Actual source code: mpiaij.c
petsc-3.7.7 2017-09-25
2: #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/
3: #include <petsc/private/vecimpl.h>
4: #include <petsc/private/isimpl.h>
5: #include <petscblaslapack.h>
6: #include <petscsf.h>
8: /*MC
9: MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices.
11: This matrix type is identical to MATSEQAIJ when constructed with a single process communicator,
12: and MATMPIAIJ otherwise. As a result, for single process communicators,
13: MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported
14: for communicators controlling multiple processes. It is recommended that you call both of
15: the above preallocation routines for simplicity.
17: Options Database Keys:
18: . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions()
20: Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when
21: enough exist.
23: Level: beginner
25: .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ
26: M*/
28: /*MC
29: MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices.
31: This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator,
32: and MATMPIAIJCRL otherwise. As a result, for single process communicators,
33: MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported
34: for communicators controlling multiple processes. It is recommended that you call both of
35: the above preallocation routines for simplicity.
37: Options Database Keys:
38: . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions()
40: Level: beginner
42: .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL
43: M*/
47: PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows)
48: {
49: PetscErrorCode ierr;
50: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data;
51: Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data;
52: Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data;
53: const PetscInt *ia,*ib;
54: const MatScalar *aa,*bb;
55: PetscInt na,nb,i,j,*rows,cnt=0,n0rows;
56: PetscInt m = M->rmap->n,rstart = M->rmap->rstart;
59: *keptrows = 0;
60: ia = a->i;
61: ib = b->i;
62: for (i=0; i<m; i++) {
63: na = ia[i+1] - ia[i];
64: nb = ib[i+1] - ib[i];
65: if (!na && !nb) {
66: cnt++;
67: goto ok1;
68: }
69: aa = a->a + ia[i];
70: for (j=0; j<na; j++) {
71: if (aa[j] != 0.0) goto ok1;
72: }
73: bb = b->a + ib[i];
74: for (j=0; j <nb; j++) {
75: if (bb[j] != 0.0) goto ok1;
76: }
77: cnt++;
78: ok1:;
79: }
80: MPIU_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));
81: if (!n0rows) return(0);
82: PetscMalloc1(M->rmap->n-cnt,&rows);
83: cnt = 0;
84: for (i=0; i<m; i++) {
85: na = ia[i+1] - ia[i];
86: nb = ib[i+1] - ib[i];
87: if (!na && !nb) continue;
88: aa = a->a + ia[i];
89: for (j=0; j<na;j++) {
90: if (aa[j] != 0.0) {
91: rows[cnt++] = rstart + i;
92: goto ok2;
93: }
94: }
95: bb = b->a + ib[i];
96: for (j=0; j<nb; j++) {
97: if (bb[j] != 0.0) {
98: rows[cnt++] = rstart + i;
99: goto ok2;
100: }
101: }
102: ok2:;
103: }
104: ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);
105: return(0);
106: }
110: PetscErrorCode MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is)
111: {
112: PetscErrorCode ierr;
113: Mat_MPIAIJ *aij = (Mat_MPIAIJ*) Y->data;
116: if (Y->assembled && Y->rmap->rstart == Y->cmap->rstart && Y->rmap->rend == Y->cmap->rend) {
117: MatDiagonalSet(aij->A,D,is);
118: } else {
119: MatDiagonalSet_Default(Y,D,is);
120: }
121: return(0);
122: }
127: PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows)
128: {
129: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data;
131: PetscInt i,rstart,nrows,*rows;
134: *zrows = NULL;
135: MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);
136: MatGetOwnershipRange(M,&rstart,NULL);
137: for (i=0; i<nrows; i++) rows[i] += rstart;
138: ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);
139: return(0);
140: }
144: PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms)
145: {
147: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data;
148: PetscInt i,n,*garray = aij->garray;
149: Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data;
150: Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data;
151: PetscReal *work;
154: MatGetSize(A,NULL,&n);
155: PetscCalloc1(n,&work);
156: if (type == NORM_2) {
157: for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
158: work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]);
159: }
160: for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
161: work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]);
162: }
163: } else if (type == NORM_1) {
164: for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
165: work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]);
166: }
167: for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
168: work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]);
169: }
170: } else if (type == NORM_INFINITY) {
171: for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
172: work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]);
173: }
174: for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
175: work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]);
176: }
178: } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType");
179: if (type == NORM_INFINITY) {
180: MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));
181: } else {
182: MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));
183: }
184: PetscFree(work);
185: if (type == NORM_2) {
186: for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]);
187: }
188: return(0);
189: }
193: PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is)
194: {
195: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
196: IS sis,gis;
197: PetscErrorCode ierr;
198: const PetscInt *isis,*igis;
199: PetscInt n,*iis,nsis,ngis,rstart,i;
202: MatFindOffBlockDiagonalEntries(a->A,&sis);
203: MatFindNonzeroRows(a->B,&gis);
204: ISGetSize(gis,&ngis);
205: ISGetSize(sis,&nsis);
206: ISGetIndices(sis,&isis);
207: ISGetIndices(gis,&igis);
209: PetscMalloc1(ngis+nsis,&iis);
210: PetscMemcpy(iis,igis,ngis*sizeof(PetscInt));
211: PetscMemcpy(iis+ngis,isis,nsis*sizeof(PetscInt));
212: n = ngis + nsis;
213: PetscSortRemoveDupsInt(&n,iis);
214: MatGetOwnershipRange(A,&rstart,NULL);
215: for (i=0; i<n; i++) iis[i] += rstart;
216: ISCreateGeneral(PetscObjectComm((PetscObject)A),n,iis,PETSC_OWN_POINTER,is);
218: ISRestoreIndices(sis,&isis);
219: ISRestoreIndices(gis,&igis);
220: ISDestroy(&sis);
221: ISDestroy(&gis);
222: return(0);
223: }
227: /*
228: Distributes a SeqAIJ matrix across a set of processes. Code stolen from
229: MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type.
231: Only for square matrices
233: Used by a preconditioner, hence PETSC_EXTERN
234: */
235: PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat)
236: {
237: PetscMPIInt rank,size;
238: PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2];
240: Mat mat;
241: Mat_SeqAIJ *gmata;
242: PetscMPIInt tag;
243: MPI_Status status;
244: PetscBool aij;
245: MatScalar *gmataa,*ao,*ad,*gmataarestore=0;
248: MPI_Comm_rank(comm,&rank);
249: MPI_Comm_size(comm,&size);
250: if (!rank) {
251: PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);
252: if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name);
253: }
254: if (reuse == MAT_INITIAL_MATRIX) {
255: MatCreate(comm,&mat);
256: MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);
257: MatGetBlockSizes(gmat,&bses[0],&bses[1]);
258: MPI_Bcast(bses,2,MPIU_INT,0,comm);
259: MatSetBlockSizes(mat,bses[0],bses[1]);
260: MatSetType(mat,MATAIJ);
261: PetscMalloc1(size+1,&rowners);
262: PetscMalloc2(m,&dlens,m,&olens);
263: MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);
265: rowners[0] = 0;
266: for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
267: rstart = rowners[rank];
268: rend = rowners[rank+1];
269: PetscObjectGetNewTag((PetscObject)mat,&tag);
270: if (!rank) {
271: gmata = (Mat_SeqAIJ*) gmat->data;
272: /* send row lengths to all processors */
273: for (i=0; i<m; i++) dlens[i] = gmata->ilen[i];
274: for (i=1; i<size; i++) {
275: MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);
276: }
277: /* determine number diagonal and off-diagonal counts */
278: PetscMemzero(olens,m*sizeof(PetscInt));
279: PetscCalloc1(m,&ld);
280: jj = 0;
281: for (i=0; i<m; i++) {
282: for (j=0; j<dlens[i]; j++) {
283: if (gmata->j[jj] < rstart) ld[i]++;
284: if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++;
285: jj++;
286: }
287: }
288: /* send column indices to other processes */
289: for (i=1; i<size; i++) {
290: nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
291: MPI_Send(&nz,1,MPIU_INT,i,tag,comm);
292: MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);
293: }
295: /* send numerical values to other processes */
296: for (i=1; i<size; i++) {
297: nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
298: MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);
299: }
300: gmataa = gmata->a;
301: gmataj = gmata->j;
303: } else {
304: /* receive row lengths */
305: MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);
306: /* receive column indices */
307: MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);
308: PetscMalloc2(nz,&gmataa,nz,&gmataj);
309: MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);
310: /* determine number diagonal and off-diagonal counts */
311: PetscMemzero(olens,m*sizeof(PetscInt));
312: PetscCalloc1(m,&ld);
313: jj = 0;
314: for (i=0; i<m; i++) {
315: for (j=0; j<dlens[i]; j++) {
316: if (gmataj[jj] < rstart) ld[i]++;
317: if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++;
318: jj++;
319: }
320: }
321: /* receive numerical values */
322: PetscMemzero(gmataa,nz*sizeof(PetscScalar));
323: MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);
324: }
325: /* set preallocation */
326: for (i=0; i<m; i++) {
327: dlens[i] -= olens[i];
328: }
329: MatSeqAIJSetPreallocation(mat,0,dlens);
330: MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);
332: for (i=0; i<m; i++) {
333: dlens[i] += olens[i];
334: }
335: cnt = 0;
336: for (i=0; i<m; i++) {
337: row = rstart + i;
338: MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);
339: cnt += dlens[i];
340: }
341: if (rank) {
342: PetscFree2(gmataa,gmataj);
343: }
344: PetscFree2(dlens,olens);
345: PetscFree(rowners);
347: ((Mat_MPIAIJ*)(mat->data))->ld = ld;
349: *inmat = mat;
350: } else { /* column indices are already set; only need to move over numerical values from process 0 */
351: Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data;
352: Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data;
353: mat = *inmat;
354: PetscObjectGetNewTag((PetscObject)mat,&tag);
355: if (!rank) {
356: /* send numerical values to other processes */
357: gmata = (Mat_SeqAIJ*) gmat->data;
358: MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);
359: gmataa = gmata->a;
360: for (i=1; i<size; i++) {
361: nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
362: MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);
363: }
364: nz = gmata->i[rowners[1]]-gmata->i[rowners[0]];
365: } else {
366: /* receive numerical values from process 0*/
367: nz = Ad->nz + Ao->nz;
368: PetscMalloc1(nz,&gmataa); gmataarestore = gmataa;
369: MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);
370: }
371: /* transfer numerical values into the diagonal A and off diagonal B parts of mat */
372: ld = ((Mat_MPIAIJ*)(mat->data))->ld;
373: ad = Ad->a;
374: ao = Ao->a;
375: if (mat->rmap->n) {
376: i = 0;
377: nz = ld[i]; PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar)); ao += nz; gmataa += nz;
378: nz = Ad->i[i+1] - Ad->i[i]; PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar)); ad += nz; gmataa += nz;
379: }
380: for (i=1; i<mat->rmap->n; i++) {
381: nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar)); ao += nz; gmataa += nz;
382: nz = Ad->i[i+1] - Ad->i[i]; PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar)); ad += nz; gmataa += nz;
383: }
384: i--;
385: if (mat->rmap->n) {
386: nz = Ao->i[i+1] - Ao->i[i] - ld[i]; PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));
387: }
388: if (rank) {
389: PetscFree(gmataarestore);
390: }
391: }
392: MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);
393: MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);
394: return(0);
395: }
397: /*
398: Local utility routine that creates a mapping from the global column
399: number to the local number in the off-diagonal part of the local
400: storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at
401: a slightly higher hash table cost; without it it is not scalable (each processor
402: has an order N integer array but is fast to acess.
403: */
406: PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat)
407: {
408: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
410: PetscInt n = aij->B->cmap->n,i;
413: if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray");
414: #if defined(PETSC_USE_CTABLE)
415: PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);
416: for (i=0; i<n; i++) {
417: PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);
418: }
419: #else
420: PetscCalloc1(mat->cmap->N+1,&aij->colmap);
421: PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));
422: for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1;
423: #endif
424: return(0);
425: }
427: #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,orow,ocol) \
428: { \
429: if (col <= lastcol1) low1 = 0; \
430: else high1 = nrow1; \
431: lastcol1 = col;\
432: while (high1-low1 > 5) { \
433: t = (low1+high1)/2; \
434: if (rp1[t] > col) high1 = t; \
435: else low1 = t; \
436: } \
437: for (_i=low1; _i<high1; _i++) { \
438: if (rp1[_i] > col) break; \
439: if (rp1[_i] == col) { \
440: if (addv == ADD_VALUES) ap1[_i] += value; \
441: else ap1[_i] = value; \
442: goto a_noinsert; \
443: } \
444: } \
445: if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \
446: if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \
447: 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); \
448: MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \
449: N = nrow1++ - 1; a->nz++; high1++; \
450: /* shift up all the later entries in this row */ \
451: for (ii=N; ii>=_i; ii--) { \
452: rp1[ii+1] = rp1[ii]; \
453: ap1[ii+1] = ap1[ii]; \
454: } \
455: rp1[_i] = col; \
456: ap1[_i] = value; \
457: A->nonzerostate++;\
458: a_noinsert: ; \
459: ailen[row] = nrow1; \
460: }
463: #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv,orow,ocol) \
464: { \
465: if (col <= lastcol2) low2 = 0; \
466: else high2 = nrow2; \
467: lastcol2 = col; \
468: while (high2-low2 > 5) { \
469: t = (low2+high2)/2; \
470: if (rp2[t] > col) high2 = t; \
471: else low2 = t; \
472: } \
473: for (_i=low2; _i<high2; _i++) { \
474: if (rp2[_i] > col) break; \
475: if (rp2[_i] == col) { \
476: if (addv == ADD_VALUES) ap2[_i] += value; \
477: else ap2[_i] = value; \
478: goto b_noinsert; \
479: } \
480: } \
481: if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
482: if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
483: 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); \
484: MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \
485: N = nrow2++ - 1; b->nz++; high2++; \
486: /* shift up all the later entries in this row */ \
487: for (ii=N; ii>=_i; ii--) { \
488: rp2[ii+1] = rp2[ii]; \
489: ap2[ii+1] = ap2[ii]; \
490: } \
491: rp2[_i] = col; \
492: ap2[_i] = value; \
493: B->nonzerostate++; \
494: b_noinsert: ; \
495: bilen[row] = nrow2; \
496: }
500: PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[])
501: {
502: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data;
503: Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data;
505: PetscInt l,*garray = mat->garray,diag;
508: /* code only works for square matrices A */
510: /* find size of row to the left of the diagonal part */
511: MatGetOwnershipRange(A,&diag,0);
512: row = row - diag;
513: for (l=0; l<b->i[row+1]-b->i[row]; l++) {
514: if (garray[b->j[b->i[row]+l]] > diag) break;
515: }
516: PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));
518: /* diagonal part */
519: PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));
521: /* right of diagonal part */
522: PetscMemcpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],(b->i[row+1]-b->i[row]-l)*sizeof(PetscScalar));
523: return(0);
524: }
528: PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
529: {
530: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
531: PetscScalar value;
533: PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend;
534: PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
535: PetscBool roworiented = aij->roworiented;
537: /* Some Variables required in the macro */
538: Mat A = aij->A;
539: Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data;
540: PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j;
541: MatScalar *aa = a->a;
542: PetscBool ignorezeroentries = a->ignorezeroentries;
543: Mat B = aij->B;
544: Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data;
545: PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n;
546: MatScalar *ba = b->a;
548: PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2;
549: PetscInt nonew;
550: MatScalar *ap1,*ap2;
553: for (i=0; i<m; i++) {
554: if (im[i] < 0) continue;
555: #if defined(PETSC_USE_DEBUG)
556: 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);
557: #endif
558: if (im[i] >= rstart && im[i] < rend) {
559: row = im[i] - rstart;
560: lastcol1 = -1;
561: rp1 = aj + ai[row];
562: ap1 = aa + ai[row];
563: rmax1 = aimax[row];
564: nrow1 = ailen[row];
565: low1 = 0;
566: high1 = nrow1;
567: lastcol2 = -1;
568: rp2 = bj + bi[row];
569: ap2 = ba + bi[row];
570: rmax2 = bimax[row];
571: nrow2 = bilen[row];
572: low2 = 0;
573: high2 = nrow2;
575: for (j=0; j<n; j++) {
576: if (roworiented) value = v[i*n+j];
577: else value = v[i+j*m];
578: if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue;
579: if (in[j] >= cstart && in[j] < cend) {
580: col = in[j] - cstart;
581: nonew = a->nonew;
582: MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]);
583: } else if (in[j] < 0) continue;
584: #if defined(PETSC_USE_DEBUG)
585: 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);
586: #endif
587: else {
588: if (mat->was_assembled) {
589: if (!aij->colmap) {
590: MatCreateColmap_MPIAIJ_Private(mat);
591: }
592: #if defined(PETSC_USE_CTABLE)
593: PetscTableFind(aij->colmap,in[j]+1,&col);
594: col--;
595: #else
596: col = aij->colmap[in[j]] - 1;
597: #endif
598: if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) {
599: MatDisAssemble_MPIAIJ(mat);
600: col = in[j];
601: /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
602: B = aij->B;
603: b = (Mat_SeqAIJ*)B->data;
604: bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a;
605: rp2 = bj + bi[row];
606: ap2 = ba + bi[row];
607: rmax2 = bimax[row];
608: nrow2 = bilen[row];
609: low2 = 0;
610: high2 = nrow2;
611: bm = aij->B->rmap->n;
612: ba = b->a;
613: } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", im[i], in[j]);
614: } else col = in[j];
615: nonew = b->nonew;
616: MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]);
617: }
618: }
619: } else {
620: 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]);
621: if (!aij->donotstash) {
622: mat->assembled = PETSC_FALSE;
623: if (roworiented) {
624: MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
625: } else {
626: MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
627: }
628: }
629: }
630: }
631: return(0);
632: }
636: PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
637: {
638: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
640: PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend;
641: PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
644: for (i=0; i<m; i++) {
645: if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/
646: 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);
647: if (idxm[i] >= rstart && idxm[i] < rend) {
648: row = idxm[i] - rstart;
649: for (j=0; j<n; j++) {
650: if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */
651: 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);
652: if (idxn[j] >= cstart && idxn[j] < cend) {
653: col = idxn[j] - cstart;
654: MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);
655: } else {
656: if (!aij->colmap) {
657: MatCreateColmap_MPIAIJ_Private(mat);
658: }
659: #if defined(PETSC_USE_CTABLE)
660: PetscTableFind(aij->colmap,idxn[j]+1,&col);
661: col--;
662: #else
663: col = aij->colmap[idxn[j]] - 1;
664: #endif
665: if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0;
666: else {
667: MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);
668: }
669: }
670: }
671: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
672: }
673: return(0);
674: }
676: extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec);
680: PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode)
681: {
682: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
684: PetscInt nstash,reallocs;
687: if (aij->donotstash || mat->nooffprocentries) return(0);
689: MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
690: MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
691: PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
692: return(0);
693: }
697: PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode)
698: {
699: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
700: Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data;
702: PetscMPIInt n;
703: PetscInt i,j,rstart,ncols,flg;
704: PetscInt *row,*col;
705: PetscBool other_disassembled;
706: PetscScalar *val;
708: /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */
711: if (!aij->donotstash && !mat->nooffprocentries) {
712: while (1) {
713: MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
714: if (!flg) break;
716: for (i=0; i<n; ) {
717: /* Now identify the consecutive vals belonging to the same row */
718: for (j=i,rstart=row[j]; j<n; j++) {
719: if (row[j] != rstart) break;
720: }
721: if (j < n) ncols = j-i;
722: else ncols = n-i;
723: /* Now assemble all these values with a single function call */
724: MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);
726: i = j;
727: }
728: }
729: MatStashScatterEnd_Private(&mat->stash);
730: }
731: MatAssemblyBegin(aij->A,mode);
732: MatAssemblyEnd(aij->A,mode);
734: /* determine if any processor has disassembled, if so we must
735: also disassemble ourselfs, in order that we may reassemble. */
736: /*
737: if nonzero structure of submatrix B cannot change then we know that
738: no processor disassembled thus we can skip this stuff
739: */
740: if (!((Mat_SeqAIJ*)aij->B->data)->nonew) {
741: MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
742: if (mat->was_assembled && !other_disassembled) {
743: MatDisAssemble_MPIAIJ(mat);
744: }
745: }
746: if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
747: MatSetUpMultiply_MPIAIJ(mat);
748: }
749: MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);
750: MatAssemblyBegin(aij->B,mode);
751: MatAssemblyEnd(aij->B,mode);
753: PetscFree2(aij->rowvalues,aij->rowindices);
755: aij->rowvalues = 0;
757: VecDestroy(&aij->diag);
758: if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ;
760: /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
761: if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
762: PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate;
763: MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
764: }
765: return(0);
766: }
770: PetscErrorCode MatZeroEntries_MPIAIJ(Mat A)
771: {
772: Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data;
776: MatZeroEntries(l->A);
777: MatZeroEntries(l->B);
778: return(0);
779: }
783: PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
784: {
785: Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data;
786: PetscInt *owners = A->rmap->range;
787: PetscInt n = A->rmap->n;
788: PetscSF sf;
789: PetscInt *lrows;
790: PetscSFNode *rrows;
791: PetscInt r, p = 0, len = 0;
795: /* Create SF where leaves are input rows and roots are owned rows */
796: PetscMalloc1(n, &lrows);
797: for (r = 0; r < n; ++r) lrows[r] = -1;
798: if (!A->nooffproczerorows) {PetscMalloc1(N, &rrows);}
799: for (r = 0; r < N; ++r) {
800: const PetscInt idx = rows[r];
801: 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);
802: if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */
803: PetscLayoutFindOwner(A->rmap,idx,&p);
804: }
805: if (A->nooffproczerorows) {
806: if (p != mat->rank) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"MAT_NO_OFF_PROC_ZERO_ROWS set, but row %D is not owned by rank %d",idx,mat->rank);
807: lrows[len++] = idx - owners[p];
808: } else {
809: rrows[r].rank = p;
810: rrows[r].index = rows[r] - owners[p];
811: }
812: }
813: if (!A->nooffproczerorows) {
814: PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);
815: PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);
816: /* Collect flags for rows to be zeroed */
817: PetscSFReduceBegin(sf, MPIU_INT, (PetscInt*)rows, lrows, MPI_LOR);
818: PetscSFReduceEnd(sf, MPIU_INT, (PetscInt*)rows, lrows, MPI_LOR);
819: PetscSFDestroy(&sf);
820: /* Compress and put in row numbers */
821: for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r;
822: }
823: /* fix right hand side if needed */
824: if (x && b) {
825: const PetscScalar *xx;
826: PetscScalar *bb;
828: VecGetArrayRead(x, &xx);
829: VecGetArray(b, &bb);
830: for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]];
831: VecRestoreArrayRead(x, &xx);
832: VecRestoreArray(b, &bb);
833: }
834: /* Must zero l->B before l->A because the (diag) case below may put values into l->B*/
835: MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);
836: if ((diag != 0.0) && (mat->A->rmap->N == mat->A->cmap->N)) {
837: MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);
838: } else if (diag != 0.0) {
839: MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);
840: if (((Mat_SeqAIJ *) mat->A->data)->nonew) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "MatZeroRows() on rectangular matrices cannot be used with the Mat options\nMAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR");
841: for (r = 0; r < len; ++r) {
842: const PetscInt row = lrows[r] + A->rmap->rstart;
843: MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);
844: }
845: MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);
846: MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);
847: } else {
848: MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);
849: }
850: PetscFree(lrows);
852: /* only change matrix nonzero state if pattern was allowed to be changed */
853: if (!((Mat_SeqAIJ*)(mat->A->data))->keepnonzeropattern) {
854: PetscObjectState state = mat->A->nonzerostate + mat->B->nonzerostate;
855: MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));
856: }
857: return(0);
858: }
862: PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
863: {
864: Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data;
865: PetscErrorCode ierr;
866: PetscMPIInt n = A->rmap->n;
867: PetscInt i,j,r,m,p = 0,len = 0;
868: PetscInt *lrows,*owners = A->rmap->range;
869: PetscSFNode *rrows;
870: PetscSF sf;
871: const PetscScalar *xx;
872: PetscScalar *bb,*mask;
873: Vec xmask,lmask;
874: Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data;
875: const PetscInt *aj, *ii,*ridx;
876: PetscScalar *aa;
879: /* Create SF where leaves are input rows and roots are owned rows */
880: PetscMalloc1(n, &lrows);
881: for (r = 0; r < n; ++r) lrows[r] = -1;
882: PetscMalloc1(N, &rrows);
883: for (r = 0; r < N; ++r) {
884: const PetscInt idx = rows[r];
885: 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);
886: if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */
887: PetscLayoutFindOwner(A->rmap,idx,&p);
888: }
889: rrows[r].rank = p;
890: rrows[r].index = rows[r] - owners[p];
891: }
892: PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);
893: PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);
894: /* Collect flags for rows to be zeroed */
895: PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
896: PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
897: PetscSFDestroy(&sf);
898: /* Compress and put in row numbers */
899: for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r;
900: /* zero diagonal part of matrix */
901: MatZeroRowsColumns(l->A,len,lrows,diag,x,b);
902: /* handle off diagonal part of matrix */
903: MatCreateVecs(A,&xmask,NULL);
904: VecDuplicate(l->lvec,&lmask);
905: VecGetArray(xmask,&bb);
906: for (i=0; i<len; i++) bb[lrows[i]] = 1;
907: VecRestoreArray(xmask,&bb);
908: VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
909: VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
910: VecDestroy(&xmask);
911: if (x) {
912: VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
913: VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
914: VecGetArrayRead(l->lvec,&xx);
915: VecGetArray(b,&bb);
916: }
917: VecGetArray(lmask,&mask);
918: /* remove zeroed rows of off diagonal matrix */
919: ii = aij->i;
920: for (i=0; i<len; i++) {
921: PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));
922: }
923: /* loop over all elements of off process part of matrix zeroing removed columns*/
924: if (aij->compressedrow.use) {
925: m = aij->compressedrow.nrows;
926: ii = aij->compressedrow.i;
927: ridx = aij->compressedrow.rindex;
928: for (i=0; i<m; i++) {
929: n = ii[i+1] - ii[i];
930: aj = aij->j + ii[i];
931: aa = aij->a + ii[i];
933: for (j=0; j<n; j++) {
934: if (PetscAbsScalar(mask[*aj])) {
935: if (b) bb[*ridx] -= *aa*xx[*aj];
936: *aa = 0.0;
937: }
938: aa++;
939: aj++;
940: }
941: ridx++;
942: }
943: } else { /* do not use compressed row format */
944: m = l->B->rmap->n;
945: for (i=0; i<m; i++) {
946: n = ii[i+1] - ii[i];
947: aj = aij->j + ii[i];
948: aa = aij->a + ii[i];
949: for (j=0; j<n; j++) {
950: if (PetscAbsScalar(mask[*aj])) {
951: if (b) bb[i] -= *aa*xx[*aj];
952: *aa = 0.0;
953: }
954: aa++;
955: aj++;
956: }
957: }
958: }
959: if (x) {
960: VecRestoreArray(b,&bb);
961: VecRestoreArrayRead(l->lvec,&xx);
962: }
963: VecRestoreArray(lmask,&mask);
964: VecDestroy(&lmask);
965: PetscFree(lrows);
967: /* only change matrix nonzero state if pattern was allowed to be changed */
968: if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) {
969: PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate;
970: MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));
971: }
972: return(0);
973: }
977: PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy)
978: {
979: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
981: PetscInt nt;
984: VecGetLocalSize(xx,&nt);
985: 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);
986: VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
987: (*a->A->ops->mult)(a->A,xx,yy);
988: VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
989: (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
990: return(0);
991: }
995: PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx)
996: {
997: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1001: MatMultDiagonalBlock(a->A,bb,xx);
1002: return(0);
1003: }
1007: PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1008: {
1009: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1013: VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1014: (*a->A->ops->multadd)(a->A,xx,yy,zz);
1015: VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1016: (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);
1017: return(0);
1018: }
1022: PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy)
1023: {
1024: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1026: PetscBool merged;
1029: VecScatterGetMerged(a->Mvctx,&merged);
1030: /* do nondiagonal part */
1031: (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1032: if (!merged) {
1033: /* send it on its way */
1034: VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1035: /* do local part */
1036: (*a->A->ops->multtranspose)(a->A,xx,yy);
1037: /* receive remote parts: note this assumes the values are not actually */
1038: /* added in yy until the next line, */
1039: VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1040: } else {
1041: /* do local part */
1042: (*a->A->ops->multtranspose)(a->A,xx,yy);
1043: /* send it on its way */
1044: VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1045: /* values actually were received in the Begin() but we need to call this nop */
1046: VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1047: }
1048: return(0);
1049: }
1053: PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f)
1054: {
1055: MPI_Comm comm;
1056: Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij;
1057: Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs;
1058: IS Me,Notme;
1060: PetscInt M,N,first,last,*notme,i;
1061: PetscMPIInt size;
1064: /* Easy test: symmetric diagonal block */
1065: Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A;
1066: MatIsTranspose(Adia,Bdia,tol,f);
1067: if (!*f) return(0);
1068: PetscObjectGetComm((PetscObject)Amat,&comm);
1069: MPI_Comm_size(comm,&size);
1070: if (size == 1) return(0);
1072: /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */
1073: MatGetSize(Amat,&M,&N);
1074: MatGetOwnershipRange(Amat,&first,&last);
1075: PetscMalloc1(N-last+first,¬me);
1076: for (i=0; i<first; i++) notme[i] = i;
1077: for (i=last; i<M; i++) notme[i-last+first] = i;
1078: ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);
1079: ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);
1080: MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);
1081: Aoff = Aoffs[0];
1082: MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);
1083: Boff = Boffs[0];
1084: MatIsTranspose(Aoff,Boff,tol,f);
1085: MatDestroyMatrices(1,&Aoffs);
1086: MatDestroyMatrices(1,&Boffs);
1087: ISDestroy(&Me);
1088: ISDestroy(&Notme);
1089: PetscFree(notme);
1090: return(0);
1091: }
1095: PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1096: {
1097: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1101: /* do nondiagonal part */
1102: (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1103: /* send it on its way */
1104: VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1105: /* do local part */
1106: (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);
1107: /* receive remote parts */
1108: VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1109: return(0);
1110: }
1112: /*
1113: This only works correctly for square matrices where the subblock A->A is the
1114: diagonal block
1115: */
1118: PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v)
1119: {
1121: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1124: if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
1125: 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");
1126: MatGetDiagonal(a->A,v);
1127: return(0);
1128: }
1132: PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa)
1133: {
1134: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1138: MatScale(a->A,aa);
1139: MatScale(a->B,aa);
1140: return(0);
1141: }
1145: PetscErrorCode MatDestroy_MPIAIJ(Mat mat)
1146: {
1147: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1151: #if defined(PETSC_USE_LOG)
1152: PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N);
1153: #endif
1154: MatStashDestroy_Private(&mat->stash);
1155: VecDestroy(&aij->diag);
1156: MatDestroy(&aij->A);
1157: MatDestroy(&aij->B);
1158: #if defined(PETSC_USE_CTABLE)
1159: PetscTableDestroy(&aij->colmap);
1160: #else
1161: PetscFree(aij->colmap);
1162: #endif
1163: PetscFree(aij->garray);
1164: VecDestroy(&aij->lvec);
1165: VecScatterDestroy(&aij->Mvctx);
1166: PetscFree2(aij->rowvalues,aij->rowindices);
1167: PetscFree(aij->ld);
1168: PetscFree(mat->data);
1170: PetscObjectChangeTypeName((PetscObject)mat,0);
1171: PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
1172: PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
1173: PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);
1174: PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);
1175: PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);
1176: PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);
1177: PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);
1178: PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);
1179: #if defined(PETSC_HAVE_ELEMENTAL)
1180: PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);
1181: #endif
1182: return(0);
1183: }
1187: PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer)
1188: {
1189: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1190: Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data;
1191: Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data;
1193: PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag;
1194: int fd;
1195: PetscInt nz,header[4],*row_lengths,*range=0,rlen,i;
1196: PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz = 0;
1197: PetscScalar *column_values;
1198: PetscInt message_count,flowcontrolcount;
1199: FILE *file;
1202: MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
1203: MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
1204: nz = A->nz + B->nz;
1205: PetscViewerBinaryGetDescriptor(viewer,&fd);
1206: if (!rank) {
1207: header[0] = MAT_FILE_CLASSID;
1208: header[1] = mat->rmap->N;
1209: header[2] = mat->cmap->N;
1211: MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1212: PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);
1213: /* get largest number of rows any processor has */
1214: rlen = mat->rmap->n;
1215: range = mat->rmap->range;
1216: for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]);
1217: } else {
1218: MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1219: rlen = mat->rmap->n;
1220: }
1222: /* load up the local row counts */
1223: PetscMalloc1(rlen+1,&row_lengths);
1224: for (i=0; i<mat->rmap->n; i++) row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i];
1226: /* store the row lengths to the file */
1227: PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1228: if (!rank) {
1229: PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);
1230: for (i=1; i<size; i++) {
1231: PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1232: rlen = range[i+1] - range[i];
1233: MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));
1234: PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);
1235: }
1236: PetscViewerFlowControlEndMaster(viewer,&message_count);
1237: } else {
1238: PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1239: MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1240: PetscViewerFlowControlEndWorker(viewer,&message_count);
1241: }
1242: PetscFree(row_lengths);
1244: /* load up the local column indices */
1245: nzmax = nz; /* th processor needs space a largest processor needs */
1246: MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));
1247: PetscMalloc1(nzmax+1,&column_indices);
1248: cnt = 0;
1249: for (i=0; i<mat->rmap->n; i++) {
1250: for (j=B->i[i]; j<B->i[i+1]; j++) {
1251: if ((col = garray[B->j[j]]) > cstart) break;
1252: column_indices[cnt++] = col;
1253: }
1254: for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart;
1255: for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]];
1256: }
1257: if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz);
1259: /* store the column indices to the file */
1260: PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1261: if (!rank) {
1262: MPI_Status status;
1263: PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);
1264: for (i=1; i<size; i++) {
1265: PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1266: MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1267: if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax);
1268: MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));
1269: PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);
1270: }
1271: PetscViewerFlowControlEndMaster(viewer,&message_count);
1272: } else {
1273: PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1274: MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1275: MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1276: PetscViewerFlowControlEndWorker(viewer,&message_count);
1277: }
1278: PetscFree(column_indices);
1280: /* load up the local column values */
1281: PetscMalloc1(nzmax+1,&column_values);
1282: cnt = 0;
1283: for (i=0; i<mat->rmap->n; i++) {
1284: for (j=B->i[i]; j<B->i[i+1]; j++) {
1285: if (garray[B->j[j]] > cstart) break;
1286: column_values[cnt++] = B->a[j];
1287: }
1288: for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k];
1289: for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j];
1290: }
1291: if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz);
1293: /* store the column values to the file */
1294: PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1295: if (!rank) {
1296: MPI_Status status;
1297: PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);
1298: for (i=1; i<size; i++) {
1299: PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1300: MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1301: if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax);
1302: MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));
1303: PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);
1304: }
1305: PetscViewerFlowControlEndMaster(viewer,&message_count);
1306: } else {
1307: PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1308: MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1309: MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));
1310: PetscViewerFlowControlEndWorker(viewer,&message_count);
1311: }
1312: PetscFree(column_values);
1314: PetscViewerBinaryGetInfoPointer(viewer,&file);
1315: if (file) fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(mat->rmap->bs));
1316: return(0);
1317: }
1319: #include <petscdraw.h>
1322: PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
1323: {
1324: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1325: PetscErrorCode ierr;
1326: PetscMPIInt rank = aij->rank,size = aij->size;
1327: PetscBool isdraw,iascii,isbinary;
1328: PetscViewer sviewer;
1329: PetscViewerFormat format;
1332: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1333: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1334: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1335: if (iascii) {
1336: PetscViewerGetFormat(viewer,&format);
1337: if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
1338: MatInfo info;
1339: PetscBool inodes;
1341: MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
1342: MatGetInfo(mat,MAT_LOCAL,&info);
1343: MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);
1344: PetscViewerASCIIPushSynchronized(viewer);
1345: if (!inodes) {
1346: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n",
1347: rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);
1348: } else {
1349: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n",
1350: rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);
1351: }
1352: MatGetInfo(aij->A,MAT_LOCAL,&info);
1353: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1354: MatGetInfo(aij->B,MAT_LOCAL,&info);
1355: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1356: PetscViewerFlush(viewer);
1357: PetscViewerASCIIPopSynchronized(viewer);
1358: PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
1359: VecScatterView(aij->Mvctx,viewer);
1360: return(0);
1361: } else if (format == PETSC_VIEWER_ASCII_INFO) {
1362: PetscInt inodecount,inodelimit,*inodes;
1363: MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);
1364: if (inodes) {
1365: PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);
1366: } else {
1367: PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");
1368: }
1369: return(0);
1370: } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
1371: return(0);
1372: }
1373: } else if (isbinary) {
1374: if (size == 1) {
1375: PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);
1376: MatView(aij->A,viewer);
1377: } else {
1378: MatView_MPIAIJ_Binary(mat,viewer);
1379: }
1380: return(0);
1381: } else if (isdraw) {
1382: PetscDraw draw;
1383: PetscBool isnull;
1384: PetscViewerDrawGetDraw(viewer,0,&draw);
1385: PetscDrawIsNull(draw,&isnull);
1386: if (isnull) return(0);
1387: }
1389: {
1390: /* assemble the entire matrix onto first processor. */
1391: Mat A;
1392: Mat_SeqAIJ *Aloc;
1393: PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct;
1394: MatScalar *a;
1396: MatCreate(PetscObjectComm((PetscObject)mat),&A);
1397: if (!rank) {
1398: MatSetSizes(A,M,N,M,N);
1399: } else {
1400: MatSetSizes(A,0,0,M,N);
1401: }
1402: /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */
1403: MatSetType(A,MATMPIAIJ);
1404: MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);
1405: MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
1406: PetscLogObjectParent((PetscObject)mat,(PetscObject)A);
1408: /* copy over the A part */
1409: Aloc = (Mat_SeqAIJ*)aij->A->data;
1410: m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
1411: row = mat->rmap->rstart;
1412: for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart;
1413: for (i=0; i<m; i++) {
1414: MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);
1415: row++;
1416: a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i];
1417: }
1418: aj = Aloc->j;
1419: for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart;
1421: /* copy over the B part */
1422: Aloc = (Mat_SeqAIJ*)aij->B->data;
1423: m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
1424: row = mat->rmap->rstart;
1425: PetscMalloc1(ai[m]+1,&cols);
1426: ct = cols;
1427: for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]];
1428: for (i=0; i<m; i++) {
1429: MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);
1430: row++;
1431: a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i];
1432: }
1433: PetscFree(ct);
1434: MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
1435: MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
1436: /*
1437: Everyone has to call to draw the matrix since the graphics waits are
1438: synchronized across all processors that share the PetscDraw object
1439: */
1440: PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
1441: if (!rank) {
1442: PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);
1443: MatView_SeqAIJ(((Mat_MPIAIJ*)(A->data))->A,sviewer);
1444: }
1445: PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
1446: PetscViewerFlush(viewer);
1447: MatDestroy(&A);
1448: }
1449: return(0);
1450: }
1454: PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer)
1455: {
1457: PetscBool iascii,isdraw,issocket,isbinary;
1460: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1461: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1462: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1463: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
1464: if (iascii || isdraw || isbinary || issocket) {
1465: MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);
1466: }
1467: return(0);
1468: }
1472: PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
1473: {
1474: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data;
1476: Vec bb1 = 0;
1477: PetscBool hasop;
1480: if (flag == SOR_APPLY_UPPER) {
1481: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1482: return(0);
1483: }
1485: if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) {
1486: VecDuplicate(bb,&bb1);
1487: }
1489: if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
1490: if (flag & SOR_ZERO_INITIAL_GUESS) {
1491: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1492: its--;
1493: }
1495: while (its--) {
1496: VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1497: VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1499: /* update rhs: bb1 = bb - B*x */
1500: VecScale(mat->lvec,-1.0);
1501: (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);
1503: /* local sweep */
1504: (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);
1505: }
1506: } else if (flag & SOR_LOCAL_FORWARD_SWEEP) {
1507: if (flag & SOR_ZERO_INITIAL_GUESS) {
1508: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1509: its--;
1510: }
1511: while (its--) {
1512: VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1513: VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1515: /* update rhs: bb1 = bb - B*x */
1516: VecScale(mat->lvec,-1.0);
1517: (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);
1519: /* local sweep */
1520: (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);
1521: }
1522: } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) {
1523: if (flag & SOR_ZERO_INITIAL_GUESS) {
1524: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1525: its--;
1526: }
1527: while (its--) {
1528: VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1529: VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1531: /* update rhs: bb1 = bb - B*x */
1532: VecScale(mat->lvec,-1.0);
1533: (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);
1535: /* local sweep */
1536: (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);
1537: }
1538: } else if (flag & SOR_EISENSTAT) {
1539: Vec xx1;
1541: VecDuplicate(bb,&xx1);
1542: (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);
1544: VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1545: VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1546: if (!mat->diag) {
1547: MatCreateVecs(matin,&mat->diag,NULL);
1548: MatGetDiagonal(matin,mat->diag);
1549: }
1550: MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);
1551: if (hasop) {
1552: MatMultDiagonalBlock(matin,xx,bb1);
1553: } else {
1554: VecPointwiseMult(bb1,mat->diag,xx);
1555: }
1556: VecAYPX(bb1,(omega-2.0)/omega,bb);
1558: MatMultAdd(mat->B,mat->lvec,bb1,bb1);
1560: /* local sweep */
1561: (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
1562: VecAXPY(xx,1.0,xx1);
1563: VecDestroy(&xx1);
1564: } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported");
1566: VecDestroy(&bb1);
1568: matin->errortype = mat->A->errortype;
1569: return(0);
1570: }
1574: PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B)
1575: {
1576: Mat aA,aB,Aperm;
1577: const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj;
1578: PetscScalar *aa,*ba;
1579: PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest;
1580: PetscSF rowsf,sf;
1581: IS parcolp = NULL;
1582: PetscBool done;
1586: MatGetLocalSize(A,&m,&n);
1587: ISGetIndices(rowp,&rwant);
1588: ISGetIndices(colp,&cwant);
1589: PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);
1591: /* Invert row permutation to find out where my rows should go */
1592: PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);
1593: PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);
1594: PetscSFSetFromOptions(rowsf);
1595: for (i=0; i<m; i++) work[i] = A->rmap->rstart + i;
1596: PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);
1597: PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);
1599: /* Invert column permutation to find out where my columns should go */
1600: PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1601: PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);
1602: PetscSFSetFromOptions(sf);
1603: for (i=0; i<n; i++) work[i] = A->cmap->rstart + i;
1604: PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);
1605: PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);
1606: PetscSFDestroy(&sf);
1608: ISRestoreIndices(rowp,&rwant);
1609: ISRestoreIndices(colp,&cwant);
1610: MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);
1612: /* Find out where my gcols should go */
1613: MatGetSize(aB,NULL,&ng);
1614: PetscMalloc1(ng,&gcdest);
1615: PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1616: PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);
1617: PetscSFSetFromOptions(sf);
1618: PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);
1619: PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);
1620: PetscSFDestroy(&sf);
1622: PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);
1623: MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);
1624: MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);
1625: for (i=0; i<m; i++) {
1626: PetscInt row = rdest[i],rowner;
1627: PetscLayoutFindOwner(A->rmap,row,&rowner);
1628: for (j=ai[i]; j<ai[i+1]; j++) {
1629: PetscInt cowner,col = cdest[aj[j]];
1630: PetscLayoutFindOwner(A->cmap,col,&cowner); /* Could build an index for the columns to eliminate this search */
1631: if (rowner == cowner) dnnz[i]++;
1632: else onnz[i]++;
1633: }
1634: for (j=bi[i]; j<bi[i+1]; j++) {
1635: PetscInt cowner,col = gcdest[bj[j]];
1636: PetscLayoutFindOwner(A->cmap,col,&cowner);
1637: if (rowner == cowner) dnnz[i]++;
1638: else onnz[i]++;
1639: }
1640: }
1641: PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);
1642: PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);
1643: PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);
1644: PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);
1645: PetscSFDestroy(&rowsf);
1647: MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);
1648: MatSeqAIJGetArray(aA,&aa);
1649: MatSeqAIJGetArray(aB,&ba);
1650: for (i=0; i<m; i++) {
1651: PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */
1652: PetscInt j0,rowlen;
1653: rowlen = ai[i+1] - ai[i];
1654: for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */
1655: for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]];
1656: MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);
1657: }
1658: rowlen = bi[i+1] - bi[i];
1659: for (j0=j=0; j<rowlen; j0=j) {
1660: for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]];
1661: MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);
1662: }
1663: }
1664: MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);
1665: MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);
1666: MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);
1667: MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);
1668: MatSeqAIJRestoreArray(aA,&aa);
1669: MatSeqAIJRestoreArray(aB,&ba);
1670: PetscFree4(dnnz,onnz,tdnnz,tonnz);
1671: PetscFree3(work,rdest,cdest);
1672: PetscFree(gcdest);
1673: if (parcolp) {ISDestroy(&colp);}
1674: *B = Aperm;
1675: return(0);
1676: }
1680: PetscErrorCode MatGetGhosts_MPIAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[])
1681: {
1682: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1686: MatGetSize(aij->B,NULL,nghosts);
1687: if (ghosts) *ghosts = aij->garray;
1688: return(0);
1689: }
1693: PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1694: {
1695: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data;
1696: Mat A = mat->A,B = mat->B;
1698: PetscReal isend[5],irecv[5];
1701: info->block_size = 1.0;
1702: MatGetInfo(A,MAT_LOCAL,info);
1704: isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1705: isend[3] = info->memory; isend[4] = info->mallocs;
1707: MatGetInfo(B,MAT_LOCAL,info);
1709: isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1710: isend[3] += info->memory; isend[4] += info->mallocs;
1711: if (flag == MAT_LOCAL) {
1712: info->nz_used = isend[0];
1713: info->nz_allocated = isend[1];
1714: info->nz_unneeded = isend[2];
1715: info->memory = isend[3];
1716: info->mallocs = isend[4];
1717: } else if (flag == MAT_GLOBAL_MAX) {
1718: MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));
1720: info->nz_used = irecv[0];
1721: info->nz_allocated = irecv[1];
1722: info->nz_unneeded = irecv[2];
1723: info->memory = irecv[3];
1724: info->mallocs = irecv[4];
1725: } else if (flag == MAT_GLOBAL_SUM) {
1726: MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));
1728: info->nz_used = irecv[0];
1729: info->nz_allocated = irecv[1];
1730: info->nz_unneeded = irecv[2];
1731: info->memory = irecv[3];
1732: info->mallocs = irecv[4];
1733: }
1734: info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */
1735: info->fill_ratio_needed = 0;
1736: info->factor_mallocs = 0;
1737: return(0);
1738: }
1742: PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg)
1743: {
1744: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1748: switch (op) {
1749: case MAT_NEW_NONZERO_LOCATIONS:
1750: case MAT_NEW_NONZERO_ALLOCATION_ERR:
1751: case MAT_UNUSED_NONZERO_LOCATION_ERR:
1752: case MAT_KEEP_NONZERO_PATTERN:
1753: case MAT_NEW_NONZERO_LOCATION_ERR:
1754: case MAT_USE_INODES:
1755: case MAT_IGNORE_ZERO_ENTRIES:
1756: MatCheckPreallocated(A,1);
1757: MatSetOption(a->A,op,flg);
1758: MatSetOption(a->B,op,flg);
1759: break;
1760: case MAT_ROW_ORIENTED:
1761: MatCheckPreallocated(A,1);
1762: a->roworiented = flg;
1764: MatSetOption(a->A,op,flg);
1765: MatSetOption(a->B,op,flg);
1766: break;
1767: case MAT_NEW_DIAGONALS:
1768: PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1769: break;
1770: case MAT_IGNORE_OFF_PROC_ENTRIES:
1771: a->donotstash = flg;
1772: break;
1773: case MAT_SPD:
1774: A->spd_set = PETSC_TRUE;
1775: A->spd = flg;
1776: if (flg) {
1777: A->symmetric = PETSC_TRUE;
1778: A->structurally_symmetric = PETSC_TRUE;
1779: A->symmetric_set = PETSC_TRUE;
1780: A->structurally_symmetric_set = PETSC_TRUE;
1781: }
1782: break;
1783: case MAT_SYMMETRIC:
1784: MatCheckPreallocated(A,1);
1785: MatSetOption(a->A,op,flg);
1786: break;
1787: case MAT_STRUCTURALLY_SYMMETRIC:
1788: MatCheckPreallocated(A,1);
1789: MatSetOption(a->A,op,flg);
1790: break;
1791: case MAT_HERMITIAN:
1792: MatCheckPreallocated(A,1);
1793: MatSetOption(a->A,op,flg);
1794: break;
1795: case MAT_SYMMETRY_ETERNAL:
1796: MatCheckPreallocated(A,1);
1797: MatSetOption(a->A,op,flg);
1798: break;
1799: default:
1800: SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1801: }
1802: return(0);
1803: }
1807: PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1808: {
1809: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data;
1810: PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p;
1812: PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart;
1813: PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend;
1814: PetscInt *cmap,*idx_p;
1817: if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
1818: mat->getrowactive = PETSC_TRUE;
1820: if (!mat->rowvalues && (idx || v)) {
1821: /*
1822: allocate enough space to hold information from the longest row.
1823: */
1824: Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data;
1825: PetscInt max = 1,tmp;
1826: for (i=0; i<matin->rmap->n; i++) {
1827: tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i];
1828: if (max < tmp) max = tmp;
1829: }
1830: PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);
1831: }
1833: if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows");
1834: lrow = row - rstart;
1836: pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1837: if (!v) {pvA = 0; pvB = 0;}
1838: if (!idx) {pcA = 0; if (!v) pcB = 0;}
1839: (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1840: (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1841: nztot = nzA + nzB;
1843: cmap = mat->garray;
1844: if (v || idx) {
1845: if (nztot) {
1846: /* Sort by increasing column numbers, assuming A and B already sorted */
1847: PetscInt imark = -1;
1848: if (v) {
1849: *v = v_p = mat->rowvalues;
1850: for (i=0; i<nzB; i++) {
1851: if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i];
1852: else break;
1853: }
1854: imark = i;
1855: for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i];
1856: for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i];
1857: }
1858: if (idx) {
1859: *idx = idx_p = mat->rowindices;
1860: if (imark > -1) {
1861: for (i=0; i<imark; i++) {
1862: idx_p[i] = cmap[cworkB[i]];
1863: }
1864: } else {
1865: for (i=0; i<nzB; i++) {
1866: if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]];
1867: else break;
1868: }
1869: imark = i;
1870: }
1871: for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i];
1872: for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]];
1873: }
1874: } else {
1875: if (idx) *idx = 0;
1876: if (v) *v = 0;
1877: }
1878: }
1879: *nz = nztot;
1880: (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1881: (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1882: return(0);
1883: }
1887: PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1888: {
1889: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1892: if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
1893: aij->getrowactive = PETSC_FALSE;
1894: return(0);
1895: }
1899: PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm)
1900: {
1901: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1902: Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data;
1904: PetscInt i,j,cstart = mat->cmap->rstart;
1905: PetscReal sum = 0.0;
1906: MatScalar *v;
1909: if (aij->size == 1) {
1910: MatNorm(aij->A,type,norm);
1911: } else {
1912: if (type == NORM_FROBENIUS) {
1913: v = amat->a;
1914: for (i=0; i<amat->nz; i++) {
1915: sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1916: }
1917: v = bmat->a;
1918: for (i=0; i<bmat->nz; i++) {
1919: sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1920: }
1921: MPIU_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
1922: *norm = PetscSqrtReal(*norm);
1923: PetscLogFlops(2*amat->nz+2*bmat->nz);
1924: } else if (type == NORM_1) { /* max column norm */
1925: PetscReal *tmp,*tmp2;
1926: PetscInt *jj,*garray = aij->garray;
1927: PetscCalloc1(mat->cmap->N+1,&tmp);
1928: PetscMalloc1(mat->cmap->N+1,&tmp2);
1929: *norm = 0.0;
1930: v = amat->a; jj = amat->j;
1931: for (j=0; j<amat->nz; j++) {
1932: tmp[cstart + *jj++] += PetscAbsScalar(*v); v++;
1933: }
1934: v = bmat->a; jj = bmat->j;
1935: for (j=0; j<bmat->nz; j++) {
1936: tmp[garray[*jj++]] += PetscAbsScalar(*v); v++;
1937: }
1938: MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
1939: for (j=0; j<mat->cmap->N; j++) {
1940: if (tmp2[j] > *norm) *norm = tmp2[j];
1941: }
1942: PetscFree(tmp);
1943: PetscFree(tmp2);
1944: PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));
1945: } else if (type == NORM_INFINITY) { /* max row norm */
1946: PetscReal ntemp = 0.0;
1947: for (j=0; j<aij->A->rmap->n; j++) {
1948: v = amat->a + amat->i[j];
1949: sum = 0.0;
1950: for (i=0; i<amat->i[j+1]-amat->i[j]; i++) {
1951: sum += PetscAbsScalar(*v); v++;
1952: }
1953: v = bmat->a + bmat->i[j];
1954: for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) {
1955: sum += PetscAbsScalar(*v); v++;
1956: }
1957: if (sum > ntemp) ntemp = sum;
1958: }
1959: MPIU_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));
1960: PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));
1961: } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm");
1962: }
1963: return(0);
1964: }
1968: PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout)
1969: {
1970: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1971: Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data;
1973: PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i;
1974: PetscInt cstart = A->cmap->rstart,ncol;
1975: Mat B;
1976: MatScalar *array;
1979: if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place");
1981: ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n;
1982: ai = Aloc->i; aj = Aloc->j;
1983: bi = Bloc->i; bj = Bloc->j;
1984: if (reuse == MAT_INITIAL_MATRIX || *matout == A) {
1985: PetscInt *d_nnz,*g_nnz,*o_nnz;
1986: PetscSFNode *oloc;
1987: PETSC_UNUSED PetscSF sf;
1989: PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);
1990: /* compute d_nnz for preallocation */
1991: PetscMemzero(d_nnz,na*sizeof(PetscInt));
1992: for (i=0; i<ai[ma]; i++) {
1993: d_nnz[aj[i]]++;
1994: aj[i] += cstart; /* global col index to be used by MatSetValues() */
1995: }
1996: /* compute local off-diagonal contributions */
1997: PetscMemzero(g_nnz,nb*sizeof(PetscInt));
1998: for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++;
1999: /* map those to global */
2000: PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
2001: PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);
2002: PetscSFSetFromOptions(sf);
2003: PetscMemzero(o_nnz,na*sizeof(PetscInt));
2004: PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);
2005: PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);
2006: PetscSFDestroy(&sf);
2008: MatCreate(PetscObjectComm((PetscObject)A),&B);
2009: MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);
2010: MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));
2011: MatSetType(B,((PetscObject)A)->type_name);
2012: MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);
2013: PetscFree4(d_nnz,o_nnz,g_nnz,oloc);
2014: } else {
2015: B = *matout;
2016: MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);
2017: for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */
2018: }
2020: /* copy over the A part */
2021: array = Aloc->a;
2022: row = A->rmap->rstart;
2023: for (i=0; i<ma; i++) {
2024: ncol = ai[i+1]-ai[i];
2025: MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);
2026: row++;
2027: array += ncol; aj += ncol;
2028: }
2029: aj = Aloc->j;
2030: for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */
2032: /* copy over the B part */
2033: PetscCalloc1(bi[mb],&cols);
2034: array = Bloc->a;
2035: row = A->rmap->rstart;
2036: for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]];
2037: cols_tmp = cols;
2038: for (i=0; i<mb; i++) {
2039: ncol = bi[i+1]-bi[i];
2040: MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);
2041: row++;
2042: array += ncol; cols_tmp += ncol;
2043: }
2044: PetscFree(cols);
2046: MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2047: MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2048: if (reuse == MAT_INITIAL_MATRIX || *matout != A) {
2049: *matout = B;
2050: } else {
2051: MatHeaderMerge(A,&B);
2052: }
2053: return(0);
2054: }
2058: PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr)
2059: {
2060: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
2061: Mat a = aij->A,b = aij->B;
2063: PetscInt s1,s2,s3;
2066: MatGetLocalSize(mat,&s2,&s3);
2067: if (rr) {
2068: VecGetLocalSize(rr,&s1);
2069: if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size");
2070: /* Overlap communication with computation. */
2071: VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);
2072: }
2073: if (ll) {
2074: VecGetLocalSize(ll,&s1);
2075: if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size");
2076: (*b->ops->diagonalscale)(b,ll,0);
2077: }
2078: /* scale the diagonal block */
2079: (*a->ops->diagonalscale)(a,ll,rr);
2081: if (rr) {
2082: /* Do a scatter end and then right scale the off-diagonal block */
2083: VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);
2084: (*b->ops->diagonalscale)(b,0,aij->lvec);
2085: }
2086: return(0);
2087: }
2091: PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A)
2092: {
2093: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2097: MatSetUnfactored(a->A);
2098: return(0);
2099: }
2103: PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag)
2104: {
2105: Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data;
2106: Mat a,b,c,d;
2107: PetscBool flg;
2111: a = matA->A; b = matA->B;
2112: c = matB->A; d = matB->B;
2114: MatEqual(a,c,&flg);
2115: if (flg) {
2116: MatEqual(b,d,&flg);
2117: }
2118: MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
2119: return(0);
2120: }
2124: PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str)
2125: {
2127: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2128: Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data;
2131: /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
2132: if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
2133: /* because of the column compression in the off-processor part of the matrix a->B,
2134: the number of columns in a->B and b->B may be different, hence we cannot call
2135: the MatCopy() directly on the two parts. If need be, we can provide a more
2136: efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices
2137: then copying the submatrices */
2138: MatCopy_Basic(A,B,str);
2139: } else {
2140: MatCopy(a->A,b->A,str);
2141: MatCopy(a->B,b->B,str);
2142: }
2143: return(0);
2144: }
2148: PetscErrorCode MatSetUp_MPIAIJ(Mat A)
2149: {
2153: MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
2154: return(0);
2155: }
2157: /*
2158: Computes the number of nonzeros per row needed for preallocation when X and Y
2159: have different nonzero structure.
2160: */
2163: 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)
2164: {
2165: PetscInt i,j,k,nzx,nzy;
2168: /* Set the number of nonzeros in the new matrix */
2169: for (i=0; i<m; i++) {
2170: const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i];
2171: nzx = xi[i+1] - xi[i];
2172: nzy = yi[i+1] - yi[i];
2173: nnz[i] = 0;
2174: for (j=0,k=0; j<nzx; j++) { /* Point in X */
2175: for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */
2176: if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++; /* Skip duplicate */
2177: nnz[i]++;
2178: }
2179: for (; k<nzy; k++) nnz[i]++;
2180: }
2181: return(0);
2182: }
2184: /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */
2187: static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz)
2188: {
2190: PetscInt m = Y->rmap->N;
2191: Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data;
2192: Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data;
2195: MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);
2196: return(0);
2197: }
2201: PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
2202: {
2204: Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data;
2205: PetscBLASInt bnz,one=1;
2206: Mat_SeqAIJ *x,*y;
2209: if (str == SAME_NONZERO_PATTERN) {
2210: PetscScalar alpha = a;
2211: x = (Mat_SeqAIJ*)xx->A->data;
2212: PetscBLASIntCast(x->nz,&bnz);
2213: y = (Mat_SeqAIJ*)yy->A->data;
2214: PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2215: x = (Mat_SeqAIJ*)xx->B->data;
2216: y = (Mat_SeqAIJ*)yy->B->data;
2217: PetscBLASIntCast(x->nz,&bnz);
2218: PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2219: PetscObjectStateIncrease((PetscObject)Y);
2220: } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
2221: MatAXPY_Basic(Y,a,X,str);
2222: } else {
2223: Mat B;
2224: PetscInt *nnz_d,*nnz_o;
2225: PetscMalloc1(yy->A->rmap->N,&nnz_d);
2226: PetscMalloc1(yy->B->rmap->N,&nnz_o);
2227: MatCreate(PetscObjectComm((PetscObject)Y),&B);
2228: PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
2229: MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
2230: MatSetBlockSizesFromMats(B,Y,Y);
2231: MatSetType(B,MATMPIAIJ);
2232: MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);
2233: MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
2234: MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);
2235: MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
2236: MatHeaderReplace(Y,&B);
2237: PetscFree(nnz_d);
2238: PetscFree(nnz_o);
2239: }
2240: return(0);
2241: }
2243: extern PetscErrorCode MatConjugate_SeqAIJ(Mat);
2247: PetscErrorCode MatConjugate_MPIAIJ(Mat mat)
2248: {
2249: #if defined(PETSC_USE_COMPLEX)
2251: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
2254: MatConjugate_SeqAIJ(aij->A);
2255: MatConjugate_SeqAIJ(aij->B);
2256: #else
2258: #endif
2259: return(0);
2260: }
2264: PetscErrorCode MatRealPart_MPIAIJ(Mat A)
2265: {
2266: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2270: MatRealPart(a->A);
2271: MatRealPart(a->B);
2272: return(0);
2273: }
2277: PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A)
2278: {
2279: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2283: MatImaginaryPart(a->A);
2284: MatImaginaryPart(a->B);
2285: return(0);
2286: }
2290: PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2291: {
2292: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2294: PetscInt i,*idxb = 0;
2295: PetscScalar *va,*vb;
2296: Vec vtmp;
2299: MatGetRowMaxAbs(a->A,v,idx);
2300: VecGetArray(v,&va);
2301: if (idx) {
2302: for (i=0; i<A->rmap->n; i++) {
2303: if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
2304: }
2305: }
2307: VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
2308: if (idx) {
2309: PetscMalloc1(A->rmap->n,&idxb);
2310: }
2311: MatGetRowMaxAbs(a->B,vtmp,idxb);
2312: VecGetArray(vtmp,&vb);
2314: for (i=0; i<A->rmap->n; i++) {
2315: if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {
2316: va[i] = vb[i];
2317: if (idx) idx[i] = a->garray[idxb[i]];
2318: }
2319: }
2321: VecRestoreArray(v,&va);
2322: VecRestoreArray(vtmp,&vb);
2323: PetscFree(idxb);
2324: VecDestroy(&vtmp);
2325: return(0);
2326: }
2330: PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2331: {
2332: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2334: PetscInt i,*idxb = 0;
2335: PetscScalar *va,*vb;
2336: Vec vtmp;
2339: MatGetRowMinAbs(a->A,v,idx);
2340: VecGetArray(v,&va);
2341: if (idx) {
2342: for (i=0; i<A->cmap->n; i++) {
2343: if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
2344: }
2345: }
2347: VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
2348: if (idx) {
2349: PetscMalloc1(A->rmap->n,&idxb);
2350: }
2351: MatGetRowMinAbs(a->B,vtmp,idxb);
2352: VecGetArray(vtmp,&vb);
2354: for (i=0; i<A->rmap->n; i++) {
2355: if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) {
2356: va[i] = vb[i];
2357: if (idx) idx[i] = a->garray[idxb[i]];
2358: }
2359: }
2361: VecRestoreArray(v,&va);
2362: VecRestoreArray(vtmp,&vb);
2363: PetscFree(idxb);
2364: VecDestroy(&vtmp);
2365: return(0);
2366: }
2370: PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2371: {
2372: Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data;
2373: PetscInt n = A->rmap->n;
2374: PetscInt cstart = A->cmap->rstart;
2375: PetscInt *cmap = mat->garray;
2376: PetscInt *diagIdx, *offdiagIdx;
2377: Vec diagV, offdiagV;
2378: PetscScalar *a, *diagA, *offdiagA;
2379: PetscInt r;
2383: PetscMalloc2(n,&diagIdx,n,&offdiagIdx);
2384: VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);
2385: VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);
2386: MatGetRowMin(mat->A, diagV, diagIdx);
2387: MatGetRowMin(mat->B, offdiagV, offdiagIdx);
2388: VecGetArray(v, &a);
2389: VecGetArray(diagV, &diagA);
2390: VecGetArray(offdiagV, &offdiagA);
2391: for (r = 0; r < n; ++r) {
2392: if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) {
2393: a[r] = diagA[r];
2394: idx[r] = cstart + diagIdx[r];
2395: } else {
2396: a[r] = offdiagA[r];
2397: idx[r] = cmap[offdiagIdx[r]];
2398: }
2399: }
2400: VecRestoreArray(v, &a);
2401: VecRestoreArray(diagV, &diagA);
2402: VecRestoreArray(offdiagV, &offdiagA);
2403: VecDestroy(&diagV);
2404: VecDestroy(&offdiagV);
2405: PetscFree2(diagIdx, offdiagIdx);
2406: return(0);
2407: }
2411: PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2412: {
2413: Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data;
2414: PetscInt n = A->rmap->n;
2415: PetscInt cstart = A->cmap->rstart;
2416: PetscInt *cmap = mat->garray;
2417: PetscInt *diagIdx, *offdiagIdx;
2418: Vec diagV, offdiagV;
2419: PetscScalar *a, *diagA, *offdiagA;
2420: PetscInt r;
2424: PetscMalloc2(n,&diagIdx,n,&offdiagIdx);
2425: VecCreateSeq(PETSC_COMM_SELF, n, &diagV);
2426: VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);
2427: MatGetRowMax(mat->A, diagV, diagIdx);
2428: MatGetRowMax(mat->B, offdiagV, offdiagIdx);
2429: VecGetArray(v, &a);
2430: VecGetArray(diagV, &diagA);
2431: VecGetArray(offdiagV, &offdiagA);
2432: for (r = 0; r < n; ++r) {
2433: if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) {
2434: a[r] = diagA[r];
2435: idx[r] = cstart + diagIdx[r];
2436: } else {
2437: a[r] = offdiagA[r];
2438: idx[r] = cmap[offdiagIdx[r]];
2439: }
2440: }
2441: VecRestoreArray(v, &a);
2442: VecRestoreArray(diagV, &diagA);
2443: VecRestoreArray(offdiagV, &offdiagA);
2444: VecDestroy(&diagV);
2445: VecDestroy(&offdiagV);
2446: PetscFree2(diagIdx, offdiagIdx);
2447: return(0);
2448: }
2452: PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat)
2453: {
2455: Mat *dummy;
2458: MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);
2459: *newmat = *dummy;
2460: PetscFree(dummy);
2461: return(0);
2462: }
2466: PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values)
2467: {
2468: Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data;
2472: MatInvertBlockDiagonal(a->A,values);
2473: A->errortype = a->A->errortype;
2474: return(0);
2475: }
2479: static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx)
2480: {
2482: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data;
2485: MatSetRandom(aij->A,rctx);
2486: MatSetRandom(aij->B,rctx);
2487: MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);
2488: MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);
2489: return(0);
2490: }
2494: PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ(Mat A,PetscBool sc)
2495: {
2497: if (sc) A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ_Scalable;
2498: else A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ;
2499: return(0);
2500: }
2504: /*@
2505: MatMPIAIJSetUseScalableIncreaseOverlap - Determine if the matrix uses a scalable algorithm to compute the overlap
2507: Collective on Mat
2509: Input Parameters:
2510: + A - the matrix
2511: - sc - PETSC_TRUE indicates use the scalable algorithm (default is not to use the scalable algorithm)
2513: Level: advanced
2515: @*/
2516: PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap(Mat A,PetscBool sc)
2517: {
2518: PetscErrorCode ierr;
2521: PetscTryMethod(A,"MatMPIAIJSetUseScalableIncreaseOverlap_C",(Mat,PetscBool),(A,sc));
2522: return(0);
2523: }
2527: PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptionItems *PetscOptionsObject,Mat A)
2528: {
2529: PetscErrorCode ierr;
2530: PetscBool sc = PETSC_FALSE,flg;
2533: PetscOptionsHead(PetscOptionsObject,"MPIAIJ options");
2534: PetscObjectOptionsBegin((PetscObject)A);
2535: if (A->ops->increaseoverlap == MatIncreaseOverlap_MPIAIJ_Scalable) sc = PETSC_TRUE;
2536: PetscOptionsBool("-mat_increase_overlap_scalable","Use a scalable algorithm to compute the overlap","MatIncreaseOverlap",sc,&sc,&flg);
2537: if (flg) {
2538: MatMPIAIJSetUseScalableIncreaseOverlap(A,sc);
2539: }
2540: PetscOptionsEnd();
2541: return(0);
2542: }
2546: PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a)
2547: {
2549: Mat_MPIAIJ *maij = (Mat_MPIAIJ*)Y->data;
2550: Mat_SeqAIJ *aij = (Mat_SeqAIJ*)maij->A->data;
2553: if (!Y->preallocated) {
2554: MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);
2555: } else if (!aij->nz) {
2556: PetscInt nonew = aij->nonew;
2557: MatSeqAIJSetPreallocation(maij->A,1,NULL);
2558: aij->nonew = nonew;
2559: }
2560: MatShift_Basic(Y,a);
2561: return(0);
2562: }
2566: PetscErrorCode MatMissingDiagonal_MPIAIJ(Mat A,PetscBool *missing,PetscInt *d)
2567: {
2568: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2572: if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
2573: MatMissingDiagonal(a->A,missing,d);
2574: if (d) {
2575: PetscInt rstart;
2576: MatGetOwnershipRange(A,&rstart,NULL);
2577: *d += rstart;
2579: }
2580: return(0);
2581: }
2584: /* -------------------------------------------------------------------*/
2585: static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ,
2586: MatGetRow_MPIAIJ,
2587: MatRestoreRow_MPIAIJ,
2588: MatMult_MPIAIJ,
2589: /* 4*/ MatMultAdd_MPIAIJ,
2590: MatMultTranspose_MPIAIJ,
2591: MatMultTransposeAdd_MPIAIJ,
2592: 0,
2593: 0,
2594: 0,
2595: /*10*/ 0,
2596: 0,
2597: 0,
2598: MatSOR_MPIAIJ,
2599: MatTranspose_MPIAIJ,
2600: /*15*/ MatGetInfo_MPIAIJ,
2601: MatEqual_MPIAIJ,
2602: MatGetDiagonal_MPIAIJ,
2603: MatDiagonalScale_MPIAIJ,
2604: MatNorm_MPIAIJ,
2605: /*20*/ MatAssemblyBegin_MPIAIJ,
2606: MatAssemblyEnd_MPIAIJ,
2607: MatSetOption_MPIAIJ,
2608: MatZeroEntries_MPIAIJ,
2609: /*24*/ MatZeroRows_MPIAIJ,
2610: 0,
2611: 0,
2612: 0,
2613: 0,
2614: /*29*/ MatSetUp_MPIAIJ,
2615: 0,
2616: 0,
2617: 0,
2618: 0,
2619: /*34*/ MatDuplicate_MPIAIJ,
2620: 0,
2621: 0,
2622: 0,
2623: 0,
2624: /*39*/ MatAXPY_MPIAIJ,
2625: MatGetSubMatrices_MPIAIJ,
2626: MatIncreaseOverlap_MPIAIJ,
2627: MatGetValues_MPIAIJ,
2628: MatCopy_MPIAIJ,
2629: /*44*/ MatGetRowMax_MPIAIJ,
2630: MatScale_MPIAIJ,
2631: MatShift_MPIAIJ,
2632: MatDiagonalSet_MPIAIJ,
2633: MatZeroRowsColumns_MPIAIJ,
2634: /*49*/ MatSetRandom_MPIAIJ,
2635: 0,
2636: 0,
2637: 0,
2638: 0,
2639: /*54*/ MatFDColoringCreate_MPIXAIJ,
2640: 0,
2641: MatSetUnfactored_MPIAIJ,
2642: MatPermute_MPIAIJ,
2643: 0,
2644: /*59*/ MatGetSubMatrix_MPIAIJ,
2645: MatDestroy_MPIAIJ,
2646: MatView_MPIAIJ,
2647: 0,
2648: MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ,
2649: /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ,
2650: MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ,
2651: 0,
2652: 0,
2653: 0,
2654: /*69*/ MatGetRowMaxAbs_MPIAIJ,
2655: MatGetRowMinAbs_MPIAIJ,
2656: 0,
2657: MatSetColoring_MPIAIJ,
2658: 0,
2659: MatSetValuesAdifor_MPIAIJ,
2660: /*75*/ MatFDColoringApply_AIJ,
2661: MatSetFromOptions_MPIAIJ,
2662: 0,
2663: 0,
2664: MatFindZeroDiagonals_MPIAIJ,
2665: /*80*/ 0,
2666: 0,
2667: 0,
2668: /*83*/ MatLoad_MPIAIJ,
2669: 0,
2670: 0,
2671: 0,
2672: 0,
2673: 0,
2674: /*89*/ MatMatMult_MPIAIJ_MPIAIJ,
2675: MatMatMultSymbolic_MPIAIJ_MPIAIJ,
2676: MatMatMultNumeric_MPIAIJ_MPIAIJ,
2677: MatPtAP_MPIAIJ_MPIAIJ,
2678: MatPtAPSymbolic_MPIAIJ_MPIAIJ,
2679: /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ,
2680: 0,
2681: 0,
2682: 0,
2683: 0,
2684: /*99*/ 0,
2685: 0,
2686: 0,
2687: MatConjugate_MPIAIJ,
2688: 0,
2689: /*104*/MatSetValuesRow_MPIAIJ,
2690: MatRealPart_MPIAIJ,
2691: MatImaginaryPart_MPIAIJ,
2692: 0,
2693: 0,
2694: /*109*/0,
2695: 0,
2696: MatGetRowMin_MPIAIJ,
2697: 0,
2698: MatMissingDiagonal_MPIAIJ,
2699: /*114*/MatGetSeqNonzeroStructure_MPIAIJ,
2700: 0,
2701: MatGetGhosts_MPIAIJ,
2702: 0,
2703: 0,
2704: /*119*/0,
2705: 0,
2706: 0,
2707: 0,
2708: MatGetMultiProcBlock_MPIAIJ,
2709: /*124*/MatFindNonzeroRows_MPIAIJ,
2710: MatGetColumnNorms_MPIAIJ,
2711: MatInvertBlockDiagonal_MPIAIJ,
2712: 0,
2713: MatGetSubMatricesMPI_MPIAIJ,
2714: /*129*/0,
2715: MatTransposeMatMult_MPIAIJ_MPIAIJ,
2716: MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ,
2717: MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ,
2718: 0,
2719: /*134*/0,
2720: 0,
2721: 0,
2722: 0,
2723: 0,
2724: /*139*/0,
2725: 0,
2726: 0,
2727: MatFDColoringSetUp_MPIXAIJ,
2728: MatFindOffBlockDiagonalEntries_MPIAIJ,
2729: /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ
2730: };
2732: /* ----------------------------------------------------------------------------------------*/
2736: PetscErrorCode MatStoreValues_MPIAIJ(Mat mat)
2737: {
2738: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
2742: MatStoreValues(aij->A);
2743: MatStoreValues(aij->B);
2744: return(0);
2745: }
2749: PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat)
2750: {
2751: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
2755: MatRetrieveValues(aij->A);
2756: MatRetrieveValues(aij->B);
2757: return(0);
2758: }
2762: PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
2763: {
2764: Mat_MPIAIJ *b;
2768: PetscLayoutSetUp(B->rmap);
2769: PetscLayoutSetUp(B->cmap);
2770: b = (Mat_MPIAIJ*)B->data;
2772: if (!B->preallocated) {
2773: /* Explicitly create 2 MATSEQAIJ matrices. */
2774: MatCreate(PETSC_COMM_SELF,&b->A);
2775: MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
2776: MatSetBlockSizesFromMats(b->A,B,B);
2777: MatSetType(b->A,MATSEQAIJ);
2778: PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
2779: MatCreate(PETSC_COMM_SELF,&b->B);
2780: MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);
2781: MatSetBlockSizesFromMats(b->B,B,B);
2782: MatSetType(b->B,MATSEQAIJ);
2783: PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);
2784: }
2786: MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);
2787: MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);
2788: B->preallocated = PETSC_TRUE;
2789: return(0);
2790: }
2794: PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
2795: {
2796: Mat mat;
2797: Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data;
2801: *newmat = 0;
2802: MatCreate(PetscObjectComm((PetscObject)matin),&mat);
2803: MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
2804: MatSetBlockSizesFromMats(mat,matin,matin);
2805: MatSetType(mat,((PetscObject)matin)->type_name);
2806: PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));
2807: a = (Mat_MPIAIJ*)mat->data;
2809: mat->factortype = matin->factortype;
2810: mat->assembled = PETSC_TRUE;
2811: mat->insertmode = NOT_SET_VALUES;
2812: mat->preallocated = PETSC_TRUE;
2814: a->size = oldmat->size;
2815: a->rank = oldmat->rank;
2816: a->donotstash = oldmat->donotstash;
2817: a->roworiented = oldmat->roworiented;
2818: a->rowindices = 0;
2819: a->rowvalues = 0;
2820: a->getrowactive = PETSC_FALSE;
2822: PetscLayoutReference(matin->rmap,&mat->rmap);
2823: PetscLayoutReference(matin->cmap,&mat->cmap);
2825: if (oldmat->colmap) {
2826: #if defined(PETSC_USE_CTABLE)
2827: PetscTableCreateCopy(oldmat->colmap,&a->colmap);
2828: #else
2829: PetscMalloc1(mat->cmap->N,&a->colmap);
2830: PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));
2831: PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));
2832: #endif
2833: } else a->colmap = 0;
2834: if (oldmat->garray) {
2835: PetscInt len;
2836: len = oldmat->B->cmap->n;
2837: PetscMalloc1(len+1,&a->garray);
2838: PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
2839: if (len) { PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt)); }
2840: } else a->garray = 0;
2842: VecDuplicate(oldmat->lvec,&a->lvec);
2843: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
2844: VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
2845: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);
2846: MatDuplicate(oldmat->A,cpvalues,&a->A);
2847: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
2848: MatDuplicate(oldmat->B,cpvalues,&a->B);
2849: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
2850: PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
2851: *newmat = mat;
2852: return(0);
2853: }
2859: PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer)
2860: {
2861: PetscScalar *vals,*svals;
2862: MPI_Comm comm;
2864: PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag;
2865: PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0;
2866: PetscInt header[4],*rowlengths = 0,M,N,m,*cols;
2867: PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols;
2868: PetscInt cend,cstart,n,*rowners;
2869: int fd;
2870: PetscInt bs = newMat->rmap->bs;
2873: /* force binary viewer to load .info file if it has not yet done so */
2874: PetscViewerSetUp(viewer);
2875: PetscObjectGetComm((PetscObject)viewer,&comm);
2876: MPI_Comm_size(comm,&size);
2877: MPI_Comm_rank(comm,&rank);
2878: PetscViewerBinaryGetDescriptor(viewer,&fd);
2879: if (!rank) {
2880: PetscBinaryRead(fd,(char*)header,4,PETSC_INT);
2881: if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
2882: if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as MPIAIJ");
2883: }
2885: PetscOptionsBegin(comm,NULL,"Options for loading MPIAIJ matrix","Mat");
2886: PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
2887: PetscOptionsEnd();
2888: if (bs < 0) bs = 1;
2890: MPI_Bcast(header+1,3,MPIU_INT,0,comm);
2891: M = header[1]; N = header[2];
2893: /* If global sizes are set, check if they are consistent with that given in the file */
2894: if (newMat->rmap->N >= 0 && newMat->rmap->N != M) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of rows:Matrix in file has (%D) and input matrix has (%D)",newMat->rmap->N,M);
2895: if (newMat->cmap->N >=0 && newMat->cmap->N != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of cols:Matrix in file has (%D) and input matrix has (%D)",newMat->cmap->N,N);
2897: /* determine ownership of all (block) rows */
2898: if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs);
2899: if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */
2900: else m = newMat->rmap->n; /* Set by user */
2902: PetscMalloc1(size+1,&rowners);
2903: MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);
2905: /* First process needs enough room for process with most rows */
2906: if (!rank) {
2907: mmax = rowners[1];
2908: for (i=2; i<=size; i++) {
2909: mmax = PetscMax(mmax, rowners[i]);
2910: }
2911: } else mmax = -1; /* unused, but compilers complain */
2913: rowners[0] = 0;
2914: for (i=2; i<=size; i++) {
2915: rowners[i] += rowners[i-1];
2916: }
2917: rstart = rowners[rank];
2918: rend = rowners[rank+1];
2920: /* distribute row lengths to all processors */
2921: PetscMalloc2(m,&ourlens,m,&offlens);
2922: if (!rank) {
2923: PetscBinaryRead(fd,ourlens,m,PETSC_INT);
2924: PetscMalloc1(mmax,&rowlengths);
2925: PetscCalloc1(size,&procsnz);
2926: for (j=0; j<m; j++) {
2927: procsnz[0] += ourlens[j];
2928: }
2929: for (i=1; i<size; i++) {
2930: PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);
2931: /* calculate the number of nonzeros on each processor */
2932: for (j=0; j<rowners[i+1]-rowners[i]; j++) {
2933: procsnz[i] += rowlengths[j];
2934: }
2935: MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);
2936: }
2937: PetscFree(rowlengths);
2938: } else {
2939: MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);
2940: }
2942: if (!rank) {
2943: /* determine max buffer needed and allocate it */
2944: maxnz = 0;
2945: for (i=0; i<size; i++) {
2946: maxnz = PetscMax(maxnz,procsnz[i]);
2947: }
2948: PetscMalloc1(maxnz,&cols);
2950: /* read in my part of the matrix column indices */
2951: nz = procsnz[0];
2952: PetscMalloc1(nz,&mycols);
2953: PetscBinaryRead(fd,mycols,nz,PETSC_INT);
2955: /* read in every one elses and ship off */
2956: for (i=1; i<size; i++) {
2957: nz = procsnz[i];
2958: PetscBinaryRead(fd,cols,nz,PETSC_INT);
2959: MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);
2960: }
2961: PetscFree(cols);
2962: } else {
2963: /* determine buffer space needed for message */
2964: nz = 0;
2965: for (i=0; i<m; i++) {
2966: nz += ourlens[i];
2967: }
2968: PetscMalloc1(nz,&mycols);
2970: /* receive message of column indices*/
2971: MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);
2972: }
2974: /* determine column ownership if matrix is not square */
2975: if (N != M) {
2976: if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank);
2977: else n = newMat->cmap->n;
2978: MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);
2979: cstart = cend - n;
2980: } else {
2981: cstart = rstart;
2982: cend = rend;
2983: n = cend - cstart;
2984: }
2986: /* loop over local rows, determining number of off diagonal entries */
2987: PetscMemzero(offlens,m*sizeof(PetscInt));
2988: jj = 0;
2989: for (i=0; i<m; i++) {
2990: for (j=0; j<ourlens[i]; j++) {
2991: if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++;
2992: jj++;
2993: }
2994: }
2996: for (i=0; i<m; i++) {
2997: ourlens[i] -= offlens[i];
2998: }
2999: MatSetSizes(newMat,m,n,M,N);
3001: if (bs > 1) {MatSetBlockSize(newMat,bs);}
3003: MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);
3005: for (i=0; i<m; i++) {
3006: ourlens[i] += offlens[i];
3007: }
3009: if (!rank) {
3010: PetscMalloc1(maxnz+1,&vals);
3012: /* read in my part of the matrix numerical values */
3013: nz = procsnz[0];
3014: PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
3016: /* insert into matrix */
3017: jj = rstart;
3018: smycols = mycols;
3019: svals = vals;
3020: for (i=0; i<m; i++) {
3021: MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
3022: smycols += ourlens[i];
3023: svals += ourlens[i];
3024: jj++;
3025: }
3027: /* read in other processors and ship out */
3028: for (i=1; i<size; i++) {
3029: nz = procsnz[i];
3030: PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
3031: MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);
3032: }
3033: PetscFree(procsnz);
3034: } else {
3035: /* receive numeric values */
3036: PetscMalloc1(nz+1,&vals);
3038: /* receive message of values*/
3039: MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);
3041: /* insert into matrix */
3042: jj = rstart;
3043: smycols = mycols;
3044: svals = vals;
3045: for (i=0; i<m; i++) {
3046: MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
3047: smycols += ourlens[i];
3048: svals += ourlens[i];
3049: jj++;
3050: }
3051: }
3052: PetscFree2(ourlens,offlens);
3053: PetscFree(vals);
3054: PetscFree(mycols);
3055: PetscFree(rowners);
3056: MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);
3057: MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);
3058: return(0);
3059: }
3063: /* TODO: Not scalable because of ISAllGather() unless getting all columns. */
3064: PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
3065: {
3067: IS iscol_local;
3068: PetscInt csize;
3071: ISGetLocalSize(iscol,&csize);
3072: if (call == MAT_REUSE_MATRIX) {
3073: PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
3074: if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3075: } else {
3076: /* check if we are grabbing all columns*/
3077: PetscBool isstride;
3078: PetscMPIInt lisstride = 0,gisstride;
3079: PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&isstride);
3080: if (isstride) {
3081: PetscInt start,len,mstart,mlen;
3082: ISStrideGetInfo(iscol,&start,NULL);
3083: ISGetLocalSize(iscol,&len);
3084: MatGetOwnershipRangeColumn(mat,&mstart,&mlen);
3085: if (mstart == start && mlen-mstart == len) lisstride = 1;
3086: }
3087: MPIU_Allreduce(&lisstride,&gisstride,1,MPI_INT,MPI_MIN,PetscObjectComm((PetscObject)mat));
3088: if (gisstride) {
3089: PetscInt N;
3090: MatGetSize(mat,NULL,&N);
3091: ISCreateStride(PetscObjectComm((PetscObject)mat),N,0,1,&iscol_local);
3092: ISSetIdentity(iscol_local);
3093: PetscInfo(mat,"Optimizing for obtaining all columns of the matrix; skipping ISAllGather()\n");
3094: } else {
3095: PetscInt cbs;
3096: ISGetBlockSize(iscol,&cbs);
3097: ISAllGather(iscol,&iscol_local);
3098: ISSetBlockSize(iscol_local,cbs);
3099: }
3100: }
3101: MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);
3102: if (call == MAT_INITIAL_MATRIX) {
3103: PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
3104: ISDestroy(&iscol_local);
3105: }
3106: return(0);
3107: }
3109: extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*);
3112: /*
3113: Not great since it makes two copies of the submatrix, first an SeqAIJ
3114: in local and then by concatenating the local matrices the end result.
3115: Writing it directly would be much like MatGetSubMatrices_MPIAIJ()
3117: Note: This requires a sequential iscol with all indices.
3118: */
3119: PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat)
3120: {
3122: PetscMPIInt rank,size;
3123: PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs;
3124: PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol;
3125: PetscBool allcolumns, colflag;
3126: Mat M,Mreuse;
3127: MatScalar *vwork,*aa;
3128: MPI_Comm comm;
3129: Mat_SeqAIJ *aij;
3132: PetscObjectGetComm((PetscObject)mat,&comm);
3133: MPI_Comm_rank(comm,&rank);
3134: MPI_Comm_size(comm,&size);
3136: ISIdentity(iscol,&colflag);
3137: ISGetLocalSize(iscol,&ncol);
3138: if (colflag && ncol == mat->cmap->N) {
3139: allcolumns = PETSC_TRUE;
3140: PetscInfo(mat,"Optimizing for obtaining all columns of the matrix\n");
3141: } else {
3142: allcolumns = PETSC_FALSE;
3143: }
3144: if (call == MAT_REUSE_MATRIX) {
3145: PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);
3146: if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3147: MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);
3148: } else {
3149: MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);
3150: }
3152: /*
3153: m - number of local rows
3154: n - number of columns (same on all processors)
3155: rstart - first row in new global matrix generated
3156: */
3157: MatGetSize(Mreuse,&m,&n);
3158: MatGetBlockSizes(Mreuse,&bs,&cbs);
3159: if (call == MAT_INITIAL_MATRIX) {
3160: aij = (Mat_SeqAIJ*)(Mreuse)->data;
3161: ii = aij->i;
3162: jj = aij->j;
3164: /*
3165: Determine the number of non-zeros in the diagonal and off-diagonal
3166: portions of the matrix in order to do correct preallocation
3167: */
3169: /* first get start and end of "diagonal" columns */
3170: if (csize == PETSC_DECIDE) {
3171: ISGetSize(isrow,&mglobal);
3172: if (mglobal == n) { /* square matrix */
3173: nlocal = m;
3174: } else {
3175: nlocal = n/size + ((n % size) > rank);
3176: }
3177: } else {
3178: nlocal = csize;
3179: }
3180: MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
3181: rstart = rend - nlocal;
3182: 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);
3184: /* next, compute all the lengths */
3185: PetscMalloc1(2*m+1,&dlens);
3186: olens = dlens + m;
3187: for (i=0; i<m; i++) {
3188: jend = ii[i+1] - ii[i];
3189: olen = 0;
3190: dlen = 0;
3191: for (j=0; j<jend; j++) {
3192: if (*jj < rstart || *jj >= rend) olen++;
3193: else dlen++;
3194: jj++;
3195: }
3196: olens[i] = olen;
3197: dlens[i] = dlen;
3198: }
3199: MatCreate(comm,&M);
3200: MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);
3201: MatSetBlockSizes(M,bs,cbs);
3202: MatSetType(M,((PetscObject)mat)->type_name);
3203: MatMPIAIJSetPreallocation(M,0,dlens,0,olens);
3204: PetscFree(dlens);
3205: } else {
3206: PetscInt ml,nl;
3208: M = *newmat;
3209: MatGetLocalSize(M,&ml,&nl);
3210: if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
3211: MatZeroEntries(M);
3212: /*
3213: The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
3214: rather than the slower MatSetValues().
3215: */
3216: M->was_assembled = PETSC_TRUE;
3217: M->assembled = PETSC_FALSE;
3218: }
3219: MatGetOwnershipRange(M,&rstart,&rend);
3220: aij = (Mat_SeqAIJ*)(Mreuse)->data;
3221: ii = aij->i;
3222: jj = aij->j;
3223: aa = aij->a;
3224: for (i=0; i<m; i++) {
3225: row = rstart + i;
3226: nz = ii[i+1] - ii[i];
3227: cwork = jj; jj += nz;
3228: vwork = aa; aa += nz;
3229: MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);
3230: }
3232: MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
3233: MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
3234: *newmat = M;
3236: /* save submatrix used in processor for next request */
3237: if (call == MAT_INITIAL_MATRIX) {
3238: PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);
3239: MatDestroy(&Mreuse);
3240: }
3241: return(0);
3242: }
3246: PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[])
3247: {
3248: PetscInt m,cstart, cend,j,nnz,i,d;
3249: PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii;
3250: const PetscInt *JJ;
3251: PetscScalar *values;
3255: if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]);
3257: PetscLayoutSetUp(B->rmap);
3258: PetscLayoutSetUp(B->cmap);
3259: m = B->rmap->n;
3260: cstart = B->cmap->rstart;
3261: cend = B->cmap->rend;
3262: rstart = B->rmap->rstart;
3264: PetscMalloc2(m,&d_nnz,m,&o_nnz);
3266: #if defined(PETSC_USE_DEBUGGING)
3267: for (i=0; i<m; i++) {
3268: nnz = Ii[i+1]- Ii[i];
3269: JJ = J + Ii[i];
3270: if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz);
3271: if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j);
3272: if (nnz && (JJ[nnz-1] >= B->cmap->N) SETERRRQ3(PETSC_ERR_ARG_WRONGSTATE,"Row %D ends with too large a column index %D (max allowed %D)",i,JJ[nnz-1],B->cmap->N);
3273: }
3274: #endif
3276: for (i=0; i<m; i++) {
3277: nnz = Ii[i+1]- Ii[i];
3278: JJ = J + Ii[i];
3279: nnz_max = PetscMax(nnz_max,nnz);
3280: d = 0;
3281: for (j=0; j<nnz; j++) {
3282: if (cstart <= JJ[j] && JJ[j] < cend) d++;
3283: }
3284: d_nnz[i] = d;
3285: o_nnz[i] = nnz - d;
3286: }
3287: MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);
3288: PetscFree2(d_nnz,o_nnz);
3290: if (v) values = (PetscScalar*)v;
3291: else {
3292: PetscCalloc1(nnz_max+1,&values);
3293: }
3295: for (i=0; i<m; i++) {
3296: ii = i + rstart;
3297: nnz = Ii[i+1]- Ii[i];
3298: MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);
3299: }
3300: MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
3301: MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
3303: if (!v) {
3304: PetscFree(values);
3305: }
3306: MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
3307: return(0);
3308: }
3312: /*@
3313: MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format
3314: (the default parallel PETSc format).
3316: Collective on MPI_Comm
3318: Input Parameters:
3319: + B - the matrix
3320: . i - the indices into j for the start of each local row (starts with zero)
3321: . j - the column indices for each local row (starts with zero)
3322: - v - optional values in the matrix
3324: Level: developer
3326: Notes:
3327: The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
3328: thus you CANNOT change the matrix entries by changing the values of a[] after you have
3329: called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.
3331: The i and j indices are 0 based, and i indices are indices corresponding to the local j array.
3333: The format which is used for the sparse matrix input, is equivalent to a
3334: row-major ordering.. i.e for the following matrix, the input data expected is
3335: as shown
3337: $ 1 0 0
3338: $ 2 0 3 P0
3339: $ -------
3340: $ 4 5 6 P1
3341: $
3342: $ Process0 [P0]: rows_owned=[0,1]
3343: $ i = {0,1,3} [size = nrow+1 = 2+1]
3344: $ j = {0,0,2} [size = 3]
3345: $ v = {1,2,3} [size = 3]
3346: $
3347: $ Process1 [P1]: rows_owned=[2]
3348: $ i = {0,3} [size = nrow+1 = 1+1]
3349: $ j = {0,1,2} [size = 3]
3350: $ v = {4,5,6} [size = 3]
3352: .keywords: matrix, aij, compressed row, sparse, parallel
3354: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ,
3355: MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays()
3356: @*/
3357: PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
3358: {
3362: PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));
3363: return(0);
3364: }
3368: /*@C
3369: MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format
3370: (the default parallel PETSc format). For good matrix assembly performance
3371: the user should preallocate the matrix storage by setting the parameters
3372: d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately,
3373: performance can be increased by more than a factor of 50.
3375: Collective on MPI_Comm
3377: Input Parameters:
3378: + B - the matrix
3379: . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix
3380: (same value is used for all local rows)
3381: . d_nnz - array containing the number of nonzeros in the various rows of the
3382: DIAGONAL portion of the local submatrix (possibly different for each row)
3383: or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure.
3384: The size of this array is equal to the number of local rows, i.e 'm'.
3385: For matrices that will be factored, you must leave room for (and set)
3386: the diagonal entry even if it is zero.
3387: . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local
3388: submatrix (same value is used for all local rows).
3389: - o_nnz - array containing the number of nonzeros in the various rows of the
3390: OFF-DIAGONAL portion of the local submatrix (possibly different for
3391: each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero
3392: structure. The size of this array is equal to the number
3393: of local rows, i.e 'm'.
3395: If the *_nnz parameter is given then the *_nz parameter is ignored
3397: The AIJ format (also called the Yale sparse matrix format or
3398: compressed row storage (CSR)), is fully compatible with standard Fortran 77
3399: storage. The stored row and column indices begin with zero.
3400: See Users-Manual: ch_mat for details.
3402: The parallel matrix is partitioned such that the first m0 rows belong to
3403: process 0, the next m1 rows belong to process 1, the next m2 rows belong
3404: to process 2 etc.. where m0,m1,m2... are the input parameter 'm'.
3406: The DIAGONAL portion of the local submatrix of a processor can be defined
3407: as the submatrix which is obtained by extraction the part corresponding to
3408: the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the
3409: first row that belongs to the processor, r2 is the last row belonging to
3410: the this processor, and c1-c2 is range of indices of the local part of a
3411: vector suitable for applying the matrix to. This is an mxn matrix. In the
3412: common case of a square matrix, the row and column ranges are the same and
3413: the DIAGONAL part is also square. The remaining portion of the local
3414: submatrix (mxN) constitute the OFF-DIAGONAL portion.
3416: If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.
3418: You can call MatGetInfo() to get information on how effective the preallocation was;
3419: for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
3420: You can also run with the option -info and look for messages with the string
3421: malloc in them to see if additional memory allocation was needed.
3423: Example usage:
3425: Consider the following 8x8 matrix with 34 non-zero values, that is
3426: assembled across 3 processors. Lets assume that proc0 owns 3 rows,
3427: proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
3428: as follows:
3430: .vb
3431: 1 2 0 | 0 3 0 | 0 4
3432: Proc0 0 5 6 | 7 0 0 | 8 0
3433: 9 0 10 | 11 0 0 | 12 0
3434: -------------------------------------
3435: 13 0 14 | 15 16 17 | 0 0
3436: Proc1 0 18 0 | 19 20 21 | 0 0
3437: 0 0 0 | 22 23 0 | 24 0
3438: -------------------------------------
3439: Proc2 25 26 27 | 0 0 28 | 29 0
3440: 30 0 0 | 31 32 33 | 0 34
3441: .ve
3443: This can be represented as a collection of submatrices as:
3445: .vb
3446: A B C
3447: D E F
3448: G H I
3449: .ve
3451: Where the submatrices A,B,C are owned by proc0, D,E,F are
3452: owned by proc1, G,H,I are owned by proc2.
3454: The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
3455: The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
3456: The 'M','N' parameters are 8,8, and have the same values on all procs.
3458: The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
3459: submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
3460: corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
3461: Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
3462: part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
3463: matrix, ans [DF] as another SeqAIJ matrix.
3465: When d_nz, o_nz parameters are specified, d_nz storage elements are
3466: allocated for every row of the local diagonal submatrix, and o_nz
3467: storage locations are allocated for every row of the OFF-DIAGONAL submat.
3468: One way to choose d_nz and o_nz is to use the max nonzerors per local
3469: rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
3470: In this case, the values of d_nz,o_nz are:
3471: .vb
3472: proc0 : dnz = 2, o_nz = 2
3473: proc1 : dnz = 3, o_nz = 2
3474: proc2 : dnz = 1, o_nz = 4
3475: .ve
3476: We are allocating m*(d_nz+o_nz) storage locations for every proc. This
3477: translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
3478: for proc3. i.e we are using 12+15+10=37 storage locations to store
3479: 34 values.
3481: When d_nnz, o_nnz parameters are specified, the storage is specified
3482: for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
3483: In the above case the values for d_nnz,o_nnz are:
3484: .vb
3485: proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
3486: proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
3487: proc2: d_nnz = [1,1] and o_nnz = [4,4]
3488: .ve
3489: Here the space allocated is sum of all the above values i.e 34, and
3490: hence pre-allocation is perfect.
3492: Level: intermediate
3494: .keywords: matrix, aij, compressed row, sparse, parallel
3496: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(),
3497: MPIAIJ, MatGetInfo(), PetscSplitOwnership()
3498: @*/
3499: PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
3500: {
3506: PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));
3507: return(0);
3508: }
3512: /*@
3513: MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard
3514: CSR format the local rows.
3516: Collective on MPI_Comm
3518: Input Parameters:
3519: + comm - MPI communicator
3520: . m - number of local rows (Cannot be PETSC_DECIDE)
3521: . n - This value should be the same as the local size used in creating the
3522: x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
3523: calculated if N is given) For square matrices n is almost always m.
3524: . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
3525: . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
3526: . i - row indices
3527: . j - column indices
3528: - a - matrix values
3530: Output Parameter:
3531: . mat - the matrix
3533: Level: intermediate
3535: Notes:
3536: The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
3537: thus you CANNOT change the matrix entries by changing the values of a[] after you have
3538: called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.
3540: The i and j indices are 0 based, and i indices are indices corresponding to the local j array.
3542: The format which is used for the sparse matrix input, is equivalent to a
3543: row-major ordering.. i.e for the following matrix, the input data expected is
3544: as shown
3546: $ 1 0 0
3547: $ 2 0 3 P0
3548: $ -------
3549: $ 4 5 6 P1
3550: $
3551: $ Process0 [P0]: rows_owned=[0,1]
3552: $ i = {0,1,3} [size = nrow+1 = 2+1]
3553: $ j = {0,0,2} [size = 3]
3554: $ v = {1,2,3} [size = 3]
3555: $
3556: $ Process1 [P1]: rows_owned=[2]
3557: $ i = {0,3} [size = nrow+1 = 1+1]
3558: $ j = {0,1,2} [size = 3]
3559: $ v = {4,5,6} [size = 3]
3561: .keywords: matrix, aij, compressed row, sparse, parallel
3563: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
3564: MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
3565: @*/
3566: PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat)
3567: {
3571: if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
3572: if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
3573: MatCreate(comm,mat);
3574: MatSetSizes(*mat,m,n,M,N);
3575: /* MatSetBlockSizes(M,bs,cbs); */
3576: MatSetType(*mat,MATMPIAIJ);
3577: MatMPIAIJSetPreallocationCSR(*mat,i,j,a);
3578: return(0);
3579: }
3583: /*@C
3584: MatCreateAIJ - Creates a sparse parallel matrix in AIJ format
3585: (the default parallel PETSc format). For good matrix assembly performance
3586: the user should preallocate the matrix storage by setting the parameters
3587: d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately,
3588: performance can be increased by more than a factor of 50.
3590: Collective on MPI_Comm
3592: Input Parameters:
3593: + comm - MPI communicator
3594: . m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
3595: This value should be the same as the local size used in creating the
3596: y vector for the matrix-vector product y = Ax.
3597: . n - This value should be the same as the local size used in creating the
3598: x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
3599: calculated if N is given) For square matrices n is almost always m.
3600: . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
3601: . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
3602: . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix
3603: (same value is used for all local rows)
3604: . d_nnz - array containing the number of nonzeros in the various rows of the
3605: DIAGONAL portion of the local submatrix (possibly different for each row)
3606: or NULL, if d_nz is used to specify the nonzero structure.
3607: The size of this array is equal to the number of local rows, i.e 'm'.
3608: . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local
3609: submatrix (same value is used for all local rows).
3610: - o_nnz - array containing the number of nonzeros in the various rows of the
3611: OFF-DIAGONAL portion of the local submatrix (possibly different for
3612: each row) or NULL, if o_nz is used to specify the nonzero
3613: structure. The size of this array is equal to the number
3614: of local rows, i.e 'm'.
3616: Output Parameter:
3617: . A - the matrix
3619: It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
3620: MatXXXXSetPreallocation() paradgm instead of this routine directly.
3621: [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]
3623: Notes:
3624: If the *_nnz parameter is given then the *_nz parameter is ignored
3626: m,n,M,N parameters specify the size of the matrix, and its partitioning across
3627: processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate
3628: storage requirements for this matrix.
3630: If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one
3631: processor than it must be used on all processors that share the object for
3632: that argument.
3634: The user MUST specify either the local or global matrix dimensions
3635: (possibly both).
3637: The parallel matrix is partitioned across processors such that the
3638: first m0 rows belong to process 0, the next m1 rows belong to
3639: process 1, the next m2 rows belong to process 2 etc.. where
3640: m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores
3641: values corresponding to [m x N] submatrix.
3643: The columns are logically partitioned with the n0 columns belonging
3644: to 0th partition, the next n1 columns belonging to the next
3645: partition etc.. where n0,n1,n2... are the input parameter 'n'.
3647: The DIAGONAL portion of the local submatrix on any given processor
3648: is the submatrix corresponding to the rows and columns m,n
3649: corresponding to the given processor. i.e diagonal matrix on
3650: process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1]
3651: etc. The remaining portion of the local submatrix [m x (N-n)]
3652: constitute the OFF-DIAGONAL portion. The example below better
3653: illustrates this concept.
3655: For a square global matrix we define each processor's diagonal portion
3656: to be its local rows and the corresponding columns (a square submatrix);
3657: each processor's off-diagonal portion encompasses the remainder of the
3658: local matrix (a rectangular submatrix).
3660: If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.
3662: When calling this routine with a single process communicator, a matrix of
3663: type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this
3664: type of communicator, use the construction mechanism
3665: .vb
3666: MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...);
3667: .ve
3669: By default, this format uses inodes (identical nodes) when possible.
3670: We search for consecutive rows with the same nonzero structure, thereby
3671: reusing matrix information to achieve increased efficiency.
3673: Options Database Keys:
3674: + -mat_no_inode - Do not use inodes
3675: . -mat_inode_limit <limit> - Sets inode limit (max limit=5)
3676: - -mat_aij_oneindex - Internally use indexing starting at 1
3677: rather than 0. Note that when calling MatSetValues(),
3678: the user still MUST index entries starting at 0!
3681: Example usage:
3683: Consider the following 8x8 matrix with 34 non-zero values, that is
3684: assembled across 3 processors. Lets assume that proc0 owns 3 rows,
3685: proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
3686: as follows
3688: .vb
3689: 1 2 0 | 0 3 0 | 0 4
3690: Proc0 0 5 6 | 7 0 0 | 8 0
3691: 9 0 10 | 11 0 0 | 12 0
3692: -------------------------------------
3693: 13 0 14 | 15 16 17 | 0 0
3694: Proc1 0 18 0 | 19 20 21 | 0 0
3695: 0 0 0 | 22 23 0 | 24 0
3696: -------------------------------------
3697: Proc2 25 26 27 | 0 0 28 | 29 0
3698: 30 0 0 | 31 32 33 | 0 34
3699: .ve
3701: This can be represented as a collection of submatrices as
3703: .vb
3704: A B C
3705: D E F
3706: G H I
3707: .ve
3709: Where the submatrices A,B,C are owned by proc0, D,E,F are
3710: owned by proc1, G,H,I are owned by proc2.
3712: The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
3713: The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
3714: The 'M','N' parameters are 8,8, and have the same values on all procs.
3716: The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
3717: submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
3718: corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
3719: Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
3720: part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
3721: matrix, ans [DF] as another SeqAIJ matrix.
3723: When d_nz, o_nz parameters are specified, d_nz storage elements are
3724: allocated for every row of the local diagonal submatrix, and o_nz
3725: storage locations are allocated for every row of the OFF-DIAGONAL submat.
3726: One way to choose d_nz and o_nz is to use the max nonzerors per local
3727: rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
3728: In this case, the values of d_nz,o_nz are
3729: .vb
3730: proc0 : dnz = 2, o_nz = 2
3731: proc1 : dnz = 3, o_nz = 2
3732: proc2 : dnz = 1, o_nz = 4
3733: .ve
3734: We are allocating m*(d_nz+o_nz) storage locations for every proc. This
3735: translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
3736: for proc3. i.e we are using 12+15+10=37 storage locations to store
3737: 34 values.
3739: When d_nnz, o_nnz parameters are specified, the storage is specified
3740: for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
3741: In the above case the values for d_nnz,o_nnz are
3742: .vb
3743: proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
3744: proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
3745: proc2: d_nnz = [1,1] and o_nnz = [4,4]
3746: .ve
3747: Here the space allocated is sum of all the above values i.e 34, and
3748: hence pre-allocation is perfect.
3750: Level: intermediate
3752: .keywords: matrix, aij, compressed row, sparse, parallel
3754: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
3755: MPIAIJ, MatCreateMPIAIJWithArrays()
3756: @*/
3757: 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)
3758: {
3760: PetscMPIInt size;
3763: MatCreate(comm,A);
3764: MatSetSizes(*A,m,n,M,N);
3765: MPI_Comm_size(comm,&size);
3766: if (size > 1) {
3767: MatSetType(*A,MATMPIAIJ);
3768: MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);
3769: } else {
3770: MatSetType(*A,MATSEQAIJ);
3771: MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);
3772: }
3773: return(0);
3774: }
3778: PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[])
3779: {
3780: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
3781: PetscBool flg;
3783:
3785: PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&flg);
3786: if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MPIAIJ matrix as input");
3787: if (Ad) *Ad = a->A;
3788: if (Ao) *Ao = a->B;
3789: if (colmap) *colmap = a->garray;
3790: return(0);
3791: }
3795: PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring)
3796: {
3798: PetscInt i;
3799: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
3802: if (coloring->ctype == IS_COLORING_GLOBAL) {
3803: ISColoringValue *allcolors,*colors;
3804: ISColoring ocoloring;
3806: /* set coloring for diagonal portion */
3807: MatSetColoring_SeqAIJ(a->A,coloring);
3809: /* set coloring for off-diagonal portion */
3810: ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);
3811: PetscMalloc1(a->B->cmap->n+1,&colors);
3812: for (i=0; i<a->B->cmap->n; i++) {
3813: colors[i] = allcolors[a->garray[i]];
3814: }
3815: PetscFree(allcolors);
3816: ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);
3817: MatSetColoring_SeqAIJ(a->B,ocoloring);
3818: ISColoringDestroy(&ocoloring);
3819: } else if (coloring->ctype == IS_COLORING_GHOSTED) {
3820: ISColoringValue *colors;
3821: PetscInt *larray;
3822: ISColoring ocoloring;
3824: /* set coloring for diagonal portion */
3825: PetscMalloc1(a->A->cmap->n+1,&larray);
3826: for (i=0; i<a->A->cmap->n; i++) {
3827: larray[i] = i + A->cmap->rstart;
3828: }
3829: ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);
3830: PetscMalloc1(a->A->cmap->n+1,&colors);
3831: for (i=0; i<a->A->cmap->n; i++) {
3832: colors[i] = coloring->colors[larray[i]];
3833: }
3834: PetscFree(larray);
3835: ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);
3836: MatSetColoring_SeqAIJ(a->A,ocoloring);
3837: ISColoringDestroy(&ocoloring);
3839: /* set coloring for off-diagonal portion */
3840: PetscMalloc1(a->B->cmap->n+1,&larray);
3841: ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);
3842: PetscMalloc1(a->B->cmap->n+1,&colors);
3843: for (i=0; i<a->B->cmap->n; i++) {
3844: colors[i] = coloring->colors[larray[i]];
3845: }
3846: PetscFree(larray);
3847: ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);
3848: MatSetColoring_SeqAIJ(a->B,ocoloring);
3849: ISColoringDestroy(&ocoloring);
3850: } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype);
3851: return(0);
3852: }
3856: PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues)
3857: {
3858: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
3862: MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);
3863: MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);
3864: return(0);
3865: }
3869: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
3870: {
3872: PetscInt m,N,i,rstart,nnz,Ii;
3873: PetscInt *indx;
3874: PetscScalar *values;
3877: MatGetSize(inmat,&m,&N);
3878: if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
3879: PetscInt *dnz,*onz,sum,bs,cbs;
3881: if (n == PETSC_DECIDE) {
3882: PetscSplitOwnership(comm,&n,&N);
3883: }
3884: /* Check sum(n) = N */
3885: MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);
3886: if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N);
3888: MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);
3889: rstart -= m;
3891: MatPreallocateInitialize(comm,m,n,dnz,onz);
3892: for (i=0; i<m; i++) {
3893: MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);
3894: MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);
3895: MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);
3896: }
3898: MatCreate(comm,outmat);
3899: MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
3900: MatGetBlockSizes(inmat,&bs,&cbs);
3901: MatSetBlockSizes(*outmat,bs,cbs);
3902: MatSetType(*outmat,MATMPIAIJ);
3903: MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);
3904: MatPreallocateFinalize(dnz,onz);
3905: }
3907: /* numeric phase */
3908: MatGetOwnershipRange(*outmat,&rstart,NULL);
3909: for (i=0; i<m; i++) {
3910: MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
3911: Ii = i + rstart;
3912: MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
3913: MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
3914: }
3915: MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
3916: MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
3917: return(0);
3918: }
3922: PetscErrorCode MatFileSplit(Mat A,char *outfile)
3923: {
3924: PetscErrorCode ierr;
3925: PetscMPIInt rank;
3926: PetscInt m,N,i,rstart,nnz;
3927: size_t len;
3928: const PetscInt *indx;
3929: PetscViewer out;
3930: char *name;
3931: Mat B;
3932: const PetscScalar *values;
3935: MatGetLocalSize(A,&m,0);
3936: MatGetSize(A,0,&N);
3937: /* Should this be the type of the diagonal block of A? */
3938: MatCreate(PETSC_COMM_SELF,&B);
3939: MatSetSizes(B,m,N,m,N);
3940: MatSetBlockSizesFromMats(B,A,A);
3941: MatSetType(B,MATSEQAIJ);
3942: MatSeqAIJSetPreallocation(B,0,NULL);
3943: MatGetOwnershipRange(A,&rstart,0);
3944: for (i=0; i<m; i++) {
3945: MatGetRow(A,i+rstart,&nnz,&indx,&values);
3946: MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);
3947: MatRestoreRow(A,i+rstart,&nnz,&indx,&values);
3948: }
3949: MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
3950: MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
3952: MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);
3953: PetscStrlen(outfile,&len);
3954: PetscMalloc1(len+5,&name);
3955: sprintf(name,"%s.%d",outfile,rank);
3956: PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);
3957: PetscFree(name);
3958: MatView(B,out);
3959: PetscViewerDestroy(&out);
3960: MatDestroy(&B);
3961: return(0);
3962: }
3964: extern PetscErrorCode MatDestroy_MPIAIJ(Mat);
3967: PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A)
3968: {
3969: PetscErrorCode ierr;
3970: Mat_Merge_SeqsToMPI *merge;
3971: PetscContainer container;
3974: PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);
3975: if (container) {
3976: PetscContainerGetPointer(container,(void**)&merge);
3977: PetscFree(merge->id_r);
3978: PetscFree(merge->len_s);
3979: PetscFree(merge->len_r);
3980: PetscFree(merge->bi);
3981: PetscFree(merge->bj);
3982: PetscFree(merge->buf_ri[0]);
3983: PetscFree(merge->buf_ri);
3984: PetscFree(merge->buf_rj[0]);
3985: PetscFree(merge->buf_rj);
3986: PetscFree(merge->coi);
3987: PetscFree(merge->coj);
3988: PetscFree(merge->owners_co);
3989: PetscLayoutDestroy(&merge->rowmap);
3990: PetscFree(merge);
3991: PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);
3992: }
3993: MatDestroy_MPIAIJ(A);
3994: return(0);
3995: }
3997: #include <../src/mat/utils/freespace.h>
3998: #include <petscbt.h>
4002: PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat)
4003: {
4004: PetscErrorCode ierr;
4005: MPI_Comm comm;
4006: Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data;
4007: PetscMPIInt size,rank,taga,*len_s;
4008: PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj;
4009: PetscInt proc,m;
4010: PetscInt **buf_ri,**buf_rj;
4011: PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj;
4012: PetscInt nrows,**buf_ri_k,**nextrow,**nextai;
4013: MPI_Request *s_waits,*r_waits;
4014: MPI_Status *status;
4015: MatScalar *aa=a->a;
4016: MatScalar **abuf_r,*ba_i;
4017: Mat_Merge_SeqsToMPI *merge;
4018: PetscContainer container;
4021: PetscObjectGetComm((PetscObject)mpimat,&comm);
4022: PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);
4024: MPI_Comm_size(comm,&size);
4025: MPI_Comm_rank(comm,&rank);
4027: PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);
4028: PetscContainerGetPointer(container,(void**)&merge);
4030: bi = merge->bi;
4031: bj = merge->bj;
4032: buf_ri = merge->buf_ri;
4033: buf_rj = merge->buf_rj;
4035: PetscMalloc1(size,&status);
4036: owners = merge->rowmap->range;
4037: len_s = merge->len_s;
4039: /* send and recv matrix values */
4040: /*-----------------------------*/
4041: PetscObjectGetNewTag((PetscObject)mpimat,&taga);
4042: PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);
4044: PetscMalloc1(merge->nsend+1,&s_waits);
4045: for (proc=0,k=0; proc<size; proc++) {
4046: if (!len_s[proc]) continue;
4047: i = owners[proc];
4048: MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);
4049: k++;
4050: }
4052: if (merge->nrecv) {MPI_Waitall(merge->nrecv,r_waits,status);}
4053: if (merge->nsend) {MPI_Waitall(merge->nsend,s_waits,status);}
4054: PetscFree(status);
4056: PetscFree(s_waits);
4057: PetscFree(r_waits);
4059: /* insert mat values of mpimat */
4060: /*----------------------------*/
4061: PetscMalloc1(N,&ba_i);
4062: PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);
4064: for (k=0; k<merge->nrecv; k++) {
4065: buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
4066: nrows = *(buf_ri_k[k]);
4067: nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */
4068: nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */
4069: }
4071: /* set values of ba */
4072: m = merge->rowmap->n;
4073: for (i=0; i<m; i++) {
4074: arow = owners[rank] + i;
4075: bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */
4076: bnzi = bi[i+1] - bi[i];
4077: PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));
4079: /* add local non-zero vals of this proc's seqmat into ba */
4080: anzi = ai[arow+1] - ai[arow];
4081: aj = a->j + ai[arow];
4082: aa = a->a + ai[arow];
4083: nextaj = 0;
4084: for (j=0; nextaj<anzi; j++) {
4085: if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */
4086: ba_i[j] += aa[nextaj++];
4087: }
4088: }
4090: /* add received vals into ba */
4091: for (k=0; k<merge->nrecv; k++) { /* k-th received message */
4092: /* i-th row */
4093: if (i == *nextrow[k]) {
4094: anzi = *(nextai[k]+1) - *nextai[k];
4095: aj = buf_rj[k] + *(nextai[k]);
4096: aa = abuf_r[k] + *(nextai[k]);
4097: nextaj = 0;
4098: for (j=0; nextaj<anzi; j++) {
4099: if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */
4100: ba_i[j] += aa[nextaj++];
4101: }
4102: }
4103: nextrow[k]++; nextai[k]++;
4104: }
4105: }
4106: MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);
4107: }
4108: MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);
4109: MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);
4111: PetscFree(abuf_r[0]);
4112: PetscFree(abuf_r);
4113: PetscFree(ba_i);
4114: PetscFree3(buf_ri_k,nextrow,nextai);
4115: PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);
4116: return(0);
4117: }
4119: extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat);
4123: PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat)
4124: {
4125: PetscErrorCode ierr;
4126: Mat B_mpi;
4127: Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data;
4128: PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri;
4129: PetscInt **buf_rj,**buf_ri,**buf_ri_k;
4130: PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j;
4131: PetscInt len,proc,*dnz,*onz,bs,cbs;
4132: PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0;
4133: PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai;
4134: MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits;
4135: MPI_Status *status;
4136: PetscFreeSpaceList free_space=NULL,current_space=NULL;
4137: PetscBT lnkbt;
4138: Mat_Merge_SeqsToMPI *merge;
4139: PetscContainer container;
4142: PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);
4144: /* make sure it is a PETSc comm */
4145: PetscCommDuplicate(comm,&comm,NULL);
4146: MPI_Comm_size(comm,&size);
4147: MPI_Comm_rank(comm,&rank);
4149: PetscNew(&merge);
4150: PetscMalloc1(size,&status);
4152: /* determine row ownership */
4153: /*---------------------------------------------------------*/
4154: PetscLayoutCreate(comm,&merge->rowmap);
4155: PetscLayoutSetLocalSize(merge->rowmap,m);
4156: PetscLayoutSetSize(merge->rowmap,M);
4157: PetscLayoutSetBlockSize(merge->rowmap,1);
4158: PetscLayoutSetUp(merge->rowmap);
4159: PetscMalloc1(size,&len_si);
4160: PetscMalloc1(size,&merge->len_s);
4162: m = merge->rowmap->n;
4163: owners = merge->rowmap->range;
4165: /* determine the number of messages to send, their lengths */
4166: /*---------------------------------------------------------*/
4167: len_s = merge->len_s;
4169: len = 0; /* length of buf_si[] */
4170: merge->nsend = 0;
4171: for (proc=0; proc<size; proc++) {
4172: len_si[proc] = 0;
4173: if (proc == rank) {
4174: len_s[proc] = 0;
4175: } else {
4176: len_si[proc] = owners[proc+1] - owners[proc] + 1;
4177: len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */
4178: }
4179: if (len_s[proc]) {
4180: merge->nsend++;
4181: nrows = 0;
4182: for (i=owners[proc]; i<owners[proc+1]; i++) {
4183: if (ai[i+1] > ai[i]) nrows++;
4184: }
4185: len_si[proc] = 2*(nrows+1);
4186: len += len_si[proc];
4187: }
4188: }
4190: /* determine the number and length of messages to receive for ij-structure */
4191: /*-------------------------------------------------------------------------*/
4192: PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);
4193: PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);
4195: /* post the Irecv of j-structure */
4196: /*-------------------------------*/
4197: PetscCommGetNewTag(comm,&tagj);
4198: PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);
4200: /* post the Isend of j-structure */
4201: /*--------------------------------*/
4202: PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);
4204: for (proc=0, k=0; proc<size; proc++) {
4205: if (!len_s[proc]) continue;
4206: i = owners[proc];
4207: MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);
4208: k++;
4209: }
4211: /* receives and sends of j-structure are complete */
4212: /*------------------------------------------------*/
4213: if (merge->nrecv) {MPI_Waitall(merge->nrecv,rj_waits,status);}
4214: if (merge->nsend) {MPI_Waitall(merge->nsend,sj_waits,status);}
4216: /* send and recv i-structure */
4217: /*---------------------------*/
4218: PetscCommGetNewTag(comm,&tagi);
4219: PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);
4221: PetscMalloc1(len+1,&buf_s);
4222: buf_si = buf_s; /* points to the beginning of k-th msg to be sent */
4223: for (proc=0,k=0; proc<size; proc++) {
4224: if (!len_s[proc]) continue;
4225: /* form outgoing message for i-structure:
4226: buf_si[0]: nrows to be sent
4227: [1:nrows]: row index (global)
4228: [nrows+1:2*nrows+1]: i-structure index
4229: */
4230: /*-------------------------------------------*/
4231: nrows = len_si[proc]/2 - 1;
4232: buf_si_i = buf_si + nrows+1;
4233: buf_si[0] = nrows;
4234: buf_si_i[0] = 0;
4235: nrows = 0;
4236: for (i=owners[proc]; i<owners[proc+1]; i++) {
4237: anzi = ai[i+1] - ai[i];
4238: if (anzi) {
4239: buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */
4240: buf_si[nrows+1] = i-owners[proc]; /* local row index */
4241: nrows++;
4242: }
4243: }
4244: MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);
4245: k++;
4246: buf_si += len_si[proc];
4247: }
4249: if (merge->nrecv) {MPI_Waitall(merge->nrecv,ri_waits,status);}
4250: if (merge->nsend) {MPI_Waitall(merge->nsend,si_waits,status);}
4252: PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);
4253: for (i=0; i<merge->nrecv; i++) {
4254: PetscInfo3(seqmat,"recv len_ri=%D, len_rj=%D from [%D]\n",len_ri[i],merge->len_r[i],merge->id_r[i]);
4255: }
4257: PetscFree(len_si);
4258: PetscFree(len_ri);
4259: PetscFree(rj_waits);
4260: PetscFree2(si_waits,sj_waits);
4261: PetscFree(ri_waits);
4262: PetscFree(buf_s);
4263: PetscFree(status);
4265: /* compute a local seq matrix in each processor */
4266: /*----------------------------------------------*/
4267: /* allocate bi array and free space for accumulating nonzero column info */
4268: PetscMalloc1(m+1,&bi);
4269: bi[0] = 0;
4271: /* create and initialize a linked list */
4272: nlnk = N+1;
4273: PetscLLCreate(N,N,nlnk,lnk,lnkbt);
4275: /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */
4276: len = ai[owners[rank+1]] - ai[owners[rank]];
4277: PetscFreeSpaceGet(PetscIntMultTruncate(2,len)+1,&free_space);
4279: current_space = free_space;
4281: /* determine symbolic info for each local row */
4282: PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);
4284: for (k=0; k<merge->nrecv; k++) {
4285: buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
4286: nrows = *buf_ri_k[k];
4287: nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */
4288: nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */
4289: }
4291: MatPreallocateInitialize(comm,m,n,dnz,onz);
4292: len = 0;
4293: for (i=0; i<m; i++) {
4294: bnzi = 0;
4295: /* add local non-zero cols of this proc's seqmat into lnk */
4296: arow = owners[rank] + i;
4297: anzi = ai[arow+1] - ai[arow];
4298: aj = a->j + ai[arow];
4299: PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);
4300: bnzi += nlnk;
4301: /* add received col data into lnk */
4302: for (k=0; k<merge->nrecv; k++) { /* k-th received message */
4303: if (i == *nextrow[k]) { /* i-th row */
4304: anzi = *(nextai[k]+1) - *nextai[k];
4305: aj = buf_rj[k] + *nextai[k];
4306: PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);
4307: bnzi += nlnk;
4308: nextrow[k]++; nextai[k]++;
4309: }
4310: }
4311: if (len < bnzi) len = bnzi; /* =max(bnzi) */
4313: /* if free space is not available, make more free space */
4314: if (current_space->local_remaining<bnzi) {
4315: PetscFreeSpaceGet(PetscIntSumTruncate(bnzi,current_space->total_array_size),¤t_space);
4316: nspacedouble++;
4317: }
4318: /* copy data into free space, then initialize lnk */
4319: PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);
4320: MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);
4322: current_space->array += bnzi;
4323: current_space->local_used += bnzi;
4324: current_space->local_remaining -= bnzi;
4326: bi[i+1] = bi[i] + bnzi;
4327: }
4329: PetscFree3(buf_ri_k,nextrow,nextai);
4331: PetscMalloc1(bi[m]+1,&bj);
4332: PetscFreeSpaceContiguous(&free_space,bj);
4333: PetscLLDestroy(lnk,lnkbt);
4335: /* create symbolic parallel matrix B_mpi */
4336: /*---------------------------------------*/
4337: MatGetBlockSizes(seqmat,&bs,&cbs);
4338: MatCreate(comm,&B_mpi);
4339: if (n==PETSC_DECIDE) {
4340: MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);
4341: } else {
4342: MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
4343: }
4344: MatSetBlockSizes(B_mpi,bs,cbs);
4345: MatSetType(B_mpi,MATMPIAIJ);
4346: MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);
4347: MatPreallocateFinalize(dnz,onz);
4348: MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);
4350: /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */
4351: B_mpi->assembled = PETSC_FALSE;
4352: B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI;
4353: merge->bi = bi;
4354: merge->bj = bj;
4355: merge->buf_ri = buf_ri;
4356: merge->buf_rj = buf_rj;
4357: merge->coi = NULL;
4358: merge->coj = NULL;
4359: merge->owners_co = NULL;
4361: PetscCommDestroy(&comm);
4363: /* attach the supporting struct to B_mpi for reuse */
4364: PetscContainerCreate(PETSC_COMM_SELF,&container);
4365: PetscContainerSetPointer(container,merge);
4366: PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);
4367: PetscContainerDestroy(&container);
4368: *mpimat = B_mpi;
4370: PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);
4371: return(0);
4372: }
4376: /*@C
4377: MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential
4378: matrices from each processor
4380: Collective on MPI_Comm
4382: Input Parameters:
4383: + comm - the communicators the parallel matrix will live on
4384: . seqmat - the input sequential matrices
4385: . m - number of local rows (or PETSC_DECIDE)
4386: . n - number of local columns (or PETSC_DECIDE)
4387: - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
4389: Output Parameter:
4390: . mpimat - the parallel matrix generated
4392: Level: advanced
4394: Notes:
4395: The dimensions of the sequential matrix in each processor MUST be the same.
4396: The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be
4397: destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat.
4398: @*/
4399: PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat)
4400: {
4402: PetscMPIInt size;
4405: MPI_Comm_size(comm,&size);
4406: if (size == 1) {
4407: PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
4408: if (scall == MAT_INITIAL_MATRIX) {
4409: MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);
4410: } else {
4411: MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);
4412: }
4413: PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
4414: return(0);
4415: }
4416: PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
4417: if (scall == MAT_INITIAL_MATRIX) {
4418: MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);
4419: }
4420: MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);
4421: PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
4422: return(0);
4423: }
4427: /*@
4428: MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with
4429: mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained
4430: with MatGetSize()
4432: Not Collective
4434: Input Parameters:
4435: + A - the matrix
4436: . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
4438: Output Parameter:
4439: . A_loc - the local sequential matrix generated
4441: Level: developer
4443: .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed()
4445: @*/
4446: PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc)
4447: {
4449: Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data;
4450: Mat_SeqAIJ *mat,*a,*b;
4451: PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray;
4452: MatScalar *aa,*ba,*cam;
4453: PetscScalar *ca;
4454: PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart;
4455: PetscInt *ci,*cj,col,ncols_d,ncols_o,jo;
4456: PetscBool match;
4457: MPI_Comm comm;
4458: PetscMPIInt size;
4461: PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);
4462: if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input");
4463: PetscObjectGetComm((PetscObject)A,&comm);
4464: MPI_Comm_size(comm,&size);
4465: if (size == 1 && scall == MAT_REUSE_MATRIX) return(0);
4467: PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);
4468: a = (Mat_SeqAIJ*)(mpimat->A)->data;
4469: b = (Mat_SeqAIJ*)(mpimat->B)->data;
4470: ai = a->i; aj = a->j; bi = b->i; bj = b->j;
4471: aa = a->a; ba = b->a;
4472: if (scall == MAT_INITIAL_MATRIX) {
4473: if (size == 1) {
4474: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);
4475: return(0);
4476: }
4478: PetscMalloc1(1+am,&ci);
4479: ci[0] = 0;
4480: for (i=0; i<am; i++) {
4481: ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]);
4482: }
4483: PetscMalloc1(1+ci[am],&cj);
4484: PetscMalloc1(1+ci[am],&ca);
4485: k = 0;
4486: for (i=0; i<am; i++) {
4487: ncols_o = bi[i+1] - bi[i];
4488: ncols_d = ai[i+1] - ai[i];
4489: /* off-diagonal portion of A */
4490: for (jo=0; jo<ncols_o; jo++) {
4491: col = cmap[*bj];
4492: if (col >= cstart) break;
4493: cj[k] = col; bj++;
4494: ca[k++] = *ba++;
4495: }
4496: /* diagonal portion of A */
4497: for (j=0; j<ncols_d; j++) {
4498: cj[k] = cstart + *aj++;
4499: ca[k++] = *aa++;
4500: }
4501: /* off-diagonal portion of A */
4502: for (j=jo; j<ncols_o; j++) {
4503: cj[k] = cmap[*bj++];
4504: ca[k++] = *ba++;
4505: }
4506: }
4507: /* put together the new matrix */
4508: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);
4509: /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
4510: /* Since these are PETSc arrays, change flags to free them as necessary. */
4511: mat = (Mat_SeqAIJ*)(*A_loc)->data;
4512: mat->free_a = PETSC_TRUE;
4513: mat->free_ij = PETSC_TRUE;
4514: mat->nonew = 0;
4515: } else if (scall == MAT_REUSE_MATRIX) {
4516: mat=(Mat_SeqAIJ*)(*A_loc)->data;
4517: ci = mat->i; cj = mat->j; cam = mat->a;
4518: for (i=0; i<am; i++) {
4519: /* off-diagonal portion of A */
4520: ncols_o = bi[i+1] - bi[i];
4521: for (jo=0; jo<ncols_o; jo++) {
4522: col = cmap[*bj];
4523: if (col >= cstart) break;
4524: *cam++ = *ba++; bj++;
4525: }
4526: /* diagonal portion of A */
4527: ncols_d = ai[i+1] - ai[i];
4528: for (j=0; j<ncols_d; j++) *cam++ = *aa++;
4529: /* off-diagonal portion of A */
4530: for (j=jo; j<ncols_o; j++) {
4531: *cam++ = *ba++; bj++;
4532: }
4533: }
4534: } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall);
4535: PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);
4536: return(0);
4537: }
4541: /*@C
4542: MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns
4544: Not Collective
4546: Input Parameters:
4547: + A - the matrix
4548: . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
4549: - row, col - index sets of rows and columns to extract (or NULL)
4551: Output Parameter:
4552: . A_loc - the local sequential matrix generated
4554: Level: developer
4556: .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat()
4558: @*/
4559: PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc)
4560: {
4561: Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data;
4563: PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx;
4564: IS isrowa,iscola;
4565: Mat *aloc;
4566: PetscBool match;
4569: PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);
4570: if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input");
4571: PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);
4572: if (!row) {
4573: start = A->rmap->rstart; end = A->rmap->rend;
4574: ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);
4575: } else {
4576: isrowa = *row;
4577: }
4578: if (!col) {
4579: start = A->cmap->rstart;
4580: cmap = a->garray;
4581: nzA = a->A->cmap->n;
4582: nzB = a->B->cmap->n;
4583: PetscMalloc1(nzA+nzB, &idx);
4584: ncols = 0;
4585: for (i=0; i<nzB; i++) {
4586: if (cmap[i] < start) idx[ncols++] = cmap[i];
4587: else break;
4588: }
4589: imark = i;
4590: for (i=0; i<nzA; i++) idx[ncols++] = start + i;
4591: for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i];
4592: ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);
4593: } else {
4594: iscola = *col;
4595: }
4596: if (scall != MAT_INITIAL_MATRIX) {
4597: PetscMalloc1(1,&aloc);
4598: aloc[0] = *A_loc;
4599: }
4600: MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);
4601: *A_loc = aloc[0];
4602: PetscFree(aloc);
4603: if (!row) {
4604: ISDestroy(&isrowa);
4605: }
4606: if (!col) {
4607: ISDestroy(&iscola);
4608: }
4609: PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);
4610: return(0);
4611: }
4615: /*@C
4616: MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A
4618: Collective on Mat
4620: Input Parameters:
4621: + A,B - the matrices in mpiaij format
4622: . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
4623: - rowb, colb - index sets of rows and columns of B to extract (or NULL)
4625: Output Parameter:
4626: + rowb, colb - index sets of rows and columns of B to extract
4627: - B_seq - the sequential matrix generated
4629: Level: developer
4631: @*/
4632: PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq)
4633: {
4634: Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data;
4636: PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark;
4637: IS isrowb,iscolb;
4638: Mat *bseq=NULL;
4641: if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
4642: 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);
4643: }
4644: PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);
4646: if (scall == MAT_INITIAL_MATRIX) {
4647: start = A->cmap->rstart;
4648: cmap = a->garray;
4649: nzA = a->A->cmap->n;
4650: nzB = a->B->cmap->n;
4651: PetscMalloc1(nzA+nzB, &idx);
4652: ncols = 0;
4653: for (i=0; i<nzB; i++) { /* row < local row index */
4654: if (cmap[i] < start) idx[ncols++] = cmap[i];
4655: else break;
4656: }
4657: imark = i;
4658: for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */
4659: for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */
4660: ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);
4661: ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);
4662: } else {
4663: if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX");
4664: isrowb = *rowb; iscolb = *colb;
4665: PetscMalloc1(1,&bseq);
4666: bseq[0] = *B_seq;
4667: }
4668: MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);
4669: *B_seq = bseq[0];
4670: PetscFree(bseq);
4671: if (!rowb) {
4672: ISDestroy(&isrowb);
4673: } else {
4674: *rowb = isrowb;
4675: }
4676: if (!colb) {
4677: ISDestroy(&iscolb);
4678: } else {
4679: *colb = iscolb;
4680: }
4681: PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);
4682: return(0);
4683: }
4687: /*
4688: MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns
4689: of the OFF-DIAGONAL portion of local A
4691: Collective on Mat
4693: Input Parameters:
4694: + A,B - the matrices in mpiaij format
4695: - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
4697: Output Parameter:
4698: + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL)
4699: . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL)
4700: . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL)
4701: - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N
4703: Level: developer
4705: */
4706: PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth)
4707: {
4708: VecScatter_MPI_General *gen_to,*gen_from;
4709: PetscErrorCode ierr;
4710: Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data;
4711: Mat_SeqAIJ *b_oth;
4712: VecScatter ctx =a->Mvctx;
4713: MPI_Comm comm;
4714: PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank;
4715: PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj;
4716: PetscScalar *rvalues,*svalues;
4717: MatScalar *b_otha,*bufa,*bufA;
4718: PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len;
4719: MPI_Request *rwaits = NULL,*swaits = NULL;
4720: MPI_Status *sstatus,rstatus;
4721: PetscMPIInt jj,size;
4722: PetscInt *cols,sbs,rbs;
4723: PetscScalar *vals;
4726: PetscObjectGetComm((PetscObject)A,&comm);
4727: MPI_Comm_size(comm,&size);
4729: if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
4730: 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);
4731: }
4732: PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);
4733: MPI_Comm_rank(comm,&rank);
4735: gen_to = (VecScatter_MPI_General*)ctx->todata;
4736: gen_from = (VecScatter_MPI_General*)ctx->fromdata;
4737: rvalues = gen_from->values; /* holds the length of receiving row */
4738: svalues = gen_to->values; /* holds the length of sending row */
4739: nrecvs = gen_from->n;
4740: nsends = gen_to->n;
4742: PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);
4743: srow = gen_to->indices; /* local row index to be sent */
4744: sstarts = gen_to->starts;
4745: sprocs = gen_to->procs;
4746: sstatus = gen_to->sstatus;
4747: sbs = gen_to->bs;
4748: rstarts = gen_from->starts;
4749: rprocs = gen_from->procs;
4750: rbs = gen_from->bs;
4752: if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX;
4753: if (scall == MAT_INITIAL_MATRIX) {
4754: /* i-array */
4755: /*---------*/
4756: /* post receives */
4757: for (i=0; i<nrecvs; i++) {
4758: rowlen = (PetscInt*)rvalues + rstarts[i]*rbs;
4759: nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */
4760: MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
4761: }
4763: /* pack the outgoing message */
4764: PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);
4766: sstartsj[0] = 0;
4767: rstartsj[0] = 0;
4768: len = 0; /* total length of j or a array to be sent */
4769: k = 0;
4770: for (i=0; i<nsends; i++) {
4771: rowlen = (PetscInt*)svalues + sstarts[i]*sbs;
4772: nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
4773: for (j=0; j<nrows; j++) {
4774: row = srow[k] + B->rmap->range[rank]; /* global row idx */
4775: for (l=0; l<sbs; l++) {
4776: MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL); /* rowlength */
4778: rowlen[j*sbs+l] = ncols;
4780: len += ncols;
4781: MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);
4782: }
4783: k++;
4784: }
4785: MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);
4787: sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */
4788: }
4789: /* recvs and sends of i-array are completed */
4790: i = nrecvs;
4791: while (i--) {
4792: MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
4793: }
4794: if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}
4796: /* allocate buffers for sending j and a arrays */
4797: PetscMalloc1(len+1,&bufj);
4798: PetscMalloc1(len+1,&bufa);
4800: /* create i-array of B_oth */
4801: PetscMalloc1(aBn+2,&b_othi);
4803: b_othi[0] = 0;
4804: len = 0; /* total length of j or a array to be received */
4805: k = 0;
4806: for (i=0; i<nrecvs; i++) {
4807: rowlen = (PetscInt*)rvalues + rstarts[i]*rbs;
4808: nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be received */
4809: for (j=0; j<nrows; j++) {
4810: b_othi[k+1] = b_othi[k] + rowlen[j];
4811: PetscIntSumError(rowlen[j],len,&len);
4812: k++;
4813: }
4814: rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */
4815: }
4817: /* allocate space for j and a arrrays of B_oth */
4818: PetscMalloc1(b_othi[aBn]+1,&b_othj);
4819: PetscMalloc1(b_othi[aBn]+1,&b_otha);
4821: /* j-array */
4822: /*---------*/
4823: /* post receives of j-array */
4824: for (i=0; i<nrecvs; i++) {
4825: nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
4826: MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
4827: }
4829: /* pack the outgoing message j-array */
4830: k = 0;
4831: for (i=0; i<nsends; i++) {
4832: nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
4833: bufJ = bufj+sstartsj[i];
4834: for (j=0; j<nrows; j++) {
4835: row = srow[k++] + B->rmap->range[rank]; /* global row idx */
4836: for (ll=0; ll<sbs; ll++) {
4837: MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);
4838: for (l=0; l<ncols; l++) {
4839: *bufJ++ = cols[l];
4840: }
4841: MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);
4842: }
4843: }
4844: MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);
4845: }
4847: /* recvs and sends of j-array are completed */
4848: i = nrecvs;
4849: while (i--) {
4850: MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
4851: }
4852: if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}
4853: } else if (scall == MAT_REUSE_MATRIX) {
4854: sstartsj = *startsj_s;
4855: rstartsj = *startsj_r;
4856: bufa = *bufa_ptr;
4857: b_oth = (Mat_SeqAIJ*)(*B_oth)->data;
4858: b_otha = b_oth->a;
4859: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container");
4861: /* a-array */
4862: /*---------*/
4863: /* post receives of a-array */
4864: for (i=0; i<nrecvs; i++) {
4865: nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
4866: MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);
4867: }
4869: /* pack the outgoing message a-array */
4870: k = 0;
4871: for (i=0; i<nsends; i++) {
4872: nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
4873: bufA = bufa+sstartsj[i];
4874: for (j=0; j<nrows; j++) {
4875: row = srow[k++] + B->rmap->range[rank]; /* global row idx */
4876: for (ll=0; ll<sbs; ll++) {
4877: MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);
4878: for (l=0; l<ncols; l++) {
4879: *bufA++ = vals[l];
4880: }
4881: MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);
4882: }
4883: }
4884: MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);
4885: }
4886: /* recvs and sends of a-array are completed */
4887: i = nrecvs;
4888: while (i--) {
4889: MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
4890: }
4891: if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}
4892: PetscFree2(rwaits,swaits);
4894: if (scall == MAT_INITIAL_MATRIX) {
4895: /* put together the new matrix */
4896: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);
4898: /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
4899: /* Since these are PETSc arrays, change flags to free them as necessary. */
4900: b_oth = (Mat_SeqAIJ*)(*B_oth)->data;
4901: b_oth->free_a = PETSC_TRUE;
4902: b_oth->free_ij = PETSC_TRUE;
4903: b_oth->nonew = 0;
4905: PetscFree(bufj);
4906: if (!startsj_s || !bufa_ptr) {
4907: PetscFree2(sstartsj,rstartsj);
4908: PetscFree(bufa_ptr);
4909: } else {
4910: *startsj_s = sstartsj;
4911: *startsj_r = rstartsj;
4912: *bufa_ptr = bufa;
4913: }
4914: }
4915: PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);
4916: return(0);
4917: }
4921: /*@C
4922: MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication.
4924: Not Collective
4926: Input Parameters:
4927: . A - The matrix in mpiaij format
4929: Output Parameter:
4930: + lvec - The local vector holding off-process values from the argument to a matrix-vector product
4931: . colmap - A map from global column index to local index into lvec
4932: - multScatter - A scatter from the argument of a matrix-vector product to lvec
4934: Level: developer
4936: @*/
4937: #if defined(PETSC_USE_CTABLE)
4938: PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter)
4939: #else
4940: PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter)
4941: #endif
4942: {
4943: Mat_MPIAIJ *a;
4950: a = (Mat_MPIAIJ*) A->data;
4951: if (lvec) *lvec = a->lvec;
4952: if (colmap) *colmap = a->colmap;
4953: if (multScatter) *multScatter = a->Mvctx;
4954: return(0);
4955: }
4957: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*);
4958: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*);
4959: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*);
4960: #if defined(PETSC_HAVE_ELEMENTAL)
4961: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*);
4962: #endif
4966: /*
4967: Computes (B'*A')' since computing B*A directly is untenable
4969: n p p
4970: ( ) ( ) ( )
4971: m ( A ) * n ( B ) = m ( C )
4972: ( ) ( ) ( )
4974: */
4975: PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C)
4976: {
4978: Mat At,Bt,Ct;
4981: MatTranspose(A,MAT_INITIAL_MATRIX,&At);
4982: MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);
4983: MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);
4984: MatDestroy(&At);
4985: MatDestroy(&Bt);
4986: MatTranspose(Ct,MAT_REUSE_MATRIX,&C);
4987: MatDestroy(&Ct);
4988: return(0);
4989: }
4993: PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C)
4994: {
4996: PetscInt m=A->rmap->n,n=B->cmap->n;
4997: Mat Cmat;
5000: 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);
5001: MatCreate(PetscObjectComm((PetscObject)A),&Cmat);
5002: MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
5003: MatSetBlockSizesFromMats(Cmat,A,B);
5004: MatSetType(Cmat,MATMPIDENSE);
5005: MatMPIDenseSetPreallocation(Cmat,NULL);
5006: MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);
5007: MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);
5009: Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ;
5011: *C = Cmat;
5012: return(0);
5013: }
5015: /* ----------------------------------------------------------------*/
5018: PETSC_INTERN PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
5019: {
5023: if (scall == MAT_INITIAL_MATRIX) {
5024: PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);
5025: MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);
5026: PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);
5027: }
5028: PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);
5029: MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);
5030: PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);
5031: return(0);
5032: }
5034: /*MC
5035: MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices.
5037: Options Database Keys:
5038: . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions()
5040: Level: beginner
5042: .seealso: MatCreateAIJ()
5043: M*/
5047: PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B)
5048: {
5049: Mat_MPIAIJ *b;
5051: PetscMPIInt size;
5054: MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
5056: PetscNewLog(B,&b);
5057: B->data = (void*)b;
5058: PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
5059: B->assembled = PETSC_FALSE;
5060: B->insertmode = NOT_SET_VALUES;
5061: b->size = size;
5063: MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
5065: /* build cache for off array entries formed */
5066: MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);
5068: b->donotstash = PETSC_FALSE;
5069: b->colmap = 0;
5070: b->garray = 0;
5071: b->roworiented = PETSC_TRUE;
5073: /* stuff used for matrix vector multiply */
5074: b->lvec = NULL;
5075: b->Mvctx = NULL;
5077: /* stuff for MatGetRow() */
5078: b->rowindices = 0;
5079: b->rowvalues = 0;
5080: b->getrowactive = PETSC_FALSE;
5082: /* flexible pointer used in CUSP/CUSPARSE classes */
5083: b->spptr = NULL;
5085: PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);
5086: PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);
5087: PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);
5088: PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);
5089: PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);
5090: PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);
5091: PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);
5092: PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);
5093: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);
5094: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);
5095: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);
5096: #if defined(PETSC_HAVE_ELEMENTAL)
5097: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);
5098: #endif
5099: PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);
5100: PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);
5101: PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);
5102: PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);
5103: return(0);
5104: }
5108: /*@
5109: MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal"
5110: and "off-diagonal" part of the matrix in CSR format.
5112: Collective on MPI_Comm
5114: Input Parameters:
5115: + comm - MPI communicator
5116: . m - number of local rows (Cannot be PETSC_DECIDE)
5117: . n - This value should be the same as the local size used in creating the
5118: x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
5119: calculated if N is given) For square matrices n is almost always m.
5120: . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
5121: . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
5122: . i - row indices for "diagonal" portion of matrix
5123: . j - column indices
5124: . a - matrix values
5125: . oi - row indices for "off-diagonal" portion of matrix
5126: . oj - column indices
5127: - oa - matrix values
5129: Output Parameter:
5130: . mat - the matrix
5132: Level: advanced
5134: Notes:
5135: The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user
5136: must free the arrays once the matrix has been destroyed and not before.
5138: The i and j indices are 0 based
5140: See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix
5142: This sets local rows and cannot be used to set off-processor values.
5144: Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a
5145: legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does
5146: not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because
5147: the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to
5148: keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all
5149: communication if it is known that only local entries will be set.
5151: .keywords: matrix, aij, compressed row, sparse, parallel
5153: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
5154: MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays()
5155: @*/
5156: 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)
5157: {
5159: Mat_MPIAIJ *maij;
5162: if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
5163: if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
5164: if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0");
5165: MatCreate(comm,mat);
5166: MatSetSizes(*mat,m,n,M,N);
5167: MatSetType(*mat,MATMPIAIJ);
5168: maij = (Mat_MPIAIJ*) (*mat)->data;
5170: (*mat)->preallocated = PETSC_TRUE;
5172: PetscLayoutSetUp((*mat)->rmap);
5173: PetscLayoutSetUp((*mat)->cmap);
5175: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);
5176: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);
5178: MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);
5179: MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);
5180: MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);
5181: MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);
5183: MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
5184: MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
5185: MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
5186: return(0);
5187: }
5189: /*
5190: Special version for direct calls from Fortran
5191: */
5192: #include <petsc/private/fortranimpl.h>
5194: #if defined(PETSC_HAVE_FORTRAN_CAPS)
5195: #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ
5196: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
5197: #define matsetvaluesmpiaij_ matsetvaluesmpiaij
5198: #endif
5200: /* Change these macros so can be used in void function */
5201: #undef CHKERRQ
5202: #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr)
5203: #undef SETERRQ2
5204: #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr)
5205: #undef SETERRQ3
5206: #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr)
5207: #undef SETERRQ
5208: #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr)
5212: PETSC_EXTERN void PETSC_STDCALL matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr)
5213: {
5214: Mat mat = *mmat;
5215: PetscInt m = *mm, n = *mn;
5216: InsertMode addv = *maddv;
5217: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
5218: PetscScalar value;
5221: MatCheckPreallocated(mat,1);
5222: if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv;
5224: #if defined(PETSC_USE_DEBUG)
5225: else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values");
5226: #endif
5227: {
5228: PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend;
5229: PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
5230: PetscBool roworiented = aij->roworiented;
5232: /* Some Variables required in the macro */
5233: Mat A = aij->A;
5234: Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data;
5235: PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j;
5236: MatScalar *aa = a->a;
5237: PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE);
5238: Mat B = aij->B;
5239: Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data;
5240: PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n;
5241: MatScalar *ba = b->a;
5243: PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2;
5244: PetscInt nonew = a->nonew;
5245: MatScalar *ap1,*ap2;
5248: for (i=0; i<m; i++) {
5249: if (im[i] < 0) continue;
5250: #if defined(PETSC_USE_DEBUG)
5251: 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);
5252: #endif
5253: if (im[i] >= rstart && im[i] < rend) {
5254: row = im[i] - rstart;
5255: lastcol1 = -1;
5256: rp1 = aj + ai[row];
5257: ap1 = aa + ai[row];
5258: rmax1 = aimax[row];
5259: nrow1 = ailen[row];
5260: low1 = 0;
5261: high1 = nrow1;
5262: lastcol2 = -1;
5263: rp2 = bj + bi[row];
5264: ap2 = ba + bi[row];
5265: rmax2 = bimax[row];
5266: nrow2 = bilen[row];
5267: low2 = 0;
5268: high2 = nrow2;
5270: for (j=0; j<n; j++) {
5271: if (roworiented) value = v[i*n+j];
5272: else value = v[i+j*m];
5273: if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue;
5274: if (in[j] >= cstart && in[j] < cend) {
5275: col = in[j] - cstart;
5276: MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]);
5277: } else if (in[j] < 0) continue;
5278: #if defined(PETSC_USE_DEBUG)
5279: 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);
5280: #endif
5281: else {
5282: if (mat->was_assembled) {
5283: if (!aij->colmap) {
5284: MatCreateColmap_MPIAIJ_Private(mat);
5285: }
5286: #if defined(PETSC_USE_CTABLE)
5287: PetscTableFind(aij->colmap,in[j]+1,&col);
5288: col--;
5289: #else
5290: col = aij->colmap[in[j]] - 1;
5291: #endif
5292: if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
5293: MatDisAssemble_MPIAIJ(mat);
5294: col = in[j];
5295: /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
5296: B = aij->B;
5297: b = (Mat_SeqAIJ*)B->data;
5298: bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j;
5299: rp2 = bj + bi[row];
5300: ap2 = ba + bi[row];
5301: rmax2 = bimax[row];
5302: nrow2 = bilen[row];
5303: low2 = 0;
5304: high2 = nrow2;
5305: bm = aij->B->rmap->n;
5306: ba = b->a;
5307: }
5308: } else col = in[j];
5309: MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]);
5310: }
5311: }
5312: } else if (!aij->donotstash) {
5313: if (roworiented) {
5314: MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
5315: } else {
5316: MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
5317: }
5318: }
5319: }
5320: }
5321: PetscFunctionReturnVoid();
5322: }