benign_corr_work,&array);
1344: msolv_ctx->benign_AIIm1ones = benign_AIIm1_ones_mat;
1345: }
1346: } else {
1347: if (sub_schurs->reuse_solver) {
1348: PCBDDCReuseSolversReset(sub_schurs->reuse_solver);
1349: }
1350: PetscFree(sub_schurs->reuse_solver);
1351: }
1352: MatDestroy(&A);
1353: ISDestroy(&is_A_all);
1355: /* Work arrays */
1356: PetscMalloc1(max_subset_size*max_subset_size,&work);
1358: /* S_Ej_all */
1359: cum = cum2 = 0;
1360: MatDenseGetArrayRead(S_all,&rS_data);
1361: MatSeqAIJGetArray(sub_schurs->S_Ej_all,&SEj_arr);
1362: if (compute_Stilda) {
1363: MatSeqAIJGetArray(sub_schurs->sum_S_Ej_inv_all,&SEjinv_arr);
1364: }
1365: for (i=0;i<sub_schurs->n_subs;i++) {
1366: PetscInt j;
1368: /* get S_E */
1369: ISGetLocalSize(sub_schurs->is_subs[i],&subset_size);
1370: if (S_lower_triangular) { /* I need to expand the upper triangular data (column oriented) */
1371: PetscInt k;
1372: for (k=0;k<subset_size;k++) {
1373: for (j=k;j<subset_size;j++) {
1374: work[k*subset_size+j] = rS_data[cum2+k*size_schur+j];
1375: work[j*subset_size+k] = PetscConj(rS_data[cum2+k*size_schur+j]);
1376: }
1377: }
1378: } else { /* just copy to workspace */
1379: PetscInt k;
1380: for (k=0;k<subset_size;k++) {
1381: for (j=0;j<subset_size;j++) {
1382: work[k*subset_size+j] = rS_data[cum2+k*size_schur+j];
1383: }
1384: }
1385: }
1386: /* insert S_E values */
1387: if (sub_schurs->change) {
1388: Mat change_sub,SEj,T;
1390: /* change basis */
1391: KSPGetOperators(sub_schurs->change[i],&change_sub,NULL);
1392: MatCreateSeqDense(PETSC_COMM_SELF,subset_size,subset_size,work,&SEj);
1393: if (!sub_schurs->change_with_qr) { /* currently there's no support for PtAP with P SeqAIJ */
1394: Mat T2;
1395: MatTransposeMatMult(change_sub,SEj,MAT_INITIAL_MATRIX,1.0,&T2);
1396: MatMatMult(T2,change_sub,MAT_INITIAL_MATRIX,1.0,&T);
1397: MatConvert(T,MATSEQDENSE,MAT_INPLACE_MATRIX,&T);
1398: MatDestroy(&T2);
1399: } else {
1400: MatPtAP(SEj,change_sub,MAT_INITIAL_MATRIX,1.0,&T);
1401: }
1402: MatCopy(T,SEj,SAME_NONZERO_PATTERN);
1403: MatDestroy(&T);
1404: MatZeroRowsColumnsIS(SEj,sub_schurs->change_primal_sub[i],1.0,NULL,NULL);
1405: MatDestroy(&SEj);
1406: }
1407: if (deluxe) {
1408: PetscArraycpy(SEj_arr,work,subset_size*subset_size);
1409: /* if adaptivity is requested, invert S_E blocks */
1410: if (compute_Stilda) {
1411: Mat M;
1412: const PetscScalar *vals;
1413: PetscBool isdense,isdensecuda;
1415: MatCreateSeqDense(PETSC_COMM_SELF,subset_size,subset_size,work,&M);
1416: MatSetOption(M,MAT_SPD,sub_schurs->is_posdef);
1417: MatSetOption(M,MAT_HERMITIAN,sub_schurs->is_hermitian);
1418: if (!PetscBTLookup(sub_schurs->is_edge,i)) {
1419: MatSetType(M,Stype);
1420: }
1421: PetscObjectTypeCompare((PetscObject)M,MATSEQDENSE,&isdense);
1422: PetscObjectTypeCompare((PetscObject)M,MATSEQDENSECUDA,&isdensecuda);
1423: if (use_cholesky) {
1424: MatCholeskyFactor(M,NULL,NULL);
1425: } else {
1426: MatLUFactor(M,NULL,NULL,NULL);
1427: }
1428: if (isdense) {
1429: MatSeqDenseInvertFactors_Private(M);
1430: #if defined(PETSC_HAVE_CUDA)
1431: } else if (isdensecuda) {
1432: MatSeqDenseCUDAInvertFactors_Private(M);
1433: #endif
1434: } else SETERRQ1(PetscObjectComm((PetscObject)M),PETSC_ERR_SUP,"Not implemented for type %s",Stype);
1435: MatDenseGetArrayRead(M,&vals);
1436: PetscArraycpy(SEjinv_arr,vals,subset_size*subset_size);
1437: MatDenseRestoreArrayRead(M,&vals);
1438: MatDestroy(&M);
1439: }
1440: } else if (compute_Stilda) { /* not using deluxe */
1441: Mat SEj;
1442: Vec D;
1443: PetscScalar *array;
1445: MatCreateSeqDense(PETSC_COMM_SELF,subset_size,subset_size,work,&SEj);
1446: VecGetArray(Dall,&array);
1447: VecCreateSeqWithArray(PETSC_COMM_SELF,1,subset_size,array+cum,&D);
1448: VecRestoreArray(Dall,&array);
1449: VecShift(D,-1.);
1450: MatDiagonalScale(SEj,D,D);
1451: MatDestroy(&SEj);
1452: VecDestroy(&D);
1453: PetscArraycpy(SEj_arr,work,subset_size*subset_size);
1454: }
1455: cum += subset_size;
1456: cum2 += subset_size*(size_schur + 1);
1457: SEj_arr += subset_size*subset_size;
1458: if (SEjinv_arr) SEjinv_arr += subset_size*subset_size;
1459: }
1460: MatDenseRestoreArrayRead(S_all,&rS_data);
1461: MatSeqAIJRestoreArray(sub_schurs->S_Ej_all,&SEj_arr);
1462: if (compute_Stilda) {
1463: MatSeqAIJRestoreArray(sub_schurs->sum_S_Ej_inv_all,&SEjinv_arr);
1464: }
1465: if (solver_S) {
1466: MatFactorRestoreSchurComplement(F,&S_all,MAT_FACTOR_SCHUR_UNFACTORED);
1467: }
1469: /* may prevent from unneeded copies, since MUMPS or MKL_Pardiso always use CPU memory
1470: however, preliminary tests indicate using GPUs is still faster in the solve phase */
1471: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
1472: if (reuse_solvers) {
1473: Mat St;
1474: MatFactorSchurStatus st;
1476: flg = PETSC_FALSE;
1477: PetscOptionsGetBool(NULL,sub_schurs->prefix,"-sub_schurs_schur_pin_to_cpu",&flg,NULL);
1478: MatFactorGetSchurComplement(F,&St,&st);
1479: MatBindToCPU(St,flg);
1480: MatFactorRestoreSchurComplement(F,&St,st);
1481: }
1482: #endif
1484: schur_factor = NULL;
1485: if (compute_Stilda && size_active_schur) {
1487: MatSeqAIJGetArray(sub_schurs->sum_S_Ej_tilda_all,&SEjinv_arr);
1488: if (sub_schurs->n_subs == 1 && size_schur == size_active_schur && deluxe) { /* we already computed the inverse */
1489: PetscArraycpy(SEjinv_arr,work,size_schur*size_schur);
1490: } else {
1491: Mat S_all_inv=NULL;
1493: if (solver_S) {
1494: /* for adaptive selection we need S^-1; for solver reusage we need S_\Delta\Delta^-1.
1495: 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 */
1496: if (factor_workaround) {/* invert without calling MatFactorInvertSchurComplement, since we are hacking */
1497: PetscScalar *data;
1498: PetscInt nd = 0;
1500: if (!use_potr) {
1501: SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Factor update not yet implemented for non SPD matrices");
1502: }
1503: MatFactorGetSchurComplement(F,&S_all_inv,NULL);
1504: MatDenseGetArray(S_all_inv,&data);
1505: if (sub_schurs->is_dir) { /* dirichlet dofs could have different scalings */
1506: ISGetLocalSize(sub_schurs->is_dir,&nd);
1507: }
1509: /* factor and invert activedofs and vertices (dirichlet dofs does not contribute) */
1510: if (schur_has_vertices) {
1511: Mat M;
1512: PetscScalar *tdata;
1513: PetscInt nv = 0, news;
1515: ISGetLocalSize(sub_schurs->is_vertices,&nv);
1516: news = size_active_schur + nv;
1517: PetscCalloc1(news*news,&tdata);
1518: for (i=0;i<size_active_schur;i++) {
1519: PetscArraycpy(tdata+i*(news+1),data+i*(size_schur+1),size_active_schur-i);
1520: PetscArraycpy(tdata+i*(news+1)+size_active_schur-i,data+i*size_schur+size_active_schur+nd,nv);
1521: }
1522: for (i=0;i<nv;i++) {
1523: PetscInt k = i+size_active_schur;
1524: PetscArraycpy(tdata+k*(news+1),data+(k+nd)*(size_schur+1),nv-i);
1525: }
1527: MatCreateSeqDense(PETSC_COMM_SELF,news,news,tdata,&M);
1528: MatSetOption(M,MAT_SPD,PETSC_TRUE);
1529: MatCholeskyFactor(M,NULL,NULL);
1530: /* save the factors */
1531: cum = 0;
1532: PetscMalloc1((size_active_schur*(size_active_schur +1))/2+nd,&schur_factor);
1533: for (i=0;i<size_active_schur;i++) {
1534: PetscArraycpy(schur_factor+cum,tdata+i*(news+1),size_active_schur-i);
1535: cum += size_active_schur - i;
1536: }
1537: for (i=0;i<nd;i++) schur_factor[cum+i] = PetscSqrtReal(PetscRealPart(data[(i+size_active_schur)*(size_schur+1)]));
1538: MatSeqDenseInvertFactors_Private(M);
1539: /* move back just the active dofs to the Schur complement */
1540: for (i=0;i<size_active_schur;i++) {
1541: PetscArraycpy(data+i*size_schur,tdata+i*news,size_active_schur);
1542: }
1543: PetscFree(tdata);
1544: MatDestroy(&M);
1545: } else { /* we can factorize and invert just the activedofs */
1546: Mat M;
1547: PetscScalar *aux;
1549: PetscMalloc1(nd,&aux);
1550: for (i=0;i<nd;i++) aux[i] = 1.0/data[(i+size_active_schur)*(size_schur+1)];
1551: MatCreateSeqDense(PETSC_COMM_SELF,size_active_schur,size_active_schur,data,&M);
1552: MatDenseSetLDA(M,size_schur);
1553: MatSetOption(M,MAT_SPD,PETSC_TRUE);
1554: MatCholeskyFactor(M,NULL,NULL);
1555: MatSeqDenseInvertFactors_Private(M);
1556: MatDestroy(&M);
1557: MatCreateSeqDense(PETSC_COMM_SELF,size_schur,nd,data+size_active_schur*size_schur,&M);
1558: MatZeroEntries(M);
1559: MatDestroy(&M);
1560: MatCreateSeqDense(PETSC_COMM_SELF,nd,size_schur,data+size_active_schur,&M);
1561: MatDenseSetLDA(M,size_schur);
1562: MatZeroEntries(M);
1563: MatDestroy(&M);
1564: for (i=0;i<nd;i++) data[(i+size_active_schur)*(size_schur+1)] = aux[i];
1565: PetscFree(aux);
1566: }
1567: MatDenseRestoreArray(S_all_inv,&data);
1568: } else { /* use MatFactor calls to invert S */
1569: MatFactorInvertSchurComplement(F);
1570: MatFactorGetSchurComplement(F,&S_all_inv,NULL);
1571: }
1572: } else { /* we need to invert explicitly since we are not using MatFactor for S */
1573: PetscObjectReference((PetscObject)S_all);
1574: S_all_inv = S_all;
1575: MatDenseGetArray(S_all_inv,&S_data);
1576: PetscBLASIntCast(size_schur,&B_N);
1577: PetscFPTrapPush(PETSC_FP_TRAP_OFF);
1578: if (use_potr) {
1579: PetscStackCallBLAS("LAPACKpotrf",LAPACKpotrf_("L",&B_N,S_data,&B_N,&B_ierr));
1580: if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRF Lapack routine %d",(int)B_ierr);
1581: PetscStackCallBLAS("LAPACKpotri",LAPACKpotri_("L",&B_N,S_data,&B_N,&B_ierr));
1582: if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRI Lapack routine %d",(int)B_ierr);
1583: } else if (use_sytr) {
1584: PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_("L",&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 SYTRF Lapack routine %d",(int)B_ierr);
1586: PetscStackCallBLAS("LAPACKsytri",LAPACKsytri_("L",&B_N,S_data,&B_N,pivots,Bwork,&B_ierr));
1587: if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRI Lapack routine %d",(int)B_ierr);
1588: } else {
1589: PetscStackCallBLAS("LAPACKgetrf",LAPACKgetrf_(&B_N,&B_N,S_data,&B_N,pivots,&B_ierr));
1590: if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRF Lapack routine %d",(int)B_ierr);
1591: PetscStackCallBLAS("LAPACKgetri",LAPACKgetri_(&B_N,S_data,&B_N,pivots,Bwork,&B_lwork,&B_ierr));
1592: if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRI Lapack routine %d",(int)B_ierr);
1593: }
1594: PetscLogFlops(1.0*size_schur*size_schur*size_schur);
1595: PetscFPTrapPop();
1596: MatDenseRestoreArray(S_all_inv,&S_data);
1597: }
1598: /* S_Ej_tilda_all */
1599: cum = cum2 = 0;
1600: MatDenseGetArrayRead(S_all_inv,&rS_data);
1601: for (i=0;i<sub_schurs->n_subs;i++) {
1602: PetscInt j;
1604: ISGetLocalSize(sub_schurs->is_subs[i],&subset_size);
1605: /* get (St^-1)_E */
1606: /* Unless we are changing the variables, I don't need to expand to upper triangular since St^-1
1607: will be properly accessed later during adaptive selection */
1608: if (S_lower_triangular) {
1609: PetscInt k;
1610: if (sub_schurs->change) {
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: work[j*subset_size+k] = work[k*subset_size+j];
1615: }
1616: }
1617: } else {
1618: for (k=0;k<subset_size;k++) {
1619: for (j=k;j<subset_size;j++) {
1620: work[k*subset_size+j] = rS_data[cum2+k*size_schur+j];
1621: }
1622: }
1623: }
1624: } else {
1625: PetscInt k;
1626: for (k=0;k<subset_size;k++) {
1627: for (j=0;j<subset_size;j++) {
1628: work[k*subset_size+j] = rS_data[cum2+k*size_schur+j];
1629: }
1630: }
1631: }
1632: if (sub_schurs->change) {
1633: Mat change_sub,SEj,T;
1635: /* change basis */
1636: KSPGetOperators(sub_schurs->change[i],&change_sub,NULL);
1637: MatCreateSeqDense(PETSC_COMM_SELF,subset_size,subset_size,work,&SEj);
1638: if (!sub_schurs->change_with_qr) { /* currently there's no support for PtAP with P SeqAIJ */
1639: Mat T2;
1640: MatTransposeMatMult(change_sub,SEj,MAT_INITIAL_MATRIX,1.0,&T2);
1641: MatMatMult(T2,change_sub,MAT_INITIAL_MATRIX,1.0,&T);
1642: MatDestroy(&T2);
1643: MatConvert(T,MATSEQDENSE,MAT_INPLACE_MATRIX,&T);
1644: } else {
1645: MatPtAP(SEj,change_sub,MAT_INITIAL_MATRIX,1.0,&T);
1646: }
1647: MatCopy(T,SEj,SAME_NONZERO_PATTERN);
1648: MatDestroy(&T);
1649: /* set diagonal entry to a very large value to pick the basis we are eliminating as the first eigenvectors with adaptive selection */
1650: MatZeroRowsColumnsIS(SEj,sub_schurs->change_primal_sub[i],1./PETSC_SMALL,NULL,NULL);
1651: MatDestroy(&SEj);
1652: }
1653: PetscArraycpy(SEjinv_arr,work,subset_size*subset_size);
1654: cum += subset_size;
1655: cum2 += subset_size*(size_schur + 1);
1656: SEjinv_arr += subset_size*subset_size;
1657: }
1658: MatDenseRestoreArrayRead(S_all_inv,&rS_data);
1659: if (solver_S) {
1660: if (schur_has_vertices) {
1661: MatFactorRestoreSchurComplement(F,&S_all_inv,MAT_FACTOR_SCHUR_FACTORED);
1662: } else {
1663: MatFactorRestoreSchurComplement(F,&S_all_inv,MAT_FACTOR_SCHUR_INVERTED);
1664: }
1665: }
1666: MatDestroy(&S_all_inv);
1667: }
1668: MatSeqAIJRestoreArray(sub_schurs->sum_S_Ej_tilda_all,&SEjinv_arr);
1670: /* move back factors if needed */
1671: if (schur_has_vertices) {
1672: Mat S_tmp;
1673: PetscInt nd = 0;
1675: if (!solver_S) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"This should not happen");
1676: MatFactorGetSchurComplement(F,&S_tmp,NULL);
1677: if (use_potr) {
1678: PetscScalar *data;
1680: MatDenseGetArray(S_tmp,&data);
1681: PetscArrayzero(data,size_schur*size_schur);
1683: if (S_lower_triangular) {
1684: cum = 0;
1685: for (i=0;i<size_active_schur;i++) {
1686: PetscArraycpy(data+i*(size_schur+1),schur_factor+cum,size_active_schur-i);
1687: cum += size_active_schur-i;
1688: }
1689: } else {
1690: PetscArraycpy(data,schur_factor,size_schur*size_schur);
1691: }
1692: if (sub_schurs->is_dir) {
1693: ISGetLocalSize(sub_schurs->is_dir,&nd);
1694: for (i=0;i<nd;i++) {
1695: data[(i+size_active_schur)*(size_schur+1)] = schur_factor[cum+i];
1696: }
1697: }
1698: /* workaround: since I cannot modify the matrices used inside the solvers for the forward and backward substitutions,
1699: set the diagonal entry of the Schur factor to a very large value */
1700: for (i=size_active_schur+nd;i<size_schur;i++) {
1701: data[i*(size_schur+1)] = infty;
1702: }
1703: MatDenseRestoreArray(S_tmp,&data);
1704: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Factor update not yet implemented for non SPD matrices");
1705: MatFactorRestoreSchurComplement(F,&S_tmp,MAT_FACTOR_SCHUR_FACTORED);
1706: }
1707: } else if (factor_workaround) { /* we need to eliminate any unneeded coupling */
1708: PetscScalar *data;
1709: PetscInt nd = 0;
1711: if (sub_schurs->is_dir) { /* dirichlet dofs could have different scalings */
1712: ISGetLocalSize(sub_schurs->is_dir,&nd);
1713: }
1714: MatFactorGetSchurComplement(F,&S_all,NULL);
1715: MatDenseGetArray(S_all,&data);
1716: for (i=0;i<size_active_schur;i++) {
1717: PetscArrayzero(data+i*size_schur+size_active_schur,size_schur-size_active_schur);
1718: }
1719: for (i=size_active_schur+nd;i<size_schur;i++) {
1720: PetscArrayzero(data+i*size_schur+size_active_schur,size_schur-size_active_schur);
1721: data[i*(size_schur+1)] = infty;
1722: }
1723: MatDenseRestoreArray(S_all,&data);
1724: MatFactorRestoreSchurComplement(F,&S_all,MAT_FACTOR_SCHUR_UNFACTORED);
1725: }
1726: PetscFree(work);
1727: PetscFree(schur_factor);
1728: VecDestroy(&Dall);
1729: }
1730: ISDestroy(&is_I_layer);
1731: MatDestroy(&S_all);
1732: MatDestroy(&A_BB);
1733: MatDestroy(&A_IB);
1734: MatDestroy(&A_BI);
1735: MatDestroy(&F);
1737: PetscMalloc1(sub_schurs->n_subs,&nnz);
1738: for (i=0;i<sub_schurs->n_subs;i++) {
1739: ISGetLocalSize(sub_schurs->is_subs[i],&nnz[i]);
1740: }
1741: ISCreateGeneral(PETSC_COMM_SELF,sub_schurs->n_subs,nnz,PETSC_OWN_POINTER,&is_I_layer);
1742: MatSetVariableBlockSizes(sub_schurs->S_Ej_all,sub_schurs->n_subs,nnz);
1743: MatAssemblyBegin(sub_schurs->S_Ej_all,MAT_FINAL_ASSEMBLY);
1744: MatAssemblyEnd(sub_schurs->S_Ej_all,MAT_FINAL_ASSEMBLY);
1745: if (compute_Stilda) {
1746: MatSetVariableBlockSizes(sub_schurs->sum_S_Ej_tilda_all,sub_schurs->n_subs,nnz);
1747: MatAssemblyBegin(sub_schurs->sum_S_Ej_tilda_all,MAT_FINAL_ASSEMBLY);
1748: MatAssemblyEnd(sub_schurs->sum_S_Ej_tilda_all,MAT_FINAL_ASSEMBLY);
1749: if (deluxe) {
1750: MatSetVariableBlockSizes(sub_schurs->sum_S_Ej_inv_all,sub_schurs->n_subs,nnz);
1751: MatAssemblyBegin(sub_schurs->sum_S_Ej_inv_all,MAT_FINAL_ASSEMBLY);
1752: MatAssemblyEnd(sub_schurs->sum_S_Ej_inv_all,MAT_FINAL_ASSEMBLY);
1753: }
1754: }
1755: ISDestroy(&is_I_layer);
1757: /* Get local part of (\sum_j S_Ej) */
1758: if (!sub_schurs->sum_S_Ej_all) {
1759: MatDuplicate(sub_schurs->S_Ej_all,MAT_DO_NOT_COPY_VALUES,&sub_schurs->sum_S_Ej_all);
1760: }
1761: VecSet(gstash,0.0);
1762: MatSeqAIJGetArray(sub_schurs->S_Ej_all,&stasharray);
1763: VecPlaceArray(lstash,stasharray);
1764: VecScatterBegin(sstash,lstash,gstash,ADD_VALUES,SCATTER_FORWARD);
1765: VecScatterEnd(sstash,lstash,gstash,ADD_VALUES,SCATTER_FORWARD);
1766: MatSeqAIJRestoreArray(sub_schurs->S_Ej_all,&stasharray);
1767: VecResetArray(lstash);
1768: MatSeqAIJGetArray(sub_schurs->sum_S_Ej_all,&stasharray);
1769: VecPlaceArray(lstash,stasharray);
1770: VecScatterBegin(sstash,gstash,lstash,INSERT_VALUES,SCATTER_REVERSE);
1771: VecScatterEnd(sstash,gstash,lstash,INSERT_VALUES,SCATTER_REVERSE);
1772: MatSeqAIJRestoreArray(sub_schurs->sum_S_Ej_all,&stasharray);
1773: VecResetArray(lstash);
1775: /* Get local part of (\sum_j S^-1_Ej) (\sum_j St^-1_Ej) */
1776: if (compute_Stilda) {
1777: VecSet(gstash,0.0);
1778: MatSeqAIJGetArray(sub_schurs->sum_S_Ej_tilda_all,&stasharray);
1779: VecPlaceArray(lstash,stasharray);
1780: VecScatterBegin(sstash,lstash,gstash,ADD_VALUES,SCATTER_FORWARD);
1781: VecScatterEnd(sstash,lstash,gstash,ADD_VALUES,SCATTER_FORWARD);
1782: VecScatterBegin(sstash,gstash,lstash,INSERT_VALUES,SCATTER_REVERSE);
1783: VecScatterEnd(sstash,gstash,lstash,INSERT_VALUES,SCATTER_REVERSE);
1784: MatSeqAIJRestoreArray(sub_schurs->sum_S_Ej_tilda_all,&stasharray);
1785: VecResetArray(lstash);
1786: if (deluxe) {
1787: VecSet(gstash,0.0);
1788: MatSeqAIJGetArray(sub_schurs->sum_S_Ej_inv_all,&stasharray);
1789: VecPlaceArray(lstash,stasharray);
1790: VecScatterBegin(sstash,lstash,gstash,ADD_VALUES,SCATTER_FORWARD);
1791: VecScatterEnd(sstash,lstash,gstash,ADD_VALUES,SCATTER_FORWARD);
1792: VecScatterBegin(sstash,gstash,lstash,INSERT_VALUES,SCATTER_REVERSE);
1793: VecScatterEnd(sstash,gstash,lstash,INSERT_VALUES,SCATTER_REVERSE);
1794: MatSeqAIJRestoreArray(sub_schurs->sum_S_Ej_inv_all,&stasharray);
1795: VecResetArray(lstash);
1796: } else {
1797: PetscScalar *array;
1798: PetscInt cum;
1800: MatSeqAIJGetArray(sub_schurs->sum_S_Ej_tilda_all,&array);
1801: cum = 0;
1802: for (i=0;i<sub_schurs->n_subs;i++) {
1803: ISGetLocalSize(sub_schurs->is_subs[i],&subset_size);
1804: PetscBLASIntCast(subset_size,&B_N);
1805: PetscFPTrapPush(PETSC_FP_TRAP_OFF);
1806: if (use_potr) {
1807: PetscStackCallBLAS("LAPACKpotrf",LAPACKpotrf_("L",&B_N,array+cum,&B_N,&B_ierr));
1808: if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRF Lapack routine %d",(int)B_ierr);
1809: PetscStackCallBLAS("LAPACKpotri",LAPACKpotri_("L",&B_N,array+cum,&B_N,&B_ierr));
1810: if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRI Lapack routine %d",(int)B_ierr);
1811: } else if (use_sytr) {
1812: PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_("L",&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 SYTRF Lapack routine %d",(int)B_ierr);
1814: PetscStackCallBLAS("LAPACKsytri",LAPACKsytri_("L",&B_N,array+cum,&B_N,pivots,Bwork,&B_ierr));
1815: if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRI Lapack routine %d",(int)B_ierr);
1816: } else {
1817: PetscStackCallBLAS("LAPACKgetrf",LAPACKgetrf_(&B_N,&B_N,array+cum,&B_N,pivots,&B_ierr));
1818: if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRF Lapack routine %d",(int)B_ierr);
1819: PetscStackCallBLAS("LAPACKgetri",LAPACKgetri_(&B_N,array+cum,&B_N,pivots,Bwork,&B_lwork,&B_ierr));
1820: if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRI Lapack routine %d",(int)B_ierr);
1821: }
1822: PetscLogFlops(1.0*subset_size*subset_size*subset_size);
1823: PetscFPTrapPop();
1824: cum += subset_size*subset_size;
1825: }
1826: MatSeqAIJRestoreArray(sub_schurs->sum_S_Ej_tilda_all,&array);
1827: PetscObjectReference((PetscObject)sub_schurs->sum_S_Ej_all);
1828: MatDestroy(&sub_schurs->sum_S_Ej_inv_all);
1829: sub_schurs->sum_S_Ej_inv_all = sub_schurs->sum_S_Ej_all;
1830: }
1831: }
1832: VecDestroy(&lstash);
1833: VecDestroy(&gstash);
1834: VecScatterDestroy(&sstash);
1836: if (matl_dbg_viewer) {
1837: PetscInt cum;
1839: if (sub_schurs->S_Ej_all) {
1840: PetscObjectSetName((PetscObject)sub_schurs->S_Ej_all,"SE");
1841: MatView(sub_schurs->S_Ej_all,matl_dbg_viewer);
1842: }
1843: if (sub_schurs->sum_S_Ej_all) {
1844: PetscObjectSetName((PetscObject)sub_schurs->sum_S_Ej_all,"SSE");
1845: MatView(sub_schurs->sum_S_Ej_all,matl_dbg_viewer);
1846: }
1847: if (sub_schurs->sum_S_Ej_inv_all) {
1848: PetscObjectSetName((PetscObject)sub_schurs->sum_S_Ej_inv_all,"SSEm");
1849: MatView(sub_schurs->sum_S_Ej_inv_all,matl_dbg_viewer);
1850: }
1851: if (sub_schurs->sum_S_Ej_tilda_all) {
1852: PetscObjectSetName((PetscObject)sub_schurs->sum_S_Ej_tilda_all,"SSEt");
1853: MatView(sub_schurs->sum_S_Ej_tilda_all,matl_dbg_viewer);
1854: }
1855: for (i=0,cum=0;i<sub_schurs->n_subs;i++) {
1856: IS is;
1857: char name[16];
1859: PetscSNPrintf(name,sizeof(name),"IE%D",i);
1860: ISGetLocalSize(sub_schurs->is_subs[i],&subset_size);
1861: ISCreateStride(PETSC_COMM_SELF,subset_size,cum,1,&is);
1862: PetscObjectSetName((PetscObject)is,name);
1863: ISView(is,matl_dbg_viewer);
1864: ISDestroy(&is);
1865: cum += subset_size;
1866: }
1867: }
1869: /* free workspace */
1870: PetscViewerDestroy(&matl_dbg_viewer);
1871: PetscFree2(Bwork,pivots);
1872: PetscCommDestroy(&comm_n);
1873: return(0);
1874: }
1876: PetscErrorCode PCBDDCSubSchursInit(PCBDDCSubSchurs sub_schurs, const char* prefix, IS is_I, IS is_B, PCBDDCGraph graph, ISLocalToGlobalMapping BtoNmap, PetscBool copycc)
1877: {
1878: IS *faces,*edges,*all_cc,vertices;
1879: PetscInt i,n_faces,n_edges,n_all_cc;
1880: PetscBool is_sorted,ispardiso,ismumps;
1881: PetscErrorCode ierr;
1884: ISSorted(is_I,&is_sorted);
1885: if (!is_sorted) SETERRQ(PetscObjectComm((PetscObject)is_I),PETSC_ERR_PLIB,"IS for I dofs should be shorted");
1886: ISSorted(is_B,&is_sorted);
1887: if (!is_sorted) SETERRQ(PetscObjectComm((PetscObject)is_B),PETSC_ERR_PLIB,"IS for B dofs should be shorted");
1889: /* reset any previous data */
1890: PCBDDCSubSchursReset(sub_schurs);
1892: /* get index sets for faces and edges (already sorted by global ordering) */
1893: PCBDDCGraphGetCandidatesIS(graph,&n_faces,&faces,&n_edges,&edges,&vertices);
1894: n_all_cc = n_faces+n_edges;
1895: PetscBTCreate(n_all_cc,&sub_schurs->is_edge);
1896: PetscMalloc1(n_all_cc,&all_cc);
1897: for (i=0;i<n_faces;i++) {
1898: if (copycc) {
1899: ISDuplicate(faces[i],&all_cc[i]);
1900: } else {
1901: PetscObjectReference((PetscObject)faces[i]);
1902: all_cc[i] = faces[i];
1903: }
1904: }
1905: for (i=0;i<n_edges;i++) {
1906: if (copycc) {
1907: ISDuplicate(edges[i],&all_cc[n_faces+i]);
1908: } else {
1909: PetscObjectReference((PetscObject)edges[i]);
1910: all_cc[n_faces+i] = edges[i];
1911: }
1912: PetscBTSet(sub_schurs->is_edge,n_faces+i);
1913: }
1914: PetscObjectReference((PetscObject)vertices);
1915: sub_schurs->is_vertices = vertices;
1916: PCBDDCGraphRestoreCandidatesIS(graph,&n_faces,&faces,&n_edges,&edges,&vertices);
1917: sub_schurs->is_dir = NULL;
1918: PCBDDCGraphGetDirichletDofsB(graph,&sub_schurs->is_dir);
1920: /* Determine if MatFactor can be used */
1921: PetscStrallocpy(prefix,&sub_schurs->prefix);
1922: #if defined(PETSC_HAVE_MUMPS)
1923: PetscStrncpy(sub_schurs->mat_solver_type,MATSOLVERMUMPS,sizeof(sub_schurs->mat_solver_type));
1924: #elif defined(PETSC_HAVE_MKL_PARDISO)
1925: PetscStrncpy(sub_schurs->mat_solver_type,MATSOLVERMKL_PARDISO,sizeof(sub_schurs->mat_solver_type));
1926: #else
1927: PetscStrncpy(sub_schurs->mat_solver_type,MATSOLVERPETSC,sizeof(sub_schurs->mat_solver_type));
1928: #endif
1929: #if defined(PETSC_USE_COMPLEX)
1930: sub_schurs->is_hermitian = PETSC_FALSE; /* Hermitian Cholesky is not supported by PETSc and external packages */
1931: #else
1932: sub_schurs->is_hermitian = PETSC_TRUE;
1933: #endif
1934: sub_schurs->is_posdef = PETSC_TRUE;
1935: sub_schurs->is_symmetric = PETSC_TRUE;
1936: sub_schurs->debug = PETSC_FALSE;
1937: sub_schurs->restrict_comm = PETSC_FALSE;
1938: PetscOptionsBegin(PetscObjectComm((PetscObject)graph->l2gmap),sub_schurs->prefix,"BDDC sub_schurs options","PC");
1939: PetscOptionsString("-sub_schurs_mat_solver_type","Specific direct solver to use",NULL,sub_schurs->mat_solver_type,sub_schurs->mat_solver_type,sizeof(sub_schurs->mat_solver_type),NULL);
1940: PetscOptionsBool("-sub_schurs_symmetric","Symmetric problem",NULL,sub_schurs->is_symmetric,&sub_schurs->is_symmetric,NULL);
1941: PetscOptionsBool("-sub_schurs_hermitian","Hermitian problem",NULL,sub_schurs->is_hermitian,&sub_schurs->is_hermitian,NULL);
1942: PetscOptionsBool("-sub_schurs_posdef","Positive definite problem",NULL,sub_schurs->is_posdef,&sub_schurs->is_posdef,NULL);
1943: PetscOptionsBool("-sub_schurs_restrictcomm","Restrict communicator on active processes only",NULL,sub_schurs->restrict_comm,&sub_schurs->restrict_comm,NULL);
1944: PetscOptionsBool("-sub_schurs_debug","Debug output",NULL,sub_schurs->debug,&sub_schurs->debug,NULL);
1945: PetscOptionsEnd();
1946: PetscStrcmp(sub_schurs->mat_solver_type,MATSOLVERMUMPS,&ismumps);
1947: PetscStrcmp(sub_schurs->mat_solver_type,MATSOLVERMKL_PARDISO,&ispardiso);
1948: sub_schurs->schur_explicit = (PetscBool)(ispardiso || ismumps);
1950: /* for reals, symmetric and hermitian are synonims */
1951: #if !defined(PETSC_USE_COMPLEX)
1952: sub_schurs->is_symmetric = (PetscBool)(sub_schurs->is_symmetric && sub_schurs->is_hermitian);
1953: sub_schurs->is_hermitian = sub_schurs->is_symmetric;
1954: #endif
1956: PetscObjectReference((PetscObject)is_I);
1957: sub_schurs->is_I = is_I;
1958: PetscObjectReference((PetscObject)is_B);
1959: sub_schurs->is_B = is_B;
1960: PetscObjectReference((PetscObject)graph->l2gmap);
1961: sub_schurs->l2gmap = graph->l2gmap;
1962: PetscObjectReference((PetscObject)BtoNmap);
1963: sub_schurs->BtoNmap = BtoNmap;
1964: sub_schurs->n_subs = n_all_cc;
1965: sub_schurs->is_subs = all_cc;
1966: sub_schurs->S_Ej_all = NULL;
1967: sub_schurs->sum_S_Ej_all = NULL;
1968: sub_schurs->sum_S_Ej_inv_all = NULL;
1969: sub_schurs->sum_S_Ej_tilda_all = NULL;
1970: sub_schurs->is_Ej_all = NULL;
1971: return(0);
1972: }
1974: PetscErrorCode PCBDDCSubSchursCreate(PCBDDCSubSchurs *sub_schurs)
1975: {
1976: PCBDDCSubSchurs schurs_ctx;
1977: PetscErrorCode ierr;
1980: PetscNew(&schurs_ctx);
1981: schurs_ctx->n_subs = 0;
1982: *sub_schurs = schurs_ctx;
1983: return(0);
1984: }
1986: PetscErrorCode PCBDDCSubSchursReset(PCBDDCSubSchurs sub_schurs)
1987: {
1988: PetscInt i;
1992: if (!sub_schurs) return(0);
1993: PetscFree(sub_schurs->prefix);
1994: MatDestroy(&sub_schurs->A);
1995: MatDestroy(&sub_schurs->S);
1996: ISDestroy(&sub_schurs->is_I);
1997: ISDestroy(&sub_schurs->is_B);
1998: ISLocalToGlobalMappingDestroy(&sub_schurs->l2gmap);
1999: ISLocalToGlobalMappingDestroy(&sub_schurs->BtoNmap);
2000: MatDestroy(&sub_schurs->S_Ej_all);
2001: MatDestroy(&sub_schurs->sum_S_Ej_all);
2002: MatDestroy(&sub_schurs->sum_S_Ej_inv_all);
2003: MatDestroy(&sub_schurs->sum_S_Ej_tilda_all);
2004: ISDestroy(&sub_schurs->is_Ej_all);
2005: ISDestroy(&sub_schurs->is_vertices);
2006: ISDestroy(&sub_schurs->is_dir);
2007: PetscBTDestroy(&sub_schurs->is_edge);
2008: for (i=0;i<sub_schurs->n_subs;i++) {
2009: ISDestroy(&sub_schurs->is_subs[i]);
2010: }
2011: if (sub_schurs->n_subs) {
2012: PetscFree(sub_schurs->is_subs);
2013: }
2014: if (sub_schurs->reuse_solver) {
2015: PCBDDCReuseSolversReset(sub_schurs->reuse_solver);
2016: }
2017: PetscFree(sub_schurs->reuse_solver);
2018: if (sub_schurs->change) {
2019: for (i=0;i<sub_schurs->n_subs;i++) {
2020: KSPDestroy(&sub_schurs->change[i]);
2021: ISDestroy(&sub_schurs->change_primal_sub[i]);
2022: }
2023: }
2024: PetscFree(sub_schurs->change);
2025: PetscFree(sub_schurs->change_primal_sub);
2026: sub_schurs->n_subs = 0;
2027: return(0);
2028: }
2030: PetscErrorCode PCBDDCSubSchursDestroy(PCBDDCSubSchurs* sub_schurs)
2031: {
2035: PCBDDCSubSchursReset(*sub_schurs);
2036: PetscFree(*sub_schurs);
2037: return(0);
2038: }
2040: PETSC_STATIC_INLINE PetscErrorCode PCBDDCAdjGetNextLayer_Private(PetscInt* queue_tip,PetscInt n_prev,PetscBT touched,PetscInt* xadj,PetscInt* adjncy,PetscInt* n_added)
2041: {
2042: PetscInt i,j,n;
2046: n = 0;
2047: for (i=-n_prev;i<0;i++) {
2048: PetscInt start_dof = queue_tip[i];
2049: for (j=xadj[start_dof];j<xadj[start_dof+1];j++) {
2050: PetscInt dof = adjncy[j];
2051: if (!PetscBTLookup(touched,dof)) {
2052: PetscBTSet(touched,dof);
2053: queue_tip[n] = dof;
2054: n++;
2055: }
2056: }
2057: }
2058: *n_added = n;
2059: return(0);
2060: }