Actual source code: mpiaij.c
petsc-3.13.6 2020-09-29
1: #include <../src/mat/impls/aij/mpi/mpiaij.h>
2: #include <petsc/private/vecimpl.h>
3: #include <petsc/private/vecscatterimpl.h>
4: #include <petsc/private/isimpl.h>
5: #include <petscblaslapack.h>
6: #include <petscsf.h>
7: #include <petsc/private/hashmapi.h>
9: /*MC
10: MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices.
12: This matrix type is identical to MATSEQAIJ when constructed with a single process communicator,
13: and MATMPIAIJ otherwise. As a result, for single process communicators,
14: MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation() is supported
15: for communicators controlling multiple processes. It is recommended that you call both of
16: the above preallocation routines for simplicity.
18: Options Database Keys:
19: . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions()
21: Developer Notes:
22: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJSELL, MATAIJMKL, MATAIJCRL, and also automatically switches over to use inodes when
23: enough exist.
25: Level: beginner
27: .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ, MATMPIAIJ
28: M*/
30: /*MC
31: MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices.
33: This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator,
34: and MATMPIAIJCRL otherwise. As a result, for single process communicators,
35: MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported
36: for communicators controlling multiple processes. It is recommended that you call both of
37: the above preallocation routines for simplicity.
39: Options Database Keys:
40: . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions()
42: Level: beginner
44: .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL
45: M*/
47: static PetscErrorCode MatBindToCPU_MPIAIJ(Mat A,PetscBool flg)
48: {
49: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
53: #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_VIENNACL)
54: A->boundtocpu = flg;
55: #endif
56: if (a->A) {
57: MatBindToCPU(a->A,flg);
58: }
59: if (a->B) {
60: MatBindToCPU(a->B,flg);
61: }
62: return(0);
63: }
66: PetscErrorCode MatSetBlockSizes_MPIAIJ(Mat M, PetscInt rbs, PetscInt cbs)
67: {
69: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data;
72: if (mat->A) {
73: MatSetBlockSizes(mat->A,rbs,cbs);
74: MatSetBlockSizes(mat->B,rbs,1);
75: }
76: return(0);
77: }
79: PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows)
80: {
81: PetscErrorCode ierr;
82: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data;
83: Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data;
84: Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data;
85: const PetscInt *ia,*ib;
86: const MatScalar *aa,*bb;
87: PetscInt na,nb,i,j,*rows,cnt=0,n0rows;
88: PetscInt m = M->rmap->n,rstart = M->rmap->rstart;
91: *keptrows = 0;
92: ia = a->i;
93: ib = b->i;
94: for (i=0; i<m; i++) {
95: na = ia[i+1] - ia[i];
96: nb = ib[i+1] - ib[i];
97: if (!na && !nb) {
98: cnt++;
99: goto ok1;
100: }
101: aa = a->a + ia[i];
102: for (j=0; j<na; j++) {
103: if (aa[j] != 0.0) goto ok1;
104: }
105: bb = b->a + ib[i];
106: for (j=0; j <nb; j++) {
107: if (bb[j] != 0.0) goto ok1;
108: }
109: cnt++;
110: ok1:;
111: }
112: MPIU_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));
113: if (!n0rows) return(0);
114: PetscMalloc1(M->rmap->n-cnt,&rows);
115: cnt = 0;
116: for (i=0; i<m; i++) {
117: na = ia[i+1] - ia[i];
118: nb = ib[i+1] - ib[i];
119: if (!na && !nb) continue;
120: aa = a->a + ia[i];
121: for (j=0; j<na;j++) {
122: if (aa[j] != 0.0) {
123: rows[cnt++] = rstart + i;
124: goto ok2;
125: }
126: }
127: bb = b->a + ib[i];
128: for (j=0; j<nb; j++) {
129: if (bb[j] != 0.0) {
130: rows[cnt++] = rstart + i;
131: goto ok2;
132: }
133: }
134: ok2:;
135: }
136: ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);
137: return(0);
138: }
140: PetscErrorCode MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is)
141: {
142: PetscErrorCode ierr;
143: Mat_MPIAIJ *aij = (Mat_MPIAIJ*) Y->data;
144: PetscBool cong;
147: MatHasCongruentLayouts(Y,&cong);
148: if (Y->assembled && cong) {
149: MatDiagonalSet(aij->A,D,is);
150: } else {
151: MatDiagonalSet_Default(Y,D,is);
152: }
153: return(0);
154: }
156: PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows)
157: {
158: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data;
160: PetscInt i,rstart,nrows,*rows;
163: *zrows = NULL;
164: MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);
165: MatGetOwnershipRange(M,&rstart,NULL);
166: for (i=0; i<nrows; i++) rows[i] += rstart;
167: ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);
168: return(0);
169: }
171: PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms)
172: {
174: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data;
175: PetscInt i,n,*garray = aij->garray;
176: Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data;
177: Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data;
178: PetscReal *work;
181: MatGetSize(A,NULL,&n);
182: PetscCalloc1(n,&work);
183: if (type == NORM_2) {
184: for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
185: work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]);
186: }
187: for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
188: work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]);
189: }
190: } else if (type == NORM_1) {
191: for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
192: work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]);
193: }
194: for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
195: work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]);
196: }
197: } else if (type == NORM_INFINITY) {
198: for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
199: work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]);
200: }
201: for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
202: work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]);
203: }
205: } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType");
206: if (type == NORM_INFINITY) {
207: MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));
208: } else {
209: MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));
210: }
211: PetscFree(work);
212: if (type == NORM_2) {
213: for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]);
214: }
215: return(0);
216: }
218: PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is)
219: {
220: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
221: IS sis,gis;
222: PetscErrorCode ierr;
223: const PetscInt *isis,*igis;
224: PetscInt n,*iis,nsis,ngis,rstart,i;
227: MatFindOffBlockDiagonalEntries(a->A,&sis);
228: MatFindNonzeroRows(a->B,&gis);
229: ISGetSize(gis,&ngis);
230: ISGetSize(sis,&nsis);
231: ISGetIndices(sis,&isis);
232: ISGetIndices(gis,&igis);
234: PetscMalloc1(ngis+nsis,&iis);
235: PetscArraycpy(iis,igis,ngis);
236: PetscArraycpy(iis+ngis,isis,nsis);
237: n = ngis + nsis;
238: PetscSortRemoveDupsInt(&n,iis);
239: MatGetOwnershipRange(A,&rstart,NULL);
240: for (i=0; i<n; i++) iis[i] += rstart;
241: ISCreateGeneral(PetscObjectComm((PetscObject)A),n,iis,PETSC_OWN_POINTER,is);
243: ISRestoreIndices(sis,&isis);
244: ISRestoreIndices(gis,&igis);
245: ISDestroy(&sis);
246: ISDestroy(&gis);
247: return(0);
248: }
250: /*
251: Distributes a SeqAIJ matrix across a set of processes. Code stolen from
252: MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type.
254: Only for square matrices
256: Used by a preconditioner, hence PETSC_EXTERN
257: */
258: PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat)
259: {
260: PetscMPIInt rank,size;
261: PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2];
263: Mat mat;
264: Mat_SeqAIJ *gmata;
265: PetscMPIInt tag;
266: MPI_Status status;
267: PetscBool aij;
268: MatScalar *gmataa,*ao,*ad,*gmataarestore=0;
271: MPI_Comm_rank(comm,&rank);
272: MPI_Comm_size(comm,&size);
273: if (!rank) {
274: PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);
275: if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name);
276: }
277: if (reuse == MAT_INITIAL_MATRIX) {
278: MatCreate(comm,&mat);
279: MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);
280: MatGetBlockSizes(gmat,&bses[0],&bses[1]);
281: MPI_Bcast(bses,2,MPIU_INT,0,comm);
282: MatSetBlockSizes(mat,bses[0],bses[1]);
283: MatSetType(mat,MATAIJ);
284: PetscMalloc1(size+1,&rowners);
285: PetscMalloc2(m,&dlens,m,&olens);
286: MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);
288: rowners[0] = 0;
289: for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
290: rstart = rowners[rank];
291: rend = rowners[rank+1];
292: PetscObjectGetNewTag((PetscObject)mat,&tag);
293: if (!rank) {
294: gmata = (Mat_SeqAIJ*) gmat->data;
295: /* send row lengths to all processors */
296: for (i=0; i<m; i++) dlens[i] = gmata->ilen[i];
297: for (i=1; i<size; i++) {
298: MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);
299: }
300: /* determine number diagonal and off-diagonal counts */
301: PetscArrayzero(olens,m);
302: PetscCalloc1(m,&ld);
303: jj = 0;
304: for (i=0; i<m; i++) {
305: for (j=0; j<dlens[i]; j++) {
306: if (gmata->j[jj] < rstart) ld[i]++;
307: if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++;
308: jj++;
309: }
310: }
311: /* send column indices to other processes */
312: for (i=1; i<size; i++) {
313: nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
314: MPI_Send(&nz,1,MPIU_INT,i,tag,comm);
315: MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);
316: }
318: /* send numerical values to other processes */
319: for (i=1; i<size; i++) {
320: nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
321: MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);
322: }
323: gmataa = gmata->a;
324: gmataj = gmata->j;
326: } else {
327: /* receive row lengths */
328: MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);
329: /* receive column indices */
330: MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);
331: PetscMalloc2(nz,&gmataa,nz,&gmataj);
332: MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);
333: /* determine number diagonal and off-diagonal counts */
334: PetscArrayzero(olens,m);
335: PetscCalloc1(m,&ld);
336: jj = 0;
337: for (i=0; i<m; i++) {
338: for (j=0; j<dlens[i]; j++) {
339: if (gmataj[jj] < rstart) ld[i]++;
340: if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++;
341: jj++;
342: }
343: }
344: /* receive numerical values */
345: PetscArrayzero(gmataa,nz);
346: MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);
347: }
348: /* set preallocation */
349: for (i=0; i<m; i++) {
350: dlens[i] -= olens[i];
351: }
352: MatSeqAIJSetPreallocation(mat,0,dlens);
353: MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);
355: for (i=0; i<m; i++) {
356: dlens[i] += olens[i];
357: }
358: cnt = 0;
359: for (i=0; i<m; i++) {
360: row = rstart + i;
361: MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);
362: cnt += dlens[i];
363: }
364: if (rank) {
365: PetscFree2(gmataa,gmataj);
366: }
367: PetscFree2(dlens,olens);
368: PetscFree(rowners);
370: ((Mat_MPIAIJ*)(mat->data))->ld = ld;
372: *inmat = mat;
373: } else { /* column indices are already set; only need to move over numerical values from process 0 */
374: Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data;
375: Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data;
376: mat = *inmat;
377: PetscObjectGetNewTag((PetscObject)mat,&tag);
378: if (!rank) {
379: /* send numerical values to other processes */
380: gmata = (Mat_SeqAIJ*) gmat->data;
381: MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);
382: gmataa = gmata->a;
383: for (i=1; i<size; i++) {
384: nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
385: MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);
386: }
387: nz = gmata->i[rowners[1]]-gmata->i[rowners[0]];
388: } else {
389: /* receive numerical values from process 0*/
390: nz = Ad->nz + Ao->nz;
391: PetscMalloc1(nz,&gmataa); gmataarestore = gmataa;
392: MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);
393: }
394: /* transfer numerical values into the diagonal A and off diagonal B parts of mat */
395: ld = ((Mat_MPIAIJ*)(mat->data))->ld;
396: ad = Ad->a;
397: ao = Ao->a;
398: if (mat->rmap->n) {
399: i = 0;
400: nz = ld[i]; PetscArraycpy(ao,gmataa,nz); ao += nz; gmataa += nz;
401: nz = Ad->i[i+1] - Ad->i[i]; PetscArraycpy(ad,gmataa,nz); ad += nz; gmataa += nz;
402: }
403: for (i=1; i<mat->rmap->n; i++) {
404: nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; PetscArraycpy(ao,gmataa,nz); ao += nz; gmataa += nz;
405: nz = Ad->i[i+1] - Ad->i[i]; PetscArraycpy(ad,gmataa,nz); ad += nz; gmataa += nz;
406: }
407: i--;
408: if (mat->rmap->n) {
409: nz = Ao->i[i+1] - Ao->i[i] - ld[i]; PetscArraycpy(ao,gmataa,nz);
410: }
411: if (rank) {
412: PetscFree(gmataarestore);
413: }
414: }
415: MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);
416: MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);
417: return(0);
418: }
420: /*
421: Local utility routine that creates a mapping from the global column
422: number to the local number in the off-diagonal part of the local
423: storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at
424: a slightly higher hash table cost; without it it is not scalable (each processor
425: has an order N integer array but is fast to acess.
426: */
427: PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat)
428: {
429: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
431: PetscInt n = aij->B->cmap->n,i;
434: if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray");
435: #if defined(PETSC_USE_CTABLE)
436: PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);
437: for (i=0; i<n; i++) {
438: PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);
439: }
440: #else
441: PetscCalloc1(mat->cmap->N+1,&aij->colmap);
442: PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));
443: for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1;
444: #endif
445: return(0);
446: }
448: #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,orow,ocol) \
449: { \
450: if (col <= lastcol1) low1 = 0; \
451: else high1 = nrow1; \
452: lastcol1 = col;\
453: while (high1-low1 > 5) { \
454: t = (low1+high1)/2; \
455: if (rp1[t] > col) high1 = t; \
456: else low1 = t; \
457: } \
458: for (_i=low1; _i<high1; _i++) { \
459: if (rp1[_i] > col) break; \
460: if (rp1[_i] == col) { \
461: if (addv == ADD_VALUES) { \
462: ap1[_i] += value; \
463: /* Not sure LogFlops will slow dow the code or not */ \
464: (void)PetscLogFlops(1.0); \
465: } \
466: else ap1[_i] = value; \
467: inserted = PETSC_TRUE; \
468: goto a_noinsert; \
469: } \
470: } \
471: if (value == 0.0 && ignorezeroentries && row != col) {low1 = 0; high1 = nrow1;goto a_noinsert;} \
472: if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \
473: if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
474: MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \
475: N = nrow1++ - 1; a->nz++; high1++; \
476: /* shift up all the later entries in this row */ \
477: PetscArraymove(rp1+_i+1,rp1+_i,N-_i+1);\
478: PetscArraymove(ap1+_i+1,ap1+_i,N-_i+1);\
479: rp1[_i] = col; \
480: ap1[_i] = value; \
481: A->nonzerostate++;\
482: a_noinsert: ; \
483: ailen[row] = nrow1; \
484: }
486: #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv,orow,ocol) \
487: { \
488: if (col <= lastcol2) low2 = 0; \
489: else high2 = nrow2; \
490: lastcol2 = col; \
491: while (high2-low2 > 5) { \
492: t = (low2+high2)/2; \
493: if (rp2[t] > col) high2 = t; \
494: else low2 = t; \
495: } \
496: for (_i=low2; _i<high2; _i++) { \
497: if (rp2[_i] > col) break; \
498: if (rp2[_i] == col) { \
499: if (addv == ADD_VALUES) { \
500: ap2[_i] += value; \
501: (void)PetscLogFlops(1.0); \
502: } \
503: else ap2[_i] = value; \
504: inserted = PETSC_TRUE; \
505: goto b_noinsert; \
506: } \
507: } \
508: if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
509: if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
510: if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
511: MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \
512: N = nrow2++ - 1; b->nz++; high2++; \
513: /* shift up all the later entries in this row */ \
514: PetscArraymove(rp2+_i+1,rp2+_i,N-_i+1);\
515: PetscArraymove(ap2+_i+1,ap2+_i,N-_i+1);\
516: rp2[_i] = col; \
517: ap2[_i] = value; \
518: B->nonzerostate++; \
519: b_noinsert: ; \
520: bilen[row] = nrow2; \
521: }
523: PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[])
524: {
525: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data;
526: Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data;
528: PetscInt l,*garray = mat->garray,diag;
531: /* code only works for square matrices A */
533: /* find size of row to the left of the diagonal part */
534: MatGetOwnershipRange(A,&diag,0);
535: row = row - diag;
536: for (l=0; l<b->i[row+1]-b->i[row]; l++) {
537: if (garray[b->j[b->i[row]+l]] > diag) break;
538: }
539: PetscArraycpy(b->a+b->i[row],v,l);
541: /* diagonal part */
542: PetscArraycpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row]));
544: /* right of diagonal part */
545: PetscArraycpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],b->i[row+1]-b->i[row]-l);
546: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
547: if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED && (l || (a->i[row+1]-a->i[row]) || (b->i[row+1]-b->i[row]-l))) A->offloadmask = PETSC_OFFLOAD_CPU;
548: #endif
549: return(0);
550: }
552: PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
553: {
554: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
555: PetscScalar value = 0.0;
557: PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend;
558: PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
559: PetscBool roworiented = aij->roworiented;
561: /* Some Variables required in the macro */
562: Mat A = aij->A;
563: Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data;
564: PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j;
565: MatScalar *aa = a->a;
566: PetscBool ignorezeroentries = a->ignorezeroentries;
567: Mat B = aij->B;
568: Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data;
569: PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n;
570: MatScalar *ba = b->a;
571: /* This variable below is only for the PETSC_HAVE_VIENNACL or PETSC_HAVE_CUDA cases, but we define it in all cases because we
572: * cannot use "#if defined" inside a macro. */
573: PETSC_UNUSED PetscBool inserted = PETSC_FALSE;
575: PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2;
576: PetscInt nonew;
577: MatScalar *ap1,*ap2;
580: for (i=0; i<m; i++) {
581: if (im[i] < 0) continue;
582: #if defined(PETSC_USE_DEBUG)
583: if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1);
584: #endif
585: if (im[i] >= rstart && im[i] < rend) {
586: row = im[i] - rstart;
587: lastcol1 = -1;
588: rp1 = aj + ai[row];
589: ap1 = aa + ai[row];
590: rmax1 = aimax[row];
591: nrow1 = ailen[row];
592: low1 = 0;
593: high1 = nrow1;
594: lastcol2 = -1;
595: rp2 = bj + bi[row];
596: ap2 = ba + bi[row];
597: rmax2 = bimax[row];
598: nrow2 = bilen[row];
599: low2 = 0;
600: high2 = nrow2;
602: for (j=0; j<n; j++) {
603: if (v) value = roworiented ? v[i*n+j] : v[i+j*m];
604: if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && im[i] != in[j]) continue;
605: if (in[j] >= cstart && in[j] < cend) {
606: col = in[j] - cstart;
607: nonew = a->nonew;
608: MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]);
609: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
610: if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED && inserted) A->offloadmask = PETSC_OFFLOAD_CPU;
611: #endif
612: } else if (in[j] < 0) continue;
613: #if defined(PETSC_USE_DEBUG)
614: else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1);
615: #endif
616: else {
617: if (mat->was_assembled) {
618: if (!aij->colmap) {
619: MatCreateColmap_MPIAIJ_Private(mat);
620: }
621: #if defined(PETSC_USE_CTABLE)
622: PetscTableFind(aij->colmap,in[j]+1,&col);
623: col--;
624: #else
625: col = aij->colmap[in[j]] - 1;
626: #endif
627: if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) {
628: MatDisAssemble_MPIAIJ(mat);
629: col = in[j];
630: /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
631: B = aij->B;
632: b = (Mat_SeqAIJ*)B->data;
633: bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a;
634: rp2 = bj + bi[row];
635: ap2 = ba + bi[row];
636: rmax2 = bimax[row];
637: nrow2 = bilen[row];
638: low2 = 0;
639: high2 = nrow2;
640: bm = aij->B->rmap->n;
641: ba = b->a;
642: inserted = PETSC_FALSE;
643: } else if (col < 0) {
644: if (1 == ((Mat_SeqAIJ*)(aij->B->data))->nonew) {
645: PetscInfo3(mat,"Skipping of insertion of new nonzero location in off-diagonal portion of matrix %g(%D,%D)\n",(double)PetscRealPart(value),im[i],in[j]);
646: } else SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", im[i], in[j]);
647: }
648: } else col = in[j];
649: nonew = b->nonew;
650: MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]);
651: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
652: if (B->offloadmask != PETSC_OFFLOAD_UNALLOCATED && inserted) B->offloadmask = PETSC_OFFLOAD_CPU;
653: #endif
654: }
655: }
656: } else {
657: if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]);
658: if (!aij->donotstash) {
659: mat->assembled = PETSC_FALSE;
660: if (roworiented) {
661: MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
662: } else {
663: MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
664: }
665: }
666: }
667: }
668: return(0);
669: }
671: /*
672: This function sets the j and ilen arrays (of the diagonal and off-diagonal part) of an MPIAIJ-matrix.
673: The values in mat_i have to be sorted and the values in mat_j have to be sorted for each row (CSR-like).
674: No off-processor parts off the matrix are allowed here and mat->was_assembled has to be PETSC_FALSE.
675: */
676: PetscErrorCode MatSetValues_MPIAIJ_CopyFromCSRFormat_Symbolic(Mat mat,const PetscInt mat_j[],const PetscInt mat_i[])
677: {
678: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
679: Mat A = aij->A; /* diagonal part of the matrix */
680: Mat B = aij->B; /* offdiagonal part of the matrix */
681: Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data;
682: Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data;
683: PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,col;
684: PetscInt *ailen = a->ilen,*aj = a->j;
685: PetscInt *bilen = b->ilen,*bj = b->j;
686: PetscInt am = aij->A->rmap->n,j;
687: PetscInt diag_so_far = 0,dnz;
688: PetscInt offd_so_far = 0,onz;
691: /* Iterate over all rows of the matrix */
692: for (j=0; j<am; j++) {
693: dnz = onz = 0;
694: /* Iterate over all non-zero columns of the current row */
695: for (col=mat_i[j]; col<mat_i[j+1]; col++) {
696: /* If column is in the diagonal */
697: if (mat_j[col] >= cstart && mat_j[col] < cend) {
698: aj[diag_so_far++] = mat_j[col] - cstart;
699: dnz++;
700: } else { /* off-diagonal entries */
701: bj[offd_so_far++] = mat_j[col];
702: onz++;
703: }
704: }
705: ailen[j] = dnz;
706: bilen[j] = onz;
707: }
708: return(0);
709: }
711: /*
712: This function sets the local j, a and ilen arrays (of the diagonal and off-diagonal part) of an MPIAIJ-matrix.
713: The values in mat_i have to be sorted and the values in mat_j have to be sorted for each row (CSR-like).
714: No off-processor parts off the matrix are allowed here, they are set at a later point by MatSetValues_MPIAIJ.
715: Also, mat->was_assembled has to be false, otherwise the statement aj[rowstart_diag+dnz_row] = mat_j[col] - cstart;
716: would not be true and the more complex MatSetValues_MPIAIJ has to be used.
717: */
718: PetscErrorCode MatSetValues_MPIAIJ_CopyFromCSRFormat(Mat mat,const PetscInt mat_j[],const PetscInt mat_i[],const PetscScalar mat_a[])
719: {
720: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
721: Mat A = aij->A; /* diagonal part of the matrix */
722: Mat B = aij->B; /* offdiagonal part of the matrix */
723: Mat_SeqAIJ *aijd =(Mat_SeqAIJ*)(aij->A)->data,*aijo=(Mat_SeqAIJ*)(aij->B)->data;
724: Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data;
725: Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data;
726: PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend;
727: PetscInt *ailen = a->ilen,*aj = a->j;
728: PetscInt *bilen = b->ilen,*bj = b->j;
729: PetscInt am = aij->A->rmap->n,j;
730: PetscInt *full_diag_i=aijd->i,*full_offd_i=aijo->i; /* These variables can also include non-local elements, which are set at a later point. */
731: PetscInt col,dnz_row,onz_row,rowstart_diag,rowstart_offd;
732: PetscScalar *aa = a->a,*ba = b->a;
735: /* Iterate over all rows of the matrix */
736: for (j=0; j<am; j++) {
737: dnz_row = onz_row = 0;
738: rowstart_offd = full_offd_i[j];
739: rowstart_diag = full_diag_i[j];
740: /* Iterate over all non-zero columns of the current row */
741: for (col=mat_i[j]; col<mat_i[j+1]; col++) {
742: /* If column is in the diagonal */
743: if (mat_j[col] >= cstart && mat_j[col] < cend) {
744: aj[rowstart_diag+dnz_row] = mat_j[col] - cstart;
745: aa[rowstart_diag+dnz_row] = mat_a[col];
746: dnz_row++;
747: } else { /* off-diagonal entries */
748: bj[rowstart_offd+onz_row] = mat_j[col];
749: ba[rowstart_offd+onz_row] = mat_a[col];
750: onz_row++;
751: }
752: }
753: ailen[j] = dnz_row;
754: bilen[j] = onz_row;
755: }
756: return(0);
757: }
759: PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
760: {
761: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
763: PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend;
764: PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
767: for (i=0; i<m; i++) {
768: if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/
769: if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1);
770: if (idxm[i] >= rstart && idxm[i] < rend) {
771: row = idxm[i] - rstart;
772: for (j=0; j<n; j++) {
773: if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */
774: if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1);
775: if (idxn[j] >= cstart && idxn[j] < cend) {
776: col = idxn[j] - cstart;
777: MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);
778: } else {
779: if (!aij->colmap) {
780: MatCreateColmap_MPIAIJ_Private(mat);
781: }
782: #if defined(PETSC_USE_CTABLE)
783: PetscTableFind(aij->colmap,idxn[j]+1,&col);
784: col--;
785: #else
786: col = aij->colmap[idxn[j]] - 1;
787: #endif
788: if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0;
789: else {
790: MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);
791: }
792: }
793: }
794: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
795: }
796: return(0);
797: }
799: extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec);
801: PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode)
802: {
803: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
805: PetscInt nstash,reallocs;
808: if (aij->donotstash || mat->nooffprocentries) return(0);
810: MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
811: MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
812: PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
813: return(0);
814: }
816: PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode)
817: {
818: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
819: Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data;
821: PetscMPIInt n;
822: PetscInt i,j,rstart,ncols,flg;
823: PetscInt *row,*col;
824: PetscBool other_disassembled;
825: PetscScalar *val;
827: /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */
830: if (!aij->donotstash && !mat->nooffprocentries) {
831: while (1) {
832: MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
833: if (!flg) break;
835: for (i=0; i<n; ) {
836: /* Now identify the consecutive vals belonging to the same row */
837: for (j=i,rstart=row[j]; j<n; j++) {
838: if (row[j] != rstart) break;
839: }
840: if (j < n) ncols = j-i;
841: else ncols = n-i;
842: /* Now assemble all these values with a single function call */
843: MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);
844: i = j;
845: }
846: }
847: MatStashScatterEnd_Private(&mat->stash);
848: }
849: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
850: if (mat->offloadmask == PETSC_OFFLOAD_CPU) aij->A->offloadmask = PETSC_OFFLOAD_CPU;
851: /* We call MatBindToCPU() on aij->A and aij->B here, because if MatBindToCPU_MPIAIJ() is called before assembly, it cannot bind these. */
852: if (mat->boundtocpu) {
853: MatBindToCPU(aij->A,PETSC_TRUE);
854: MatBindToCPU(aij->B,PETSC_TRUE);
855: }
856: #endif
857: MatAssemblyBegin(aij->A,mode);
858: MatAssemblyEnd(aij->A,mode);
860: /* determine if any processor has disassembled, if so we must
861: also disassemble ourself, in order that we may reassemble. */
862: /*
863: if nonzero structure of submatrix B cannot change then we know that
864: no processor disassembled thus we can skip this stuff
865: */
866: if (!((Mat_SeqAIJ*)aij->B->data)->nonew) {
867: MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
868: if (mat->was_assembled && !other_disassembled) {
869: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
870: aij->B->offloadmask = PETSC_OFFLOAD_BOTH; /* do not copy on the GPU when assembling inside MatDisAssemble_MPIAIJ */
871: #endif
872: MatDisAssemble_MPIAIJ(mat);
873: }
874: }
875: if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
876: MatSetUpMultiply_MPIAIJ(mat);
877: }
878: MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);
879: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
880: if (mat->offloadmask == PETSC_OFFLOAD_CPU && aij->B->offloadmask != PETSC_OFFLOAD_UNALLOCATED) aij->B->offloadmask = PETSC_OFFLOAD_CPU;
881: #endif
882: MatAssemblyBegin(aij->B,mode);
883: MatAssemblyEnd(aij->B,mode);
885: PetscFree2(aij->rowvalues,aij->rowindices);
887: aij->rowvalues = 0;
889: VecDestroy(&aij->diag);
890: if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ;
892: /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
893: if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
894: PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate;
895: MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
896: }
897: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
898: mat->offloadmask = PETSC_OFFLOAD_BOTH;
899: #endif
900: return(0);
901: }
903: PetscErrorCode MatZeroEntries_MPIAIJ(Mat A)
904: {
905: Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data;
909: MatZeroEntries(l->A);
910: MatZeroEntries(l->B);
911: return(0);
912: }
914: PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
915: {
916: Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data;
917: PetscObjectState sA, sB;
918: PetscInt *lrows;
919: PetscInt r, len;
920: PetscBool cong, lch, gch;
921: PetscErrorCode ierr;
924: /* get locally owned rows */
925: MatZeroRowsMapLocal_Private(A,N,rows,&len,&lrows);
926: MatHasCongruentLayouts(A,&cong);
927: /* fix right hand side if needed */
928: if (x && b) {
929: const PetscScalar *xx;
930: PetscScalar *bb;
932: if (!cong) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Need matching row/col layout");
933: VecGetArrayRead(x, &xx);
934: VecGetArray(b, &bb);
935: for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]];
936: VecRestoreArrayRead(x, &xx);
937: VecRestoreArray(b, &bb);
938: }
940: sA = mat->A->nonzerostate;
941: sB = mat->B->nonzerostate;
943: if (diag != 0.0 && cong) {
944: MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);
945: MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);
946: } else if (diag != 0.0) { /* non-square or non congruent layouts -> if keepnonzeropattern is false, we allow for new insertion */
947: Mat_SeqAIJ *aijA = (Mat_SeqAIJ*)mat->A->data;
948: Mat_SeqAIJ *aijB = (Mat_SeqAIJ*)mat->B->data;
949: PetscInt nnwA, nnwB;
950: PetscBool nnzA, nnzB;
952: nnwA = aijA->nonew;
953: nnwB = aijB->nonew;
954: nnzA = aijA->keepnonzeropattern;
955: nnzB = aijB->keepnonzeropattern;
956: if (!nnzA) {
957: PetscInfo(mat->A,"Requested to not keep the pattern and add a nonzero diagonal; may encounter reallocations on diagonal block.\n");
958: aijA->nonew = 0;
959: }
960: if (!nnzB) {
961: PetscInfo(mat->B,"Requested to not keep the pattern and add a nonzero diagonal; may encounter reallocations on off-diagonal block.\n");
962: aijB->nonew = 0;
963: }
964: /* Must zero here before the next loop */
965: MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);
966: MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);
967: for (r = 0; r < len; ++r) {
968: const PetscInt row = lrows[r] + A->rmap->rstart;
969: if (row >= A->cmap->N) continue;
970: MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);
971: }
972: aijA->nonew = nnwA;
973: aijB->nonew = nnwB;
974: } else {
975: MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);
976: MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);
977: }
978: PetscFree(lrows);
979: MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
980: MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
982: /* reduce nonzerostate */
983: lch = (PetscBool)(sA != mat->A->nonzerostate || sB != mat->B->nonzerostate);
984: MPIU_Allreduce(&lch,&gch,1,MPIU_BOOL,MPI_LOR,PetscObjectComm((PetscObject)A));
985: if (gch) A->nonzerostate++;
986: return(0);
987: }
989: PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
990: {
991: Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data;
992: PetscErrorCode ierr;
993: PetscMPIInt n = A->rmap->n;
994: PetscInt i,j,r,m,len = 0;
995: PetscInt *lrows,*owners = A->rmap->range;
996: PetscMPIInt p = 0;
997: PetscSFNode *rrows;
998: PetscSF sf;
999: const PetscScalar *xx;
1000: PetscScalar *bb,*mask;
1001: Vec xmask,lmask;
1002: Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data;
1003: const PetscInt *aj, *ii,*ridx;
1004: PetscScalar *aa;
1007: /* Create SF where leaves are input rows and roots are owned rows */
1008: PetscMalloc1(n, &lrows);
1009: for (r = 0; r < n; ++r) lrows[r] = -1;
1010: PetscMalloc1(N, &rrows);
1011: for (r = 0; r < N; ++r) {
1012: const PetscInt idx = rows[r];
1013: if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N);
1014: if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */
1015: PetscLayoutFindOwner(A->rmap,idx,&p);
1016: }
1017: rrows[r].rank = p;
1018: rrows[r].index = rows[r] - owners[p];
1019: }
1020: PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);
1021: PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);
1022: /* Collect flags for rows to be zeroed */
1023: PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
1024: PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
1025: PetscSFDestroy(&sf);
1026: /* Compress and put in row numbers */
1027: for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r;
1028: /* zero diagonal part of matrix */
1029: MatZeroRowsColumns(l->A,len,lrows,diag,x,b);
1030: /* handle off diagonal part of matrix */
1031: MatCreateVecs(A,&xmask,NULL);
1032: VecDuplicate(l->lvec,&lmask);
1033: VecGetArray(xmask,&bb);
1034: for (i=0; i<len; i++) bb[lrows[i]] = 1;
1035: VecRestoreArray(xmask,&bb);
1036: VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
1037: VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
1038: VecDestroy(&xmask);
1039: if (x && b) { /* this code is buggy when the row and column layout don't match */
1040: PetscBool cong;
1042: MatHasCongruentLayouts(A,&cong);
1043: if (!cong) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Need matching row/col layout");
1044: VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
1045: VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
1046: VecGetArrayRead(l->lvec,&xx);
1047: VecGetArray(b,&bb);
1048: }
1049: VecGetArray(lmask,&mask);
1050: /* remove zeroed rows of off diagonal matrix */
1051: ii = aij->i;
1052: for (i=0; i<len; i++) {
1053: PetscArrayzero(aij->a + ii[lrows[i]],ii[lrows[i]+1] - ii[lrows[i]]);
1054: }
1055: /* loop over all elements of off process part of matrix zeroing removed columns*/
1056: if (aij->compressedrow.use) {
1057: m = aij->compressedrow.nrows;
1058: ii = aij->compressedrow.i;
1059: ridx = aij->compressedrow.rindex;
1060: for (i=0; i<m; i++) {
1061: n = ii[i+1] - ii[i];
1062: aj = aij->j + ii[i];
1063: aa = aij->a + ii[i];
1065: for (j=0; j<n; j++) {
1066: if (PetscAbsScalar(mask[*aj])) {
1067: if (b) bb[*ridx] -= *aa*xx[*aj];
1068: *aa = 0.0;
1069: }
1070: aa++;
1071: aj++;
1072: }
1073: ridx++;
1074: }
1075: } else { /* do not use compressed row format */
1076: m = l->B->rmap->n;
1077: for (i=0; i<m; i++) {
1078: n = ii[i+1] - ii[i];
1079: aj = aij->j + ii[i];
1080: aa = aij->a + ii[i];
1081: for (j=0; j<n; j++) {
1082: if (PetscAbsScalar(mask[*aj])) {
1083: if (b) bb[i] -= *aa*xx[*aj];
1084: *aa = 0.0;
1085: }
1086: aa++;
1087: aj++;
1088: }
1089: }
1090: }
1091: if (x && b) {
1092: VecRestoreArray(b,&bb);
1093: VecRestoreArrayRead(l->lvec,&xx);
1094: }
1095: VecRestoreArray(lmask,&mask);
1096: VecDestroy(&lmask);
1097: PetscFree(lrows);
1099: /* only change matrix nonzero state if pattern was allowed to be changed */
1100: if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) {
1101: PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate;
1102: MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));
1103: }
1104: return(0);
1105: }
1107: PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy)
1108: {
1109: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1111: PetscInt nt;
1112: VecScatter Mvctx = a->Mvctx;
1115: VecGetLocalSize(xx,&nt);
1116: if (nt != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap->n,nt);
1117: VecScatterBegin(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1118: (*a->A->ops->mult)(a->A,xx,yy);
1119: VecScatterEnd(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1120: (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
1121: return(0);
1122: }
1124: PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx)
1125: {
1126: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1130: MatMultDiagonalBlock(a->A,bb,xx);
1131: return(0);
1132: }
1134: PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1135: {
1136: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1138: VecScatter Mvctx = a->Mvctx;
1141: if (a->Mvctx_mpi1_flg) Mvctx = a->Mvctx_mpi1;
1142: VecScatterBegin(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1143: (*a->A->ops->multadd)(a->A,xx,yy,zz);
1144: VecScatterEnd(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1145: (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);
1146: return(0);
1147: }
1149: PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy)
1150: {
1151: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1155: /* do nondiagonal part */
1156: (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1157: /* do local part */
1158: (*a->A->ops->multtranspose)(a->A,xx,yy);
1159: /* add partial results together */
1160: VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1161: VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1162: return(0);
1163: }
1165: PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f)
1166: {
1167: MPI_Comm comm;
1168: Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij;
1169: Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs;
1170: IS Me,Notme;
1172: PetscInt M,N,first,last,*notme,i;
1173: PetscBool lf;
1174: PetscMPIInt size;
1177: /* Easy test: symmetric diagonal block */
1178: Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A;
1179: MatIsTranspose(Adia,Bdia,tol,&lf);
1180: MPIU_Allreduce(&lf,f,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)Amat));
1181: if (!*f) return(0);
1182: PetscObjectGetComm((PetscObject)Amat,&comm);
1183: MPI_Comm_size(comm,&size);
1184: if (size == 1) return(0);
1186: /* Hard test: off-diagonal block. This takes a MatCreateSubMatrix. */
1187: MatGetSize(Amat,&M,&N);
1188: MatGetOwnershipRange(Amat,&first,&last);
1189: PetscMalloc1(N-last+first,¬me);
1190: for (i=0; i<first; i++) notme[i] = i;
1191: for (i=last; i<M; i++) notme[i-last+first] = i;
1192: ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);
1193: ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);
1194: MatCreateSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);
1195: Aoff = Aoffs[0];
1196: MatCreateSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);
1197: Boff = Boffs[0];
1198: MatIsTranspose(Aoff,Boff,tol,f);
1199: MatDestroyMatrices(1,&Aoffs);
1200: MatDestroyMatrices(1,&Boffs);
1201: ISDestroy(&Me);
1202: ISDestroy(&Notme);
1203: PetscFree(notme);
1204: return(0);
1205: }
1207: PetscErrorCode MatIsSymmetric_MPIAIJ(Mat A,PetscReal tol,PetscBool *f)
1208: {
1212: MatIsTranspose_MPIAIJ(A,A,tol,f);
1213: return(0);
1214: }
1216: PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1217: {
1218: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1222: /* do nondiagonal part */
1223: (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1224: /* do local part */
1225: (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);
1226: /* add partial results together */
1227: VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1228: VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1229: return(0);
1230: }
1232: /*
1233: This only works correctly for square matrices where the subblock A->A is the
1234: diagonal block
1235: */
1236: PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v)
1237: {
1239: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1242: if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
1243: if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"row partition must equal col partition");
1244: MatGetDiagonal(a->A,v);
1245: return(0);
1246: }
1248: PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa)
1249: {
1250: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1254: MatScale(a->A,aa);
1255: MatScale(a->B,aa);
1256: return(0);
1257: }
1259: PetscErrorCode MatDestroy_MPIAIJ(Mat mat)
1260: {
1261: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1265: #if defined(PETSC_USE_LOG)
1266: PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N);
1267: #endif
1268: MatStashDestroy_Private(&mat->stash);
1269: VecDestroy(&aij->diag);
1270: MatDestroy(&aij->A);
1271: MatDestroy(&aij->B);
1272: #if defined(PETSC_USE_CTABLE)
1273: PetscTableDestroy(&aij->colmap);
1274: #else
1275: PetscFree(aij->colmap);
1276: #endif
1277: PetscFree(aij->garray);
1278: VecDestroy(&aij->lvec);
1279: VecScatterDestroy(&aij->Mvctx);
1280: if (aij->Mvctx_mpi1) {VecScatterDestroy(&aij->Mvctx_mpi1);}
1281: PetscFree2(aij->rowvalues,aij->rowindices);
1282: PetscFree(aij->ld);
1283: PetscFree(mat->data);
1285: PetscObjectChangeTypeName((PetscObject)mat,0);
1286: PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
1287: PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
1288: PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);
1289: PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);
1290: PetscObjectComposeFunction((PetscObject)mat,"MatResetPreallocation_C",NULL);
1291: PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);
1292: PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);
1293: PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpibaij_C",NULL);
1294: PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);
1295: #if defined(PETSC_HAVE_ELEMENTAL)
1296: PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);
1297: #endif
1298: #if defined(PETSC_HAVE_HYPRE)
1299: PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_hypre_C",NULL);
1300: PetscObjectComposeFunction((PetscObject)mat,"MatProductSetFromOptions_transpose_mpiaij_mpiaij_C",NULL);
1301: #endif
1302: PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_is_C",NULL);
1303: PetscObjectComposeFunction((PetscObject)mat,"MatProductSetFromOptions_is_mpiaij_C",NULL);
1304: PetscObjectComposeFunction((PetscObject)mat,"MatProductSetFromOptions_mpiaij_mpiaij_C",NULL);
1305: return(0);
1306: }
1308: PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer)
1309: {
1310: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1311: Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data;
1312: Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data;
1313: const PetscInt *garray = aij->garray;
1314: PetscInt header[4],M,N,m,rs,cs,nz,cnt,i,ja,jb;
1315: PetscInt *rowlens;
1316: PetscInt *colidxs;
1317: PetscScalar *matvals;
1318: PetscErrorCode ierr;
1321: PetscViewerSetUp(viewer);
1323: M = mat->rmap->N;
1324: N = mat->cmap->N;
1325: m = mat->rmap->n;
1326: rs = mat->rmap->rstart;
1327: cs = mat->cmap->rstart;
1328: nz = A->nz + B->nz;
1330: /* write matrix header */
1331: header[0] = MAT_FILE_CLASSID;
1332: header[1] = M; header[2] = N; header[3] = nz;
1333: MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1334: PetscViewerBinaryWrite(viewer,header,4,PETSC_INT);
1336: /* fill in and store row lengths */
1337: PetscMalloc1(m,&rowlens);
1338: for (i=0; i<m; i++) rowlens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i];
1339: PetscViewerBinaryWriteAll(viewer,rowlens,m,rs,M,PETSC_INT);
1340: PetscFree(rowlens);
1342: /* fill in and store column indices */
1343: PetscMalloc1(nz,&colidxs);
1344: for (cnt=0, i=0; i<m; i++) {
1345: for (jb=B->i[i]; jb<B->i[i+1]; jb++) {
1346: if (garray[B->j[jb]] > cs) break;
1347: colidxs[cnt++] = garray[B->j[jb]];
1348: }
1349: for (ja=A->i[i]; ja<A->i[i+1]; ja++)
1350: colidxs[cnt++] = A->j[ja] + cs;
1351: for (; jb<B->i[i+1]; jb++)
1352: colidxs[cnt++] = garray[B->j[jb]];
1353: }
1354: if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);
1355: PetscViewerBinaryWriteAll(viewer,colidxs,nz,PETSC_DETERMINE,PETSC_DETERMINE,PETSC_INT);
1356: PetscFree(colidxs);
1358: /* fill in and store nonzero values */
1359: PetscMalloc1(nz,&matvals);
1360: for (cnt=0, i=0; i<m; i++) {
1361: for (jb=B->i[i]; jb<B->i[i+1]; jb++) {
1362: if (garray[B->j[jb]] > cs) break;
1363: matvals[cnt++] = B->a[jb];
1364: }
1365: for (ja=A->i[i]; ja<A->i[i+1]; ja++)
1366: matvals[cnt++] = A->a[ja];
1367: for (; jb<B->i[i+1]; jb++)
1368: matvals[cnt++] = B->a[jb];
1369: }
1370: if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);
1371: PetscViewerBinaryWriteAll(viewer,matvals,nz,PETSC_DETERMINE,PETSC_DETERMINE,PETSC_SCALAR);
1372: PetscFree(matvals);
1374: /* write block size option to the viewer's .info file */
1375: MatView_Binary_BlockSizes(mat,viewer);
1376: return(0);
1377: }
1379: #include <petscdraw.h>
1380: PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
1381: {
1382: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1383: PetscErrorCode ierr;
1384: PetscMPIInt rank = aij->rank,size = aij->size;
1385: PetscBool isdraw,iascii,isbinary;
1386: PetscViewer sviewer;
1387: PetscViewerFormat format;
1390: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1391: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1392: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1393: if (iascii) {
1394: PetscViewerGetFormat(viewer,&format);
1395: if (format == PETSC_VIEWER_LOAD_BALANCE) {
1396: PetscInt i,nmax = 0,nmin = PETSC_MAX_INT,navg = 0,*nz,nzlocal = ((Mat_SeqAIJ*) (aij->A->data))->nz + ((Mat_SeqAIJ*) (aij->B->data))->nz;
1397: PetscMalloc1(size,&nz);
1398: MPI_Allgather(&nzlocal,1,MPIU_INT,nz,1,MPIU_INT,PetscObjectComm((PetscObject)mat));
1399: for (i=0; i<(PetscInt)size; i++) {
1400: nmax = PetscMax(nmax,nz[i]);
1401: nmin = PetscMin(nmin,nz[i]);
1402: navg += nz[i];
1403: }
1404: PetscFree(nz);
1405: navg = navg/size;
1406: PetscViewerASCIIPrintf(viewer,"Load Balance - Nonzeros: Min %D avg %D max %D\n",nmin,navg,nmax);
1407: return(0);
1408: }
1409: PetscViewerGetFormat(viewer,&format);
1410: if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
1411: MatInfo info;
1412: PetscBool inodes;
1414: MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
1415: MatGetInfo(mat,MAT_LOCAL,&info);
1416: MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);
1417: PetscViewerASCIIPushSynchronized(viewer);
1418: if (!inodes) {
1419: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %g, not using I-node routines\n",
1420: rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(double)info.memory);
1421: } else {
1422: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %g, using I-node routines\n",
1423: rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(double)info.memory);
1424: }
1425: MatGetInfo(aij->A,MAT_LOCAL,&info);
1426: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1427: MatGetInfo(aij->B,MAT_LOCAL,&info);
1428: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1429: PetscViewerFlush(viewer);
1430: PetscViewerASCIIPopSynchronized(viewer);
1431: PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
1432: VecScatterView(aij->Mvctx,viewer);
1433: return(0);
1434: } else if (format == PETSC_VIEWER_ASCII_INFO) {
1435: PetscInt inodecount,inodelimit,*inodes;
1436: MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);
1437: if (inodes) {
1438: PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);
1439: } else {
1440: PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");
1441: }
1442: return(0);
1443: } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
1444: return(0);
1445: }
1446: } else if (isbinary) {
1447: if (size == 1) {
1448: PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);
1449: MatView(aij->A,viewer);
1450: } else {
1451: MatView_MPIAIJ_Binary(mat,viewer);
1452: }
1453: return(0);
1454: } else if (iascii && size == 1) {
1455: PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);
1456: MatView(aij->A,viewer);
1457: return(0);
1458: } else if (isdraw) {
1459: PetscDraw draw;
1460: PetscBool isnull;
1461: PetscViewerDrawGetDraw(viewer,0,&draw);
1462: PetscDrawIsNull(draw,&isnull);
1463: if (isnull) return(0);
1464: }
1466: { /* assemble the entire matrix onto first processor */
1467: Mat A = NULL, Av;
1468: IS isrow,iscol;
1470: ISCreateStride(PetscObjectComm((PetscObject)mat),!rank ? mat->rmap->N : 0,0,1,&isrow);
1471: ISCreateStride(PetscObjectComm((PetscObject)mat),!rank ? mat->cmap->N : 0,0,1,&iscol);
1472: MatCreateSubMatrix(mat,isrow,iscol,MAT_INITIAL_MATRIX,&A);
1473: MatMPIAIJGetSeqAIJ(A,&Av,NULL,NULL);
1474: /* The commented code uses MatCreateSubMatrices instead */
1475: /*
1476: Mat *AA, A = NULL, Av;
1477: IS isrow,iscol;
1479: ISCreateStride(PetscObjectComm((PetscObject)mat),!rank ? mat->rmap->N : 0,0,1,&isrow);
1480: ISCreateStride(PetscObjectComm((PetscObject)mat),!rank ? mat->cmap->N : 0,0,1,&iscol);
1481: MatCreateSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&AA);
1482: if (!rank) {
1483: PetscObjectReference((PetscObject)AA[0]);
1484: A = AA[0];
1485: Av = AA[0];
1486: }
1487: MatDestroySubMatrices(1,&AA);
1488: */
1489: ISDestroy(&iscol);
1490: ISDestroy(&isrow);
1491: /*
1492: Everyone has to call to draw the matrix since the graphics waits are
1493: synchronized across all processors that share the PetscDraw object
1494: */
1495: PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
1496: if (!rank) {
1497: if (((PetscObject)mat)->name) {
1498: PetscObjectSetName((PetscObject)Av,((PetscObject)mat)->name);
1499: }
1500: MatView_SeqAIJ(Av,sviewer);
1501: }
1502: PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
1503: PetscViewerFlush(viewer);
1504: MatDestroy(&A);
1505: }
1506: return(0);
1507: }
1509: PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer)
1510: {
1512: PetscBool iascii,isdraw,issocket,isbinary;
1515: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1516: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1517: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1518: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
1519: if (iascii || isdraw || isbinary || issocket) {
1520: MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);
1521: }
1522: return(0);
1523: }
1525: PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
1526: {
1527: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data;
1529: Vec bb1 = 0;
1530: PetscBool hasop;
1533: if (flag == SOR_APPLY_UPPER) {
1534: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1535: return(0);
1536: }
1538: if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) {
1539: VecDuplicate(bb,&bb1);
1540: }
1542: if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
1543: if (flag & SOR_ZERO_INITIAL_GUESS) {
1544: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1545: its--;
1546: }
1548: while (its--) {
1549: VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1550: VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1552: /* update rhs: bb1 = bb - B*x */
1553: VecScale(mat->lvec,-1.0);
1554: (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);
1556: /* local sweep */
1557: (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);
1558: }
1559: } else if (flag & SOR_LOCAL_FORWARD_SWEEP) {
1560: if (flag & SOR_ZERO_INITIAL_GUESS) {
1561: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1562: its--;
1563: }
1564: while (its--) {
1565: VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1566: VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1568: /* update rhs: bb1 = bb - B*x */
1569: VecScale(mat->lvec,-1.0);
1570: (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);
1572: /* local sweep */
1573: (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);
1574: }
1575: } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) {
1576: if (flag & SOR_ZERO_INITIAL_GUESS) {
1577: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1578: its--;
1579: }
1580: while (its--) {
1581: VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1582: VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1584: /* update rhs: bb1 = bb - B*x */
1585: VecScale(mat->lvec,-1.0);
1586: (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);
1588: /* local sweep */
1589: (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);
1590: }
1591: } else if (flag & SOR_EISENSTAT) {
1592: Vec xx1;
1594: VecDuplicate(bb,&xx1);
1595: (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);
1597: VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1598: VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1599: if (!mat->diag) {
1600: MatCreateVecs(matin,&mat->diag,NULL);
1601: MatGetDiagonal(matin,mat->diag);
1602: }
1603: MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);
1604: if (hasop) {
1605: MatMultDiagonalBlock(matin,xx,bb1);
1606: } else {
1607: VecPointwiseMult(bb1,mat->diag,xx);
1608: }
1609: VecAYPX(bb1,(omega-2.0)/omega,bb);
1611: MatMultAdd(mat->B,mat->lvec,bb1,bb1);
1613: /* local sweep */
1614: (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
1615: VecAXPY(xx,1.0,xx1);
1616: VecDestroy(&xx1);
1617: } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported");
1619: VecDestroy(&bb1);
1621: matin->factorerrortype = mat->A->factorerrortype;
1622: return(0);
1623: }
1625: PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B)
1626: {
1627: Mat aA,aB,Aperm;
1628: const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj;
1629: PetscScalar *aa,*ba;
1630: PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest;
1631: PetscSF rowsf,sf;
1632: IS parcolp = NULL;
1633: PetscBool done;
1637: MatGetLocalSize(A,&m,&n);
1638: ISGetIndices(rowp,&rwant);
1639: ISGetIndices(colp,&cwant);
1640: PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);
1642: /* Invert row permutation to find out where my rows should go */
1643: PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);
1644: PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);
1645: PetscSFSetFromOptions(rowsf);
1646: for (i=0; i<m; i++) work[i] = A->rmap->rstart + i;
1647: PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);
1648: PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);
1650: /* Invert column permutation to find out where my columns should go */
1651: PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1652: PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);
1653: PetscSFSetFromOptions(sf);
1654: for (i=0; i<n; i++) work[i] = A->cmap->rstart + i;
1655: PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);
1656: PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);
1657: PetscSFDestroy(&sf);
1659: ISRestoreIndices(rowp,&rwant);
1660: ISRestoreIndices(colp,&cwant);
1661: MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);
1663: /* Find out where my gcols should go */
1664: MatGetSize(aB,NULL,&ng);
1665: PetscMalloc1(ng,&gcdest);
1666: PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1667: PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);
1668: PetscSFSetFromOptions(sf);
1669: PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);
1670: PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);
1671: PetscSFDestroy(&sf);
1673: PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);
1674: MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);
1675: MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);
1676: for (i=0; i<m; i++) {
1677: PetscInt row = rdest[i];
1678: PetscMPIInt rowner;
1679: PetscLayoutFindOwner(A->rmap,row,&rowner);
1680: for (j=ai[i]; j<ai[i+1]; j++) {
1681: PetscInt col = cdest[aj[j]];
1682: PetscMPIInt cowner;
1683: PetscLayoutFindOwner(A->cmap,col,&cowner); /* Could build an index for the columns to eliminate this search */
1684: if (rowner == cowner) dnnz[i]++;
1685: else onnz[i]++;
1686: }
1687: for (j=bi[i]; j<bi[i+1]; j++) {
1688: PetscInt col = gcdest[bj[j]];
1689: PetscMPIInt cowner;
1690: PetscLayoutFindOwner(A->cmap,col,&cowner);
1691: if (rowner == cowner) dnnz[i]++;
1692: else onnz[i]++;
1693: }
1694: }
1695: PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);
1696: PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);
1697: PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);
1698: PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);
1699: PetscSFDestroy(&rowsf);
1701: MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);
1702: MatSeqAIJGetArray(aA,&aa);
1703: MatSeqAIJGetArray(aB,&ba);
1704: for (i=0; i<m; i++) {
1705: PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */
1706: PetscInt j0,rowlen;
1707: rowlen = ai[i+1] - ai[i];
1708: for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */
1709: for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]];
1710: MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);
1711: }
1712: rowlen = bi[i+1] - bi[i];
1713: for (j0=j=0; j<rowlen; j0=j) {
1714: for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]];
1715: MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);
1716: }
1717: }
1718: MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);
1719: MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);
1720: MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);
1721: MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);
1722: MatSeqAIJRestoreArray(aA,&aa);
1723: MatSeqAIJRestoreArray(aB,&ba);
1724: PetscFree4(dnnz,onnz,tdnnz,tonnz);
1725: PetscFree3(work,rdest,cdest);
1726: PetscFree(gcdest);
1727: if (parcolp) {ISDestroy(&colp);}
1728: *B = Aperm;
1729: return(0);
1730: }
1732: PetscErrorCode MatGetGhosts_MPIAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[])
1733: {
1734: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1738: MatGetSize(aij->B,NULL,nghosts);
1739: if (ghosts) *ghosts = aij->garray;
1740: return(0);
1741: }
1743: PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1744: {
1745: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data;
1746: Mat A = mat->A,B = mat->B;
1748: PetscLogDouble isend[5],irecv[5];
1751: info->block_size = 1.0;
1752: MatGetInfo(A,MAT_LOCAL,info);
1754: isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1755: isend[3] = info->memory; isend[4] = info->mallocs;
1757: MatGetInfo(B,MAT_LOCAL,info);
1759: isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1760: isend[3] += info->memory; isend[4] += info->mallocs;
1761: if (flag == MAT_LOCAL) {
1762: info->nz_used = isend[0];
1763: info->nz_allocated = isend[1];
1764: info->nz_unneeded = isend[2];
1765: info->memory = isend[3];
1766: info->mallocs = isend[4];
1767: } else if (flag == MAT_GLOBAL_MAX) {
1768: MPIU_Allreduce(isend,irecv,5,MPIU_PETSCLOGDOUBLE,MPI_MAX,PetscObjectComm((PetscObject)matin));
1770: info->nz_used = irecv[0];
1771: info->nz_allocated = irecv[1];
1772: info->nz_unneeded = irecv[2];
1773: info->memory = irecv[3];
1774: info->mallocs = irecv[4];
1775: } else if (flag == MAT_GLOBAL_SUM) {
1776: MPIU_Allreduce(isend,irecv,5,MPIU_PETSCLOGDOUBLE,MPI_SUM,PetscObjectComm((PetscObject)matin));
1778: info->nz_used = irecv[0];
1779: info->nz_allocated = irecv[1];
1780: info->nz_unneeded = irecv[2];
1781: info->memory = irecv[3];
1782: info->mallocs = irecv[4];
1783: }
1784: info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */
1785: info->fill_ratio_needed = 0;
1786: info->factor_mallocs = 0;
1787: return(0);
1788: }
1790: PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg)
1791: {
1792: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1796: switch (op) {
1797: case MAT_NEW_NONZERO_LOCATIONS:
1798: case MAT_NEW_NONZERO_ALLOCATION_ERR:
1799: case MAT_UNUSED_NONZERO_LOCATION_ERR:
1800: case MAT_KEEP_NONZERO_PATTERN:
1801: case MAT_NEW_NONZERO_LOCATION_ERR:
1802: case MAT_USE_INODES:
1803: case MAT_IGNORE_ZERO_ENTRIES:
1804: MatCheckPreallocated(A,1);
1805: MatSetOption(a->A,op,flg);
1806: MatSetOption(a->B,op,flg);
1807: break;
1808: case MAT_ROW_ORIENTED:
1809: MatCheckPreallocated(A,1);
1810: a->roworiented = flg;
1812: MatSetOption(a->A,op,flg);
1813: MatSetOption(a->B,op,flg);
1814: break;
1815: case MAT_NEW_DIAGONALS:
1816: case MAT_SORTED_FULL:
1817: PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1818: break;
1819: case MAT_IGNORE_OFF_PROC_ENTRIES:
1820: a->donotstash = flg;
1821: break;
1822: /* Symmetry flags are handled directly by MatSetOption() and they don't affect preallocation */
1823: case MAT_SPD:
1824: case MAT_SYMMETRIC:
1825: case MAT_STRUCTURALLY_SYMMETRIC:
1826: case MAT_HERMITIAN:
1827: case MAT_SYMMETRY_ETERNAL:
1828: break;
1829: case MAT_SUBMAT_SINGLEIS:
1830: A->submat_singleis = flg;
1831: break;
1832: case MAT_STRUCTURE_ONLY:
1833: /* The option is handled directly by MatSetOption() */
1834: break;
1835: default:
1836: SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1837: }
1838: return(0);
1839: }
1841: PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1842: {
1843: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data;
1844: PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p;
1846: PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart;
1847: PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend;
1848: PetscInt *cmap,*idx_p;
1851: if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
1852: mat->getrowactive = PETSC_TRUE;
1854: if (!mat->rowvalues && (idx || v)) {
1855: /*
1856: allocate enough space to hold information from the longest row.
1857: */
1858: Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data;
1859: PetscInt max = 1,tmp;
1860: for (i=0; i<matin->rmap->n; i++) {
1861: tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i];
1862: if (max < tmp) max = tmp;
1863: }
1864: PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);
1865: }
1867: if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows");
1868: lrow = row - rstart;
1870: pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1871: if (!v) {pvA = 0; pvB = 0;}
1872: if (!idx) {pcA = 0; if (!v) pcB = 0;}
1873: (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1874: (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1875: nztot = nzA + nzB;
1877: cmap = mat->garray;
1878: if (v || idx) {
1879: if (nztot) {
1880: /* Sort by increasing column numbers, assuming A and B already sorted */
1881: PetscInt imark = -1;
1882: if (v) {
1883: *v = v_p = mat->rowvalues;
1884: for (i=0; i<nzB; i++) {
1885: if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i];
1886: else break;
1887: }
1888: imark = i;
1889: for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i];
1890: for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i];
1891: }
1892: if (idx) {
1893: *idx = idx_p = mat->rowindices;
1894: if (imark > -1) {
1895: for (i=0; i<imark; i++) {
1896: idx_p[i] = cmap[cworkB[i]];
1897: }
1898: } else {
1899: for (i=0; i<nzB; i++) {
1900: if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]];
1901: else break;
1902: }
1903: imark = i;
1904: }
1905: for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i];
1906: for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]];
1907: }
1908: } else {
1909: if (idx) *idx = 0;
1910: if (v) *v = 0;
1911: }
1912: }
1913: *nz = nztot;
1914: (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1915: (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1916: return(0);
1917: }
1919: PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1920: {
1921: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1924: if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
1925: aij->getrowactive = PETSC_FALSE;
1926: return(0);
1927: }
1929: PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm)
1930: {
1931: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1932: Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data;
1934: PetscInt i,j,cstart = mat->cmap->rstart;
1935: PetscReal sum = 0.0;
1936: MatScalar *v;
1939: if (aij->size == 1) {
1940: MatNorm(aij->A,type,norm);
1941: } else {
1942: if (type == NORM_FROBENIUS) {
1943: v = amat->a;
1944: for (i=0; i<amat->nz; i++) {
1945: sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1946: }
1947: v = bmat->a;
1948: for (i=0; i<bmat->nz; i++) {
1949: sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1950: }
1951: MPIU_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
1952: *norm = PetscSqrtReal(*norm);
1953: PetscLogFlops(2.0*amat->nz+2.0*bmat->nz);
1954: } else if (type == NORM_1) { /* max column norm */
1955: PetscReal *tmp,*tmp2;
1956: PetscInt *jj,*garray = aij->garray;
1957: PetscCalloc1(mat->cmap->N+1,&tmp);
1958: PetscMalloc1(mat->cmap->N+1,&tmp2);
1959: *norm = 0.0;
1960: v = amat->a; jj = amat->j;
1961: for (j=0; j<amat->nz; j++) {
1962: tmp[cstart + *jj++] += PetscAbsScalar(*v); v++;
1963: }
1964: v = bmat->a; jj = bmat->j;
1965: for (j=0; j<bmat->nz; j++) {
1966: tmp[garray[*jj++]] += PetscAbsScalar(*v); v++;
1967: }
1968: MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
1969: for (j=0; j<mat->cmap->N; j++) {
1970: if (tmp2[j] > *norm) *norm = tmp2[j];
1971: }
1972: PetscFree(tmp);
1973: PetscFree(tmp2);
1974: PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));
1975: } else if (type == NORM_INFINITY) { /* max row norm */
1976: PetscReal ntemp = 0.0;
1977: for (j=0; j<aij->A->rmap->n; j++) {
1978: v = amat->a + amat->i[j];
1979: sum = 0.0;
1980: for (i=0; i<amat->i[j+1]-amat->i[j]; i++) {
1981: sum += PetscAbsScalar(*v); v++;
1982: }
1983: v = bmat->a + bmat->i[j];
1984: for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) {
1985: sum += PetscAbsScalar(*v); v++;
1986: }
1987: if (sum > ntemp) ntemp = sum;
1988: }
1989: MPIU_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));
1990: PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));
1991: } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm");
1992: }
1993: return(0);
1994: }
1996: PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout)
1997: {
1998: Mat_MPIAIJ *a =(Mat_MPIAIJ*)A->data,*b;
1999: Mat_SeqAIJ *Aloc =(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data,*sub_B_diag;
2000: PetscInt M = A->rmap->N,N=A->cmap->N,ma,na,mb,nb,row,*cols,*cols_tmp,*B_diag_ilen,i,ncol,A_diag_ncol;
2001: const PetscInt *ai,*aj,*bi,*bj,*B_diag_i;
2002: PetscErrorCode ierr;
2003: Mat B,A_diag,*B_diag;
2004: const MatScalar *array;
2007: ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n;
2008: ai = Aloc->i; aj = Aloc->j;
2009: bi = Bloc->i; bj = Bloc->j;
2010: if (reuse == MAT_INITIAL_MATRIX || *matout == A) {
2011: PetscInt *d_nnz,*g_nnz,*o_nnz;
2012: PetscSFNode *oloc;
2013: PETSC_UNUSED PetscSF sf;
2015: PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);
2016: /* compute d_nnz for preallocation */
2017: PetscArrayzero(d_nnz,na);
2018: for (i=0; i<ai[ma]; i++) {
2019: d_nnz[aj[i]]++;
2020: }
2021: /* compute local off-diagonal contributions */
2022: PetscArrayzero(g_nnz,nb);
2023: for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++;
2024: /* map those to global */
2025: PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
2026: PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);
2027: PetscSFSetFromOptions(sf);
2028: PetscArrayzero(o_nnz,na);
2029: PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);
2030: PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);
2031: PetscSFDestroy(&sf);
2033: MatCreate(PetscObjectComm((PetscObject)A),&B);
2034: MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);
2035: MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));
2036: MatSetType(B,((PetscObject)A)->type_name);
2037: MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);
2038: PetscFree4(d_nnz,o_nnz,g_nnz,oloc);
2039: } else {
2040: B = *matout;
2041: MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);
2042: }
2044: b = (Mat_MPIAIJ*)B->data;
2045: A_diag = a->A;
2046: B_diag = &b->A;
2047: sub_B_diag = (Mat_SeqAIJ*)(*B_diag)->data;
2048: A_diag_ncol = A_diag->cmap->N;
2049: B_diag_ilen = sub_B_diag->ilen;
2050: B_diag_i = sub_B_diag->i;
2052: /* Set ilen for diagonal of B */
2053: for (i=0; i<A_diag_ncol; i++) {
2054: B_diag_ilen[i] = B_diag_i[i+1] - B_diag_i[i];
2055: }
2057: /* Transpose the diagonal part of the matrix. In contrast to the offdiagonal part, this can be done
2058: very quickly (=without using MatSetValues), because all writes are local. */
2059: MatTranspose(A_diag,MAT_REUSE_MATRIX,B_diag);
2061: /* copy over the B part */
2062: PetscMalloc1(bi[mb],&cols);
2063: array = Bloc->a;
2064: row = A->rmap->rstart;
2065: for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]];
2066: cols_tmp = cols;
2067: for (i=0; i<mb; i++) {
2068: ncol = bi[i+1]-bi[i];
2069: MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);
2070: row++;
2071: array += ncol; cols_tmp += ncol;
2072: }
2073: PetscFree(cols);
2075: MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2076: MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2077: if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) {
2078: *matout = B;
2079: } else {
2080: MatHeaderMerge(A,&B);
2081: }
2082: return(0);
2083: }
2085: PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr)
2086: {
2087: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
2088: Mat a = aij->A,b = aij->B;
2090: PetscInt s1,s2,s3;
2093: MatGetLocalSize(mat,&s2,&s3);
2094: if (rr) {
2095: VecGetLocalSize(rr,&s1);
2096: if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size");
2097: /* Overlap communication with computation. */
2098: VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);
2099: }
2100: if (ll) {
2101: VecGetLocalSize(ll,&s1);
2102: if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size");
2103: (*b->ops->diagonalscale)(b,ll,0);
2104: }
2105: /* scale the diagonal block */
2106: (*a->ops->diagonalscale)(a,ll,rr);
2108: if (rr) {
2109: /* Do a scatter end and then right scale the off-diagonal block */
2110: VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);
2111: (*b->ops->diagonalscale)(b,0,aij->lvec);
2112: }
2113: return(0);
2114: }
2116: PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A)
2117: {
2118: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2122: MatSetUnfactored(a->A);
2123: return(0);
2124: }
2126: PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag)
2127: {
2128: Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data;
2129: Mat a,b,c,d;
2130: PetscBool flg;
2134: a = matA->A; b = matA->B;
2135: c = matB->A; d = matB->B;
2137: MatEqual(a,c,&flg);
2138: if (flg) {
2139: MatEqual(b,d,&flg);
2140: }
2141: MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
2142: return(0);
2143: }
2145: PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str)
2146: {
2148: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2149: Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data;
2152: /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
2153: if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
2154: /* because of the column compression in the off-processor part of the matrix a->B,
2155: the number of columns in a->B and b->B may be different, hence we cannot call
2156: the MatCopy() directly on the two parts. If need be, we can provide a more
2157: efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices
2158: then copying the submatrices */
2159: MatCopy_Basic(A,B,str);
2160: } else {
2161: MatCopy(a->A,b->A,str);
2162: MatCopy(a->B,b->B,str);
2163: }
2164: PetscObjectStateIncrease((PetscObject)B);
2165: return(0);
2166: }
2168: PetscErrorCode MatSetUp_MPIAIJ(Mat A)
2169: {
2173: MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
2174: return(0);
2175: }
2177: /*
2178: Computes the number of nonzeros per row needed for preallocation when X and Y
2179: have different nonzero structure.
2180: */
2181: PetscErrorCode MatAXPYGetPreallocation_MPIX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *xltog,const PetscInt *yi,const PetscInt *yj,const PetscInt *yltog,PetscInt *nnz)
2182: {
2183: PetscInt i,j,k,nzx,nzy;
2186: /* Set the number of nonzeros in the new matrix */
2187: for (i=0; i<m; i++) {
2188: const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i];
2189: nzx = xi[i+1] - xi[i];
2190: nzy = yi[i+1] - yi[i];
2191: nnz[i] = 0;
2192: for (j=0,k=0; j<nzx; j++) { /* Point in X */
2193: for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */
2194: if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++; /* Skip duplicate */
2195: nnz[i]++;
2196: }
2197: for (; k<nzy; k++) nnz[i]++;
2198: }
2199: return(0);
2200: }
2202: /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */
2203: static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz)
2204: {
2206: PetscInt m = Y->rmap->N;
2207: Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data;
2208: Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data;
2211: MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);
2212: return(0);
2213: }
2215: PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
2216: {
2218: Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data;
2219: PetscBLASInt bnz,one=1;
2220: Mat_SeqAIJ *x,*y;
2223: if (str == SAME_NONZERO_PATTERN) {
2224: PetscScalar alpha = a;
2225: x = (Mat_SeqAIJ*)xx->A->data;
2226: PetscBLASIntCast(x->nz,&bnz);
2227: y = (Mat_SeqAIJ*)yy->A->data;
2228: PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2229: x = (Mat_SeqAIJ*)xx->B->data;
2230: y = (Mat_SeqAIJ*)yy->B->data;
2231: PetscBLASIntCast(x->nz,&bnz);
2232: PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2233: PetscObjectStateIncrease((PetscObject)Y);
2234: /* the MatAXPY_Basic* subroutines calls MatAssembly, so the matrix on the GPU
2235: will be updated */
2236: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
2237: if (Y->offloadmask != PETSC_OFFLOAD_UNALLOCATED) {
2238: Y->offloadmask = PETSC_OFFLOAD_CPU;
2239: }
2240: #endif
2241: } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
2242: MatAXPY_Basic(Y,a,X,str);
2243: } else {
2244: Mat B;
2245: PetscInt *nnz_d,*nnz_o;
2246: PetscMalloc1(yy->A->rmap->N,&nnz_d);
2247: PetscMalloc1(yy->B->rmap->N,&nnz_o);
2248: MatCreate(PetscObjectComm((PetscObject)Y),&B);
2249: PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
2250: MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
2251: MatSetBlockSizesFromMats(B,Y,Y);
2252: MatSetType(B,MATMPIAIJ);
2253: MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);
2254: MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
2255: MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);
2256: MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
2257: MatHeaderReplace(Y,&B);
2258: PetscFree(nnz_d);
2259: PetscFree(nnz_o);
2260: }
2261: return(0);
2262: }
2264: extern PetscErrorCode MatConjugate_SeqAIJ(Mat);
2266: PetscErrorCode MatConjugate_MPIAIJ(Mat mat)
2267: {
2268: #if defined(PETSC_USE_COMPLEX)
2270: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
2273: MatConjugate_SeqAIJ(aij->A);
2274: MatConjugate_SeqAIJ(aij->B);
2275: #else
2277: #endif
2278: return(0);
2279: }
2281: PetscErrorCode MatRealPart_MPIAIJ(Mat A)
2282: {
2283: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2287: MatRealPart(a->A);
2288: MatRealPart(a->B);
2289: return(0);
2290: }
2292: PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A)
2293: {
2294: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2298: MatImaginaryPart(a->A);
2299: MatImaginaryPart(a->B);
2300: return(0);
2301: }
2303: PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2304: {
2305: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2307: PetscInt i,*idxb = 0;
2308: PetscScalar *va,*vb;
2309: Vec vtmp;
2312: MatGetRowMaxAbs(a->A,v,idx);
2313: VecGetArray(v,&va);
2314: if (idx) {
2315: for (i=0; i<A->rmap->n; i++) {
2316: if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
2317: }
2318: }
2320: VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
2321: if (idx) {
2322: PetscMalloc1(A->rmap->n,&idxb);
2323: }
2324: MatGetRowMaxAbs(a->B,vtmp,idxb);
2325: VecGetArray(vtmp,&vb);
2327: for (i=0; i<A->rmap->n; i++) {
2328: if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {
2329: va[i] = vb[i];
2330: if (idx) idx[i] = a->garray[idxb[i]];
2331: }
2332: }
2334: VecRestoreArray(v,&va);
2335: VecRestoreArray(vtmp,&vb);
2336: PetscFree(idxb);
2337: VecDestroy(&vtmp);
2338: return(0);
2339: }
2341: PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2342: {
2343: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2345: PetscInt i,*idxb = 0;
2346: PetscScalar *va,*vb;
2347: Vec vtmp;
2350: MatGetRowMinAbs(a->A,v,idx);
2351: VecGetArray(v,&va);
2352: if (idx) {
2353: for (i=0; i<A->cmap->n; i++) {
2354: if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
2355: }
2356: }
2358: VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
2359: if (idx) {
2360: PetscMalloc1(A->rmap->n,&idxb);
2361: }
2362: MatGetRowMinAbs(a->B,vtmp,idxb);
2363: VecGetArray(vtmp,&vb);
2365: for (i=0; i<A->rmap->n; i++) {
2366: if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) {
2367: va[i] = vb[i];
2368: if (idx) idx[i] = a->garray[idxb[i]];
2369: }
2370: }
2372: VecRestoreArray(v,&va);
2373: VecRestoreArray(vtmp,&vb);
2374: PetscFree(idxb);
2375: VecDestroy(&vtmp);
2376: return(0);
2377: }
2379: PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2380: {
2381: Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data;
2382: PetscInt n = A->rmap->n;
2383: PetscInt cstart = A->cmap->rstart;
2384: PetscInt *cmap = mat->garray;
2385: PetscInt *diagIdx, *offdiagIdx;
2386: Vec diagV, offdiagV;
2387: PetscScalar *a, *diagA, *offdiagA;
2388: PetscInt r;
2392: PetscMalloc2(n,&diagIdx,n,&offdiagIdx);
2393: VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);
2394: VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);
2395: MatGetRowMin(mat->A, diagV, diagIdx);
2396: MatGetRowMin(mat->B, offdiagV, offdiagIdx);
2397: VecGetArray(v, &a);
2398: VecGetArray(diagV, &diagA);
2399: VecGetArray(offdiagV, &offdiagA);
2400: for (r = 0; r < n; ++r) {
2401: if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) {
2402: a[r] = diagA[r];
2403: idx[r] = cstart + diagIdx[r];
2404: } else {
2405: a[r] = offdiagA[r];
2406: idx[r] = cmap[offdiagIdx[r]];
2407: }
2408: }
2409: VecRestoreArray(v, &a);
2410: VecRestoreArray(diagV, &diagA);
2411: VecRestoreArray(offdiagV, &offdiagA);
2412: VecDestroy(&diagV);
2413: VecDestroy(&offdiagV);
2414: PetscFree2(diagIdx, offdiagIdx);
2415: return(0);
2416: }
2418: PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2419: {
2420: Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data;
2421: PetscInt n = A->rmap->n;
2422: PetscInt cstart = A->cmap->rstart;
2423: PetscInt *cmap = mat->garray;
2424: PetscInt *diagIdx, *offdiagIdx;
2425: Vec diagV, offdiagV;
2426: PetscScalar *a, *diagA, *offdiagA;
2427: PetscInt r;
2431: PetscMalloc2(n,&diagIdx,n,&offdiagIdx);
2432: VecCreateSeq(PETSC_COMM_SELF, n, &diagV);
2433: VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);
2434: MatGetRowMax(mat->A, diagV, diagIdx);
2435: MatGetRowMax(mat->B, offdiagV, offdiagIdx);
2436: VecGetArray(v, &a);
2437: VecGetArray(diagV, &diagA);
2438: VecGetArray(offdiagV, &offdiagA);
2439: for (r = 0; r < n; ++r) {
2440: if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) {
2441: a[r] = diagA[r];
2442: idx[r] = cstart + diagIdx[r];
2443: } else {
2444: a[r] = offdiagA[r];
2445: idx[r] = cmap[offdiagIdx[r]];
2446: }
2447: }
2448: VecRestoreArray(v, &a);
2449: VecRestoreArray(diagV, &diagA);
2450: VecRestoreArray(offdiagV, &offdiagA);
2451: VecDestroy(&diagV);
2452: VecDestroy(&offdiagV);
2453: PetscFree2(diagIdx, offdiagIdx);
2454: return(0);
2455: }
2457: PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat)
2458: {
2460: Mat *dummy;
2463: MatCreateSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);
2464: *newmat = *dummy;
2465: PetscFree(dummy);
2466: return(0);
2467: }
2469: PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values)
2470: {
2471: Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data;
2475: MatInvertBlockDiagonal(a->A,values);
2476: A->factorerrortype = a->A->factorerrortype;
2477: return(0);
2478: }
2480: static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx)
2481: {
2483: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data;
2486: if (!x->assembled && !x->preallocated) SETERRQ(PetscObjectComm((PetscObject)x), PETSC_ERR_ARG_WRONGSTATE, "MatSetRandom on an unassembled and unpreallocated MATMPIAIJ is not allowed");
2487: MatSetRandom(aij->A,rctx);
2488: if (x->assembled) {
2489: MatSetRandom(aij->B,rctx);
2490: } else {
2491: MatSetRandomSkipColumnRange_SeqAIJ_Private(aij->B,x->cmap->rstart,x->cmap->rend,rctx);
2492: }
2493: MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);
2494: MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);
2495: return(0);
2496: }
2498: PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ(Mat A,PetscBool sc)
2499: {
2501: if (sc) A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ_Scalable;
2502: else A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ;
2503: return(0);
2504: }
2506: /*@
2507: MatMPIAIJSetUseScalableIncreaseOverlap - Determine if the matrix uses a scalable algorithm to compute the overlap
2509: Collective on Mat
2511: Input Parameters:
2512: + A - the matrix
2513: - sc - PETSC_TRUE indicates use the scalable algorithm (default is not to use the scalable algorithm)
2515: Level: advanced
2517: @*/
2518: PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap(Mat A,PetscBool sc)
2519: {
2520: PetscErrorCode ierr;
2523: PetscTryMethod(A,"MatMPIAIJSetUseScalableIncreaseOverlap_C",(Mat,PetscBool),(A,sc));
2524: return(0);
2525: }
2527: PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptionItems *PetscOptionsObject,Mat A)
2528: {
2529: PetscErrorCode ierr;
2530: PetscBool sc = PETSC_FALSE,flg;
2533: PetscOptionsHead(PetscOptionsObject,"MPIAIJ options");
2534: if (A->ops->increaseoverlap == MatIncreaseOverlap_MPIAIJ_Scalable) sc = PETSC_TRUE;
2535: PetscOptionsBool("-mat_increase_overlap_scalable","Use a scalable algorithm to compute the overlap","MatIncreaseOverlap",sc,&sc,&flg);
2536: if (flg) {
2537: MatMPIAIJSetUseScalableIncreaseOverlap(A,sc);
2538: }
2539: PetscOptionsTail();
2540: return(0);
2541: }
2543: PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a)
2544: {
2546: Mat_MPIAIJ *maij = (Mat_MPIAIJ*)Y->data;
2547: Mat_SeqAIJ *aij = (Mat_SeqAIJ*)maij->A->data;
2550: if (!Y->preallocated) {
2551: MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);
2552: } else if (!aij->nz) {
2553: PetscInt nonew = aij->nonew;
2554: MatSeqAIJSetPreallocation(maij->A,1,NULL);
2555: aij->nonew = nonew;
2556: }
2557: MatShift_Basic(Y,a);
2558: return(0);
2559: }
2561: PetscErrorCode MatMissingDiagonal_MPIAIJ(Mat A,PetscBool *missing,PetscInt *d)
2562: {
2563: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2567: if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
2568: MatMissingDiagonal(a->A,missing,d);
2569: if (d) {
2570: PetscInt rstart;
2571: MatGetOwnershipRange(A,&rstart,NULL);
2572: *d += rstart;
2574: }
2575: return(0);
2576: }
2578: PetscErrorCode MatInvertVariableBlockDiagonal_MPIAIJ(Mat A,PetscInt nblocks,const PetscInt *bsizes,PetscScalar *diag)
2579: {
2580: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2584: MatInvertVariableBlockDiagonal(a->A,nblocks,bsizes,diag);
2585: return(0);
2586: }
2588: /* -------------------------------------------------------------------*/
2589: static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ,
2590: MatGetRow_MPIAIJ,
2591: MatRestoreRow_MPIAIJ,
2592: MatMult_MPIAIJ,
2593: /* 4*/ MatMultAdd_MPIAIJ,
2594: MatMultTranspose_MPIAIJ,
2595: MatMultTransposeAdd_MPIAIJ,
2596: 0,
2597: 0,
2598: 0,
2599: /*10*/ 0,
2600: 0,
2601: 0,
2602: MatSOR_MPIAIJ,
2603: MatTranspose_MPIAIJ,
2604: /*15*/ MatGetInfo_MPIAIJ,
2605: MatEqual_MPIAIJ,
2606: MatGetDiagonal_MPIAIJ,
2607: MatDiagonalScale_MPIAIJ,
2608: MatNorm_MPIAIJ,
2609: /*20*/ MatAssemblyBegin_MPIAIJ,
2610: MatAssemblyEnd_MPIAIJ,
2611: MatSetOption_MPIAIJ,
2612: MatZeroEntries_MPIAIJ,
2613: /*24*/ MatZeroRows_MPIAIJ,
2614: 0,
2615: 0,
2616: 0,
2617: 0,
2618: /*29*/ MatSetUp_MPIAIJ,
2619: 0,
2620: 0,
2621: MatGetDiagonalBlock_MPIAIJ,
2622: 0,
2623: /*34*/ MatDuplicate_MPIAIJ,
2624: 0,
2625: 0,
2626: 0,
2627: 0,
2628: /*39*/ MatAXPY_MPIAIJ,
2629: MatCreateSubMatrices_MPIAIJ,
2630: MatIncreaseOverlap_MPIAIJ,
2631: MatGetValues_MPIAIJ,
2632: MatCopy_MPIAIJ,
2633: /*44*/ MatGetRowMax_MPIAIJ,
2634: MatScale_MPIAIJ,
2635: MatShift_MPIAIJ,
2636: MatDiagonalSet_MPIAIJ,
2637: MatZeroRowsColumns_MPIAIJ,
2638: /*49*/ MatSetRandom_MPIAIJ,
2639: 0,
2640: 0,
2641: 0,
2642: 0,
2643: /*54*/ MatFDColoringCreate_MPIXAIJ,
2644: 0,
2645: MatSetUnfactored_MPIAIJ,
2646: MatPermute_MPIAIJ,
2647: 0,
2648: /*59*/ MatCreateSubMatrix_MPIAIJ,
2649: MatDestroy_MPIAIJ,
2650: MatView_MPIAIJ,
2651: 0,
2652: 0,
2653: /*64*/ 0,
2654: MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ,
2655: 0,
2656: 0,
2657: 0,
2658: /*69*/ MatGetRowMaxAbs_MPIAIJ,
2659: MatGetRowMinAbs_MPIAIJ,
2660: 0,
2661: 0,
2662: 0,
2663: 0,
2664: /*75*/ MatFDColoringApply_AIJ,
2665: MatSetFromOptions_MPIAIJ,
2666: 0,
2667: 0,
2668: MatFindZeroDiagonals_MPIAIJ,
2669: /*80*/ 0,
2670: 0,
2671: 0,
2672: /*83*/ MatLoad_MPIAIJ,
2673: MatIsSymmetric_MPIAIJ,
2674: 0,
2675: 0,
2676: 0,
2677: 0,
2678: /*89*/ 0,
2679: 0,
2680: MatMatMultNumeric_MPIAIJ_MPIAIJ,
2681: 0,
2682: 0,
2683: /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ,
2684: 0,
2685: 0,
2686: 0,
2687: MatBindToCPU_MPIAIJ,
2688: /*99*/ MatProductSetFromOptions_MPIAIJ,
2689: 0,
2690: 0,
2691: MatConjugate_MPIAIJ,
2692: 0,
2693: /*104*/MatSetValuesRow_MPIAIJ,
2694: MatRealPart_MPIAIJ,
2695: MatImaginaryPart_MPIAIJ,
2696: 0,
2697: 0,
2698: /*109*/0,
2699: 0,
2700: MatGetRowMin_MPIAIJ,
2701: 0,
2702: MatMissingDiagonal_MPIAIJ,
2703: /*114*/MatGetSeqNonzeroStructure_MPIAIJ,
2704: 0,
2705: MatGetGhosts_MPIAIJ,
2706: 0,
2707: 0,
2708: /*119*/0,
2709: 0,
2710: 0,
2711: 0,
2712: MatGetMultiProcBlock_MPIAIJ,
2713: /*124*/MatFindNonzeroRows_MPIAIJ,
2714: MatGetColumnNorms_MPIAIJ,
2715: MatInvertBlockDiagonal_MPIAIJ,
2716: MatInvertVariableBlockDiagonal_MPIAIJ,
2717: MatCreateSubMatricesMPI_MPIAIJ,
2718: /*129*/0,
2719: 0,
2720: 0,
2721: MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ,
2722: 0,
2723: /*134*/0,
2724: 0,
2725: 0,
2726: 0,
2727: 0,
2728: /*139*/MatSetBlockSizes_MPIAIJ,
2729: 0,
2730: 0,
2731: MatFDColoringSetUp_MPIXAIJ,
2732: MatFindOffBlockDiagonalEntries_MPIAIJ,
2733: MatCreateMPIMatConcatenateSeqMat_MPIAIJ,
2734: /*145*/0,
2735: 0,
2736: 0
2737: };
2739: /* ----------------------------------------------------------------------------------------*/
2741: PetscErrorCode MatStoreValues_MPIAIJ(Mat mat)
2742: {
2743: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
2747: MatStoreValues(aij->A);
2748: MatStoreValues(aij->B);
2749: return(0);
2750: }
2752: PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat)
2753: {
2754: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
2758: MatRetrieveValues(aij->A);
2759: MatRetrieveValues(aij->B);
2760: return(0);
2761: }
2763: PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
2764: {
2765: Mat_MPIAIJ *b;
2767: PetscMPIInt size;
2770: PetscLayoutSetUp(B->rmap);
2771: PetscLayoutSetUp(B->cmap);
2772: b = (Mat_MPIAIJ*)B->data;
2774: #if defined(PETSC_USE_CTABLE)
2775: PetscTableDestroy(&b->colmap);
2776: #else
2777: PetscFree(b->colmap);
2778: #endif
2779: PetscFree(b->garray);
2780: VecDestroy(&b->lvec);
2781: VecScatterDestroy(&b->Mvctx);
2783: /* Because the B will have been resized we simply destroy it and create a new one each time */
2784: MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
2785: MatDestroy(&b->B);
2786: MatCreate(PETSC_COMM_SELF,&b->B);
2787: MatSetSizes(b->B,B->rmap->n,size > 1 ? B->cmap->N : 0,B->rmap->n,size > 1 ? B->cmap->N : 0);
2788: MatSetBlockSizesFromMats(b->B,B,B);
2789: MatSetType(b->B,MATSEQAIJ);
2790: PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);
2792: if (!B->preallocated) {
2793: MatCreate(PETSC_COMM_SELF,&b->A);
2794: MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
2795: MatSetBlockSizesFromMats(b->A,B,B);
2796: MatSetType(b->A,MATSEQAIJ);
2797: PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
2798: }
2800: MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);
2801: MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);
2802: B->preallocated = PETSC_TRUE;
2803: B->was_assembled = PETSC_FALSE;
2804: B->assembled = PETSC_FALSE;
2805: return(0);
2806: }
2808: PetscErrorCode MatResetPreallocation_MPIAIJ(Mat B)
2809: {
2810: Mat_MPIAIJ *b;
2815: PetscLayoutSetUp(B->rmap);
2816: PetscLayoutSetUp(B->cmap);
2817: b = (Mat_MPIAIJ*)B->data;
2819: #if defined(PETSC_USE_CTABLE)
2820: PetscTableDestroy(&b->colmap);
2821: #else
2822: PetscFree(b->colmap);
2823: #endif
2824: PetscFree(b->garray);
2825: VecDestroy(&b->lvec);
2826: VecScatterDestroy(&b->Mvctx);
2828: MatResetPreallocation(b->A);
2829: MatResetPreallocation(b->B);
2830: B->preallocated = PETSC_TRUE;
2831: B->was_assembled = PETSC_FALSE;
2832: B->assembled = PETSC_FALSE;
2833: return(0);
2834: }
2836: PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
2837: {
2838: Mat mat;
2839: Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data;
2843: *newmat = 0;
2844: MatCreate(PetscObjectComm((PetscObject)matin),&mat);
2845: MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
2846: MatSetBlockSizesFromMats(mat,matin,matin);
2847: MatSetType(mat,((PetscObject)matin)->type_name);
2848: a = (Mat_MPIAIJ*)mat->data;
2850: mat->factortype = matin->factortype;
2851: mat->assembled = matin->assembled;
2852: mat->insertmode = NOT_SET_VALUES;
2853: mat->preallocated = matin->preallocated;
2855: a->size = oldmat->size;
2856: a->rank = oldmat->rank;
2857: a->donotstash = oldmat->donotstash;
2858: a->roworiented = oldmat->roworiented;
2859: a->rowindices = NULL;
2860: a->rowvalues = NULL;
2861: a->getrowactive = PETSC_FALSE;
2863: PetscLayoutReference(matin->rmap,&mat->rmap);
2864: PetscLayoutReference(matin->cmap,&mat->cmap);
2866: if (oldmat->colmap) {
2867: #if defined(PETSC_USE_CTABLE)
2868: PetscTableCreateCopy(oldmat->colmap,&a->colmap);
2869: #else
2870: PetscMalloc1(mat->cmap->N,&a->colmap);
2871: PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));
2872: PetscArraycpy(a->colmap,oldmat->colmap,mat->cmap->N);
2873: #endif
2874: } else a->colmap = NULL;
2875: if (oldmat->garray) {
2876: PetscInt len;
2877: len = oldmat->B->cmap->n;
2878: PetscMalloc1(len+1,&a->garray);
2879: PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
2880: if (len) { PetscArraycpy(a->garray,oldmat->garray,len); }
2881: } else a->garray = NULL;
2883: /* It may happen MatDuplicate is called with a non-assembled matrix
2884: In fact, MatDuplicate only requires the matrix to be preallocated
2885: This may happen inside a DMCreateMatrix_Shell */
2886: if (oldmat->lvec) {
2887: VecDuplicate(oldmat->lvec,&a->lvec);
2888: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
2889: }
2890: if (oldmat->Mvctx) {
2891: VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
2892: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);
2893: }
2894: if (oldmat->Mvctx_mpi1) {
2895: VecScatterCopy(oldmat->Mvctx_mpi1,&a->Mvctx_mpi1);
2896: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx_mpi1);
2897: }
2899: MatDuplicate(oldmat->A,cpvalues,&a->A);
2900: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
2901: MatDuplicate(oldmat->B,cpvalues,&a->B);
2902: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
2903: PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
2904: *newmat = mat;
2905: return(0);
2906: }
2908: PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer)
2909: {
2910: PetscBool isbinary, ishdf5;
2916: /* force binary viewer to load .info file if it has not yet done so */
2917: PetscViewerSetUp(viewer);
2918: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
2919: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERHDF5, &ishdf5);
2920: if (isbinary) {
2921: MatLoad_MPIAIJ_Binary(newMat,viewer);
2922: } else if (ishdf5) {
2923: #if defined(PETSC_HAVE_HDF5)
2924: MatLoad_AIJ_HDF5(newMat,viewer);
2925: #else
2926: SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_SUP,"HDF5 not supported in this build.\nPlease reconfigure using --download-hdf5");
2927: #endif
2928: } else {
2929: SETERRQ2(PetscObjectComm((PetscObject)newMat),PETSC_ERR_SUP,"Viewer type %s not yet supported for reading %s matrices",((PetscObject)viewer)->type_name,((PetscObject)newMat)->type_name);
2930: }
2931: return(0);
2932: }
2934: PetscErrorCode MatLoad_MPIAIJ_Binary(Mat mat, PetscViewer viewer)
2935: {
2936: PetscInt header[4],M,N,m,nz,rows,cols,sum,i;
2937: PetscInt *rowidxs,*colidxs;
2938: PetscScalar *matvals;
2942: PetscViewerSetUp(viewer);
2944: /* read in matrix header */
2945: PetscViewerBinaryRead(viewer,header,4,NULL,PETSC_INT);
2946: if (header[0] != MAT_FILE_CLASSID) SETERRQ(PetscObjectComm((PetscObject)viewer),PETSC_ERR_FILE_UNEXPECTED,"Not a matrix object in file");
2947: M = header[1]; N = header[2]; nz = header[3];
2948: if (M < 0) SETERRQ1(PetscObjectComm((PetscObject)viewer),PETSC_ERR_FILE_UNEXPECTED,"Matrix row size (%D) in file is negative",M);
2949: if (N < 0) SETERRQ1(PetscObjectComm((PetscObject)viewer),PETSC_ERR_FILE_UNEXPECTED,"Matrix column size (%D) in file is negative",N);
2950: if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk, cannot load as MPIAIJ");
2952: /* set block sizes from the viewer's .info file */
2953: MatLoad_Binary_BlockSizes(mat,viewer);
2954: /* set global sizes if not set already */
2955: if (mat->rmap->N < 0) mat->rmap->N = M;
2956: if (mat->cmap->N < 0) mat->cmap->N = N;
2957: PetscLayoutSetUp(mat->rmap);
2958: PetscLayoutSetUp(mat->cmap);
2960: /* check if the matrix sizes are correct */
2961: MatGetSize(mat,&rows,&cols);
2962: if (M != rows || N != cols) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Matrix in file of different sizes (%D, %D) than the input matrix (%D, %D)",M,N,rows,cols);
2964: /* read in row lengths and build row indices */
2965: MatGetLocalSize(mat,&m,NULL);
2966: PetscMalloc1(m+1,&rowidxs);
2967: PetscViewerBinaryReadAll(viewer,rowidxs+1,m,PETSC_DECIDE,M,PETSC_INT);
2968: rowidxs[0] = 0; for (i=0; i<m; i++) rowidxs[i+1] += rowidxs[i];
2969: MPIU_Allreduce(&rowidxs[m],&sum,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)viewer));
2970: if (sum != nz) SETERRQ2(PetscObjectComm((PetscObject)viewer),PETSC_ERR_FILE_UNEXPECTED,"Inconsistent matrix data in file: nonzeros = %D, sum-row-lengths = %D\n",nz,sum);
2971: /* read in column indices and matrix values */
2972: PetscMalloc2(rowidxs[m],&colidxs,rowidxs[m],&matvals);
2973: PetscViewerBinaryReadAll(viewer,colidxs,rowidxs[m],PETSC_DETERMINE,PETSC_DETERMINE,PETSC_INT);
2974: PetscViewerBinaryReadAll(viewer,matvals,rowidxs[m],PETSC_DETERMINE,PETSC_DETERMINE,PETSC_SCALAR);
2975: /* store matrix indices and values */
2976: MatMPIAIJSetPreallocationCSR(mat,rowidxs,colidxs,matvals);
2977: PetscFree(rowidxs);
2978: PetscFree2(colidxs,matvals);
2979: return(0);
2980: }
2982: /* Not scalable because of ISAllGather() unless getting all columns. */
2983: PetscErrorCode ISGetSeqIS_Private(Mat mat,IS iscol,IS *isseq)
2984: {
2986: IS iscol_local;
2987: PetscBool isstride;
2988: PetscMPIInt lisstride=0,gisstride;
2991: /* check if we are grabbing all columns*/
2992: PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&isstride);
2994: if (isstride) {
2995: PetscInt start,len,mstart,mlen;
2996: ISStrideGetInfo(iscol,&start,NULL);
2997: ISGetLocalSize(iscol,&len);
2998: MatGetOwnershipRangeColumn(mat,&mstart,&mlen);
2999: if (mstart == start && mlen-mstart == len) lisstride = 1;
3000: }
3002: MPIU_Allreduce(&lisstride,&gisstride,1,MPI_INT,MPI_MIN,PetscObjectComm((PetscObject)mat));
3003: if (gisstride) {
3004: PetscInt N;
3005: MatGetSize(mat,NULL,&N);
3006: ISCreateStride(PETSC_COMM_SELF,N,0,1,&iscol_local);
3007: ISSetIdentity(iscol_local);
3008: PetscInfo(mat,"Optimizing for obtaining all columns of the matrix; skipping ISAllGather()\n");
3009: } else {
3010: PetscInt cbs;
3011: ISGetBlockSize(iscol,&cbs);
3012: ISAllGather(iscol,&iscol_local);
3013: ISSetBlockSize(iscol_local,cbs);
3014: }
3016: *isseq = iscol_local;
3017: return(0);
3018: }
3020: /*
3021: Used by MatCreateSubMatrix_MPIAIJ_SameRowColDist() to avoid ISAllGather() and global size of iscol_local
3022: (see MatCreateSubMatrix_MPIAIJ_nonscalable)
3024: Input Parameters:
3025: mat - matrix
3026: isrow - parallel row index set; its local indices are a subset of local columns of mat,
3027: i.e., mat->rstart <= isrow[i] < mat->rend
3028: iscol - parallel column index set; its local indices are a subset of local columns of mat,
3029: i.e., mat->cstart <= iscol[i] < mat->cend
3030: Output Parameter:
3031: isrow_d,iscol_d - sequential row and column index sets for retrieving mat->A
3032: iscol_o - sequential column index set for retrieving mat->B
3033: garray - column map; garray[i] indicates global location of iscol_o[i] in iscol
3034: */
3035: PetscErrorCode ISGetSeqIS_SameColDist_Private(Mat mat,IS isrow,IS iscol,IS *isrow_d,IS *iscol_d,IS *iscol_o,const PetscInt *garray[])
3036: {
3038: Vec x,cmap;
3039: const PetscInt *is_idx;
3040: PetscScalar *xarray,*cmaparray;
3041: PetscInt ncols,isstart,*idx,m,rstart,*cmap1,count;
3042: Mat_MPIAIJ *a=(Mat_MPIAIJ*)mat->data;
3043: Mat B=a->B;
3044: Vec lvec=a->lvec,lcmap;
3045: PetscInt i,cstart,cend,Bn=B->cmap->N;
3046: MPI_Comm comm;
3047: VecScatter Mvctx=a->Mvctx;
3050: PetscObjectGetComm((PetscObject)mat,&comm);
3051: ISGetLocalSize(iscol,&ncols);
3053: /* (1) iscol is a sub-column vector of mat, pad it with '-1.' to form a full vector x */
3054: MatCreateVecs(mat,&x,NULL);
3055: VecSet(x,-1.0);
3056: VecDuplicate(x,&cmap);
3057: VecSet(cmap,-1.0);
3059: /* Get start indices */
3060: MPI_Scan(&ncols,&isstart,1,MPIU_INT,MPI_SUM,comm);
3061: isstart -= ncols;
3062: MatGetOwnershipRangeColumn(mat,&cstart,&cend);
3064: ISGetIndices(iscol,&is_idx);
3065: VecGetArray(x,&xarray);
3066: VecGetArray(cmap,&cmaparray);
3067: PetscMalloc1(ncols,&idx);
3068: for (i=0; i<ncols; i++) {
3069: xarray[is_idx[i]-cstart] = (PetscScalar)is_idx[i];
3070: cmaparray[is_idx[i]-cstart] = i + isstart; /* global index of iscol[i] */
3071: idx[i] = is_idx[i]-cstart; /* local index of iscol[i] */
3072: }
3073: VecRestoreArray(x,&xarray);
3074: VecRestoreArray(cmap,&cmaparray);
3075: ISRestoreIndices(iscol,&is_idx);
3077: /* Get iscol_d */
3078: ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,iscol_d);
3079: ISGetBlockSize(iscol,&i);
3080: ISSetBlockSize(*iscol_d,i);
3082: /* Get isrow_d */
3083: ISGetLocalSize(isrow,&m);
3084: rstart = mat->rmap->rstart;
3085: PetscMalloc1(m,&idx);
3086: ISGetIndices(isrow,&is_idx);
3087: for (i=0; i<m; i++) idx[i] = is_idx[i]-rstart;
3088: ISRestoreIndices(isrow,&is_idx);
3090: ISCreateGeneral(PETSC_COMM_SELF,m,idx,PETSC_OWN_POINTER,isrow_d);
3091: ISGetBlockSize(isrow,&i);
3092: ISSetBlockSize(*isrow_d,i);
3094: /* (2) Scatter x and cmap using aij->Mvctx to get their off-process portions (see MatMult_MPIAIJ) */
3095: VecScatterBegin(Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);
3096: VecScatterEnd(Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);
3098: VecDuplicate(lvec,&lcmap);
3100: VecScatterBegin(Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);
3101: VecScatterEnd(Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);
3103: /* (3) create sequential iscol_o (a subset of iscol) and isgarray */
3104: /* off-process column indices */
3105: count = 0;
3106: PetscMalloc1(Bn,&idx);
3107: PetscMalloc1(Bn,&cmap1);
3109: VecGetArray(lvec,&xarray);
3110: VecGetArray(lcmap,&cmaparray);
3111: for (i=0; i<Bn; i++) {
3112: if (PetscRealPart(xarray[i]) > -1.0) {
3113: idx[count] = i; /* local column index in off-diagonal part B */
3114: cmap1[count] = (PetscInt)PetscRealPart(cmaparray[i]); /* column index in submat */
3115: count++;
3116: }
3117: }
3118: VecRestoreArray(lvec,&xarray);
3119: VecRestoreArray(lcmap,&cmaparray);
3121: ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_COPY_VALUES,iscol_o);
3122: /* cannot ensure iscol_o has same blocksize as iscol! */
3124: PetscFree(idx);
3125: *garray = cmap1;
3127: VecDestroy(&x);
3128: VecDestroy(&cmap);
3129: VecDestroy(&lcmap);
3130: return(0);
3131: }
3133: /* isrow and iscol have same processor distribution as mat, output *submat is a submatrix of local mat */
3134: PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowColDist(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *submat)
3135: {
3137: Mat_MPIAIJ *a = (Mat_MPIAIJ*)mat->data,*asub;
3138: Mat M = NULL;
3139: MPI_Comm comm;
3140: IS iscol_d,isrow_d,iscol_o;
3141: Mat Asub = NULL,Bsub = NULL;
3142: PetscInt n;
3145: PetscObjectGetComm((PetscObject)mat,&comm);
3147: if (call == MAT_REUSE_MATRIX) {
3148: /* Retrieve isrow_d, iscol_d and iscol_o from submat */
3149: PetscObjectQuery((PetscObject)*submat,"isrow_d",(PetscObject*)&isrow_d);
3150: if (!isrow_d) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"isrow_d passed in was not used before, cannot reuse");
3152: PetscObjectQuery((PetscObject)*submat,"iscol_d",(PetscObject*)&iscol_d);
3153: if (!iscol_d) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"iscol_d passed in was not used before, cannot reuse");
3155: PetscObjectQuery((PetscObject)*submat,"iscol_o",(PetscObject*)&iscol_o);
3156: if (!iscol_o) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"iscol_o passed in was not used before, cannot reuse");
3158: /* Update diagonal and off-diagonal portions of submat */
3159: asub = (Mat_MPIAIJ*)(*submat)->data;
3160: MatCreateSubMatrix_SeqAIJ(a->A,isrow_d,iscol_d,PETSC_DECIDE,MAT_REUSE_MATRIX,&asub->A);
3161: ISGetLocalSize(iscol_o,&n);
3162: if (n) {
3163: MatCreateSubMatrix_SeqAIJ(a->B,isrow_d,iscol_o,PETSC_DECIDE,MAT_REUSE_MATRIX,&asub->B);
3164: }
3165: MatAssemblyBegin(*submat,MAT_FINAL_ASSEMBLY);
3166: MatAssemblyEnd(*submat,MAT_FINAL_ASSEMBLY);
3168: } else { /* call == MAT_INITIAL_MATRIX) */
3169: const PetscInt *garray;
3170: PetscInt BsubN;
3172: /* Create isrow_d, iscol_d, iscol_o and isgarray (replace isgarray with array?) */
3173: ISGetSeqIS_SameColDist_Private(mat,isrow,iscol,&isrow_d,&iscol_d,&iscol_o,&garray);
3175: /* Create local submatrices Asub and Bsub */
3176: MatCreateSubMatrix_SeqAIJ(a->A,isrow_d,iscol_d,PETSC_DECIDE,MAT_INITIAL_MATRIX,&Asub);
3177: MatCreateSubMatrix_SeqAIJ(a->B,isrow_d,iscol_o,PETSC_DECIDE,MAT_INITIAL_MATRIX,&Bsub);
3179: /* Create submatrix M */
3180: MatCreateMPIAIJWithSeqAIJ(comm,Asub,Bsub,garray,&M);
3182: /* If Bsub has empty columns, compress iscol_o such that it will retrieve condensed Bsub from a->B during reuse */
3183: asub = (Mat_MPIAIJ*)M->data;
3185: ISGetLocalSize(iscol_o,&BsubN);
3186: n = asub->B->cmap->N;
3187: if (BsubN > n) {
3188: /* This case can be tested using ~petsc/src/tao/bound/tutorials/runplate2_3 */
3189: const PetscInt *idx;
3190: PetscInt i,j,*idx_new,*subgarray = asub->garray;
3191: PetscInfo2(M,"submatrix Bn %D != BsubN %D, update iscol_o\n",n,BsubN);
3193: PetscMalloc1(n,&idx_new);
3194: j = 0;
3195: ISGetIndices(iscol_o,&idx);
3196: for (i=0; i<n; i++) {
3197: if (j >= BsubN) break;
3198: while (subgarray[i] > garray[j]) j++;
3200: if (subgarray[i] == garray[j]) {
3201: idx_new[i] = idx[j++];
3202: } else SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"subgarray[%D]=%D cannot < garray[%D]=%D",i,subgarray[i],j,garray[j]);
3203: }
3204: ISRestoreIndices(iscol_o,&idx);
3206: ISDestroy(&iscol_o);
3207: ISCreateGeneral(PETSC_COMM_SELF,n,idx_new,PETSC_OWN_POINTER,&iscol_o);
3209: } else if (BsubN < n) {
3210: SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Columns of Bsub cannot be smaller than B's",BsubN,asub->B->cmap->N);
3211: }
3213: PetscFree(garray);
3214: *submat = M;
3216: /* Save isrow_d, iscol_d and iscol_o used in processor for next request */
3217: PetscObjectCompose((PetscObject)M,"isrow_d",(PetscObject)isrow_d);
3218: ISDestroy(&isrow_d);
3220: PetscObjectCompose((PetscObject)M,"iscol_d",(PetscObject)iscol_d);
3221: ISDestroy(&iscol_d);
3223: PetscObjectCompose((PetscObject)M,"iscol_o",(PetscObject)iscol_o);
3224: ISDestroy(&iscol_o);
3225: }
3226: return(0);
3227: }
3229: PetscErrorCode MatCreateSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
3230: {
3232: IS iscol_local=NULL,isrow_d;
3233: PetscInt csize;
3234: PetscInt n,i,j,start,end;
3235: PetscBool sameRowDist=PETSC_FALSE,sameDist[2],tsameDist[2];
3236: MPI_Comm comm;
3239: /* If isrow has same processor distribution as mat,
3240: call MatCreateSubMatrix_MPIAIJ_SameRowDist() to avoid using a hash table with global size of iscol */
3241: if (call == MAT_REUSE_MATRIX) {
3242: PetscObjectQuery((PetscObject)*newmat,"isrow_d",(PetscObject*)&isrow_d);
3243: if (isrow_d) {
3244: sameRowDist = PETSC_TRUE;
3245: tsameDist[1] = PETSC_TRUE; /* sameColDist */
3246: } else {
3247: PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_local);
3248: if (iscol_local) {
3249: sameRowDist = PETSC_TRUE;
3250: tsameDist[1] = PETSC_FALSE; /* !sameColDist */
3251: }
3252: }
3253: } else {
3254: /* Check if isrow has same processor distribution as mat */
3255: sameDist[0] = PETSC_FALSE;
3256: ISGetLocalSize(isrow,&n);
3257: if (!n) {
3258: sameDist[0] = PETSC_TRUE;
3259: } else {
3260: ISGetMinMax(isrow,&i,&j);
3261: MatGetOwnershipRange(mat,&start,&end);
3262: if (i >= start && j < end) {
3263: sameDist[0] = PETSC_TRUE;
3264: }
3265: }
3267: /* Check if iscol has same processor distribution as mat */
3268: sameDist[1] = PETSC_FALSE;
3269: ISGetLocalSize(iscol,&n);
3270: if (!n) {
3271: sameDist[1] = PETSC_TRUE;
3272: } else {
3273: ISGetMinMax(iscol,&i,&j);
3274: MatGetOwnershipRangeColumn(mat,&start,&end);
3275: if (i >= start && j < end) sameDist[1] = PETSC_TRUE;
3276: }
3278: PetscObjectGetComm((PetscObject)mat,&comm);
3279: MPIU_Allreduce(&sameDist,&tsameDist,2,MPIU_BOOL,MPI_LAND,comm);
3280: sameRowDist = tsameDist[0];
3281: }
3283: if (sameRowDist) {
3284: if (tsameDist[1]) { /* sameRowDist & sameColDist */
3285: /* isrow and iscol have same processor distribution as mat */
3286: MatCreateSubMatrix_MPIAIJ_SameRowColDist(mat,isrow,iscol,call,newmat);
3287: return(0);
3288: } else { /* sameRowDist */
3289: /* isrow has same processor distribution as mat */
3290: if (call == MAT_INITIAL_MATRIX) {
3291: PetscBool sorted;
3292: ISGetSeqIS_Private(mat,iscol,&iscol_local);
3293: ISGetLocalSize(iscol_local,&n); /* local size of iscol_local = global columns of newmat */
3294: ISGetSize(iscol,&i);
3295: if (n != i) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"n %d != size of iscol %d",n,i);
3297: ISSorted(iscol_local,&sorted);
3298: if (sorted) {
3299: /* MatCreateSubMatrix_MPIAIJ_SameRowDist() requires iscol_local be sorted; it can have duplicate indices */
3300: MatCreateSubMatrix_MPIAIJ_SameRowDist(mat,isrow,iscol,iscol_local,MAT_INITIAL_MATRIX,newmat);
3301: return(0);
3302: }
3303: } else { /* call == MAT_REUSE_MATRIX */
3304: IS iscol_sub;
3305: PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);
3306: if (iscol_sub) {
3307: MatCreateSubMatrix_MPIAIJ_SameRowDist(mat,isrow,iscol,NULL,call,newmat);
3308: return(0);
3309: }
3310: }
3311: }
3312: }
3314: /* General case: iscol -> iscol_local which has global size of iscol */
3315: if (call == MAT_REUSE_MATRIX) {
3316: PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
3317: if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3318: } else {
3319: if (!iscol_local) {
3320: ISGetSeqIS_Private(mat,iscol,&iscol_local);
3321: }
3322: }
3324: ISGetLocalSize(iscol,&csize);
3325: MatCreateSubMatrix_MPIAIJ_nonscalable(mat,isrow,iscol_local,csize,call,newmat);
3327: if (call == MAT_INITIAL_MATRIX) {
3328: PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
3329: ISDestroy(&iscol_local);
3330: }
3331: return(0);
3332: }
3334: /*@C
3335: MatCreateMPIAIJWithSeqAIJ - creates a MPIAIJ matrix using SeqAIJ matrices that contain the "diagonal"
3336: and "off-diagonal" part of the matrix in CSR format.
3338: Collective
3340: Input Parameters:
3341: + comm - MPI communicator
3342: . A - "diagonal" portion of matrix
3343: . B - "off-diagonal" portion of matrix, may have empty columns, will be destroyed by this routine
3344: - garray - global index of B columns
3346: Output Parameter:
3347: . mat - the matrix, with input A as its local diagonal matrix
3348: Level: advanced
3350: Notes:
3351: See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix.
3352: A becomes part of output mat, B is destroyed by this routine. The user cannot use A and B anymore.
3354: .seealso: MatCreateMPIAIJWithSplitArrays()
3355: @*/
3356: PetscErrorCode MatCreateMPIAIJWithSeqAIJ(MPI_Comm comm,Mat A,Mat B,const PetscInt garray[],Mat *mat)
3357: {
3359: Mat_MPIAIJ *maij;
3360: Mat_SeqAIJ *b=(Mat_SeqAIJ*)B->data,*bnew;
3361: PetscInt *oi=b->i,*oj=b->j,i,nz,col;
3362: PetscScalar *oa=b->a;
3363: Mat Bnew;
3364: PetscInt m,n,N;
3367: MatCreate(comm,mat);
3368: MatGetSize(A,&m,&n);
3369: if (m != B->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Am %D != Bm %D",m,B->rmap->N);
3370: if (A->rmap->bs != B->rmap->bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"A row bs %D != B row bs %D",A->rmap->bs,B->rmap->bs);
3371: /* remove check below; When B is created using iscol_o from ISGetSeqIS_SameColDist_Private(), its bs may not be same as A */
3372: /* if (A->cmap->bs != B->cmap->bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"A column bs %D != B column bs %D",A->cmap->bs,B->cmap->bs); */
3374: /* Get global columns of mat */
3375: MPIU_Allreduce(&n,&N,1,MPIU_INT,MPI_SUM,comm);
3377: MatSetSizes(*mat,m,n,PETSC_DECIDE,N);
3378: MatSetType(*mat,MATMPIAIJ);
3379: MatSetBlockSizes(*mat,A->rmap->bs,A->cmap->bs);
3380: maij = (Mat_MPIAIJ*)(*mat)->data;
3382: (*mat)->preallocated = PETSC_TRUE;
3384: PetscLayoutSetUp((*mat)->rmap);
3385: PetscLayoutSetUp((*mat)->cmap);
3387: /* Set A as diagonal portion of *mat */
3388: maij->A = A;
3390: nz = oi[m];
3391: for (i=0; i<nz; i++) {
3392: col = oj[i];
3393: oj[i] = garray[col];
3394: }
3396: /* Set Bnew as off-diagonal portion of *mat */
3397: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,N,oi,oj,oa,&Bnew);
3398: bnew = (Mat_SeqAIJ*)Bnew->data;
3399: bnew->maxnz = b->maxnz; /* allocated nonzeros of B */
3400: maij->B = Bnew;
3402: if (B->rmap->N != Bnew->rmap->N) SETERRQ2(PETSC_COMM_SELF,0,"BN %d != BnewN %d",B->rmap->N,Bnew->rmap->N);
3404: b->singlemalloc = PETSC_FALSE; /* B arrays are shared by Bnew */
3405: b->free_a = PETSC_FALSE;
3406: b->free_ij = PETSC_FALSE;
3407: MatDestroy(&B);
3409: bnew->singlemalloc = PETSC_TRUE; /* arrays will be freed by MatDestroy(&Bnew) */
3410: bnew->free_a = PETSC_TRUE;
3411: bnew->free_ij = PETSC_TRUE;
3413: /* condense columns of maij->B */
3414: MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);
3415: MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
3416: MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
3417: MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);
3418: MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
3419: return(0);
3420: }
3422: extern PetscErrorCode MatCreateSubMatrices_MPIAIJ_SingleIS_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool,Mat*);
3424: PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowDist(Mat mat,IS isrow,IS iscol,IS iscol_local,MatReuse call,Mat *newmat)
3425: {
3427: PetscInt i,m,n,rstart,row,rend,nz,j,bs,cbs;
3428: PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal;
3429: Mat_MPIAIJ *a=(Mat_MPIAIJ*)mat->data;
3430: Mat M,Msub,B=a->B;
3431: MatScalar *aa;
3432: Mat_SeqAIJ *aij;
3433: PetscInt *garray = a->garray,*colsub,Ncols;
3434: PetscInt count,Bn=B->cmap->N,cstart=mat->cmap->rstart,cend=mat->cmap->rend;
3435: IS iscol_sub,iscmap;
3436: const PetscInt *is_idx,*cmap;
3437: PetscBool allcolumns=PETSC_FALSE;
3438: MPI_Comm comm;
3441: PetscObjectGetComm((PetscObject)mat,&comm);
3443: if (call == MAT_REUSE_MATRIX) {
3444: PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);
3445: if (!iscol_sub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"SubIScol passed in was not used before, cannot reuse");
3446: ISGetLocalSize(iscol_sub,&count);
3448: PetscObjectQuery((PetscObject)*newmat,"Subcmap",(PetscObject*)&iscmap);
3449: if (!iscmap) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Subcmap passed in was not used before, cannot reuse");
3451: PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Msub);
3452: if (!Msub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3454: MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_REUSE_MATRIX,PETSC_FALSE,&Msub);
3456: } else { /* call == MAT_INITIAL_MATRIX) */
3457: PetscBool flg;
3459: ISGetLocalSize(iscol,&n);
3460: ISGetSize(iscol,&Ncols);
3462: /* (1) iscol -> nonscalable iscol_local */
3463: /* Check for special case: each processor gets entire matrix columns */
3464: ISIdentity(iscol_local,&flg);
3465: if (flg && n == mat->cmap->N) allcolumns = PETSC_TRUE;
3466: MPIU_Allreduce(MPI_IN_PLACE,&allcolumns,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)mat));
3467: if (allcolumns) {
3468: iscol_sub = iscol_local;
3469: PetscObjectReference((PetscObject)iscol_local);
3470: ISCreateStride(PETSC_COMM_SELF,n,0,1,&iscmap);
3472: } else {
3473: /* (2) iscol_local -> iscol_sub and iscmap. Implementation below requires iscol_local be sorted, it can have duplicate indices */
3474: PetscInt *idx,*cmap1,k;
3475: PetscMalloc1(Ncols,&idx);
3476: PetscMalloc1(Ncols,&cmap1);
3477: ISGetIndices(iscol_local,&is_idx);
3478: count = 0;
3479: k = 0;
3480: for (i=0; i<Ncols; i++) {
3481: j = is_idx[i];
3482: if (j >= cstart && j < cend) {
3483: /* diagonal part of mat */
3484: idx[count] = j;
3485: cmap1[count++] = i; /* column index in submat */
3486: } else if (Bn) {
3487: /* off-diagonal part of mat */
3488: if (j == garray[k]) {
3489: idx[count] = j;
3490: cmap1[count++] = i; /* column index in submat */
3491: } else if (j > garray[k]) {
3492: while (j > garray[k] && k < Bn-1) k++;
3493: if (j == garray[k]) {
3494: idx[count] = j;
3495: cmap1[count++] = i; /* column index in submat */
3496: }
3497: }
3498: }
3499: }
3500: ISRestoreIndices(iscol_local,&is_idx);
3502: ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_OWN_POINTER,&iscol_sub);
3503: ISGetBlockSize(iscol,&cbs);
3504: ISSetBlockSize(iscol_sub,cbs);
3506: ISCreateGeneral(PetscObjectComm((PetscObject)iscol_local),count,cmap1,PETSC_OWN_POINTER,&iscmap);
3507: }
3509: /* (3) Create sequential Msub */
3510: MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_INITIAL_MATRIX,allcolumns,&Msub);
3511: }
3513: ISGetLocalSize(iscol_sub,&count);
3514: aij = (Mat_SeqAIJ*)(Msub)->data;
3515: ii = aij->i;
3516: ISGetIndices(iscmap,&cmap);
3518: /*
3519: m - number of local rows
3520: Ncols - number of columns (same on all processors)
3521: rstart - first row in new global matrix generated
3522: */
3523: MatGetSize(Msub,&m,NULL);
3525: if (call == MAT_INITIAL_MATRIX) {
3526: /* (4) Create parallel newmat */
3527: PetscMPIInt rank,size;
3528: PetscInt csize;
3530: MPI_Comm_size(comm,&size);
3531: MPI_Comm_rank(comm,&rank);
3533: /*
3534: Determine the number of non-zeros in the diagonal and off-diagonal
3535: portions of the matrix in order to do correct preallocation
3536: */
3538: /* first get start and end of "diagonal" columns */
3539: ISGetLocalSize(iscol,&csize);
3540: if (csize == PETSC_DECIDE) {
3541: ISGetSize(isrow,&mglobal);
3542: if (mglobal == Ncols) { /* square matrix */
3543: nlocal = m;
3544: } else {
3545: nlocal = Ncols/size + ((Ncols % size) > rank);
3546: }
3547: } else {
3548: nlocal = csize;
3549: }
3550: MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
3551: rstart = rend - nlocal;
3552: if (rank == size - 1 && rend != Ncols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,Ncols);
3554: /* next, compute all the lengths */
3555: jj = aij->j;
3556: PetscMalloc1(2*m+1,&dlens);
3557: olens = dlens + m;
3558: for (i=0; i<m; i++) {
3559: jend = ii[i+1] - ii[i];
3560: olen = 0;
3561: dlen = 0;
3562: for (j=0; j<jend; j++) {
3563: if (cmap[*jj] < rstart || cmap[*jj] >= rend) olen++;
3564: else dlen++;
3565: jj++;
3566: }
3567: olens[i] = olen;
3568: dlens[i] = dlen;
3569: }
3571: ISGetBlockSize(isrow,&bs);
3572: ISGetBlockSize(iscol,&cbs);
3574: MatCreate(comm,&M);
3575: MatSetSizes(M,m,nlocal,PETSC_DECIDE,Ncols);
3576: MatSetBlockSizes(M,bs,cbs);
3577: MatSetType(M,((PetscObject)mat)->type_name);
3578: MatMPIAIJSetPreallocation(M,0,dlens,0,olens);
3579: PetscFree(dlens);
3581: } else { /* call == MAT_REUSE_MATRIX */
3582: M = *newmat;
3583: MatGetLocalSize(M,&i,NULL);
3584: if (i != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
3585: MatZeroEntries(M);
3586: /*
3587: The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
3588: rather than the slower MatSetValues().
3589: */
3590: M->was_assembled = PETSC_TRUE;
3591: M->assembled = PETSC_FALSE;
3592: }
3594: /* (5) Set values of Msub to *newmat */
3595: PetscMalloc1(count,&colsub);
3596: MatGetOwnershipRange(M,&rstart,NULL);
3598: jj = aij->j;
3599: aa = aij->a;
3600: for (i=0; i<m; i++) {
3601: row = rstart + i;
3602: nz = ii[i+1] - ii[i];
3603: for (j=0; j<nz; j++) colsub[j] = cmap[jj[j]];
3604: MatSetValues_MPIAIJ(M,1,&row,nz,colsub,aa,INSERT_VALUES);
3605: jj += nz; aa += nz;
3606: }
3607: ISRestoreIndices(iscmap,&cmap);
3609: MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
3610: MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
3612: PetscFree(colsub);
3614: /* save Msub, iscol_sub and iscmap used in processor for next request */
3615: if (call == MAT_INITIAL_MATRIX) {
3616: *newmat = M;
3617: PetscObjectCompose((PetscObject)(*newmat),"SubMatrix",(PetscObject)Msub);
3618: MatDestroy(&Msub);
3620: PetscObjectCompose((PetscObject)(*newmat),"SubIScol",(PetscObject)iscol_sub);
3621: ISDestroy(&iscol_sub);
3623: PetscObjectCompose((PetscObject)(*newmat),"Subcmap",(PetscObject)iscmap);
3624: ISDestroy(&iscmap);
3626: if (iscol_local) {
3627: PetscObjectCompose((PetscObject)(*newmat),"ISAllGather",(PetscObject)iscol_local);
3628: ISDestroy(&iscol_local);
3629: }
3630: }
3631: return(0);
3632: }
3634: /*
3635: Not great since it makes two copies of the submatrix, first an SeqAIJ
3636: in local and then by concatenating the local matrices the end result.
3637: Writing it directly would be much like MatCreateSubMatrices_MPIAIJ()
3639: Note: This requires a sequential iscol with all indices.
3640: */
3641: PetscErrorCode MatCreateSubMatrix_MPIAIJ_nonscalable(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat)
3642: {
3644: PetscMPIInt rank,size;
3645: PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs;
3646: PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal;
3647: Mat M,Mreuse;
3648: MatScalar *aa,*vwork;
3649: MPI_Comm comm;
3650: Mat_SeqAIJ *aij;
3651: PetscBool colflag,allcolumns=PETSC_FALSE;
3654: PetscObjectGetComm((PetscObject)mat,&comm);
3655: MPI_Comm_rank(comm,&rank);
3656: MPI_Comm_size(comm,&size);
3658: /* Check for special case: each processor gets entire matrix columns */
3659: ISIdentity(iscol,&colflag);
3660: ISGetLocalSize(iscol,&n);
3661: if (colflag && n == mat->cmap->N) allcolumns = PETSC_TRUE;
3662: MPIU_Allreduce(MPI_IN_PLACE,&allcolumns,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)mat));
3664: if (call == MAT_REUSE_MATRIX) {
3665: PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);
3666: if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3667: MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,allcolumns,&Mreuse);
3668: } else {
3669: MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,allcolumns,&Mreuse);
3670: }
3672: /*
3673: m - number of local rows
3674: n - number of columns (same on all processors)
3675: rstart - first row in new global matrix generated
3676: */
3677: MatGetSize(Mreuse,&m,&n);
3678: MatGetBlockSizes(Mreuse,&bs,&cbs);
3679: if (call == MAT_INITIAL_MATRIX) {
3680: aij = (Mat_SeqAIJ*)(Mreuse)->data;
3681: ii = aij->i;
3682: jj = aij->j;
3684: /*
3685: Determine the number of non-zeros in the diagonal and off-diagonal
3686: portions of the matrix in order to do correct preallocation
3687: */
3689: /* first get start and end of "diagonal" columns */
3690: if (csize == PETSC_DECIDE) {
3691: ISGetSize(isrow,&mglobal);
3692: if (mglobal == n) { /* square matrix */
3693: nlocal = m;
3694: } else {
3695: nlocal = n/size + ((n % size) > rank);
3696: }
3697: } else {
3698: nlocal = csize;
3699: }
3700: MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
3701: rstart = rend - nlocal;
3702: if (rank == size - 1 && rend != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n);
3704: /* next, compute all the lengths */
3705: PetscMalloc1(2*m+1,&dlens);
3706: olens = dlens + m;
3707: for (i=0; i<m; i++) {
3708: jend = ii[i+1] - ii[i];
3709: olen = 0;
3710: dlen = 0;
3711: for (j=0; j<jend; j++) {
3712: if (*jj < rstart || *jj >= rend) olen++;
3713: else dlen++;
3714: jj++;
3715: }
3716: olens[i] = olen;
3717: dlens[i] = dlen;
3718: }
3719: MatCreate(comm,&M);
3720: MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);
3721: MatSetBlockSizes(M,bs,cbs);
3722: MatSetType(M,((PetscObject)mat)->type_name);
3723: MatMPIAIJSetPreallocation(M,0,dlens,0,olens);
3724: PetscFree(dlens);
3725: } else {
3726: PetscInt ml,nl;
3728: M = *newmat;
3729: MatGetLocalSize(M,&ml,&nl);
3730: if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
3731: MatZeroEntries(M);
3732: /*
3733: The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
3734: rather than the slower MatSetValues().
3735: */
3736: M->was_assembled = PETSC_TRUE;
3737: M->assembled = PETSC_FALSE;
3738: }
3739: MatGetOwnershipRange(M,&rstart,&rend);
3740: aij = (Mat_SeqAIJ*)(Mreuse)->data;
3741: ii = aij->i;
3742: jj = aij->j;
3743: aa = aij->a;
3744: for (i=0; i<m; i++) {
3745: row = rstart + i;
3746: nz = ii[i+1] - ii[i];
3747: cwork = jj; jj += nz;
3748: vwork = aa; aa += nz;
3749: MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);
3750: }
3752: MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
3753: MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
3754: *newmat = M;
3756: /* save submatrix used in processor for next request */
3757: if (call == MAT_INITIAL_MATRIX) {
3758: PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);
3759: MatDestroy(&Mreuse);
3760: }
3761: return(0);
3762: }
3764: PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[])
3765: {
3766: PetscInt m,cstart, cend,j,nnz,i,d;
3767: PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii;
3768: const PetscInt *JJ;
3770: PetscBool nooffprocentries;
3773: if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]);
3775: PetscLayoutSetUp(B->rmap);
3776: PetscLayoutSetUp(B->cmap);
3777: m = B->rmap->n;
3778: cstart = B->cmap->rstart;
3779: cend = B->cmap->rend;
3780: rstart = B->rmap->rstart;
3782: PetscCalloc2(m,&d_nnz,m,&o_nnz);
3784: #if defined(PETSC_USE_DEBUG)
3785: for (i=0; i<m; i++) {
3786: nnz = Ii[i+1]- Ii[i];
3787: JJ = J + Ii[i];
3788: if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz);
3789: if (nnz && (JJ[0] < 0)) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,JJ[0]);
3790: if (nnz && (JJ[nnz-1] >= B->cmap->N)) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Row %D ends with too large a column index %D (max allowed %D)",i,JJ[nnz-1],B->cmap->N);
3791: }
3792: #endif
3794: for (i=0; i<m; i++) {
3795: nnz = Ii[i+1]- Ii[i];
3796: JJ = J + Ii[i];
3797: nnz_max = PetscMax(nnz_max,nnz);
3798: d = 0;
3799: for (j=0; j<nnz; j++) {
3800: if (cstart <= JJ[j] && JJ[j] < cend) d++;
3801: }
3802: d_nnz[i] = d;
3803: o_nnz[i] = nnz - d;
3804: }
3805: MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);
3806: PetscFree2(d_nnz,o_nnz);
3808: for (i=0; i<m; i++) {
3809: ii = i + rstart;
3810: MatSetValues_MPIAIJ(B,1,&ii,Ii[i+1] - Ii[i],J+Ii[i], v ? v + Ii[i] : NULL,INSERT_VALUES);
3811: }
3812: nooffprocentries = B->nooffprocentries;
3813: B->nooffprocentries = PETSC_TRUE;
3814: MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
3815: MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
3816: B->nooffprocentries = nooffprocentries;
3818: MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
3819: return(0);
3820: }
3822: /*@
3823: MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format
3824: (the default parallel PETSc format).
3826: Collective
3828: Input Parameters:
3829: + B - the matrix
3830: . i - the indices into j for the start of each local row (starts with zero)
3831: . j - the column indices for each local row (starts with zero)
3832: - v - optional values in the matrix
3834: Level: developer
3836: Notes:
3837: The i, j, and v arrays ARE copied by this routine into the internal format used by PETSc;
3838: thus you CANNOT change the matrix entries by changing the values of v[] after you have
3839: called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.
3841: The i and j indices are 0 based, and i indices are indices corresponding to the local j array.
3843: The format which is used for the sparse matrix input, is equivalent to a
3844: row-major ordering.. i.e for the following matrix, the input data expected is
3845: as shown
3847: $ 1 0 0
3848: $ 2 0 3 P0
3849: $ -------
3850: $ 4 5 6 P1
3851: $
3852: $ Process0 [P0]: rows_owned=[0,1]
3853: $ i = {0,1,3} [size = nrow+1 = 2+1]
3854: $ j = {0,0,2} [size = 3]
3855: $ v = {1,2,3} [size = 3]
3856: $
3857: $ Process1 [P1]: rows_owned=[2]
3858: $ i = {0,3} [size = nrow+1 = 1+1]
3859: $ j = {0,1,2} [size = 3]
3860: $ v = {4,5,6} [size = 3]
3862: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MATMPIAIJ,
3863: MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays()
3864: @*/
3865: PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
3866: {
3870: PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));
3871: return(0);
3872: }
3874: /*@C
3875: MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format
3876: (the default parallel PETSc format). For good matrix assembly performance
3877: the user should preallocate the matrix storage by setting the parameters
3878: d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately,
3879: performance can be increased by more than a factor of 50.
3881: Collective
3883: Input Parameters:
3884: + B - the matrix
3885: . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix
3886: (same value is used for all local rows)
3887: . d_nnz - array containing the number of nonzeros in the various rows of the
3888: DIAGONAL portion of the local submatrix (possibly different for each row)
3889: or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure.
3890: The size of this array is equal to the number of local rows, i.e 'm'.
3891: For matrices that will be factored, you must leave room for (and set)
3892: the diagonal entry even if it is zero.
3893: . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local
3894: submatrix (same value is used for all local rows).
3895: - o_nnz - array containing the number of nonzeros in the various rows of the
3896: OFF-DIAGONAL portion of the local submatrix (possibly different for
3897: each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero
3898: structure. The size of this array is equal to the number
3899: of local rows, i.e 'm'.
3901: If the *_nnz parameter is given then the *_nz parameter is ignored
3903: The AIJ format (also called the Yale sparse matrix format or
3904: compressed row storage (CSR)), is fully compatible with standard Fortran 77
3905: storage. The stored row and column indices begin with zero.
3906: See Users-Manual: ch_mat for details.
3908: The parallel matrix is partitioned such that the first m0 rows belong to
3909: process 0, the next m1 rows belong to process 1, the next m2 rows belong
3910: to process 2 etc.. where m0,m1,m2... are the input parameter 'm'.
3912: The DIAGONAL portion of the local submatrix of a processor can be defined
3913: as the submatrix which is obtained by extraction the part corresponding to
3914: the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the
3915: first row that belongs to the processor, r2 is the last row belonging to
3916: the this processor, and c1-c2 is range of indices of the local part of a
3917: vector suitable for applying the matrix to. This is an mxn matrix. In the
3918: common case of a square matrix, the row and column ranges are the same and
3919: the DIAGONAL part is also square. The remaining portion of the local
3920: submatrix (mxN) constitute the OFF-DIAGONAL portion.
3922: If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.
3924: You can call MatGetInfo() to get information on how effective the preallocation was;
3925: for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
3926: You can also run with the option -info and look for messages with the string
3927: malloc in them to see if additional memory allocation was needed.
3929: Example usage:
3931: Consider the following 8x8 matrix with 34 non-zero values, that is
3932: assembled across 3 processors. Lets assume that proc0 owns 3 rows,
3933: proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
3934: as follows:
3936: .vb
3937: 1 2 0 | 0 3 0 | 0 4
3938: Proc0 0 5 6 | 7 0 0 | 8 0
3939: 9 0 10 | 11 0 0 | 12 0
3940: -------------------------------------
3941: 13 0 14 | 15 16 17 | 0 0
3942: Proc1 0 18 0 | 19 20 21 | 0 0
3943: 0 0 0 | 22 23 0 | 24 0
3944: -------------------------------------
3945: Proc2 25 26 27 | 0 0 28 | 29 0
3946: 30 0 0 | 31 32 33 | 0 34
3947: .ve
3949: This can be represented as a collection of submatrices as:
3951: .vb
3952: A B C
3953: D E F
3954: G H I
3955: .ve
3957: Where the submatrices A,B,C are owned by proc0, D,E,F are
3958: owned by proc1, G,H,I are owned by proc2.
3960: The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
3961: The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
3962: The 'M','N' parameters are 8,8, and have the same values on all procs.
3964: The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
3965: submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
3966: corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
3967: Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
3968: part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
3969: matrix, ans [DF] as another SeqAIJ matrix.
3971: When d_nz, o_nz parameters are specified, d_nz storage elements are
3972: allocated for every row of the local diagonal submatrix, and o_nz
3973: storage locations are allocated for every row of the OFF-DIAGONAL submat.
3974: One way to choose d_nz and o_nz is to use the max nonzerors per local
3975: rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
3976: In this case, the values of d_nz,o_nz are:
3977: .vb
3978: proc0 : dnz = 2, o_nz = 2
3979: proc1 : dnz = 3, o_nz = 2
3980: proc2 : dnz = 1, o_nz = 4
3981: .ve
3982: We are allocating m*(d_nz+o_nz) storage locations for every proc. This
3983: translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
3984: for proc3. i.e we are using 12+15+10=37 storage locations to store
3985: 34 values.
3987: When d_nnz, o_nnz parameters are specified, the storage is specified
3988: for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
3989: In the above case the values for d_nnz,o_nnz are:
3990: .vb
3991: proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
3992: proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
3993: proc2: d_nnz = [1,1] and o_nnz = [4,4]
3994: .ve
3995: Here the space allocated is sum of all the above values i.e 34, and
3996: hence pre-allocation is perfect.
3998: Level: intermediate
4000: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(),
4001: MATMPIAIJ, MatGetInfo(), PetscSplitOwnership()
4002: @*/
4003: PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
4004: {
4010: PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));
4011: return(0);
4012: }
4014: /*@
4015: MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard
4016: CSR format for the local rows.
4018: Collective
4020: Input Parameters:
4021: + comm - MPI communicator
4022: . m - number of local rows (Cannot be PETSC_DECIDE)
4023: . n - This value should be the same as the local size used in creating the
4024: x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
4025: calculated if N is given) For square matrices n is almost always m.
4026: . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
4027: . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
4028: . i - row indices; that is i[0] = 0, i[row] = i[row-1] + number of elements in that row of the matrix
4029: . j - column indices
4030: - a - matrix values
4032: Output Parameter:
4033: . mat - the matrix
4035: Level: intermediate
4037: Notes:
4038: The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
4039: thus you CANNOT change the matrix entries by changing the values of a[] after you have
4040: called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.
4042: The i and j indices are 0 based, and i indices are indices corresponding to the local j array.
4044: The format which is used for the sparse matrix input, is equivalent to a
4045: row-major ordering.. i.e for the following matrix, the input data expected is
4046: as shown
4048: Once you have created the matrix you can update it with new numerical values using MatUpdateMPIAIJWithArrays
4050: $ 1 0 0
4051: $ 2 0 3 P0
4052: $ -------
4053: $ 4 5 6 P1
4054: $
4055: $ Process0 [P0]: rows_owned=[0,1]
4056: $ i = {0,1,3} [size = nrow+1 = 2+1]
4057: $ j = {0,0,2} [size = 3]
4058: $ v = {1,2,3} [size = 3]
4059: $
4060: $ Process1 [P1]: rows_owned=[2]
4061: $ i = {0,3} [size = nrow+1 = 1+1]
4062: $ j = {0,1,2} [size = 3]
4063: $ v = {4,5,6} [size = 3]
4065: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
4066: MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays(), MatUpdateMPIAIJWithArrays()
4067: @*/
4068: PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat)
4069: {
4073: if (i && i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
4074: if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
4075: MatCreate(comm,mat);
4076: MatSetSizes(*mat,m,n,M,N);
4077: /* MatSetBlockSizes(M,bs,cbs); */
4078: MatSetType(*mat,MATMPIAIJ);
4079: MatMPIAIJSetPreallocationCSR(*mat,i,j,a);
4080: return(0);
4081: }
4083: /*@
4084: MatUpdateMPIAIJWithArrays - updates a MPI AIJ matrix using arrays that contain in standard
4085: CSR format for the local rows. Only the numerical values are updated the other arrays must be identical
4087: Collective
4089: Input Parameters:
4090: + mat - the matrix
4091: . m - number of local rows (Cannot be PETSC_DECIDE)
4092: . n - This value should be the same as the local size used in creating the
4093: x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
4094: calculated if N is given) For square matrices n is almost always m.
4095: . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
4096: . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
4097: . Ii - row indices; that is Ii[0] = 0, Ii[row] = Ii[row-1] + number of elements in that row of the matrix
4098: . J - column indices
4099: - v - matrix values
4101: Level: intermediate
4103: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
4104: MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays(), MatUpdateMPIAIJWithArrays()
4105: @*/
4106: PetscErrorCode MatUpdateMPIAIJWithArrays(Mat mat,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[])
4107: {
4109: PetscInt cstart,nnz,i,j;
4110: PetscInt *ld;
4111: PetscBool nooffprocentries;
4112: Mat_MPIAIJ *Aij = (Mat_MPIAIJ*)mat->data;
4113: Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)Aij->A->data, *Ao = (Mat_SeqAIJ*)Aij->B->data;
4114: PetscScalar *ad = Ad->a, *ao = Ao->a;
4115: const PetscInt *Adi = Ad->i;
4116: PetscInt ldi,Iii,md;
4119: if (Ii[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
4120: if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
4121: if (m != mat->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Local number of rows cannot change from call to MatUpdateMPIAIJWithArrays()");
4122: if (n != mat->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Local number of columns cannot change from call to MatUpdateMPIAIJWithArrays()");
4124: cstart = mat->cmap->rstart;
4125: if (!Aij->ld) {
4126: /* count number of entries below block diagonal */
4127: PetscCalloc1(m,&ld);
4128: Aij->ld = ld;
4129: for (i=0; i<m; i++) {
4130: nnz = Ii[i+1]- Ii[i];
4131: j = 0;
4132: while (J[j] < cstart && j < nnz) {j++;}
4133: J += nnz;
4134: ld[i] = j;
4135: }
4136: } else {
4137: ld = Aij->ld;
4138: }
4140: for (i=0; i<m; i++) {
4141: nnz = Ii[i+1]- Ii[i];
4142: Iii = Ii[i];
4143: ldi = ld[i];
4144: md = Adi[i+1]-Adi[i];
4145: PetscArraycpy(ao,v + Iii,ldi);
4146: PetscArraycpy(ad,v + Iii + ldi,md);
4147: PetscArraycpy(ao + ldi,v + Iii + ldi + md,nnz - ldi - md);
4148: ad += md;
4149: ao += nnz - md;
4150: }
4151: nooffprocentries = mat->nooffprocentries;
4152: mat->nooffprocentries = PETSC_TRUE;
4153: PetscObjectStateIncrease((PetscObject)Aij->A);
4154: PetscObjectStateIncrease((PetscObject)Aij->B);
4155: PetscObjectStateIncrease((PetscObject)mat);
4156: MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);
4157: MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);
4158: mat->nooffprocentries = nooffprocentries;
4159: return(0);
4160: }
4162: /*@C
4163: MatCreateAIJ - Creates a sparse parallel matrix in AIJ format
4164: (the default parallel PETSc format). For good matrix assembly performance
4165: the user should preallocate the matrix storage by setting the parameters
4166: d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately,
4167: performance can be increased by more than a factor of 50.
4169: Collective
4171: Input Parameters:
4172: + comm - MPI communicator
4173: . m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
4174: This value should be the same as the local size used in creating the
4175: y vector for the matrix-vector product y = Ax.
4176: . n - This value should be the same as the local size used in creating the
4177: x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
4178: calculated if N is given) For square matrices n is almost always m.
4179: . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
4180: . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
4181: . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix
4182: (same value is used for all local rows)
4183: . d_nnz - array containing the number of nonzeros in the various rows of the
4184: DIAGONAL portion of the local submatrix (possibly different for each row)
4185: or NULL, if d_nz is used to specify the nonzero structure.
4186: The size of this array is equal to the number of local rows, i.e 'm'.
4187: . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local
4188: submatrix (same value is used for all local rows).
4189: - o_nnz - array containing the number of nonzeros in the various rows of the
4190: OFF-DIAGONAL portion of the local submatrix (possibly different for
4191: each row) or NULL, if o_nz is used to specify the nonzero
4192: structure. The size of this array is equal to the number
4193: of local rows, i.e 'm'.
4195: Output Parameter:
4196: . A - the matrix
4198: It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
4199: MatXXXXSetPreallocation() paradigm instead of this routine directly.
4200: [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]
4202: Notes:
4203: If the *_nnz parameter is given then the *_nz parameter is ignored
4205: m,n,M,N parameters specify the size of the matrix, and its partitioning across
4206: processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate
4207: storage requirements for this matrix.
4209: If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one
4210: processor than it must be used on all processors that share the object for
4211: that argument.
4213: The user MUST specify either the local or global matrix dimensions
4214: (possibly both).
4216: The parallel matrix is partitioned across processors such that the
4217: first m0 rows belong to process 0, the next m1 rows belong to
4218: process 1, the next m2 rows belong to process 2 etc.. where
4219: m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores
4220: values corresponding to [m x N] submatrix.
4222: The columns are logically partitioned with the n0 columns belonging
4223: to 0th partition, the next n1 columns belonging to the next
4224: partition etc.. where n0,n1,n2... are the input parameter 'n'.
4226: The DIAGONAL portion of the local submatrix on any given processor
4227: is the submatrix corresponding to the rows and columns m,n
4228: corresponding to the given processor. i.e diagonal matrix on
4229: process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1]
4230: etc. The remaining portion of the local submatrix [m x (N-n)]
4231: constitute the OFF-DIAGONAL portion. The example below better
4232: illustrates this concept.
4234: For a square global matrix we define each processor's diagonal portion
4235: to be its local rows and the corresponding columns (a square submatrix);
4236: each processor's off-diagonal portion encompasses the remainder of the
4237: local matrix (a rectangular submatrix).
4239: If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.
4241: When calling this routine with a single process communicator, a matrix of
4242: type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this
4243: type of communicator, use the construction mechanism
4244: .vb
4245: MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...);
4246: .ve
4248: $ MatCreate(...,&A);
4249: $ MatSetType(A,MATMPIAIJ);
4250: $ MatSetSizes(A, m,n,M,N);
4251: $ MatMPIAIJSetPreallocation(A,...);
4253: By default, this format uses inodes (identical nodes) when possible.
4254: We search for consecutive rows with the same nonzero structure, thereby
4255: reusing matrix information to achieve increased efficiency.
4257: Options Database Keys:
4258: + -mat_no_inode - Do not use inodes
4259: - -mat_inode_limit <limit> - Sets inode limit (max limit=5)
4263: Example usage:
4265: Consider the following 8x8 matrix with 34 non-zero values, that is
4266: assembled across 3 processors. Lets assume that proc0 owns 3 rows,
4267: proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
4268: as follows
4270: .vb
4271: 1 2 0 | 0 3 0 | 0 4
4272: Proc0 0 5 6 | 7 0 0 | 8 0
4273: 9 0 10 | 11 0 0 | 12 0
4274: -------------------------------------
4275: 13 0 14 | 15 16 17 | 0 0
4276: Proc1 0 18 0 | 19 20 21 | 0 0
4277: 0 0 0 | 22 23 0 | 24 0
4278: -------------------------------------
4279: Proc2 25 26 27 | 0 0 28 | 29 0
4280: 30 0 0 | 31 32 33 | 0 34
4281: .ve
4283: This can be represented as a collection of submatrices as
4285: .vb
4286: A B C
4287: D E F
4288: G H I
4289: .ve
4291: Where the submatrices A,B,C are owned by proc0, D,E,F are
4292: owned by proc1, G,H,I are owned by proc2.
4294: The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
4295: The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
4296: The 'M','N' parameters are 8,8, and have the same values on all procs.
4298: The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
4299: submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
4300: corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
4301: Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
4302: part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
4303: matrix, ans [DF] as another SeqAIJ matrix.
4305: When d_nz, o_nz parameters are specified, d_nz storage elements are
4306: allocated for every row of the local diagonal submatrix, and o_nz
4307: storage locations are allocated for every row of the OFF-DIAGONAL submat.
4308: One way to choose d_nz and o_nz is to use the max nonzerors per local
4309: rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
4310: In this case, the values of d_nz,o_nz are
4311: .vb
4312: proc0 : dnz = 2, o_nz = 2
4313: proc1 : dnz = 3, o_nz = 2
4314: proc2 : dnz = 1, o_nz = 4
4315: .ve
4316: We are allocating m*(d_nz+o_nz) storage locations for every proc. This
4317: translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
4318: for proc3. i.e we are using 12+15+10=37 storage locations to store
4319: 34 values.
4321: When d_nnz, o_nnz parameters are specified, the storage is specified
4322: for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
4323: In the above case the values for d_nnz,o_nnz are
4324: .vb
4325: proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
4326: proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
4327: proc2: d_nnz = [1,1] and o_nnz = [4,4]
4328: .ve
4329: Here the space allocated is sum of all the above values i.e 34, and
4330: hence pre-allocation is perfect.
4332: Level: intermediate
4334: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
4335: MATMPIAIJ, MatCreateMPIAIJWithArrays()
4336: @*/
4337: PetscErrorCode MatCreateAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A)
4338: {
4340: PetscMPIInt size;
4343: MatCreate(comm,A);
4344: MatSetSizes(*A,m,n,M,N);
4345: MPI_Comm_size(comm,&size);
4346: if (size > 1) {
4347: MatSetType(*A,MATMPIAIJ);
4348: MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);
4349: } else {
4350: MatSetType(*A,MATSEQAIJ);
4351: MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);
4352: }
4353: return(0);
4354: }
4356: /*@C
4357: MatMPIAIJGetSeqAIJ - Returns the local piece of this distributed matrix
4358:
4359: Not collective
4360:
4361: Input Parameter:
4362: . A - The MPIAIJ matrix
4364: Output Parameters:
4365: + Ad - The local diagonal block as a SeqAIJ matrix
4366: . Ao - The local off-diagonal block as a SeqAIJ matrix
4367: - colmap - An array mapping local column numbers of Ao to global column numbers of the parallel matrix
4369: Note: The rows in Ad and Ao are in [0, Nr), where Nr is the number of local rows on this process. The columns
4370: in Ad are in [0, Nc) where Nc is the number of local columns. The columns are Ao are in [0, Nco), where Nco is
4371: the number of nonzero columns in the local off-diagonal piece of the matrix A. The array colmap maps these
4372: local column numbers to global column numbers in the original matrix.
4374: Level: intermediate
4376: .seealso: MatMPIAIJGetLocalMat(), MatMPIAIJGetLocalMatCondensed(), MatCreateAIJ(), MATMPIAIJ, MATSEQAIJ
4377: @*/
4378: PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[])
4379: {
4380: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
4381: PetscBool flg;
4385: PetscStrbeginswith(((PetscObject)A)->type_name,MATMPIAIJ,&flg);
4386: if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MATMPIAIJ matrix as input");
4387: if (Ad) *Ad = a->A;
4388: if (Ao) *Ao = a->B;
4389: if (colmap) *colmap = a->garray;
4390: return(0);
4391: }
4393: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
4394: {
4396: PetscInt m,N,i,rstart,nnz,Ii;
4397: PetscInt *indx;
4398: PetscScalar *values;
4401: MatGetSize(inmat,&m,&N);
4402: if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
4403: PetscInt *dnz,*onz,sum,bs,cbs;
4405: if (n == PETSC_DECIDE) {
4406: PetscSplitOwnership(comm,&n,&N);
4407: }
4408: /* Check sum(n) = N */
4409: MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);
4410: if (sum != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns %D != global columns %D",sum,N);
4412: MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);
4413: rstart -= m;
4415: MatPreallocateInitialize(comm,m,n,dnz,onz);
4416: for (i=0; i<m; i++) {
4417: MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);
4418: MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);
4419: MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);
4420: }
4422: MatCreate(comm,outmat);
4423: MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
4424: MatGetBlockSizes(inmat,&bs,&cbs);
4425: MatSetBlockSizes(*outmat,bs,cbs);
4426: MatSetType(*outmat,MATAIJ);
4427: MatSeqAIJSetPreallocation(*outmat,0,dnz);
4428: MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);
4429: MatPreallocateFinalize(dnz,onz);
4430: }
4432: /* numeric phase */
4433: MatGetOwnershipRange(*outmat,&rstart,NULL);
4434: for (i=0; i<m; i++) {
4435: MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
4436: Ii = i + rstart;
4437: MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
4438: MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
4439: }
4440: MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
4441: MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
4442: return(0);
4443: }
4445: PetscErrorCode MatFileSplit(Mat A,char *outfile)
4446: {
4447: PetscErrorCode ierr;
4448: PetscMPIInt rank;
4449: PetscInt m,N,i,rstart,nnz;
4450: size_t len;
4451: const PetscInt *indx;
4452: PetscViewer out;
4453: char *name;
4454: Mat B;
4455: const PetscScalar *values;
4458: MatGetLocalSize(A,&m,0);
4459: MatGetSize(A,0,&N);
4460: /* Should this be the type of the diagonal block of A? */
4461: MatCreate(PETSC_COMM_SELF,&B);
4462: MatSetSizes(B,m,N,m,N);
4463: MatSetBlockSizesFromMats(B,A,A);
4464: MatSetType(B,MATSEQAIJ);
4465: MatSeqAIJSetPreallocation(B,0,NULL);
4466: MatGetOwnershipRange(A,&rstart,0);
4467: for (i=0; i<m; i++) {
4468: MatGetRow(A,i+rstart,&nnz,&indx,&values);
4469: MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);
4470: MatRestoreRow(A,i+rstart,&nnz,&indx,&values);
4471: }
4472: MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
4473: MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
4475: MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);
4476: PetscStrlen(outfile,&len);
4477: PetscMalloc1(len+5,&name);
4478: sprintf(name,"%s.%d",outfile,rank);
4479: PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);
4480: PetscFree(name);
4481: MatView(B,out);
4482: PetscViewerDestroy(&out);
4483: MatDestroy(&B);
4484: return(0);
4485: }
4487: PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A)
4488: {
4489: PetscErrorCode ierr;
4490: Mat_Merge_SeqsToMPI *merge;
4491: PetscContainer container;
4494: PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);
4495: if (container) {
4496: PetscContainerGetPointer(container,(void**)&merge);
4497: PetscFree(merge->id_r);
4498: PetscFree(merge->len_s);
4499: PetscFree(merge->len_r);
4500: PetscFree(merge->bi);
4501: PetscFree(merge->bj);
4502: PetscFree(merge->buf_ri[0]);
4503: PetscFree(merge->buf_ri);
4504: PetscFree(merge->buf_rj[0]);
4505: PetscFree(merge->buf_rj);
4506: PetscFree(merge->coi);
4507: PetscFree(merge->coj);
4508: PetscFree(merge->owners_co);
4509: PetscLayoutDestroy(&merge->rowmap);
4510: PetscFree(merge);
4511: PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);
4512: }
4513: MatDestroy_MPIAIJ(A);
4514: return(0);
4515: }
4517: #include <../src/mat/utils/freespace.h>
4518: #include <petscbt.h>
4520: PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat)
4521: {
4522: PetscErrorCode ierr;
4523: MPI_Comm comm;
4524: Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data;
4525: PetscMPIInt size,rank,taga,*len_s;
4526: PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj;
4527: PetscInt proc,m;
4528: PetscInt **buf_ri,**buf_rj;
4529: PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj;
4530: PetscInt nrows,**buf_ri_k,**nextrow,**nextai;
4531: MPI_Request *s_waits,*r_waits;
4532: MPI_Status *status;
4533: MatScalar *aa=a->a;
4534: MatScalar **abuf_r,*ba_i;
4535: Mat_Merge_SeqsToMPI *merge;
4536: PetscContainer container;
4539: PetscObjectGetComm((PetscObject)mpimat,&comm);
4540: PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);
4542: MPI_Comm_size(comm,&size);
4543: MPI_Comm_rank(comm,&rank);
4545: PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);
4546: PetscContainerGetPointer(container,(void**)&merge);
4548: bi = merge->bi;
4549: bj = merge->bj;
4550: buf_ri = merge->buf_ri;
4551: buf_rj = merge->buf_rj;
4553: PetscMalloc1(size,&status);
4554: owners = merge->rowmap->range;
4555: len_s = merge->len_s;
4557: /* send and recv matrix values */
4558: /*-----------------------------*/
4559: PetscObjectGetNewTag((PetscObject)mpimat,&taga);
4560: PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);
4562: PetscMalloc1(merge->nsend+1,&s_waits);
4563: for (proc=0,k=0; proc<size; proc++) {
4564: if (!len_s[proc]) continue;
4565: i = owners[proc];
4566: MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);
4567: k++;
4568: }
4570: if (merge->nrecv) {MPI_Waitall(merge->nrecv,r_waits,status);}
4571: if (merge->nsend) {MPI_Waitall(merge->nsend,s_waits,status);}
4572: PetscFree(status);
4574: PetscFree(s_waits);
4575: PetscFree(r_waits);
4577: /* insert mat values of mpimat */
4578: /*----------------------------*/
4579: PetscMalloc1(N,&ba_i);
4580: PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);
4582: for (k=0; k<merge->nrecv; k++) {
4583: buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
4584: nrows = *(buf_ri_k[k]);
4585: nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */
4586: nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */
4587: }
4589: /* set values of ba */
4590: m = merge->rowmap->n;
4591: for (i=0; i<m; i++) {
4592: arow = owners[rank] + i;
4593: bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */
4594: bnzi = bi[i+1] - bi[i];
4595: PetscArrayzero(ba_i,bnzi);
4597: /* add local non-zero vals of this proc's seqmat into ba */
4598: anzi = ai[arow+1] - ai[arow];
4599: aj = a->j + ai[arow];
4600: aa = a->a + ai[arow];
4601: nextaj = 0;
4602: for (j=0; nextaj<anzi; j++) {
4603: if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */
4604: ba_i[j] += aa[nextaj++];
4605: }
4606: }
4608: /* add received vals into ba */
4609: for (k=0; k<merge->nrecv; k++) { /* k-th received message */
4610: /* i-th row */
4611: if (i == *nextrow[k]) {
4612: anzi = *(nextai[k]+1) - *nextai[k];
4613: aj = buf_rj[k] + *(nextai[k]);
4614: aa = abuf_r[k] + *(nextai[k]);
4615: nextaj = 0;
4616: for (j=0; nextaj<anzi; j++) {
4617: if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */
4618: ba_i[j] += aa[nextaj++];
4619: }
4620: }
4621: nextrow[k]++; nextai[k]++;
4622: }
4623: }
4624: MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);
4625: }
4626: MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);
4627: MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);
4629: PetscFree(abuf_r[0]);
4630: PetscFree(abuf_r);
4631: PetscFree(ba_i);
4632: PetscFree3(buf_ri_k,nextrow,nextai);
4633: PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);
4634: return(0);
4635: }
4637: PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat)
4638: {
4639: PetscErrorCode ierr;
4640: Mat B_mpi;
4641: Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data;
4642: PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri;
4643: PetscInt **buf_rj,**buf_ri,**buf_ri_k;
4644: PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j;
4645: PetscInt len,proc,*dnz,*onz,bs,cbs;
4646: PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0;
4647: PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai;
4648: MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits;
4649: MPI_Status *status;
4650: PetscFreeSpaceList free_space=NULL,current_space=NULL;
4651: PetscBT lnkbt;
4652: Mat_Merge_SeqsToMPI *merge;
4653: PetscContainer container;
4656: PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);
4658: /* make sure it is a PETSc comm */
4659: PetscCommDuplicate(comm,&comm,NULL);
4660: MPI_Comm_size(comm,&size);
4661: MPI_Comm_rank(comm,&rank);
4663: PetscNew(&merge);
4664: PetscMalloc1(size,&status);
4666: /* determine row ownership */
4667: /*---------------------------------------------------------*/
4668: PetscLayoutCreate(comm,&merge->rowmap);
4669: PetscLayoutSetLocalSize(merge->rowmap,m);
4670: PetscLayoutSetSize(merge->rowmap,M);
4671: PetscLayoutSetBlockSize(merge->rowmap,1);
4672: PetscLayoutSetUp(merge->rowmap);
4673: PetscMalloc1(size,&len_si);
4674: PetscMalloc1(size,&merge->len_s);
4676: m = merge->rowmap->n;
4677: owners = merge->rowmap->range;
4679: /* determine the number of messages to send, their lengths */
4680: /*---------------------------------------------------------*/
4681: len_s = merge->len_s;
4683: len = 0; /* length of buf_si[] */
4684: merge->nsend = 0;
4685: for (proc=0; proc<size; proc++) {
4686: len_si[proc] = 0;
4687: if (proc == rank) {
4688: len_s[proc] = 0;
4689: } else {
4690: len_si[proc] = owners[proc+1] - owners[proc] + 1;
4691: len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */
4692: }
4693: if (len_s[proc]) {
4694: merge->nsend++;
4695: nrows = 0;
4696: for (i=owners[proc]; i<owners[proc+1]; i++) {
4697: if (ai[i+1] > ai[i]) nrows++;
4698: }
4699: len_si[proc] = 2*(nrows+1);
4700: len += len_si[proc];
4701: }
4702: }
4704: /* determine the number and length of messages to receive for ij-structure */
4705: /*-------------------------------------------------------------------------*/
4706: PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);
4707: PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);
4709: /* post the Irecv of j-structure */
4710: /*-------------------------------*/
4711: PetscCommGetNewTag(comm,&tagj);
4712: PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);
4714: /* post the Isend of j-structure */
4715: /*--------------------------------*/
4716: PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);
4718: for (proc=0, k=0; proc<size; proc++) {
4719: if (!len_s[proc]) continue;
4720: i = owners[proc];
4721: MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);
4722: k++;
4723: }
4725: /* receives and sends of j-structure are complete */
4726: /*------------------------------------------------*/
4727: if (merge->nrecv) {MPI_Waitall(merge->nrecv,rj_waits,status);}
4728: if (merge->nsend) {MPI_Waitall(merge->nsend,sj_waits,status);}
4730: /* send and recv i-structure */
4731: /*---------------------------*/
4732: PetscCommGetNewTag(comm,&tagi);
4733: PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);
4735: PetscMalloc1(len+1,&buf_s);
4736: buf_si = buf_s; /* points to the beginning of k-th msg to be sent */
4737: for (proc=0,k=0; proc<size; proc++) {
4738: if (!len_s[proc]) continue;
4739: /* form outgoing message for i-structure:
4740: buf_si[0]: nrows to be sent
4741: [1:nrows]: row index (global)
4742: [nrows+1:2*nrows+1]: i-structure index
4743: */
4744: /*-------------------------------------------*/
4745: nrows = len_si[proc]/2 - 1;
4746: buf_si_i = buf_si + nrows+1;
4747: buf_si[0] = nrows;
4748: buf_si_i[0] = 0;
4749: nrows = 0;
4750: for (i=owners[proc]; i<owners[proc+1]; i++) {
4751: anzi = ai[i+1] - ai[i];
4752: if (anzi) {
4753: buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */
4754: buf_si[nrows+1] = i-owners[proc]; /* local row index */
4755: nrows++;
4756: }
4757: }
4758: MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);
4759: k++;
4760: buf_si += len_si[proc];
4761: }
4763: if (merge->nrecv) {MPI_Waitall(merge->nrecv,ri_waits,status);}
4764: if (merge->nsend) {MPI_Waitall(merge->nsend,si_waits,status);}
4766: PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);
4767: for (i=0; i<merge->nrecv; i++) {
4768: PetscInfo3(seqmat,"recv len_ri=%D, len_rj=%D from [%D]\n",len_ri[i],merge->len_r[i],merge->id_r[i]);
4769: }
4771: PetscFree(len_si);
4772: PetscFree(len_ri);
4773: PetscFree(rj_waits);
4774: PetscFree2(si_waits,sj_waits);
4775: PetscFree(ri_waits);
4776: PetscFree(buf_s);
4777: PetscFree(status);
4779: /* compute a local seq matrix in each processor */
4780: /*----------------------------------------------*/
4781: /* allocate bi array and free space for accumulating nonzero column info */
4782: PetscMalloc1(m+1,&bi);
4783: bi[0] = 0;
4785: /* create and initialize a linked list */
4786: nlnk = N+1;
4787: PetscLLCreate(N,N,nlnk,lnk,lnkbt);
4789: /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */
4790: len = ai[owners[rank+1]] - ai[owners[rank]];
4791: PetscFreeSpaceGet(PetscIntMultTruncate(2,len)+1,&free_space);
4793: current_space = free_space;
4795: /* determine symbolic info for each local row */
4796: PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);
4798: for (k=0; k<merge->nrecv; k++) {
4799: buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
4800: nrows = *buf_ri_k[k];
4801: nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */
4802: nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */
4803: }
4805: MatPreallocateInitialize(comm,m,n,dnz,onz);
4806: len = 0;
4807: for (i=0; i<m; i++) {
4808: bnzi = 0;
4809: /* add local non-zero cols of this proc's seqmat into lnk */
4810: arow = owners[rank] + i;
4811: anzi = ai[arow+1] - ai[arow];
4812: aj = a->j + ai[arow];
4813: PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);
4814: bnzi += nlnk;
4815: /* add received col data into lnk */
4816: for (k=0; k<merge->nrecv; k++) { /* k-th received message */
4817: if (i == *nextrow[k]) { /* i-th row */
4818: anzi = *(nextai[k]+1) - *nextai[k];
4819: aj = buf_rj[k] + *nextai[k];
4820: PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);
4821: bnzi += nlnk;
4822: nextrow[k]++; nextai[k]++;
4823: }
4824: }
4825: if (len < bnzi) len = bnzi; /* =max(bnzi) */
4827: /* if free space is not available, make more free space */
4828: if (current_space->local_remaining<bnzi) {
4829: PetscFreeSpaceGet(PetscIntSumTruncate(bnzi,current_space->total_array_size),¤t_space);
4830: nspacedouble++;
4831: }
4832: /* copy data into free space, then initialize lnk */
4833: PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);
4834: MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);
4836: current_space->array += bnzi;
4837: current_space->local_used += bnzi;
4838: current_space->local_remaining -= bnzi;
4840: bi[i+1] = bi[i] + bnzi;
4841: }
4843: PetscFree3(buf_ri_k,nextrow,nextai);
4845: PetscMalloc1(bi[m]+1,&bj);
4846: PetscFreeSpaceContiguous(&free_space,bj);
4847: PetscLLDestroy(lnk,lnkbt);
4849: /* create symbolic parallel matrix B_mpi */
4850: /*---------------------------------------*/
4851: MatGetBlockSizes(seqmat,&bs,&cbs);
4852: MatCreate(comm,&B_mpi);
4853: if (n==PETSC_DECIDE) {
4854: MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);
4855: } else {
4856: MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
4857: }
4858: MatSetBlockSizes(B_mpi,bs,cbs);
4859: MatSetType(B_mpi,MATMPIAIJ);
4860: MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);
4861: MatPreallocateFinalize(dnz,onz);
4862: MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);
4864: /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */
4865: B_mpi->assembled = PETSC_FALSE;
4866: B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI;
4867: merge->bi = bi;
4868: merge->bj = bj;
4869: merge->buf_ri = buf_ri;
4870: merge->buf_rj = buf_rj;
4871: merge->coi = NULL;
4872: merge->coj = NULL;
4873: merge->owners_co = NULL;
4875: PetscCommDestroy(&comm);
4877: /* attach the supporting struct to B_mpi for reuse */
4878: PetscContainerCreate(PETSC_COMM_SELF,&container);
4879: PetscContainerSetPointer(container,merge);
4880: PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);
4881: PetscContainerDestroy(&container);
4882: *mpimat = B_mpi;
4884: PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);
4885: return(0);
4886: }
4888: /*@C
4889: MatCreateMPIAIJSumSeqAIJ - Creates a MATMPIAIJ matrix by adding sequential
4890: matrices from each processor
4892: Collective
4894: Input Parameters:
4895: + comm - the communicators the parallel matrix will live on
4896: . seqmat - the input sequential matrices
4897: . m - number of local rows (or PETSC_DECIDE)
4898: . n - number of local columns (or PETSC_DECIDE)
4899: - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
4901: Output Parameter:
4902: . mpimat - the parallel matrix generated
4904: Level: advanced
4906: Notes:
4907: The dimensions of the sequential matrix in each processor MUST be the same.
4908: The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be
4909: destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat.
4910: @*/
4911: PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat)
4912: {
4914: PetscMPIInt size;
4917: MPI_Comm_size(comm,&size);
4918: if (size == 1) {
4919: PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
4920: if (scall == MAT_INITIAL_MATRIX) {
4921: MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);
4922: } else {
4923: MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);
4924: }
4925: PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
4926: return(0);
4927: }
4928: PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
4929: if (scall == MAT_INITIAL_MATRIX) {
4930: MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);
4931: }
4932: MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);
4933: PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
4934: return(0);
4935: }
4937: /*@
4938: MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MATMPIAIJ matrix by taking all its local rows and putting them into a sequential matrix with
4939: mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained
4940: with MatGetSize()
4942: Not Collective
4944: Input Parameters:
4945: + A - the matrix
4946: - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
4948: Output Parameter:
4949: . A_loc - the local sequential matrix generated
4951: Level: developer
4953: Notes:
4954: When the communicator associated with A has size 1 and MAT_INITIAL_MATRIX is requested, the matrix returned is the diagonal part of A.
4955: If MAT_REUSE_MATRIX is requested with comm size 1, MatCopy(Adiag,*A_loc,SAME_NONZERO_PATTERN) is called.
4956: This means that one can preallocate the proper sequential matrix first and then call this routine with MAT_REUSE_MATRIX to safely
4957: modify the values of the returned A_loc.
4959: .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMatCondensed()
4961: @*/
4962: PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc)
4963: {
4965: Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data;
4966: Mat_SeqAIJ *mat,*a,*b;
4967: PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray;
4968: MatScalar *aa,*ba,*cam;
4969: PetscScalar *ca;
4970: PetscMPIInt size;
4971: PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart;
4972: PetscInt *ci,*cj,col,ncols_d,ncols_o,jo;
4973: PetscBool match;
4976: PetscStrbeginswith(((PetscObject)A)->type_name,MATMPIAIJ,&match);
4977: if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input");
4978: MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);
4979: if (size == 1) {
4980: if (scall == MAT_INITIAL_MATRIX) {
4981: PetscObjectReference((PetscObject)mpimat->A);
4982: *A_loc = mpimat->A;
4983: } else if (scall == MAT_REUSE_MATRIX) {
4984: MatCopy(mpimat->A,*A_loc,SAME_NONZERO_PATTERN);
4985: }
4986: return(0);
4987: }
4989: PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);
4990: a = (Mat_SeqAIJ*)(mpimat->A)->data;
4991: b = (Mat_SeqAIJ*)(mpimat->B)->data;
4992: ai = a->i; aj = a->j; bi = b->i; bj = b->j;
4993: aa = a->a; ba = b->a;
4994: if (scall == MAT_INITIAL_MATRIX) {
4995: PetscMalloc1(1+am,&ci);
4996: ci[0] = 0;
4997: for (i=0; i<am; i++) {
4998: ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]);
4999: }
5000: PetscMalloc1(1+ci[am],&cj);
5001: PetscMalloc1(1+ci[am],&ca);
5002: k = 0;
5003: for (i=0; i<am; i++) {
5004: ncols_o = bi[i+1] - bi[i];
5005: ncols_d = ai[i+1] - ai[i];
5006: /* off-diagonal portion of A */
5007: for (jo=0; jo<ncols_o; jo++) {
5008: col = cmap[*bj];
5009: if (col >= cstart) break;
5010: cj[k] = col; bj++;
5011: ca[k++] = *ba++;
5012: }
5013: /* diagonal portion of A */
5014: for (j=0; j<ncols_d; j++) {
5015: cj[k] = cstart + *aj++;
5016: ca[k++] = *aa++;
5017: }
5018: /* off-diagonal portion of A */
5019: for (j=jo; j<ncols_o; j++) {
5020: cj[k] = cmap[*bj++];
5021: ca[k++] = *ba++;
5022: }
5023: }
5024: /* put together the new matrix */
5025: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);
5026: /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
5027: /* Since these are PETSc arrays, change flags to free them as necessary. */
5028: mat = (Mat_SeqAIJ*)(*A_loc)->data;
5029: mat->free_a = PETSC_TRUE;
5030: mat->free_ij = PETSC_TRUE;
5031: mat->nonew = 0;
5032: } else if (scall == MAT_REUSE_MATRIX) {
5033: mat=(Mat_SeqAIJ*)(*A_loc)->data;
5034: ci = mat->i; cj = mat->j; cam = mat->a;
5035: for (i=0; i<am; i++) {
5036: /* off-diagonal portion of A */
5037: ncols_o = bi[i+1] - bi[i];
5038: for (jo=0; jo<ncols_o; jo++) {
5039: col = cmap[*bj];
5040: if (col >= cstart) break;
5041: *cam++ = *ba++; bj++;
5042: }
5043: /* diagonal portion of A */
5044: ncols_d = ai[i+1] - ai[i];
5045: for (j=0; j<ncols_d; j++) *cam++ = *aa++;
5046: /* off-diagonal portion of A */
5047: for (j=jo; j<ncols_o; j++) {
5048: *cam++ = *ba++; bj++;
5049: }
5050: }
5051: } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall);
5052: PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);
5053: return(0);
5054: }
5056: /*@C
5057: MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MATMPIAIJ matrix by taking all its local rows and NON-ZERO columns
5059: Not Collective
5061: Input Parameters:
5062: + A - the matrix
5063: . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
5064: - row, col - index sets of rows and columns to extract (or NULL)
5066: Output Parameter:
5067: . A_loc - the local sequential matrix generated
5069: Level: developer
5071: .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat()
5073: @*/
5074: PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc)
5075: {
5076: Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data;
5078: PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx;
5079: IS isrowa,iscola;
5080: Mat *aloc;
5081: PetscBool match;
5084: PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);
5085: if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input");
5086: PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);
5087: if (!row) {
5088: start = A->rmap->rstart; end = A->rmap->rend;
5089: ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);
5090: } else {
5091: isrowa = *row;
5092: }
5093: if (!col) {
5094: start = A->cmap->rstart;
5095: cmap = a->garray;
5096: nzA = a->A->cmap->n;
5097: nzB = a->B->cmap->n;
5098: PetscMalloc1(nzA+nzB, &idx);
5099: ncols = 0;
5100: for (i=0; i<nzB; i++) {
5101: if (cmap[i] < start) idx[ncols++] = cmap[i];
5102: else break;
5103: }
5104: imark = i;
5105: for (i=0; i<nzA; i++) idx[ncols++] = start + i;
5106: for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i];
5107: ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);
5108: } else {
5109: iscola = *col;
5110: }
5111: if (scall != MAT_INITIAL_MATRIX) {
5112: PetscMalloc1(1,&aloc);
5113: aloc[0] = *A_loc;
5114: }
5115: MatCreateSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);
5116: if (!col) { /* attach global id of condensed columns */
5117: PetscObjectCompose((PetscObject)aloc[0],"_petsc_GetLocalMatCondensed_iscol",(PetscObject)iscola);
5118: }
5119: *A_loc = aloc[0];
5120: PetscFree(aloc);
5121: if (!row) {
5122: ISDestroy(&isrowa);
5123: }
5124: if (!col) {
5125: ISDestroy(&iscola);
5126: }
5127: PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);
5128: return(0);
5129: }
5131: /*
5132: * Destroy a mat that may be composed with PetscSF communication objects.
5133: * The SF objects were created in MatCreateSeqSubMatrixWithRows_Private.
5134: * */
5135: PetscErrorCode MatDestroy_SeqAIJ_PetscSF(Mat mat)
5136: {
5137: PetscSF sf,osf;
5138: IS map;
5139: PetscErrorCode ierr;
5142: PetscObjectQuery((PetscObject)mat,"diagsf",(PetscObject*)&sf);
5143: PetscObjectQuery((PetscObject)mat,"offdiagsf",(PetscObject*)&osf);
5144: PetscSFDestroy(&sf);
5145: PetscSFDestroy(&osf);
5146: PetscObjectQuery((PetscObject)mat,"aoffdiagtopothmapping",(PetscObject*)&map);
5147: ISDestroy(&map);
5148: MatDestroy_SeqAIJ(mat);
5149: return(0);
5150: }
5152: /*
5153: * Create a sequential AIJ matrix based on row indices. a whole column is extracted once a row is matched.
5154: * Row could be local or remote.The routine is designed to be scalable in memory so that nothing is based
5155: * on a global size.
5156: * */
5157: PetscErrorCode MatCreateSeqSubMatrixWithRows_Private(Mat P,IS rows,Mat *P_oth)
5158: {
5159: Mat_MPIAIJ *p=(Mat_MPIAIJ*)P->data;
5160: Mat_SeqAIJ *pd=(Mat_SeqAIJ*)(p->A)->data,*po=(Mat_SeqAIJ*)(p->B)->data,*p_oth;
5161: PetscInt plocalsize,nrows,*ilocal,*oilocal,i,lidx,*nrcols,*nlcols,ncol;
5162: PetscMPIInt owner;
5163: PetscSFNode *iremote,*oiremote;
5164: const PetscInt *lrowindices;
5165: PetscErrorCode ierr;
5166: PetscSF sf,osf;
5167: PetscInt pcstart,*roffsets,*loffsets,*pnnz,j;
5168: PetscInt ontotalcols,dntotalcols,ntotalcols,nout;
5169: MPI_Comm comm;
5170: ISLocalToGlobalMapping mapping;
5173: PetscObjectGetComm((PetscObject)P,&comm);
5174: /* plocalsize is the number of roots
5175: * nrows is the number of leaves
5176: * */
5177: MatGetLocalSize(P,&plocalsize,NULL);
5178: ISGetLocalSize(rows,&nrows);
5179: PetscCalloc1(nrows,&iremote);
5180: ISGetIndices(rows,&lrowindices);
5181: for (i=0;i<nrows;i++) {
5182: /* Find a remote index and an owner for a row
5183: * The row could be local or remote
5184: * */
5185: owner = 0;
5186: lidx = 0;
5187: PetscLayoutFindOwnerIndex(P->rmap,lrowindices[i],&owner,&lidx);
5188: iremote[i].index = lidx;
5189: iremote[i].rank = owner;
5190: }
5191: /* Create SF to communicate how many nonzero columns for each row */
5192: PetscSFCreate(comm,&sf);
5193: /* SF will figure out the number of nonzero colunms for each row, and their
5194: * offsets
5195: * */
5196: PetscSFSetGraph(sf,plocalsize,nrows,NULL,PETSC_OWN_POINTER,iremote,PETSC_OWN_POINTER);
5197: PetscSFSetFromOptions(sf);
5198: PetscSFSetUp(sf);
5200: PetscCalloc1(2*(plocalsize+1),&roffsets);
5201: PetscCalloc1(2*plocalsize,&nrcols);
5202: PetscCalloc1(nrows,&pnnz);
5203: roffsets[0] = 0;
5204: roffsets[1] = 0;
5205: for (i=0;i<plocalsize;i++) {
5206: /* diag */
5207: nrcols[i*2+0] = pd->i[i+1] - pd->i[i];
5208: /* off diag */
5209: nrcols[i*2+1] = po->i[i+1] - po->i[i];
5210: /* compute offsets so that we relative location for each row */
5211: roffsets[(i+1)*2+0] = roffsets[i*2+0] + nrcols[i*2+0];
5212: roffsets[(i+1)*2+1] = roffsets[i*2+1] + nrcols[i*2+1];
5213: }
5214: PetscCalloc1(2*nrows,&nlcols);
5215: PetscCalloc1(2*nrows,&loffsets);
5216: /* 'r' means root, and 'l' means leaf */
5217: PetscSFBcastBegin(sf,MPIU_2INT,nrcols,nlcols);
5218: PetscSFBcastBegin(sf,MPIU_2INT,roffsets,loffsets);
5219: PetscSFBcastEnd(sf,MPIU_2INT,nrcols,nlcols);
5220: PetscSFBcastEnd(sf,MPIU_2INT,roffsets,loffsets);
5221: PetscSFDestroy(&sf);
5222: PetscFree(roffsets);
5223: PetscFree(nrcols);
5224: dntotalcols = 0;
5225: ontotalcols = 0;
5226: ncol = 0;
5227: for (i=0;i<nrows;i++) {
5228: pnnz[i] = nlcols[i*2+0] + nlcols[i*2+1];
5229: ncol = PetscMax(pnnz[i],ncol);
5230: /* diag */
5231: dntotalcols += nlcols[i*2+0];
5232: /* off diag */
5233: ontotalcols += nlcols[i*2+1];
5234: }
5235: /* We do not need to figure the right number of columns
5236: * since all the calculations will be done by going through the raw data
5237: * */
5238: MatCreateSeqAIJ(PETSC_COMM_SELF,nrows,ncol,0,pnnz,P_oth);
5239: MatSetUp(*P_oth);
5240: PetscFree(pnnz);
5241: p_oth = (Mat_SeqAIJ*) (*P_oth)->data;
5242: /* diag */
5243: PetscCalloc1(dntotalcols,&iremote);
5244: /* off diag */
5245: PetscCalloc1(ontotalcols,&oiremote);
5246: /* diag */
5247: PetscCalloc1(dntotalcols,&ilocal);
5248: /* off diag */
5249: PetscCalloc1(ontotalcols,&oilocal);
5250: dntotalcols = 0;
5251: ontotalcols = 0;
5252: ntotalcols = 0;
5253: for (i=0;i<nrows;i++) {
5254: owner = 0;
5255: PetscLayoutFindOwnerIndex(P->rmap,lrowindices[i],&owner,NULL);
5256: /* Set iremote for diag matrix */
5257: for (j=0;j<nlcols[i*2+0];j++) {
5258: iremote[dntotalcols].index = loffsets[i*2+0] + j;
5259: iremote[dntotalcols].rank = owner;
5260: /* P_oth is seqAIJ so that ilocal need to point to the first part of memory */
5261: ilocal[dntotalcols++] = ntotalcols++;
5262: }
5263: /* off diag */
5264: for (j=0;j<nlcols[i*2+1];j++) {
5265: oiremote[ontotalcols].index = loffsets[i*2+1] + j;
5266: oiremote[ontotalcols].rank = owner;
5267: oilocal[ontotalcols++] = ntotalcols++;
5268: }
5269: }
5270: ISRestoreIndices(rows,&lrowindices);
5271: PetscFree(loffsets);
5272: PetscFree(nlcols);
5273: PetscSFCreate(comm,&sf);
5274: /* P serves as roots and P_oth is leaves
5275: * Diag matrix
5276: * */
5277: PetscSFSetGraph(sf,pd->i[plocalsize],dntotalcols,ilocal,PETSC_OWN_POINTER,iremote,PETSC_OWN_POINTER);
5278: PetscSFSetFromOptions(sf);
5279: PetscSFSetUp(sf);
5281: PetscSFCreate(comm,&osf);
5282: /* Off diag */
5283: PetscSFSetGraph(osf,po->i[plocalsize],ontotalcols,oilocal,PETSC_OWN_POINTER,oiremote,PETSC_OWN_POINTER);
5284: PetscSFSetFromOptions(osf);
5285: PetscSFSetUp(osf);
5286: /* We operate on the matrix internal data for saving memory */
5287: PetscSFBcastBegin(sf,MPIU_SCALAR,pd->a,p_oth->a);
5288: PetscSFBcastBegin(osf,MPIU_SCALAR,po->a,p_oth->a);
5289: MatGetOwnershipRangeColumn(P,&pcstart,NULL);
5290: /* Convert to global indices for diag matrix */
5291: for (i=0;i<pd->i[plocalsize];i++) pd->j[i] += pcstart;
5292: PetscSFBcastBegin(sf,MPIU_INT,pd->j,p_oth->j);
5293: /* We want P_oth store global indices */
5294: ISLocalToGlobalMappingCreate(comm,1,p->B->cmap->n,p->garray,PETSC_COPY_VALUES,&mapping);
5295: /* Use memory scalable approach */
5296: ISLocalToGlobalMappingSetType(mapping,ISLOCALTOGLOBALMAPPINGHASH);
5297: ISLocalToGlobalMappingApply(mapping,po->i[plocalsize],po->j,po->j);
5298: PetscSFBcastBegin(osf,MPIU_INT,po->j,p_oth->j);
5299: PetscSFBcastEnd(sf,MPIU_INT,pd->j,p_oth->j);
5300: /* Convert back to local indices */
5301: for (i=0;i<pd->i[plocalsize];i++) pd->j[i] -= pcstart;
5302: PetscSFBcastEnd(osf,MPIU_INT,po->j,p_oth->j);
5303: nout = 0;
5304: ISGlobalToLocalMappingApply(mapping,IS_GTOLM_DROP,po->i[plocalsize],po->j,&nout,po->j);
5305: if (nout != po->i[plocalsize]) SETERRQ2(comm,PETSC_ERR_ARG_INCOMP,"n %D does not equal to nout %D \n",po->i[plocalsize],nout);
5306: ISLocalToGlobalMappingDestroy(&mapping);
5307: /* Exchange values */
5308: PetscSFBcastEnd(sf,MPIU_SCALAR,pd->a,p_oth->a);
5309: PetscSFBcastEnd(osf,MPIU_SCALAR,po->a,p_oth->a);
5310: /* Stop PETSc from shrinking memory */
5311: for (i=0;i<nrows;i++) p_oth->ilen[i] = p_oth->imax[i];
5312: MatAssemblyBegin(*P_oth,MAT_FINAL_ASSEMBLY);
5313: MatAssemblyEnd(*P_oth,MAT_FINAL_ASSEMBLY);
5314: /* Attach PetscSF objects to P_oth so that we can reuse it later */
5315: PetscObjectCompose((PetscObject)*P_oth,"diagsf",(PetscObject)sf);
5316: PetscObjectCompose((PetscObject)*P_oth,"offdiagsf",(PetscObject)osf);
5317: /* ``New MatDestroy" takes care of PetscSF objects as well */
5318: (*P_oth)->ops->destroy = MatDestroy_SeqAIJ_PetscSF;
5319: return(0);
5320: }
5322: /*
5323: * Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A
5324: * This supports MPIAIJ and MAIJ
5325: * */
5326: PetscErrorCode MatGetBrowsOfAcols_MPIXAIJ(Mat A,Mat P,PetscInt dof,MatReuse reuse,Mat *P_oth)
5327: {
5328: Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data,*p=(Mat_MPIAIJ*)P->data;
5329: Mat_SeqAIJ *p_oth;
5330: Mat_SeqAIJ *pd=(Mat_SeqAIJ*)(p->A)->data,*po=(Mat_SeqAIJ*)(p->B)->data;
5331: IS rows,map;
5332: PetscHMapI hamp;
5333: PetscInt i,htsize,*rowindices,off,*mapping,key,count;
5334: MPI_Comm comm;
5335: PetscSF sf,osf;
5336: PetscBool has;
5337: PetscErrorCode ierr;
5340: PetscObjectGetComm((PetscObject)A,&comm);
5341: PetscLogEventBegin(MAT_GetBrowsOfAocols,A,P,0,0);
5342: /* If it is the first time, create an index set of off-diag nonzero columns of A,
5343: * and then create a submatrix (that often is an overlapping matrix)
5344: * */
5345: if (reuse==MAT_INITIAL_MATRIX) {
5346: /* Use a hash table to figure out unique keys */
5347: PetscHMapICreate(&hamp);
5348: PetscHMapIResize(hamp,a->B->cmap->n);
5349: PetscCalloc1(a->B->cmap->n,&mapping);
5350: count = 0;
5351: /* Assume that a->g is sorted, otherwise the following does not make sense */
5352: for (i=0;i<a->B->cmap->n;i++) {
5353: key = a->garray[i]/dof;
5354: PetscHMapIHas(hamp,key,&has);
5355: if (!has) {
5356: mapping[i] = count;
5357: PetscHMapISet(hamp,key,count++);
5358: } else {
5359: /* Current 'i' has the same value the previous step */
5360: mapping[i] = count-1;
5361: }
5362: }
5363: ISCreateGeneral(comm,a->B->cmap->n,mapping,PETSC_OWN_POINTER,&map);
5364: PetscHMapIGetSize(hamp,&htsize);
5365: if (htsize!=count) SETERRQ2(comm,PETSC_ERR_ARG_INCOMP," Size of hash map %D is inconsistent with count %D \n",htsize,count);
5366: PetscCalloc1(htsize,&rowindices);
5367: off = 0;
5368: PetscHMapIGetKeys(hamp,&off,rowindices);
5369: PetscHMapIDestroy(&hamp);
5370: PetscSortInt(htsize,rowindices);
5371: ISCreateGeneral(comm,htsize,rowindices,PETSC_OWN_POINTER,&rows);
5372: /* In case, the matrix was already created but users want to recreate the matrix */
5373: MatDestroy(P_oth);
5374: MatCreateSeqSubMatrixWithRows_Private(P,rows,P_oth);
5375: PetscObjectCompose((PetscObject)*P_oth,"aoffdiagtopothmapping",(PetscObject)map);
5376: ISDestroy(&rows);
5377: } else if (reuse==MAT_REUSE_MATRIX) {
5378: /* If matrix was already created, we simply update values using SF objects
5379: * that as attached to the matrix ealier.
5380: * */
5381: PetscObjectQuery((PetscObject)*P_oth,"diagsf",(PetscObject*)&sf);
5382: PetscObjectQuery((PetscObject)*P_oth,"offdiagsf",(PetscObject*)&osf);
5383: if (!sf || !osf) {
5384: SETERRQ(comm,PETSC_ERR_ARG_NULL,"Matrix is not initialized yet \n");
5385: }
5386: p_oth = (Mat_SeqAIJ*) (*P_oth)->data;
5387: /* Update values in place */
5388: PetscSFBcastBegin(sf,MPIU_SCALAR,pd->a,p_oth->a);
5389: PetscSFBcastBegin(osf,MPIU_SCALAR,po->a,p_oth->a);
5390: PetscSFBcastEnd(sf,MPIU_SCALAR,pd->a,p_oth->a);
5391: PetscSFBcastEnd(osf,MPIU_SCALAR,po->a,p_oth->a);
5392: } else {
5393: SETERRQ(comm,PETSC_ERR_ARG_UNKNOWN_TYPE,"Unknown reuse type \n");
5394: }
5395: PetscLogEventEnd(MAT_GetBrowsOfAocols,A,P,0,0);
5396: return(0);
5397: }
5399: /*@C
5400: MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A
5402: Collective on Mat
5404: Input Parameters:
5405: + A,B - the matrices in mpiaij format
5406: . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
5407: - rowb, colb - index sets of rows and columns of B to extract (or NULL)
5409: Output Parameter:
5410: + rowb, colb - index sets of rows and columns of B to extract
5411: - B_seq - the sequential matrix generated
5413: Level: developer
5415: @*/
5416: PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq)
5417: {
5418: Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data;
5420: PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark;
5421: IS isrowb,iscolb;
5422: Mat *bseq=NULL;
5425: if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
5426: SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%D, %D) != (%D,%D)",A->cmap->rstart,A->cmap->rend,B->rmap->rstart,B->rmap->rend);
5427: }
5428: PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);
5430: if (scall == MAT_INITIAL_MATRIX) {
5431: start = A->cmap->rstart;
5432: cmap = a->garray;
5433: nzA = a->A->cmap->n;
5434: nzB = a->B->cmap->n;
5435: PetscMalloc1(nzA+nzB, &idx);
5436: ncols = 0;
5437: for (i=0; i<nzB; i++) { /* row < local row index */
5438: if (cmap[i] < start) idx[ncols++] = cmap[i];
5439: else break;
5440: }
5441: imark = i;
5442: for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */
5443: for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */
5444: ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);
5445: ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);
5446: } else {
5447: if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX");
5448: isrowb = *rowb; iscolb = *colb;
5449: PetscMalloc1(1,&bseq);
5450: bseq[0] = *B_seq;
5451: }
5452: MatCreateSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);
5453: *B_seq = bseq[0];
5454: PetscFree(bseq);
5455: if (!rowb) {
5456: ISDestroy(&isrowb);
5457: } else {
5458: *rowb = isrowb;
5459: }
5460: if (!colb) {
5461: ISDestroy(&iscolb);
5462: } else {
5463: *colb = iscolb;
5464: }
5465: PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);
5466: return(0);
5467: }
5469: /*
5470: MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns
5471: of the OFF-DIAGONAL portion of local A
5473: Collective on Mat
5475: Input Parameters:
5476: + A,B - the matrices in mpiaij format
5477: - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
5479: Output Parameter:
5480: + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL)
5481: . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL)
5482: . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL)
5483: - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N
5485: Developer Notes: This directly accesses information inside the VecScatter associated with the matrix-vector product
5486: for this matrix. This is not desirable..
5488: Level: developer
5490: */
5491: PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth)
5492: {
5493: PetscErrorCode ierr;
5494: Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data;
5495: Mat_SeqAIJ *b_oth;
5496: VecScatter ctx;
5497: MPI_Comm comm;
5498: const PetscMPIInt *rprocs,*sprocs;
5499: const PetscInt *srow,*rstarts,*sstarts;
5500: PetscInt *rowlen,*bufj,*bufJ,ncols = 0,aBn=a->B->cmap->n,row,*b_othi,*b_othj,*rvalues=NULL,*svalues=NULL,*cols,sbs,rbs;
5501: PetscInt i,j,k=0,l,ll,nrecvs,nsends,nrows,*rstartsj = 0,*sstartsj,len;
5502: PetscScalar *b_otha,*bufa,*bufA,*vals = NULL;
5503: MPI_Request *rwaits = NULL,*swaits = NULL;
5504: MPI_Status rstatus;
5505: PetscMPIInt jj,size,tag,rank,nsends_mpi,nrecvs_mpi;
5508: PetscObjectGetComm((PetscObject)A,&comm);
5509: MPI_Comm_size(comm,&size);
5511: if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
5512: SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%d, %d) != (%d,%d)",A->cmap->rstart,A->cmap->rend,B->rmap->rstart,B->rmap->rend);
5513: }
5514: PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);
5515: MPI_Comm_rank(comm,&rank);
5517: if (size == 1) {
5518: startsj_s = NULL;
5519: bufa_ptr = NULL;
5520: *B_oth = NULL;
5521: return(0);
5522: }
5524: ctx = a->Mvctx;
5525: tag = ((PetscObject)ctx)->tag;
5527: if (ctx->inuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE," Scatter ctx already in use");
5528: VecScatterGetRemote_Private(ctx,PETSC_TRUE/*send*/,&nsends,&sstarts,&srow,&sprocs,&sbs);
5529: /* rprocs[] must be ordered so that indices received from them are ordered in rvalues[], which is key to algorithms used in this subroutine */
5530: VecScatterGetRemoteOrdered_Private(ctx,PETSC_FALSE/*recv*/,&nrecvs,&rstarts,NULL/*indices not needed*/,&rprocs,&rbs);
5531: PetscMPIIntCast(nsends,&nsends_mpi);
5532: PetscMPIIntCast(nrecvs,&nrecvs_mpi);
5533: PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);
5535: if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX;
5536: if (scall == MAT_INITIAL_MATRIX) {
5537: /* i-array */
5538: /*---------*/
5539: /* post receives */
5540: if (nrecvs) {PetscMalloc1(rbs*(rstarts[nrecvs] - rstarts[0]),&rvalues);} /* rstarts can be NULL when nrecvs=0 */
5541: for (i=0; i<nrecvs; i++) {
5542: rowlen = rvalues + rstarts[i]*rbs;
5543: nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */
5544: MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
5545: }
5547: /* pack the outgoing message */
5548: PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);
5550: sstartsj[0] = 0;
5551: rstartsj[0] = 0;
5552: len = 0; /* total length of j or a array to be sent */
5553: if (nsends) {
5554: k = sstarts[0]; /* ATTENTION: sstarts[0] and rstarts[0] are not necessarily zero */
5555: PetscMalloc1(sbs*(sstarts[nsends]-sstarts[0]),&svalues);
5556: }
5557: for (i=0; i<nsends; i++) {
5558: rowlen = svalues + (sstarts[i]-sstarts[0])*sbs;
5559: nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
5560: for (j=0; j<nrows; j++) {
5561: row = srow[k] + B->rmap->range[rank]; /* global row idx */
5562: for (l=0; l<sbs; l++) {
5563: MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL); /* rowlength */
5565: rowlen[j*sbs+l] = ncols;
5567: len += ncols;
5568: MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);
5569: }
5570: k++;
5571: }
5572: MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);
5574: sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */
5575: }
5576: /* recvs and sends of i-array are completed */
5577: i = nrecvs;
5578: while (i--) {
5579: MPI_Waitany(nrecvs_mpi,rwaits,&jj,&rstatus);
5580: }
5581: if (nsends) {MPI_Waitall(nsends_mpi,swaits,MPI_STATUSES_IGNORE);}
5582: PetscFree(svalues);
5584: /* allocate buffers for sending j and a arrays */
5585: PetscMalloc1(len+1,&bufj);
5586: PetscMalloc1(len+1,&bufa);
5588: /* create i-array of B_oth */
5589: PetscMalloc1(aBn+2,&b_othi);
5591: b_othi[0] = 0;
5592: len = 0; /* total length of j or a array to be received */
5593: k = 0;
5594: for (i=0; i<nrecvs; i++) {
5595: rowlen = rvalues + (rstarts[i]-rstarts[0])*rbs;
5596: nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of rows to be received */
5597: for (j=0; j<nrows; j++) {
5598: b_othi[k+1] = b_othi[k] + rowlen[j];
5599: PetscIntSumError(rowlen[j],len,&len);
5600: k++;
5601: }
5602: rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */
5603: }
5604: PetscFree(rvalues);
5606: /* allocate space for j and a arrrays of B_oth */
5607: PetscMalloc1(b_othi[aBn]+1,&b_othj);
5608: PetscMalloc1(b_othi[aBn]+1,&b_otha);
5610: /* j-array */
5611: /*---------*/
5612: /* post receives of j-array */
5613: for (i=0; i<nrecvs; i++) {
5614: nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
5615: MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
5616: }
5618: /* pack the outgoing message j-array */
5619: if (nsends) k = sstarts[0];
5620: for (i=0; i<nsends; i++) {
5621: nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
5622: bufJ = bufj+sstartsj[i];
5623: for (j=0; j<nrows; j++) {
5624: row = srow[k++] + B->rmap->range[rank]; /* global row idx */
5625: for (ll=0; ll<sbs; ll++) {
5626: MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);
5627: for (l=0; l<ncols; l++) {
5628: *bufJ++ = cols[l];
5629: }
5630: MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);
5631: }
5632: }
5633: MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);
5634: }
5636: /* recvs and sends of j-array are completed */
5637: i = nrecvs;
5638: while (i--) {
5639: MPI_Waitany(nrecvs_mpi,rwaits,&jj,&rstatus);
5640: }
5641: if (nsends) {MPI_Waitall(nsends_mpi,swaits,MPI_STATUSES_IGNORE);}
5642: } else if (scall == MAT_REUSE_MATRIX) {
5643: sstartsj = *startsj_s;
5644: rstartsj = *startsj_r;
5645: bufa = *bufa_ptr;
5646: b_oth = (Mat_SeqAIJ*)(*B_oth)->data;
5647: b_otha = b_oth->a;
5648: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container");
5650: /* a-array */
5651: /*---------*/
5652: /* post receives of a-array */
5653: for (i=0; i<nrecvs; i++) {
5654: nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
5655: MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);
5656: }
5658: /* pack the outgoing message a-array */
5659: if (nsends) k = sstarts[0];
5660: for (i=0; i<nsends; i++) {
5661: nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
5662: bufA = bufa+sstartsj[i];
5663: for (j=0; j<nrows; j++) {
5664: row = srow[k++] + B->rmap->range[rank]; /* global row idx */
5665: for (ll=0; ll<sbs; ll++) {
5666: MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);
5667: for (l=0; l<ncols; l++) {
5668: *bufA++ = vals[l];
5669: }
5670: MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);
5671: }
5672: }
5673: MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);
5674: }
5675: /* recvs and sends of a-array are completed */
5676: i = nrecvs;
5677: while (i--) {
5678: MPI_Waitany(nrecvs_mpi,rwaits,&jj,&rstatus);
5679: }
5680: if (nsends) {MPI_Waitall(nsends_mpi,swaits,MPI_STATUSES_IGNORE);}
5681: PetscFree2(rwaits,swaits);
5683: if (scall == MAT_INITIAL_MATRIX) {
5684: /* put together the new matrix */
5685: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);
5687: /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
5688: /* Since these are PETSc arrays, change flags to free them as necessary. */
5689: b_oth = (Mat_SeqAIJ*)(*B_oth)->data;
5690: b_oth->free_a = PETSC_TRUE;
5691: b_oth->free_ij = PETSC_TRUE;
5692: b_oth->nonew = 0;
5694: PetscFree(bufj);
5695: if (!startsj_s || !bufa_ptr) {
5696: PetscFree2(sstartsj,rstartsj);
5697: PetscFree(bufa_ptr);
5698: } else {
5699: *startsj_s = sstartsj;
5700: *startsj_r = rstartsj;
5701: *bufa_ptr = bufa;
5702: }
5703: }
5705: VecScatterRestoreRemote_Private(ctx,PETSC_TRUE,&nsends,&sstarts,&srow,&sprocs,&sbs);
5706: VecScatterRestoreRemoteOrdered_Private(ctx,PETSC_FALSE,&nrecvs,&rstarts,NULL,&rprocs,&rbs);
5707: PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);
5708: return(0);
5709: }
5711: /*@C
5712: MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication.
5714: Not Collective
5716: Input Parameters:
5717: . A - The matrix in mpiaij format
5719: Output Parameter:
5720: + lvec - The local vector holding off-process values from the argument to a matrix-vector product
5721: . colmap - A map from global column index to local index into lvec
5722: - multScatter - A scatter from the argument of a matrix-vector product to lvec
5724: Level: developer
5726: @*/
5727: #if defined(PETSC_USE_CTABLE)
5728: PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter)
5729: #else
5730: PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter)
5731: #endif
5732: {
5733: Mat_MPIAIJ *a;
5740: a = (Mat_MPIAIJ*) A->data;
5741: if (lvec) *lvec = a->lvec;
5742: if (colmap) *colmap = a->colmap;
5743: if (multScatter) *multScatter = a->Mvctx;
5744: return(0);
5745: }
5747: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*);
5748: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*);
5749: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJSELL(Mat,MatType,MatReuse,Mat*);
5750: #if defined(PETSC_HAVE_MKL_SPARSE)
5751: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJMKL(Mat,MatType,MatReuse,Mat*);
5752: #endif
5753: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIBAIJ(Mat,MatType,MatReuse,Mat*);
5754: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*);
5755: #if defined(PETSC_HAVE_ELEMENTAL)
5756: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*);
5757: #endif
5758: #if defined(PETSC_HAVE_HYPRE)
5759: PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*);
5760: #endif
5761: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISELL(Mat,MatType,MatReuse,Mat*);
5762: PETSC_INTERN PetscErrorCode MatConvert_XAIJ_IS(Mat,MatType,MatReuse,Mat*);
5763: PETSC_INTERN PetscErrorCode MatProductSetFromOptions_IS_XAIJ(Mat);
5765: /*
5766: Computes (B'*A')' since computing B*A directly is untenable
5768: n p p
5769: ( ) ( ) ( )
5770: m ( A ) * n ( B ) = m ( C )
5771: ( ) ( ) ( )
5773: */
5774: PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C)
5775: {
5777: Mat At,Bt,Ct;
5780: MatTranspose(A,MAT_INITIAL_MATRIX,&At);
5781: MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);
5782: MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);
5783: MatDestroy(&At);
5784: MatDestroy(&Bt);
5785: MatTranspose(Ct,MAT_REUSE_MATRIX,&C);
5786: MatDestroy(&Ct);
5787: return(0);
5788: }
5790: PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat C)
5791: {
5793: PetscInt m=A->rmap->n,n=B->cmap->n;
5796: if (A->cmap->n != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"A->cmap->n %d != B->rmap->n %d\n",A->cmap->n,B->rmap->n);
5797: MatSetSizes(C,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
5798: MatSetBlockSizesFromMats(C,A,B);
5799: MatSetType(C,MATMPIDENSE);
5800: MatMPIDenseSetPreallocation(C,NULL);
5801: MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);
5802: MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);
5804: C->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ;
5805: return(0);
5806: }
5808: /* ----------------------------------------------------------------*/
5809: static PetscErrorCode MatProductSetFromOptions_MPIDense_MPIAIJ_AB(Mat C)
5810: {
5811: Mat_Product *product = C->product;
5812: Mat A = product->A,B=product->B;
5815: if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend)
5816: SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%D, %D) != (%D,%D)",A->cmap->rstart,A->cmap->rend,B->rmap->rstart,B->rmap->rend);
5818: C->ops->matmultsymbolic = MatMatMultSymbolic_MPIDense_MPIAIJ;
5819: C->ops->productsymbolic = MatProductSymbolic_AB;
5820: return(0);
5821: }
5823: PETSC_INTERN PetscErrorCode MatProductSetFromOptions_MPIDense_MPIAIJ(Mat C)
5824: {
5826: Mat_Product *product = C->product;
5829: if (product->type == MATPRODUCT_AB) {
5830: MatProductSetFromOptions_MPIDense_MPIAIJ_AB(C);
5831: } else SETERRQ1(PetscObjectComm((PetscObject)C),PETSC_ERR_SUP,"MatProduct type %s is not supported for MPIDense and MPIAIJ matrices",MatProductTypes[product->type]);
5832: return(0);
5833: }
5834: /* ----------------------------------------------------------------*/
5836: /*MC
5837: MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices.
5839: Options Database Keys:
5840: . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions()
5842: Level: beginner
5844: Notes:
5845: MatSetValues() may be called for this matrix type with a NULL argument for the numerical values,
5846: in this case the values associated with the rows and columns one passes in are set to zero
5847: in the matrix
5849: MatSetOptions(,MAT_STRUCTURE_ONLY,PETSC_TRUE) may be called for this matrix type. In this no
5850: space is allocated for the nonzero entries and any entries passed with MatSetValues() are ignored
5852: .seealso: MatCreateAIJ()
5853: M*/
5855: PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B)
5856: {
5857: Mat_MPIAIJ *b;
5859: PetscMPIInt size;
5862: MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
5864: PetscNewLog(B,&b);
5865: B->data = (void*)b;
5866: PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
5867: B->assembled = PETSC_FALSE;
5868: B->insertmode = NOT_SET_VALUES;
5869: b->size = size;
5871: MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
5873: /* build cache for off array entries formed */
5874: MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);
5876: b->donotstash = PETSC_FALSE;
5877: b->colmap = 0;
5878: b->garray = 0;
5879: b->roworiented = PETSC_TRUE;
5881: /* stuff used for matrix vector multiply */
5882: b->lvec = NULL;
5883: b->Mvctx = NULL;
5885: /* stuff for MatGetRow() */
5886: b->rowindices = 0;
5887: b->rowvalues = 0;
5888: b->getrowactive = PETSC_FALSE;
5890: /* flexible pointer used in CUSP/CUSPARSE classes */
5891: b->spptr = NULL;
5893: PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);
5894: PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);
5895: PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);
5896: PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);
5897: PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);
5898: PetscObjectComposeFunction((PetscObject)B,"MatResetPreallocation_C",MatResetPreallocation_MPIAIJ);
5899: PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);
5900: PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);
5901: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);
5902: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijsell_C",MatConvert_MPIAIJ_MPIAIJSELL);
5903: #if defined(PETSC_HAVE_MKL_SPARSE)
5904: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijmkl_C",MatConvert_MPIAIJ_MPIAIJMKL);
5905: #endif
5906: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);
5907: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpibaij_C",MatConvert_MPIAIJ_MPIBAIJ);
5908: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);
5909: #if defined(PETSC_HAVE_ELEMENTAL)
5910: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);
5911: #endif
5912: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_is_C",MatConvert_XAIJ_IS);
5913: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisell_C",MatConvert_MPIAIJ_MPISELL);
5914: PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);
5915: PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);
5916: #if defined(PETSC_HAVE_HYPRE)
5917: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_hypre_C",MatConvert_AIJ_HYPRE);
5918: PetscObjectComposeFunction((PetscObject)B,"MatProductSetFromOptions_transpose_mpiaij_mpiaij_C",MatProductSetFromOptions_Transpose_AIJ_AIJ);
5919: #endif
5920: PetscObjectComposeFunction((PetscObject)B,"MatProductSetFromOptions_is_mpiaij_C",MatProductSetFromOptions_IS_XAIJ);
5921: PetscObjectComposeFunction((PetscObject)B,"MatProductSetFromOptions_mpiaij_mpiaij_C",MatProductSetFromOptions_MPIAIJ);
5922: PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);
5923: return(0);
5924: }
5926: /*@C
5927: MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal"
5928: and "off-diagonal" part of the matrix in CSR format.
5930: Collective
5932: Input Parameters:
5933: + comm - MPI communicator
5934: . m - number of local rows (Cannot be PETSC_DECIDE)
5935: . n - This value should be the same as the local size used in creating the
5936: x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
5937: calculated if N is given) For square matrices n is almost always m.
5938: . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
5939: . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
5940: . i - row indices for "diagonal" portion of matrix; that is i[0] = 0, i[row] = i[row-1] + number of elements in that row of the matrix
5941: . j - column indices
5942: . a - matrix values
5943: . oi - row indices for "off-diagonal" portion of matrix; that is oi[0] = 0, oi[row] = oi[row-1] + number of elements in that row of the matrix
5944: . oj - column indices
5945: - oa - matrix values
5947: Output Parameter:
5948: . mat - the matrix
5950: Level: advanced
5952: Notes:
5953: The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user
5954: must free the arrays once the matrix has been destroyed and not before.
5956: The i and j indices are 0 based
5958: See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix
5960: This sets local rows and cannot be used to set off-processor values.
5962: Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a
5963: legacy Section 1.5 Writing Application Codes with PETSc natively assembles into exactly this split format. The code to do so is nontrivial and does
5964: not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because
5965: the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to
5966: keep track of the underlying array. Use MatSetOption(A,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all
5967: communication if it is known that only local entries will be set.
5969: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
5970: MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays()
5971: @*/
5972: PetscErrorCode MatCreateMPIAIJWithSplitArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt i[],PetscInt j[],PetscScalar a[],PetscInt oi[], PetscInt oj[],PetscScalar oa[],Mat *mat)
5973: {
5975: Mat_MPIAIJ *maij;
5978: if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
5979: if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
5980: if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0");
5981: MatCreate(comm,mat);
5982: MatSetSizes(*mat,m,n,M,N);
5983: MatSetType(*mat,MATMPIAIJ);
5984: maij = (Mat_MPIAIJ*) (*mat)->data;
5986: (*mat)->preallocated = PETSC_TRUE;
5988: PetscLayoutSetUp((*mat)->rmap);
5989: PetscLayoutSetUp((*mat)->cmap);
5991: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);
5992: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);
5994: MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);
5995: MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);
5996: MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);
5997: MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);
5999: MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);
6000: MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
6001: MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
6002: MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);
6003: MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
6004: return(0);
6005: }
6007: /*
6008: Special version for direct calls from Fortran
6009: */
6010: #include <petsc/private/fortranimpl.h>
6012: /* Change these macros so can be used in void function */
6013: #undef CHKERRQ
6014: #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr)
6015: #undef SETERRQ2
6016: #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr)
6017: #undef SETERRQ3
6018: #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr)
6019: #undef SETERRQ
6020: #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr)
6022: #if defined(PETSC_HAVE_FORTRAN_CAPS)
6023: #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ
6024: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
6025: #define matsetvaluesmpiaij_ matsetvaluesmpiaij
6026: #else
6027: #endif
6028: PETSC_EXTERN void matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr)
6029: {
6030: Mat mat = *mmat;
6031: PetscInt m = *mm, n = *mn;
6032: InsertMode addv = *maddv;
6033: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
6034: PetscScalar value;
6037: MatCheckPreallocated(mat,1);
6038: if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv;
6040: #if defined(PETSC_USE_DEBUG)
6041: else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values");
6042: #endif
6043: {
6044: PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend;
6045: PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
6046: PetscBool roworiented = aij->roworiented;
6048: /* Some Variables required in the macro */
6049: Mat A = aij->A;
6050: Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data;
6051: PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j;
6052: MatScalar *aa = a->a;
6053: PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE);
6054: Mat B = aij->B;
6055: Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data;
6056: PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n;
6057: MatScalar *ba = b->a;
6058: /* This variable below is only for the PETSC_HAVE_VIENNACL or PETSC_HAVE_CUDA cases, but we define it in all cases because we
6059: * cannot use "#if defined" inside a macro. */
6060: PETSC_UNUSED PetscBool inserted = PETSC_FALSE;
6062: PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2;
6063: PetscInt nonew = a->nonew;
6064: MatScalar *ap1,*ap2;
6067: for (i=0; i<m; i++) {
6068: if (im[i] < 0) continue;
6069: #if defined(PETSC_USE_DEBUG)
6070: if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1);
6071: #endif
6072: if (im[i] >= rstart && im[i] < rend) {
6073: row = im[i] - rstart;
6074: lastcol1 = -1;
6075: rp1 = aj + ai[row];
6076: ap1 = aa + ai[row];
6077: rmax1 = aimax[row];
6078: nrow1 = ailen[row];
6079: low1 = 0;
6080: high1 = nrow1;
6081: lastcol2 = -1;
6082: rp2 = bj + bi[row];
6083: ap2 = ba + bi[row];
6084: rmax2 = bimax[row];
6085: nrow2 = bilen[row];
6086: low2 = 0;
6087: high2 = nrow2;
6089: for (j=0; j<n; j++) {
6090: if (roworiented) value = v[i*n+j];
6091: else value = v[i+j*m];
6092: if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && im[i] != in[j]) continue;
6093: if (in[j] >= cstart && in[j] < cend) {
6094: col = in[j] - cstart;
6095: MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]);
6096: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
6097: if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED && inserted) A->offloadmask = PETSC_OFFLOAD_CPU;
6098: #endif
6099: } else if (in[j] < 0) continue;
6100: #if defined(PETSC_USE_DEBUG)
6101: /* extra brace on SETERRQ2() is required for --with-errorchecking=0 - due to the next 'else' clause */
6102: else if (in[j] >= mat->cmap->N) {SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1);}
6103: #endif
6104: else {
6105: if (mat->was_assembled) {
6106: if (!aij->colmap) {
6107: MatCreateColmap_MPIAIJ_Private(mat);
6108: }
6109: #if defined(PETSC_USE_CTABLE)
6110: PetscTableFind(aij->colmap,in[j]+1,&col);
6111: col--;
6112: #else
6113: col = aij->colmap[in[j]] - 1;
6114: #endif
6115: if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
6116: MatDisAssemble_MPIAIJ(mat);
6117: col = in[j];
6118: /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
6119: B = aij->B;
6120: b = (Mat_SeqAIJ*)B->data;
6121: bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j;
6122: rp2 = bj + bi[row];
6123: ap2 = ba + bi[row];
6124: rmax2 = bimax[row];
6125: nrow2 = bilen[row];
6126: low2 = 0;
6127: high2 = nrow2;
6128: bm = aij->B->rmap->n;
6129: ba = b->a;
6130: inserted = PETSC_FALSE;
6131: }
6132: } else col = in[j];
6133: MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]);
6134: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
6135: if (B->offloadmask != PETSC_OFFLOAD_UNALLOCATED && inserted) B->offloadmask = PETSC_OFFLOAD_CPU;
6136: #endif
6137: }
6138: }
6139: } else if (!aij->donotstash) {
6140: if (roworiented) {
6141: MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
6142: } else {
6143: MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
6144: }
6145: }
6146: }
6147: }
6148: PetscFunctionReturnVoid();
6149: }