Actual source code: mpiaij.c
petsc-3.8.4 2018-03-24
3: #include <../src/mat/impls/aij/mpi/mpiaij.h>
4: #include <petsc/private/vecimpl.h>
5: #include <petsc/private/isimpl.h>
6: #include <petscblaslapack.h>
7: #include <petscsf.h>
9: /*MC
10: MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices.
12: This matrix type is identical to MATSEQAIJ when constructed with a single process communicator,
13: and MATMPIAIJ otherwise. As a result, for single process communicators,
14: MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported
15: for communicators controlling multiple processes. It is recommended that you call both of
16: the above preallocation routines for simplicity.
18: Options Database Keys:
19: . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions()
21: Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJMKL, MATAIJCRL, and also automatically switches over to use inodes when
22: enough exist.
24: Level: beginner
26: .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ, MATMPIAIJ
27: M*/
29: /*MC
30: MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices.
32: This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator,
33: and MATMPIAIJCRL otherwise. As a result, for single process communicators,
34: MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported
35: for communicators controlling multiple processes. It is recommended that you call both of
36: the above preallocation routines for simplicity.
38: Options Database Keys:
39: . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions()
41: Level: beginner
43: .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL
44: M*/
46: PetscErrorCode MatSetBlockSizes_MPIAIJ(Mat M, PetscInt rbs, PetscInt cbs)
47: {
49: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data;
52: if (mat->A) {
53: MatSetBlockSizes(mat->A,rbs,cbs);
54: MatSetBlockSizes(mat->B,rbs,1);
55: }
56: return(0);
57: }
59: PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows)
60: {
61: PetscErrorCode ierr;
62: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data;
63: Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data;
64: Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data;
65: const PetscInt *ia,*ib;
66: const MatScalar *aa,*bb;
67: PetscInt na,nb,i,j,*rows,cnt=0,n0rows;
68: PetscInt m = M->rmap->n,rstart = M->rmap->rstart;
71: *keptrows = 0;
72: ia = a->i;
73: ib = b->i;
74: for (i=0; i<m; i++) {
75: na = ia[i+1] - ia[i];
76: nb = ib[i+1] - ib[i];
77: if (!na && !nb) {
78: cnt++;
79: goto ok1;
80: }
81: aa = a->a + ia[i];
82: for (j=0; j<na; j++) {
83: if (aa[j] != 0.0) goto ok1;
84: }
85: bb = b->a + ib[i];
86: for (j=0; j <nb; j++) {
87: if (bb[j] != 0.0) goto ok1;
88: }
89: cnt++;
90: ok1:;
91: }
92: MPIU_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));
93: if (!n0rows) return(0);
94: PetscMalloc1(M->rmap->n-cnt,&rows);
95: cnt = 0;
96: for (i=0; i<m; i++) {
97: na = ia[i+1] - ia[i];
98: nb = ib[i+1] - ib[i];
99: if (!na && !nb) continue;
100: aa = a->a + ia[i];
101: for (j=0; j<na;j++) {
102: if (aa[j] != 0.0) {
103: rows[cnt++] = rstart + i;
104: goto ok2;
105: }
106: }
107: bb = b->a + ib[i];
108: for (j=0; j<nb; j++) {
109: if (bb[j] != 0.0) {
110: rows[cnt++] = rstart + i;
111: goto ok2;
112: }
113: }
114: ok2:;
115: }
116: ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);
117: return(0);
118: }
120: PetscErrorCode MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is)
121: {
122: PetscErrorCode ierr;
123: Mat_MPIAIJ *aij = (Mat_MPIAIJ*) Y->data;
126: if (Y->assembled && Y->rmap->rstart == Y->cmap->rstart && Y->rmap->rend == Y->cmap->rend) {
127: MatDiagonalSet(aij->A,D,is);
128: } else {
129: MatDiagonalSet_Default(Y,D,is);
130: }
131: return(0);
132: }
134: PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows)
135: {
136: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data;
138: PetscInt i,rstart,nrows,*rows;
141: *zrows = NULL;
142: MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);
143: MatGetOwnershipRange(M,&rstart,NULL);
144: for (i=0; i<nrows; i++) rows[i] += rstart;
145: ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);
146: return(0);
147: }
149: PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms)
150: {
152: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data;
153: PetscInt i,n,*garray = aij->garray;
154: Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data;
155: Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data;
156: PetscReal *work;
159: MatGetSize(A,NULL,&n);
160: PetscCalloc1(n,&work);
161: if (type == NORM_2) {
162: for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
163: work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]);
164: }
165: for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
166: work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]);
167: }
168: } else if (type == NORM_1) {
169: for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
170: work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]);
171: }
172: for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
173: work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]);
174: }
175: } else if (type == NORM_INFINITY) {
176: for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
177: work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]);
178: }
179: for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
180: work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]);
181: }
183: } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType");
184: if (type == NORM_INFINITY) {
185: MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));
186: } else {
187: MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));
188: }
189: PetscFree(work);
190: if (type == NORM_2) {
191: for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]);
192: }
193: return(0);
194: }
196: PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is)
197: {
198: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
199: IS sis,gis;
200: PetscErrorCode ierr;
201: const PetscInt *isis,*igis;
202: PetscInt n,*iis,nsis,ngis,rstart,i;
205: MatFindOffBlockDiagonalEntries(a->A,&sis);
206: MatFindNonzeroRows(a->B,&gis);
207: ISGetSize(gis,&ngis);
208: ISGetSize(sis,&nsis);
209: ISGetIndices(sis,&isis);
210: ISGetIndices(gis,&igis);
212: PetscMalloc1(ngis+nsis,&iis);
213: PetscMemcpy(iis,igis,ngis*sizeof(PetscInt));
214: PetscMemcpy(iis+ngis,isis,nsis*sizeof(PetscInt));
215: n = ngis + nsis;
216: PetscSortRemoveDupsInt(&n,iis);
217: MatGetOwnershipRange(A,&rstart,NULL);
218: for (i=0; i<n; i++) iis[i] += rstart;
219: ISCreateGeneral(PetscObjectComm((PetscObject)A),n,iis,PETSC_OWN_POINTER,is);
221: ISRestoreIndices(sis,&isis);
222: ISRestoreIndices(gis,&igis);
223: ISDestroy(&sis);
224: ISDestroy(&gis);
225: return(0);
226: }
228: /*
229: Distributes a SeqAIJ matrix across a set of processes. Code stolen from
230: MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type.
232: Only for square matrices
234: Used by a preconditioner, hence PETSC_EXTERN
235: */
236: PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat)
237: {
238: PetscMPIInt rank,size;
239: PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2];
241: Mat mat;
242: Mat_SeqAIJ *gmata;
243: PetscMPIInt tag;
244: MPI_Status status;
245: PetscBool aij;
246: MatScalar *gmataa,*ao,*ad,*gmataarestore=0;
249: MPI_Comm_rank(comm,&rank);
250: MPI_Comm_size(comm,&size);
251: if (!rank) {
252: PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);
253: if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name);
254: }
255: if (reuse == MAT_INITIAL_MATRIX) {
256: MatCreate(comm,&mat);
257: MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);
258: MatGetBlockSizes(gmat,&bses[0],&bses[1]);
259: MPI_Bcast(bses,2,MPIU_INT,0,comm);
260: MatSetBlockSizes(mat,bses[0],bses[1]);
261: MatSetType(mat,MATAIJ);
262: PetscMalloc1(size+1,&rowners);
263: PetscMalloc2(m,&dlens,m,&olens);
264: MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);
266: rowners[0] = 0;
267: for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
268: rstart = rowners[rank];
269: rend = rowners[rank+1];
270: PetscObjectGetNewTag((PetscObject)mat,&tag);
271: if (!rank) {
272: gmata = (Mat_SeqAIJ*) gmat->data;
273: /* send row lengths to all processors */
274: for (i=0; i<m; i++) dlens[i] = gmata->ilen[i];
275: for (i=1; i<size; i++) {
276: MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);
277: }
278: /* determine number diagonal and off-diagonal counts */
279: PetscMemzero(olens,m*sizeof(PetscInt));
280: PetscCalloc1(m,&ld);
281: jj = 0;
282: for (i=0; i<m; i++) {
283: for (j=0; j<dlens[i]; j++) {
284: if (gmata->j[jj] < rstart) ld[i]++;
285: if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++;
286: jj++;
287: }
288: }
289: /* send column indices to other processes */
290: for (i=1; i<size; i++) {
291: nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
292: MPI_Send(&nz,1,MPIU_INT,i,tag,comm);
293: MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);
294: }
296: /* send numerical values to other processes */
297: for (i=1; i<size; i++) {
298: nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
299: MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);
300: }
301: gmataa = gmata->a;
302: gmataj = gmata->j;
304: } else {
305: /* receive row lengths */
306: MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);
307: /* receive column indices */
308: MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);
309: PetscMalloc2(nz,&gmataa,nz,&gmataj);
310: MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);
311: /* determine number diagonal and off-diagonal counts */
312: PetscMemzero(olens,m*sizeof(PetscInt));
313: PetscCalloc1(m,&ld);
314: jj = 0;
315: for (i=0; i<m; i++) {
316: for (j=0; j<dlens[i]; j++) {
317: if (gmataj[jj] < rstart) ld[i]++;
318: if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++;
319: jj++;
320: }
321: }
322: /* receive numerical values */
323: PetscMemzero(gmataa,nz*sizeof(PetscScalar));
324: MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);
325: }
326: /* set preallocation */
327: for (i=0; i<m; i++) {
328: dlens[i] -= olens[i];
329: }
330: MatSeqAIJSetPreallocation(mat,0,dlens);
331: MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);
333: for (i=0; i<m; i++) {
334: dlens[i] += olens[i];
335: }
336: cnt = 0;
337: for (i=0; i<m; i++) {
338: row = rstart + i;
339: MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);
340: cnt += dlens[i];
341: }
342: if (rank) {
343: PetscFree2(gmataa,gmataj);
344: }
345: PetscFree2(dlens,olens);
346: PetscFree(rowners);
348: ((Mat_MPIAIJ*)(mat->data))->ld = ld;
350: *inmat = mat;
351: } else { /* column indices are already set; only need to move over numerical values from process 0 */
352: Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data;
353: Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data;
354: mat = *inmat;
355: PetscObjectGetNewTag((PetscObject)mat,&tag);
356: if (!rank) {
357: /* send numerical values to other processes */
358: gmata = (Mat_SeqAIJ*) gmat->data;
359: MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);
360: gmataa = gmata->a;
361: for (i=1; i<size; i++) {
362: nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
363: MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);
364: }
365: nz = gmata->i[rowners[1]]-gmata->i[rowners[0]];
366: } else {
367: /* receive numerical values from process 0*/
368: nz = Ad->nz + Ao->nz;
369: PetscMalloc1(nz,&gmataa); gmataarestore = gmataa;
370: MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);
371: }
372: /* transfer numerical values into the diagonal A and off diagonal B parts of mat */
373: ld = ((Mat_MPIAIJ*)(mat->data))->ld;
374: ad = Ad->a;
375: ao = Ao->a;
376: if (mat->rmap->n) {
377: i = 0;
378: nz = ld[i]; PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar)); ao += nz; gmataa += nz;
379: nz = Ad->i[i+1] - Ad->i[i]; PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar)); ad += nz; gmataa += nz;
380: }
381: for (i=1; i<mat->rmap->n; i++) {
382: nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar)); ao += nz; gmataa += nz;
383: nz = Ad->i[i+1] - Ad->i[i]; PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar)); ad += nz; gmataa += nz;
384: }
385: i--;
386: if (mat->rmap->n) {
387: nz = Ao->i[i+1] - Ao->i[i] - ld[i]; PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));
388: }
389: if (rank) {
390: PetscFree(gmataarestore);
391: }
392: }
393: MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);
394: MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);
395: return(0);
396: }
398: /*
399: Local utility routine that creates a mapping from the global column
400: number to the local number in the off-diagonal part of the local
401: storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at
402: a slightly higher hash table cost; without it it is not scalable (each processor
403: has an order N integer array but is fast to acess.
404: */
405: PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat)
406: {
407: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
409: PetscInt n = aij->B->cmap->n,i;
412: if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray");
413: #if defined(PETSC_USE_CTABLE)
414: PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);
415: for (i=0; i<n; i++) {
416: PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);
417: }
418: #else
419: PetscCalloc1(mat->cmap->N+1,&aij->colmap);
420: PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));
421: for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1;
422: #endif
423: return(0);
424: }
426: #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,orow,ocol) \
427: { \
428: if (col <= lastcol1) low1 = 0; \
429: else high1 = nrow1; \
430: lastcol1 = col;\
431: while (high1-low1 > 5) { \
432: t = (low1+high1)/2; \
433: if (rp1[t] > col) high1 = t; \
434: else low1 = t; \
435: } \
436: for (_i=low1; _i<high1; _i++) { \
437: if (rp1[_i] > col) break; \
438: if (rp1[_i] == col) { \
439: if (addv == ADD_VALUES) ap1[_i] += value; \
440: else ap1[_i] = value; \
441: goto a_noinsert; \
442: } \
443: } \
444: if (value == 0.0 && ignorezeroentries && row != col) {low1 = 0; high1 = nrow1;goto a_noinsert;} \
445: if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \
446: 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); \
447: MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \
448: N = nrow1++ - 1; a->nz++; high1++; \
449: /* shift up all the later entries in this row */ \
450: for (ii=N; ii>=_i; ii--) { \
451: rp1[ii+1] = rp1[ii]; \
452: ap1[ii+1] = ap1[ii]; \
453: } \
454: rp1[_i] = col; \
455: ap1[_i] = value; \
456: A->nonzerostate++;\
457: a_noinsert: ; \
458: ailen[row] = nrow1; \
459: }
461: #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv,orow,ocol) \
462: { \
463: if (col <= lastcol2) low2 = 0; \
464: else high2 = nrow2; \
465: lastcol2 = col; \
466: while (high2-low2 > 5) { \
467: t = (low2+high2)/2; \
468: if (rp2[t] > col) high2 = t; \
469: else low2 = t; \
470: } \
471: for (_i=low2; _i<high2; _i++) { \
472: if (rp2[_i] > col) break; \
473: if (rp2[_i] == col) { \
474: if (addv == ADD_VALUES) ap2[_i] += value; \
475: else ap2[_i] = value; \
476: goto b_noinsert; \
477: } \
478: } \
479: if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
480: if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
481: 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); \
482: MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \
483: N = nrow2++ - 1; b->nz++; high2++; \
484: /* shift up all the later entries in this row */ \
485: for (ii=N; ii>=_i; ii--) { \
486: rp2[ii+1] = rp2[ii]; \
487: ap2[ii+1] = ap2[ii]; \
488: } \
489: rp2[_i] = col; \
490: ap2[_i] = value; \
491: B->nonzerostate++; \
492: b_noinsert: ; \
493: bilen[row] = nrow2; \
494: }
496: PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[])
497: {
498: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data;
499: Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data;
501: PetscInt l,*garray = mat->garray,diag;
504: /* code only works for square matrices A */
506: /* find size of row to the left of the diagonal part */
507: MatGetOwnershipRange(A,&diag,0);
508: row = row - diag;
509: for (l=0; l<b->i[row+1]-b->i[row]; l++) {
510: if (garray[b->j[b->i[row]+l]] > diag) break;
511: }
512: PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));
514: /* diagonal part */
515: PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));
517: /* right of diagonal part */
518: 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));
519: return(0);
520: }
522: PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
523: {
524: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
525: PetscScalar value;
527: PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend;
528: PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
529: PetscBool roworiented = aij->roworiented;
531: /* Some Variables required in the macro */
532: Mat A = aij->A;
533: Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data;
534: PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j;
535: MatScalar *aa = a->a;
536: PetscBool ignorezeroentries = a->ignorezeroentries;
537: Mat B = aij->B;
538: Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data;
539: PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n;
540: MatScalar *ba = b->a;
542: PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2;
543: PetscInt nonew;
544: MatScalar *ap1,*ap2;
547: for (i=0; i<m; i++) {
548: if (im[i] < 0) continue;
549: #if defined(PETSC_USE_DEBUG)
550: 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);
551: #endif
552: if (im[i] >= rstart && im[i] < rend) {
553: row = im[i] - rstart;
554: lastcol1 = -1;
555: rp1 = aj + ai[row];
556: ap1 = aa + ai[row];
557: rmax1 = aimax[row];
558: nrow1 = ailen[row];
559: low1 = 0;
560: high1 = nrow1;
561: lastcol2 = -1;
562: rp2 = bj + bi[row];
563: ap2 = ba + bi[row];
564: rmax2 = bimax[row];
565: nrow2 = bilen[row];
566: low2 = 0;
567: high2 = nrow2;
569: for (j=0; j<n; j++) {
570: if (roworiented) value = v[i*n+j];
571: else value = v[i+j*m];
572: if (in[j] >= cstart && in[j] < cend) {
573: col = in[j] - cstart;
574: nonew = a->nonew;
575: if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue;
576: MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]);
577: } else if (in[j] < 0) continue;
578: #if defined(PETSC_USE_DEBUG)
579: 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);
580: #endif
581: else {
582: if (mat->was_assembled) {
583: if (!aij->colmap) {
584: MatCreateColmap_MPIAIJ_Private(mat);
585: }
586: #if defined(PETSC_USE_CTABLE)
587: PetscTableFind(aij->colmap,in[j]+1,&col);
588: col--;
589: #else
590: col = aij->colmap[in[j]] - 1;
591: #endif
592: if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) {
593: MatDisAssemble_MPIAIJ(mat);
594: col = in[j];
595: /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
596: B = aij->B;
597: b = (Mat_SeqAIJ*)B->data;
598: bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a;
599: rp2 = bj + bi[row];
600: ap2 = ba + bi[row];
601: rmax2 = bimax[row];
602: nrow2 = bilen[row];
603: low2 = 0;
604: high2 = nrow2;
605: bm = aij->B->rmap->n;
606: ba = b->a;
607: } 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]);
608: } else col = in[j];
609: nonew = b->nonew;
610: MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]);
611: }
612: }
613: } else {
614: 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]);
615: if (!aij->donotstash) {
616: mat->assembled = PETSC_FALSE;
617: if (roworiented) {
618: MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
619: } else {
620: MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
621: }
622: }
623: }
624: }
625: return(0);
626: }
628: PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
629: {
630: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
632: PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend;
633: PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
636: for (i=0; i<m; i++) {
637: if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/
638: 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);
639: if (idxm[i] >= rstart && idxm[i] < rend) {
640: row = idxm[i] - rstart;
641: for (j=0; j<n; j++) {
642: if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */
643: 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);
644: if (idxn[j] >= cstart && idxn[j] < cend) {
645: col = idxn[j] - cstart;
646: MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);
647: } else {
648: if (!aij->colmap) {
649: MatCreateColmap_MPIAIJ_Private(mat);
650: }
651: #if defined(PETSC_USE_CTABLE)
652: PetscTableFind(aij->colmap,idxn[j]+1,&col);
653: col--;
654: #else
655: col = aij->colmap[idxn[j]] - 1;
656: #endif
657: if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0;
658: else {
659: MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);
660: }
661: }
662: }
663: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
664: }
665: return(0);
666: }
668: extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec);
670: PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode)
671: {
672: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
674: PetscInt nstash,reallocs;
677: if (aij->donotstash || mat->nooffprocentries) return(0);
679: MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
680: MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
681: PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
682: return(0);
683: }
685: PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode)
686: {
687: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
688: Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data;
690: PetscMPIInt n;
691: PetscInt i,j,rstart,ncols,flg;
692: PetscInt *row,*col;
693: PetscBool other_disassembled;
694: PetscScalar *val;
696: /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */
699: if (!aij->donotstash && !mat->nooffprocentries) {
700: while (1) {
701: MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
702: if (!flg) break;
704: for (i=0; i<n; ) {
705: /* Now identify the consecutive vals belonging to the same row */
706: for (j=i,rstart=row[j]; j<n; j++) {
707: if (row[j] != rstart) break;
708: }
709: if (j < n) ncols = j-i;
710: else ncols = n-i;
711: /* Now assemble all these values with a single function call */
712: MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);
714: i = j;
715: }
716: }
717: MatStashScatterEnd_Private(&mat->stash);
718: }
719: MatAssemblyBegin(aij->A,mode);
720: MatAssemblyEnd(aij->A,mode);
722: /* determine if any processor has disassembled, if so we must
723: also disassemble ourselfs, in order that we may reassemble. */
724: /*
725: if nonzero structure of submatrix B cannot change then we know that
726: no processor disassembled thus we can skip this stuff
727: */
728: if (!((Mat_SeqAIJ*)aij->B->data)->nonew) {
729: MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
730: if (mat->was_assembled && !other_disassembled) {
731: MatDisAssemble_MPIAIJ(mat);
732: }
733: }
734: if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
735: MatSetUpMultiply_MPIAIJ(mat);
736: }
737: MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);
738: MatAssemblyBegin(aij->B,mode);
739: MatAssemblyEnd(aij->B,mode);
741: PetscFree2(aij->rowvalues,aij->rowindices);
743: aij->rowvalues = 0;
745: VecDestroy(&aij->diag);
746: if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ;
748: /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
749: if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
750: PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate;
751: MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
752: }
753: return(0);
754: }
756: PetscErrorCode MatZeroEntries_MPIAIJ(Mat A)
757: {
758: Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data;
762: MatZeroEntries(l->A);
763: MatZeroEntries(l->B);
764: return(0);
765: }
767: PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
768: {
769: Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data;
770: PetscInt *lrows;
771: PetscInt r, len;
775: /* get locally owned rows */
776: MatZeroRowsMapLocal_Private(A,N,rows,&len,&lrows);
777: /* fix right hand side if needed */
778: if (x && b) {
779: const PetscScalar *xx;
780: PetscScalar *bb;
782: VecGetArrayRead(x, &xx);
783: VecGetArray(b, &bb);
784: for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]];
785: VecRestoreArrayRead(x, &xx);
786: VecRestoreArray(b, &bb);
787: }
788: /* Must zero l->B before l->A because the (diag) case below may put values into l->B*/
789: MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);
790: if (A->congruentlayouts == -1) { /* first time we compare rows and cols layouts */
791: PetscBool cong;
792: PetscLayoutCompare(A->rmap,A->cmap,&cong);
793: if (cong) A->congruentlayouts = 1;
794: else A->congruentlayouts = 0;
795: }
796: if ((diag != 0.0) && A->congruentlayouts) {
797: MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);
798: } else if (diag != 0.0) {
799: MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);
800: 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");
801: for (r = 0; r < len; ++r) {
802: const PetscInt row = lrows[r] + A->rmap->rstart;
803: MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);
804: }
805: MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);
806: MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);
807: } else {
808: MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);
809: }
810: PetscFree(lrows);
812: /* only change matrix nonzero state if pattern was allowed to be changed */
813: if (!((Mat_SeqAIJ*)(mat->A->data))->keepnonzeropattern) {
814: PetscObjectState state = mat->A->nonzerostate + mat->B->nonzerostate;
815: MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));
816: }
817: return(0);
818: }
820: PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
821: {
822: Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data;
823: PetscErrorCode ierr;
824: PetscMPIInt n = A->rmap->n;
825: PetscInt i,j,r,m,p = 0,len = 0;
826: PetscInt *lrows,*owners = A->rmap->range;
827: PetscSFNode *rrows;
828: PetscSF sf;
829: const PetscScalar *xx;
830: PetscScalar *bb,*mask;
831: Vec xmask,lmask;
832: Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data;
833: const PetscInt *aj, *ii,*ridx;
834: PetscScalar *aa;
837: /* Create SF where leaves are input rows and roots are owned rows */
838: PetscMalloc1(n, &lrows);
839: for (r = 0; r < n; ++r) lrows[r] = -1;
840: PetscMalloc1(N, &rrows);
841: for (r = 0; r < N; ++r) {
842: const PetscInt idx = rows[r];
843: 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);
844: if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */
845: PetscLayoutFindOwner(A->rmap,idx,&p);
846: }
847: rrows[r].rank = p;
848: rrows[r].index = rows[r] - owners[p];
849: }
850: PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);
851: PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);
852: /* Collect flags for rows to be zeroed */
853: PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
854: PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
855: PetscSFDestroy(&sf);
856: /* Compress and put in row numbers */
857: for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r;
858: /* zero diagonal part of matrix */
859: MatZeroRowsColumns(l->A,len,lrows,diag,x,b);
860: /* handle off diagonal part of matrix */
861: MatCreateVecs(A,&xmask,NULL);
862: VecDuplicate(l->lvec,&lmask);
863: VecGetArray(xmask,&bb);
864: for (i=0; i<len; i++) bb[lrows[i]] = 1;
865: VecRestoreArray(xmask,&bb);
866: VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
867: VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
868: VecDestroy(&xmask);
869: if (x) {
870: VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
871: VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
872: VecGetArrayRead(l->lvec,&xx);
873: VecGetArray(b,&bb);
874: }
875: VecGetArray(lmask,&mask);
876: /* remove zeroed rows of off diagonal matrix */
877: ii = aij->i;
878: for (i=0; i<len; i++) {
879: PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));
880: }
881: /* loop over all elements of off process part of matrix zeroing removed columns*/
882: if (aij->compressedrow.use) {
883: m = aij->compressedrow.nrows;
884: ii = aij->compressedrow.i;
885: ridx = aij->compressedrow.rindex;
886: for (i=0; i<m; i++) {
887: n = ii[i+1] - ii[i];
888: aj = aij->j + ii[i];
889: aa = aij->a + ii[i];
891: for (j=0; j<n; j++) {
892: if (PetscAbsScalar(mask[*aj])) {
893: if (b) bb[*ridx] -= *aa*xx[*aj];
894: *aa = 0.0;
895: }
896: aa++;
897: aj++;
898: }
899: ridx++;
900: }
901: } else { /* do not use compressed row format */
902: m = l->B->rmap->n;
903: for (i=0; i<m; i++) {
904: n = ii[i+1] - ii[i];
905: aj = aij->j + ii[i];
906: aa = aij->a + ii[i];
907: for (j=0; j<n; j++) {
908: if (PetscAbsScalar(mask[*aj])) {
909: if (b) bb[i] -= *aa*xx[*aj];
910: *aa = 0.0;
911: }
912: aa++;
913: aj++;
914: }
915: }
916: }
917: if (x) {
918: VecRestoreArray(b,&bb);
919: VecRestoreArrayRead(l->lvec,&xx);
920: }
921: VecRestoreArray(lmask,&mask);
922: VecDestroy(&lmask);
923: PetscFree(lrows);
925: /* only change matrix nonzero state if pattern was allowed to be changed */
926: if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) {
927: PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate;
928: MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));
929: }
930: return(0);
931: }
933: PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy)
934: {
935: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
937: PetscInt nt;
940: VecGetLocalSize(xx,&nt);
941: 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);
942: VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
943: (*a->A->ops->mult)(a->A,xx,yy);
944: VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
945: (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
946: return(0);
947: }
949: PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx)
950: {
951: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
955: MatMultDiagonalBlock(a->A,bb,xx);
956: return(0);
957: }
959: PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
960: {
961: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
965: VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
966: (*a->A->ops->multadd)(a->A,xx,yy,zz);
967: VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
968: (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);
969: return(0);
970: }
972: PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy)
973: {
974: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
976: PetscBool merged;
979: VecScatterGetMerged(a->Mvctx,&merged);
980: /* do nondiagonal part */
981: (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
982: if (!merged) {
983: /* send it on its way */
984: VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
985: /* do local part */
986: (*a->A->ops->multtranspose)(a->A,xx,yy);
987: /* receive remote parts: note this assumes the values are not actually */
988: /* added in yy until the next line, */
989: VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
990: } else {
991: /* do local part */
992: (*a->A->ops->multtranspose)(a->A,xx,yy);
993: /* send it on its way */
994: VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
995: /* values actually were received in the Begin() but we need to call this nop */
996: VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
997: }
998: return(0);
999: }
1001: PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f)
1002: {
1003: MPI_Comm comm;
1004: Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij;
1005: Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs;
1006: IS Me,Notme;
1008: PetscInt M,N,first,last,*notme,i;
1009: PetscMPIInt size;
1012: /* Easy test: symmetric diagonal block */
1013: Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A;
1014: MatIsTranspose(Adia,Bdia,tol,f);
1015: if (!*f) return(0);
1016: PetscObjectGetComm((PetscObject)Amat,&comm);
1017: MPI_Comm_size(comm,&size);
1018: if (size == 1) return(0);
1020: /* Hard test: off-diagonal block. This takes a MatCreateSubMatrix. */
1021: MatGetSize(Amat,&M,&N);
1022: MatGetOwnershipRange(Amat,&first,&last);
1023: PetscMalloc1(N-last+first,¬me);
1024: for (i=0; i<first; i++) notme[i] = i;
1025: for (i=last; i<M; i++) notme[i-last+first] = i;
1026: ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);
1027: ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);
1028: MatCreateSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);
1029: Aoff = Aoffs[0];
1030: MatCreateSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);
1031: Boff = Boffs[0];
1032: MatIsTranspose(Aoff,Boff,tol,f);
1033: MatDestroyMatrices(1,&Aoffs);
1034: MatDestroyMatrices(1,&Boffs);
1035: ISDestroy(&Me);
1036: ISDestroy(&Notme);
1037: PetscFree(notme);
1038: return(0);
1039: }
1041: PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1042: {
1043: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1047: /* do nondiagonal part */
1048: (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1049: /* send it on its way */
1050: VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1051: /* do local part */
1052: (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);
1053: /* receive remote parts */
1054: VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1055: return(0);
1056: }
1058: /*
1059: This only works correctly for square matrices where the subblock A->A is the
1060: diagonal block
1061: */
1062: PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v)
1063: {
1065: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1068: if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
1069: 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");
1070: MatGetDiagonal(a->A,v);
1071: return(0);
1072: }
1074: PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa)
1075: {
1076: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1080: MatScale(a->A,aa);
1081: MatScale(a->B,aa);
1082: return(0);
1083: }
1085: PetscErrorCode MatDestroy_MPIAIJ(Mat mat)
1086: {
1087: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1091: #if defined(PETSC_USE_LOG)
1092: PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N);
1093: #endif
1094: MatStashDestroy_Private(&mat->stash);
1095: VecDestroy(&aij->diag);
1096: MatDestroy(&aij->A);
1097: MatDestroy(&aij->B);
1098: #if defined(PETSC_USE_CTABLE)
1099: PetscTableDestroy(&aij->colmap);
1100: #else
1101: PetscFree(aij->colmap);
1102: #endif
1103: PetscFree(aij->garray);
1104: VecDestroy(&aij->lvec);
1105: VecScatterDestroy(&aij->Mvctx);
1106: PetscFree2(aij->rowvalues,aij->rowindices);
1107: PetscFree(aij->ld);
1108: PetscFree(mat->data);
1110: PetscObjectChangeTypeName((PetscObject)mat,0);
1111: PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
1112: PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
1113: PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);
1114: PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);
1115: PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);
1116: PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);
1117: PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);
1118: #if defined(PETSC_HAVE_ELEMENTAL)
1119: PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);
1120: #endif
1121: #if defined(PETSC_HAVE_HYPRE)
1122: PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_hypre_C",NULL);
1123: PetscObjectComposeFunction((PetscObject)mat,"MatMatMatMult_transpose_mpiaij_mpiaij_C",NULL);
1124: #endif
1125: return(0);
1126: }
1128: PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer)
1129: {
1130: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1131: Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data;
1132: Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data;
1134: PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag;
1135: int fd;
1136: PetscInt nz,header[4],*row_lengths,*range=0,rlen,i;
1137: PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz = 0;
1138: PetscScalar *column_values;
1139: PetscInt message_count,flowcontrolcount;
1140: FILE *file;
1143: MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
1144: MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
1145: nz = A->nz + B->nz;
1146: PetscViewerBinaryGetDescriptor(viewer,&fd);
1147: if (!rank) {
1148: header[0] = MAT_FILE_CLASSID;
1149: header[1] = mat->rmap->N;
1150: header[2] = mat->cmap->N;
1152: MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1153: PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);
1154: /* get largest number of rows any processor has */
1155: rlen = mat->rmap->n;
1156: range = mat->rmap->range;
1157: for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]);
1158: } else {
1159: MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1160: rlen = mat->rmap->n;
1161: }
1163: /* load up the local row counts */
1164: PetscMalloc1(rlen+1,&row_lengths);
1165: 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];
1167: /* store the row lengths to the file */
1168: PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1169: if (!rank) {
1170: PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);
1171: for (i=1; i<size; i++) {
1172: PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1173: rlen = range[i+1] - range[i];
1174: MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));
1175: PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);
1176: }
1177: PetscViewerFlowControlEndMaster(viewer,&message_count);
1178: } else {
1179: PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1180: MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1181: PetscViewerFlowControlEndWorker(viewer,&message_count);
1182: }
1183: PetscFree(row_lengths);
1185: /* load up the local column indices */
1186: nzmax = nz; /* th processor needs space a largest processor needs */
1187: MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));
1188: PetscMalloc1(nzmax+1,&column_indices);
1189: cnt = 0;
1190: for (i=0; i<mat->rmap->n; i++) {
1191: for (j=B->i[i]; j<B->i[i+1]; j++) {
1192: if ((col = garray[B->j[j]]) > cstart) break;
1193: column_indices[cnt++] = col;
1194: }
1195: for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart;
1196: for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]];
1197: }
1198: 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);
1200: /* store the column indices to the file */
1201: PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1202: if (!rank) {
1203: MPI_Status status;
1204: PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);
1205: for (i=1; i<size; i++) {
1206: PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1207: MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1208: if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax);
1209: MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));
1210: PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);
1211: }
1212: PetscViewerFlowControlEndMaster(viewer,&message_count);
1213: } else {
1214: PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1215: MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1216: MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1217: PetscViewerFlowControlEndWorker(viewer,&message_count);
1218: }
1219: PetscFree(column_indices);
1221: /* load up the local column values */
1222: PetscMalloc1(nzmax+1,&column_values);
1223: cnt = 0;
1224: for (i=0; i<mat->rmap->n; i++) {
1225: for (j=B->i[i]; j<B->i[i+1]; j++) {
1226: if (garray[B->j[j]] > cstart) break;
1227: column_values[cnt++] = B->a[j];
1228: }
1229: for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k];
1230: for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j];
1231: }
1232: 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);
1234: /* store the column values to the file */
1235: PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1236: if (!rank) {
1237: MPI_Status status;
1238: PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);
1239: for (i=1; i<size; i++) {
1240: PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1241: MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1242: if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax);
1243: MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));
1244: PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);
1245: }
1246: PetscViewerFlowControlEndMaster(viewer,&message_count);
1247: } else {
1248: PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1249: MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1250: MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));
1251: PetscViewerFlowControlEndWorker(viewer,&message_count);
1252: }
1253: PetscFree(column_values);
1255: PetscViewerBinaryGetInfoPointer(viewer,&file);
1256: if (file) fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(mat->rmap->bs));
1257: return(0);
1258: }
1260: #include <petscdraw.h>
1261: PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
1262: {
1263: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1264: PetscErrorCode ierr;
1265: PetscMPIInt rank = aij->rank,size = aij->size;
1266: PetscBool isdraw,iascii,isbinary;
1267: PetscViewer sviewer;
1268: PetscViewerFormat format;
1271: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1272: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1273: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1274: if (iascii) {
1275: PetscViewerGetFormat(viewer,&format);
1276: if (format == PETSC_VIEWER_LOAD_BALANCE) {
1277: PetscInt i,nmax = 0,nmin = PETSC_MAX_INT,navg = 0,*nz,nzlocal = ((Mat_SeqAIJ*) (aij->A->data))->nz + ((Mat_SeqAIJ*) (aij->B->data))->nz;
1278: PetscMalloc1(size,&nz);
1279: MPI_Allgather(&nzlocal,1,MPIU_INT,nz,1,MPIU_INT,PetscObjectComm((PetscObject)mat));
1280: for (i=0; i<(PetscInt)size; i++) {
1281: nmax = PetscMax(nmax,nz[i]);
1282: nmin = PetscMin(nmin,nz[i]);
1283: navg += nz[i];
1284: }
1285: PetscFree(nz);
1286: navg = navg/size;
1287: PetscViewerASCIIPrintf(viewer,"Load Balance - Nonzeros: Min %D avg %D max %D\n",nmin,navg,nmax);
1288: return(0);
1289: }
1290: PetscViewerGetFormat(viewer,&format);
1291: if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
1292: MatInfo info;
1293: PetscBool inodes;
1295: MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
1296: MatGetInfo(mat,MAT_LOCAL,&info);
1297: MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);
1298: PetscViewerASCIIPushSynchronized(viewer);
1299: if (!inodes) {
1300: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n",
1301: rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);
1302: } else {
1303: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n",
1304: rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);
1305: }
1306: MatGetInfo(aij->A,MAT_LOCAL,&info);
1307: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1308: MatGetInfo(aij->B,MAT_LOCAL,&info);
1309: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1310: PetscViewerFlush(viewer);
1311: PetscViewerASCIIPopSynchronized(viewer);
1312: PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
1313: VecScatterView(aij->Mvctx,viewer);
1314: return(0);
1315: } else if (format == PETSC_VIEWER_ASCII_INFO) {
1316: PetscInt inodecount,inodelimit,*inodes;
1317: MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);
1318: if (inodes) {
1319: PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);
1320: } else {
1321: PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");
1322: }
1323: return(0);
1324: } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
1325: return(0);
1326: }
1327: } else if (isbinary) {
1328: if (size == 1) {
1329: PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);
1330: MatView(aij->A,viewer);
1331: } else {
1332: MatView_MPIAIJ_Binary(mat,viewer);
1333: }
1334: return(0);
1335: } else if (isdraw) {
1336: PetscDraw draw;
1337: PetscBool isnull;
1338: PetscViewerDrawGetDraw(viewer,0,&draw);
1339: PetscDrawIsNull(draw,&isnull);
1340: if (isnull) return(0);
1341: }
1343: {
1344: /* assemble the entire matrix onto first processor. */
1345: Mat A;
1346: Mat_SeqAIJ *Aloc;
1347: PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct;
1348: MatScalar *a;
1350: MatCreate(PetscObjectComm((PetscObject)mat),&A);
1351: if (!rank) {
1352: MatSetSizes(A,M,N,M,N);
1353: } else {
1354: MatSetSizes(A,0,0,M,N);
1355: }
1356: /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */
1357: MatSetType(A,MATMPIAIJ);
1358: MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);
1359: MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
1360: PetscLogObjectParent((PetscObject)mat,(PetscObject)A);
1362: /* copy over the A part */
1363: Aloc = (Mat_SeqAIJ*)aij->A->data;
1364: m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
1365: row = mat->rmap->rstart;
1366: for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart;
1367: for (i=0; i<m; i++) {
1368: MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);
1369: row++;
1370: a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i];
1371: }
1372: aj = Aloc->j;
1373: for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart;
1375: /* copy over the B part */
1376: Aloc = (Mat_SeqAIJ*)aij->B->data;
1377: m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
1378: row = mat->rmap->rstart;
1379: PetscMalloc1(ai[m]+1,&cols);
1380: ct = cols;
1381: for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]];
1382: for (i=0; i<m; i++) {
1383: MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);
1384: row++;
1385: a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i];
1386: }
1387: PetscFree(ct);
1388: MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
1389: MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
1390: /*
1391: Everyone has to call to draw the matrix since the graphics waits are
1392: synchronized across all processors that share the PetscDraw object
1393: */
1394: PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
1395: if (!rank) {
1396: PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);
1397: MatView_SeqAIJ(((Mat_MPIAIJ*)(A->data))->A,sviewer);
1398: }
1399: PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
1400: PetscViewerFlush(viewer);
1401: MatDestroy(&A);
1402: }
1403: return(0);
1404: }
1406: PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer)
1407: {
1409: PetscBool iascii,isdraw,issocket,isbinary;
1412: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1413: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1414: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1415: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
1416: if (iascii || isdraw || isbinary || issocket) {
1417: MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);
1418: }
1419: return(0);
1420: }
1422: PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
1423: {
1424: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data;
1426: Vec bb1 = 0;
1427: PetscBool hasop;
1430: if (flag == SOR_APPLY_UPPER) {
1431: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1432: return(0);
1433: }
1435: if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) {
1436: VecDuplicate(bb,&bb1);
1437: }
1439: if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
1440: if (flag & SOR_ZERO_INITIAL_GUESS) {
1441: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1442: its--;
1443: }
1445: while (its--) {
1446: VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1447: VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1449: /* update rhs: bb1 = bb - B*x */
1450: VecScale(mat->lvec,-1.0);
1451: (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);
1453: /* local sweep */
1454: (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);
1455: }
1456: } else if (flag & SOR_LOCAL_FORWARD_SWEEP) {
1457: if (flag & SOR_ZERO_INITIAL_GUESS) {
1458: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1459: its--;
1460: }
1461: while (its--) {
1462: VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1463: VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1465: /* update rhs: bb1 = bb - B*x */
1466: VecScale(mat->lvec,-1.0);
1467: (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);
1469: /* local sweep */
1470: (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);
1471: }
1472: } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) {
1473: if (flag & SOR_ZERO_INITIAL_GUESS) {
1474: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1475: its--;
1476: }
1477: while (its--) {
1478: VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1479: VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1481: /* update rhs: bb1 = bb - B*x */
1482: VecScale(mat->lvec,-1.0);
1483: (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);
1485: /* local sweep */
1486: (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);
1487: }
1488: } else if (flag & SOR_EISENSTAT) {
1489: Vec xx1;
1491: VecDuplicate(bb,&xx1);
1492: (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);
1494: VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1495: VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1496: if (!mat->diag) {
1497: MatCreateVecs(matin,&mat->diag,NULL);
1498: MatGetDiagonal(matin,mat->diag);
1499: }
1500: MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);
1501: if (hasop) {
1502: MatMultDiagonalBlock(matin,xx,bb1);
1503: } else {
1504: VecPointwiseMult(bb1,mat->diag,xx);
1505: }
1506: VecAYPX(bb1,(omega-2.0)/omega,bb);
1508: MatMultAdd(mat->B,mat->lvec,bb1,bb1);
1510: /* local sweep */
1511: (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
1512: VecAXPY(xx,1.0,xx1);
1513: VecDestroy(&xx1);
1514: } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported");
1516: VecDestroy(&bb1);
1518: matin->factorerrortype = mat->A->factorerrortype;
1519: return(0);
1520: }
1522: PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B)
1523: {
1524: Mat aA,aB,Aperm;
1525: const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj;
1526: PetscScalar *aa,*ba;
1527: PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest;
1528: PetscSF rowsf,sf;
1529: IS parcolp = NULL;
1530: PetscBool done;
1534: MatGetLocalSize(A,&m,&n);
1535: ISGetIndices(rowp,&rwant);
1536: ISGetIndices(colp,&cwant);
1537: PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);
1539: /* Invert row permutation to find out where my rows should go */
1540: PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);
1541: PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);
1542: PetscSFSetFromOptions(rowsf);
1543: for (i=0; i<m; i++) work[i] = A->rmap->rstart + i;
1544: PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);
1545: PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);
1547: /* Invert column permutation to find out where my columns should go */
1548: PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1549: PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);
1550: PetscSFSetFromOptions(sf);
1551: for (i=0; i<n; i++) work[i] = A->cmap->rstart + i;
1552: PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);
1553: PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);
1554: PetscSFDestroy(&sf);
1556: ISRestoreIndices(rowp,&rwant);
1557: ISRestoreIndices(colp,&cwant);
1558: MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);
1560: /* Find out where my gcols should go */
1561: MatGetSize(aB,NULL,&ng);
1562: PetscMalloc1(ng,&gcdest);
1563: PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1564: PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);
1565: PetscSFSetFromOptions(sf);
1566: PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);
1567: PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);
1568: PetscSFDestroy(&sf);
1570: PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);
1571: MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);
1572: MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);
1573: for (i=0; i<m; i++) {
1574: PetscInt row = rdest[i],rowner;
1575: PetscLayoutFindOwner(A->rmap,row,&rowner);
1576: for (j=ai[i]; j<ai[i+1]; j++) {
1577: PetscInt cowner,col = cdest[aj[j]];
1578: PetscLayoutFindOwner(A->cmap,col,&cowner); /* Could build an index for the columns to eliminate this search */
1579: if (rowner == cowner) dnnz[i]++;
1580: else onnz[i]++;
1581: }
1582: for (j=bi[i]; j<bi[i+1]; j++) {
1583: PetscInt cowner,col = gcdest[bj[j]];
1584: PetscLayoutFindOwner(A->cmap,col,&cowner);
1585: if (rowner == cowner) dnnz[i]++;
1586: else onnz[i]++;
1587: }
1588: }
1589: PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);
1590: PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);
1591: PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);
1592: PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);
1593: PetscSFDestroy(&rowsf);
1595: MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);
1596: MatSeqAIJGetArray(aA,&aa);
1597: MatSeqAIJGetArray(aB,&ba);
1598: for (i=0; i<m; i++) {
1599: PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */
1600: PetscInt j0,rowlen;
1601: rowlen = ai[i+1] - ai[i];
1602: for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */
1603: for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]];
1604: MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);
1605: }
1606: rowlen = bi[i+1] - bi[i];
1607: for (j0=j=0; j<rowlen; j0=j) {
1608: for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]];
1609: MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);
1610: }
1611: }
1612: MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);
1613: MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);
1614: MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);
1615: MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);
1616: MatSeqAIJRestoreArray(aA,&aa);
1617: MatSeqAIJRestoreArray(aB,&ba);
1618: PetscFree4(dnnz,onnz,tdnnz,tonnz);
1619: PetscFree3(work,rdest,cdest);
1620: PetscFree(gcdest);
1621: if (parcolp) {ISDestroy(&colp);}
1622: *B = Aperm;
1623: return(0);
1624: }
1626: PetscErrorCode MatGetGhosts_MPIAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[])
1627: {
1628: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1632: MatGetSize(aij->B,NULL,nghosts);
1633: if (ghosts) *ghosts = aij->garray;
1634: return(0);
1635: }
1637: PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1638: {
1639: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data;
1640: Mat A = mat->A,B = mat->B;
1642: PetscReal isend[5],irecv[5];
1645: info->block_size = 1.0;
1646: MatGetInfo(A,MAT_LOCAL,info);
1648: isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1649: isend[3] = info->memory; isend[4] = info->mallocs;
1651: MatGetInfo(B,MAT_LOCAL,info);
1653: isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1654: isend[3] += info->memory; isend[4] += info->mallocs;
1655: if (flag == MAT_LOCAL) {
1656: info->nz_used = isend[0];
1657: info->nz_allocated = isend[1];
1658: info->nz_unneeded = isend[2];
1659: info->memory = isend[3];
1660: info->mallocs = isend[4];
1661: } else if (flag == MAT_GLOBAL_MAX) {
1662: MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));
1664: info->nz_used = irecv[0];
1665: info->nz_allocated = irecv[1];
1666: info->nz_unneeded = irecv[2];
1667: info->memory = irecv[3];
1668: info->mallocs = irecv[4];
1669: } else if (flag == MAT_GLOBAL_SUM) {
1670: MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));
1672: info->nz_used = irecv[0];
1673: info->nz_allocated = irecv[1];
1674: info->nz_unneeded = irecv[2];
1675: info->memory = irecv[3];
1676: info->mallocs = irecv[4];
1677: }
1678: info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */
1679: info->fill_ratio_needed = 0;
1680: info->factor_mallocs = 0;
1681: return(0);
1682: }
1684: PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg)
1685: {
1686: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1690: switch (op) {
1691: case MAT_NEW_NONZERO_LOCATIONS:
1692: case MAT_NEW_NONZERO_ALLOCATION_ERR:
1693: case MAT_UNUSED_NONZERO_LOCATION_ERR:
1694: case MAT_KEEP_NONZERO_PATTERN:
1695: case MAT_NEW_NONZERO_LOCATION_ERR:
1696: case MAT_USE_INODES:
1697: case MAT_IGNORE_ZERO_ENTRIES:
1698: MatCheckPreallocated(A,1);
1699: MatSetOption(a->A,op,flg);
1700: MatSetOption(a->B,op,flg);
1701: break;
1702: case MAT_ROW_ORIENTED:
1703: MatCheckPreallocated(A,1);
1704: a->roworiented = flg;
1706: MatSetOption(a->A,op,flg);
1707: MatSetOption(a->B,op,flg);
1708: break;
1709: case MAT_NEW_DIAGONALS:
1710: PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1711: break;
1712: case MAT_IGNORE_OFF_PROC_ENTRIES:
1713: a->donotstash = flg;
1714: break;
1715: case MAT_SPD:
1716: A->spd_set = PETSC_TRUE;
1717: A->spd = flg;
1718: if (flg) {
1719: A->symmetric = PETSC_TRUE;
1720: A->structurally_symmetric = PETSC_TRUE;
1721: A->symmetric_set = PETSC_TRUE;
1722: A->structurally_symmetric_set = PETSC_TRUE;
1723: }
1724: break;
1725: case MAT_SYMMETRIC:
1726: MatCheckPreallocated(A,1);
1727: MatSetOption(a->A,op,flg);
1728: break;
1729: case MAT_STRUCTURALLY_SYMMETRIC:
1730: MatCheckPreallocated(A,1);
1731: MatSetOption(a->A,op,flg);
1732: break;
1733: case MAT_HERMITIAN:
1734: MatCheckPreallocated(A,1);
1735: MatSetOption(a->A,op,flg);
1736: break;
1737: case MAT_SYMMETRY_ETERNAL:
1738: MatCheckPreallocated(A,1);
1739: MatSetOption(a->A,op,flg);
1740: break;
1741: case MAT_SUBMAT_SINGLEIS:
1742: A->submat_singleis = flg;
1743: break;
1744: case MAT_STRUCTURE_ONLY:
1745: /* The option is handled directly by MatSetOption() */
1746: break;
1747: default:
1748: SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1749: }
1750: return(0);
1751: }
1753: PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1754: {
1755: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data;
1756: PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p;
1758: PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart;
1759: PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend;
1760: PetscInt *cmap,*idx_p;
1763: if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
1764: mat->getrowactive = PETSC_TRUE;
1766: if (!mat->rowvalues && (idx || v)) {
1767: /*
1768: allocate enough space to hold information from the longest row.
1769: */
1770: Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data;
1771: PetscInt max = 1,tmp;
1772: for (i=0; i<matin->rmap->n; i++) {
1773: tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i];
1774: if (max < tmp) max = tmp;
1775: }
1776: PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);
1777: }
1779: if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows");
1780: lrow = row - rstart;
1782: pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1783: if (!v) {pvA = 0; pvB = 0;}
1784: if (!idx) {pcA = 0; if (!v) pcB = 0;}
1785: (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1786: (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1787: nztot = nzA + nzB;
1789: cmap = mat->garray;
1790: if (v || idx) {
1791: if (nztot) {
1792: /* Sort by increasing column numbers, assuming A and B already sorted */
1793: PetscInt imark = -1;
1794: if (v) {
1795: *v = v_p = mat->rowvalues;
1796: for (i=0; i<nzB; i++) {
1797: if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i];
1798: else break;
1799: }
1800: imark = i;
1801: for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i];
1802: for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i];
1803: }
1804: if (idx) {
1805: *idx = idx_p = mat->rowindices;
1806: if (imark > -1) {
1807: for (i=0; i<imark; i++) {
1808: idx_p[i] = cmap[cworkB[i]];
1809: }
1810: } else {
1811: for (i=0; i<nzB; i++) {
1812: if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]];
1813: else break;
1814: }
1815: imark = i;
1816: }
1817: for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i];
1818: for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]];
1819: }
1820: } else {
1821: if (idx) *idx = 0;
1822: if (v) *v = 0;
1823: }
1824: }
1825: *nz = nztot;
1826: (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1827: (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1828: return(0);
1829: }
1831: PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1832: {
1833: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1836: if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
1837: aij->getrowactive = PETSC_FALSE;
1838: return(0);
1839: }
1841: PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm)
1842: {
1843: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1844: Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data;
1846: PetscInt i,j,cstart = mat->cmap->rstart;
1847: PetscReal sum = 0.0;
1848: MatScalar *v;
1851: if (aij->size == 1) {
1852: MatNorm(aij->A,type,norm);
1853: } else {
1854: if (type == NORM_FROBENIUS) {
1855: v = amat->a;
1856: for (i=0; i<amat->nz; i++) {
1857: sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1858: }
1859: v = bmat->a;
1860: for (i=0; i<bmat->nz; i++) {
1861: sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1862: }
1863: MPIU_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
1864: *norm = PetscSqrtReal(*norm);
1865: PetscLogFlops(2*amat->nz+2*bmat->nz);
1866: } else if (type == NORM_1) { /* max column norm */
1867: PetscReal *tmp,*tmp2;
1868: PetscInt *jj,*garray = aij->garray;
1869: PetscCalloc1(mat->cmap->N+1,&tmp);
1870: PetscMalloc1(mat->cmap->N+1,&tmp2);
1871: *norm = 0.0;
1872: v = amat->a; jj = amat->j;
1873: for (j=0; j<amat->nz; j++) {
1874: tmp[cstart + *jj++] += PetscAbsScalar(*v); v++;
1875: }
1876: v = bmat->a; jj = bmat->j;
1877: for (j=0; j<bmat->nz; j++) {
1878: tmp[garray[*jj++]] += PetscAbsScalar(*v); v++;
1879: }
1880: MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
1881: for (j=0; j<mat->cmap->N; j++) {
1882: if (tmp2[j] > *norm) *norm = tmp2[j];
1883: }
1884: PetscFree(tmp);
1885: PetscFree(tmp2);
1886: PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));
1887: } else if (type == NORM_INFINITY) { /* max row norm */
1888: PetscReal ntemp = 0.0;
1889: for (j=0; j<aij->A->rmap->n; j++) {
1890: v = amat->a + amat->i[j];
1891: sum = 0.0;
1892: for (i=0; i<amat->i[j+1]-amat->i[j]; i++) {
1893: sum += PetscAbsScalar(*v); v++;
1894: }
1895: v = bmat->a + bmat->i[j];
1896: for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) {
1897: sum += PetscAbsScalar(*v); v++;
1898: }
1899: if (sum > ntemp) ntemp = sum;
1900: }
1901: MPIU_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));
1902: PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));
1903: } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm");
1904: }
1905: return(0);
1906: }
1908: PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout)
1909: {
1910: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1911: Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data;
1913: PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i;
1914: PetscInt cstart = A->cmap->rstart,ncol;
1915: Mat B;
1916: MatScalar *array;
1919: if (reuse == MAT_INPLACE_MATRIX && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place");
1921: ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n;
1922: ai = Aloc->i; aj = Aloc->j;
1923: bi = Bloc->i; bj = Bloc->j;
1924: if (reuse == MAT_INITIAL_MATRIX || *matout == A) {
1925: PetscInt *d_nnz,*g_nnz,*o_nnz;
1926: PetscSFNode *oloc;
1927: PETSC_UNUSED PetscSF sf;
1929: PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);
1930: /* compute d_nnz for preallocation */
1931: PetscMemzero(d_nnz,na*sizeof(PetscInt));
1932: for (i=0; i<ai[ma]; i++) {
1933: d_nnz[aj[i]]++;
1934: aj[i] += cstart; /* global col index to be used by MatSetValues() */
1935: }
1936: /* compute local off-diagonal contributions */
1937: PetscMemzero(g_nnz,nb*sizeof(PetscInt));
1938: for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++;
1939: /* map those to global */
1940: PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1941: PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);
1942: PetscSFSetFromOptions(sf);
1943: PetscMemzero(o_nnz,na*sizeof(PetscInt));
1944: PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);
1945: PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);
1946: PetscSFDestroy(&sf);
1948: MatCreate(PetscObjectComm((PetscObject)A),&B);
1949: MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);
1950: MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));
1951: MatSetType(B,((PetscObject)A)->type_name);
1952: MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);
1953: PetscFree4(d_nnz,o_nnz,g_nnz,oloc);
1954: } else {
1955: B = *matout;
1956: MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);
1957: for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */
1958: }
1960: /* copy over the A part */
1961: array = Aloc->a;
1962: row = A->rmap->rstart;
1963: for (i=0; i<ma; i++) {
1964: ncol = ai[i+1]-ai[i];
1965: MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);
1966: row++;
1967: array += ncol; aj += ncol;
1968: }
1969: aj = Aloc->j;
1970: for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */
1972: /* copy over the B part */
1973: PetscCalloc1(bi[mb],&cols);
1974: array = Bloc->a;
1975: row = A->rmap->rstart;
1976: for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]];
1977: cols_tmp = cols;
1978: for (i=0; i<mb; i++) {
1979: ncol = bi[i+1]-bi[i];
1980: MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);
1981: row++;
1982: array += ncol; cols_tmp += ncol;
1983: }
1984: PetscFree(cols);
1986: MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
1987: MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
1988: if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) {
1989: *matout = B;
1990: } else {
1991: MatHeaderMerge(A,&B);
1992: }
1993: return(0);
1994: }
1996: PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr)
1997: {
1998: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1999: Mat a = aij->A,b = aij->B;
2001: PetscInt s1,s2,s3;
2004: MatGetLocalSize(mat,&s2,&s3);
2005: if (rr) {
2006: VecGetLocalSize(rr,&s1);
2007: if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size");
2008: /* Overlap communication with computation. */
2009: VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);
2010: }
2011: if (ll) {
2012: VecGetLocalSize(ll,&s1);
2013: if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size");
2014: (*b->ops->diagonalscale)(b,ll,0);
2015: }
2016: /* scale the diagonal block */
2017: (*a->ops->diagonalscale)(a,ll,rr);
2019: if (rr) {
2020: /* Do a scatter end and then right scale the off-diagonal block */
2021: VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);
2022: (*b->ops->diagonalscale)(b,0,aij->lvec);
2023: }
2024: return(0);
2025: }
2027: PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A)
2028: {
2029: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2033: MatSetUnfactored(a->A);
2034: return(0);
2035: }
2037: PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag)
2038: {
2039: Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data;
2040: Mat a,b,c,d;
2041: PetscBool flg;
2045: a = matA->A; b = matA->B;
2046: c = matB->A; d = matB->B;
2048: MatEqual(a,c,&flg);
2049: if (flg) {
2050: MatEqual(b,d,&flg);
2051: }
2052: MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
2053: return(0);
2054: }
2056: PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str)
2057: {
2059: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2060: Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data;
2063: /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
2064: if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
2065: /* because of the column compression in the off-processor part of the matrix a->B,
2066: the number of columns in a->B and b->B may be different, hence we cannot call
2067: the MatCopy() directly on the two parts. If need be, we can provide a more
2068: efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices
2069: then copying the submatrices */
2070: MatCopy_Basic(A,B,str);
2071: } else {
2072: MatCopy(a->A,b->A,str);
2073: MatCopy(a->B,b->B,str);
2074: }
2075: PetscObjectStateIncrease((PetscObject)B);
2076: return(0);
2077: }
2079: PetscErrorCode MatSetUp_MPIAIJ(Mat A)
2080: {
2084: MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
2085: return(0);
2086: }
2088: /*
2089: Computes the number of nonzeros per row needed for preallocation when X and Y
2090: have different nonzero structure.
2091: */
2092: 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)
2093: {
2094: PetscInt i,j,k,nzx,nzy;
2097: /* Set the number of nonzeros in the new matrix */
2098: for (i=0; i<m; i++) {
2099: const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i];
2100: nzx = xi[i+1] - xi[i];
2101: nzy = yi[i+1] - yi[i];
2102: nnz[i] = 0;
2103: for (j=0,k=0; j<nzx; j++) { /* Point in X */
2104: for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */
2105: if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++; /* Skip duplicate */
2106: nnz[i]++;
2107: }
2108: for (; k<nzy; k++) nnz[i]++;
2109: }
2110: return(0);
2111: }
2113: /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */
2114: static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz)
2115: {
2117: PetscInt m = Y->rmap->N;
2118: Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data;
2119: Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data;
2122: MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);
2123: return(0);
2124: }
2126: PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
2127: {
2129: Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data;
2130: PetscBLASInt bnz,one=1;
2131: Mat_SeqAIJ *x,*y;
2134: if (str == SAME_NONZERO_PATTERN) {
2135: PetscScalar alpha = a;
2136: x = (Mat_SeqAIJ*)xx->A->data;
2137: PetscBLASIntCast(x->nz,&bnz);
2138: y = (Mat_SeqAIJ*)yy->A->data;
2139: PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2140: x = (Mat_SeqAIJ*)xx->B->data;
2141: y = (Mat_SeqAIJ*)yy->B->data;
2142: PetscBLASIntCast(x->nz,&bnz);
2143: PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2144: PetscObjectStateIncrease((PetscObject)Y);
2145: } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
2146: MatAXPY_Basic(Y,a,X,str);
2147: } else {
2148: Mat B;
2149: PetscInt *nnz_d,*nnz_o;
2150: PetscMalloc1(yy->A->rmap->N,&nnz_d);
2151: PetscMalloc1(yy->B->rmap->N,&nnz_o);
2152: MatCreate(PetscObjectComm((PetscObject)Y),&B);
2153: PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
2154: MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
2155: MatSetBlockSizesFromMats(B,Y,Y);
2156: MatSetType(B,MATMPIAIJ);
2157: MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);
2158: MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
2159: MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);
2160: MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
2161: MatHeaderReplace(Y,&B);
2162: PetscFree(nnz_d);
2163: PetscFree(nnz_o);
2164: }
2165: return(0);
2166: }
2168: extern PetscErrorCode MatConjugate_SeqAIJ(Mat);
2170: PetscErrorCode MatConjugate_MPIAIJ(Mat mat)
2171: {
2172: #if defined(PETSC_USE_COMPLEX)
2174: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
2177: MatConjugate_SeqAIJ(aij->A);
2178: MatConjugate_SeqAIJ(aij->B);
2179: #else
2181: #endif
2182: return(0);
2183: }
2185: PetscErrorCode MatRealPart_MPIAIJ(Mat A)
2186: {
2187: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2191: MatRealPart(a->A);
2192: MatRealPart(a->B);
2193: return(0);
2194: }
2196: PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A)
2197: {
2198: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2202: MatImaginaryPart(a->A);
2203: MatImaginaryPart(a->B);
2204: return(0);
2205: }
2207: PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2208: {
2209: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2211: PetscInt i,*idxb = 0;
2212: PetscScalar *va,*vb;
2213: Vec vtmp;
2216: MatGetRowMaxAbs(a->A,v,idx);
2217: VecGetArray(v,&va);
2218: if (idx) {
2219: for (i=0; i<A->rmap->n; i++) {
2220: if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
2221: }
2222: }
2224: VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
2225: if (idx) {
2226: PetscMalloc1(A->rmap->n,&idxb);
2227: }
2228: MatGetRowMaxAbs(a->B,vtmp,idxb);
2229: VecGetArray(vtmp,&vb);
2231: for (i=0; i<A->rmap->n; i++) {
2232: if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {
2233: va[i] = vb[i];
2234: if (idx) idx[i] = a->garray[idxb[i]];
2235: }
2236: }
2238: VecRestoreArray(v,&va);
2239: VecRestoreArray(vtmp,&vb);
2240: PetscFree(idxb);
2241: VecDestroy(&vtmp);
2242: return(0);
2243: }
2245: PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2246: {
2247: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2249: PetscInt i,*idxb = 0;
2250: PetscScalar *va,*vb;
2251: Vec vtmp;
2254: MatGetRowMinAbs(a->A,v,idx);
2255: VecGetArray(v,&va);
2256: if (idx) {
2257: for (i=0; i<A->cmap->n; i++) {
2258: if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
2259: }
2260: }
2262: VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
2263: if (idx) {
2264: PetscMalloc1(A->rmap->n,&idxb);
2265: }
2266: MatGetRowMinAbs(a->B,vtmp,idxb);
2267: VecGetArray(vtmp,&vb);
2269: for (i=0; i<A->rmap->n; i++) {
2270: if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) {
2271: va[i] = vb[i];
2272: if (idx) idx[i] = a->garray[idxb[i]];
2273: }
2274: }
2276: VecRestoreArray(v,&va);
2277: VecRestoreArray(vtmp,&vb);
2278: PetscFree(idxb);
2279: VecDestroy(&vtmp);
2280: return(0);
2281: }
2283: PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2284: {
2285: Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data;
2286: PetscInt n = A->rmap->n;
2287: PetscInt cstart = A->cmap->rstart;
2288: PetscInt *cmap = mat->garray;
2289: PetscInt *diagIdx, *offdiagIdx;
2290: Vec diagV, offdiagV;
2291: PetscScalar *a, *diagA, *offdiagA;
2292: PetscInt r;
2296: PetscMalloc2(n,&diagIdx,n,&offdiagIdx);
2297: VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);
2298: VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);
2299: MatGetRowMin(mat->A, diagV, diagIdx);
2300: MatGetRowMin(mat->B, offdiagV, offdiagIdx);
2301: VecGetArray(v, &a);
2302: VecGetArray(diagV, &diagA);
2303: VecGetArray(offdiagV, &offdiagA);
2304: for (r = 0; r < n; ++r) {
2305: if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) {
2306: a[r] = diagA[r];
2307: idx[r] = cstart + diagIdx[r];
2308: } else {
2309: a[r] = offdiagA[r];
2310: idx[r] = cmap[offdiagIdx[r]];
2311: }
2312: }
2313: VecRestoreArray(v, &a);
2314: VecRestoreArray(diagV, &diagA);
2315: VecRestoreArray(offdiagV, &offdiagA);
2316: VecDestroy(&diagV);
2317: VecDestroy(&offdiagV);
2318: PetscFree2(diagIdx, offdiagIdx);
2319: return(0);
2320: }
2322: PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2323: {
2324: Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data;
2325: PetscInt n = A->rmap->n;
2326: PetscInt cstart = A->cmap->rstart;
2327: PetscInt *cmap = mat->garray;
2328: PetscInt *diagIdx, *offdiagIdx;
2329: Vec diagV, offdiagV;
2330: PetscScalar *a, *diagA, *offdiagA;
2331: PetscInt r;
2335: PetscMalloc2(n,&diagIdx,n,&offdiagIdx);
2336: VecCreateSeq(PETSC_COMM_SELF, n, &diagV);
2337: VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);
2338: MatGetRowMax(mat->A, diagV, diagIdx);
2339: MatGetRowMax(mat->B, offdiagV, offdiagIdx);
2340: VecGetArray(v, &a);
2341: VecGetArray(diagV, &diagA);
2342: VecGetArray(offdiagV, &offdiagA);
2343: for (r = 0; r < n; ++r) {
2344: if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) {
2345: a[r] = diagA[r];
2346: idx[r] = cstart + diagIdx[r];
2347: } else {
2348: a[r] = offdiagA[r];
2349: idx[r] = cmap[offdiagIdx[r]];
2350: }
2351: }
2352: VecRestoreArray(v, &a);
2353: VecRestoreArray(diagV, &diagA);
2354: VecRestoreArray(offdiagV, &offdiagA);
2355: VecDestroy(&diagV);
2356: VecDestroy(&offdiagV);
2357: PetscFree2(diagIdx, offdiagIdx);
2358: return(0);
2359: }
2361: PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat)
2362: {
2364: Mat *dummy;
2367: MatCreateSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);
2368: *newmat = *dummy;
2369: PetscFree(dummy);
2370: return(0);
2371: }
2373: PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values)
2374: {
2375: Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data;
2379: MatInvertBlockDiagonal(a->A,values);
2380: A->factorerrortype = a->A->factorerrortype;
2381: return(0);
2382: }
2384: static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx)
2385: {
2387: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data;
2390: MatSetRandom(aij->A,rctx);
2391: MatSetRandom(aij->B,rctx);
2392: MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);
2393: MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);
2394: return(0);
2395: }
2397: PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ(Mat A,PetscBool sc)
2398: {
2400: if (sc) A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ_Scalable;
2401: else A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ;
2402: return(0);
2403: }
2405: /*@
2406: MatMPIAIJSetUseScalableIncreaseOverlap - Determine if the matrix uses a scalable algorithm to compute the overlap
2408: Collective on Mat
2410: Input Parameters:
2411: + A - the matrix
2412: - sc - PETSC_TRUE indicates use the scalable algorithm (default is not to use the scalable algorithm)
2414: Level: advanced
2416: @*/
2417: PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap(Mat A,PetscBool sc)
2418: {
2419: PetscErrorCode ierr;
2422: PetscTryMethod(A,"MatMPIAIJSetUseScalableIncreaseOverlap_C",(Mat,PetscBool),(A,sc));
2423: return(0);
2424: }
2426: PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptionItems *PetscOptionsObject,Mat A)
2427: {
2428: PetscErrorCode ierr;
2429: PetscBool sc = PETSC_FALSE,flg;
2432: PetscOptionsHead(PetscOptionsObject,"MPIAIJ options");
2433: PetscObjectOptionsBegin((PetscObject)A);
2434: if (A->ops->increaseoverlap == MatIncreaseOverlap_MPIAIJ_Scalable) sc = PETSC_TRUE;
2435: PetscOptionsBool("-mat_increase_overlap_scalable","Use a scalable algorithm to compute the overlap","MatIncreaseOverlap",sc,&sc,&flg);
2436: if (flg) {
2437: MatMPIAIJSetUseScalableIncreaseOverlap(A,sc);
2438: }
2439: PetscOptionsEnd();
2440: return(0);
2441: }
2443: PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a)
2444: {
2446: Mat_MPIAIJ *maij = (Mat_MPIAIJ*)Y->data;
2447: Mat_SeqAIJ *aij = (Mat_SeqAIJ*)maij->A->data;
2450: if (!Y->preallocated) {
2451: MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);
2452: } else if (!aij->nz) {
2453: PetscInt nonew = aij->nonew;
2454: MatSeqAIJSetPreallocation(maij->A,1,NULL);
2455: aij->nonew = nonew;
2456: }
2457: MatShift_Basic(Y,a);
2458: return(0);
2459: }
2461: PetscErrorCode MatMissingDiagonal_MPIAIJ(Mat A,PetscBool *missing,PetscInt *d)
2462: {
2463: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2467: if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
2468: MatMissingDiagonal(a->A,missing,d);
2469: if (d) {
2470: PetscInt rstart;
2471: MatGetOwnershipRange(A,&rstart,NULL);
2472: *d += rstart;
2474: }
2475: return(0);
2476: }
2479: /* -------------------------------------------------------------------*/
2480: static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ,
2481: MatGetRow_MPIAIJ,
2482: MatRestoreRow_MPIAIJ,
2483: MatMult_MPIAIJ,
2484: /* 4*/ MatMultAdd_MPIAIJ,
2485: MatMultTranspose_MPIAIJ,
2486: MatMultTransposeAdd_MPIAIJ,
2487: 0,
2488: 0,
2489: 0,
2490: /*10*/ 0,
2491: 0,
2492: 0,
2493: MatSOR_MPIAIJ,
2494: MatTranspose_MPIAIJ,
2495: /*15*/ MatGetInfo_MPIAIJ,
2496: MatEqual_MPIAIJ,
2497: MatGetDiagonal_MPIAIJ,
2498: MatDiagonalScale_MPIAIJ,
2499: MatNorm_MPIAIJ,
2500: /*20*/ MatAssemblyBegin_MPIAIJ,
2501: MatAssemblyEnd_MPIAIJ,
2502: MatSetOption_MPIAIJ,
2503: MatZeroEntries_MPIAIJ,
2504: /*24*/ MatZeroRows_MPIAIJ,
2505: 0,
2506: 0,
2507: 0,
2508: 0,
2509: /*29*/ MatSetUp_MPIAIJ,
2510: 0,
2511: 0,
2512: MatGetDiagonalBlock_MPIAIJ,
2513: 0,
2514: /*34*/ MatDuplicate_MPIAIJ,
2515: 0,
2516: 0,
2517: 0,
2518: 0,
2519: /*39*/ MatAXPY_MPIAIJ,
2520: MatCreateSubMatrices_MPIAIJ,
2521: MatIncreaseOverlap_MPIAIJ,
2522: MatGetValues_MPIAIJ,
2523: MatCopy_MPIAIJ,
2524: /*44*/ MatGetRowMax_MPIAIJ,
2525: MatScale_MPIAIJ,
2526: MatShift_MPIAIJ,
2527: MatDiagonalSet_MPIAIJ,
2528: MatZeroRowsColumns_MPIAIJ,
2529: /*49*/ MatSetRandom_MPIAIJ,
2530: 0,
2531: 0,
2532: 0,
2533: 0,
2534: /*54*/ MatFDColoringCreate_MPIXAIJ,
2535: 0,
2536: MatSetUnfactored_MPIAIJ,
2537: MatPermute_MPIAIJ,
2538: 0,
2539: /*59*/ MatCreateSubMatrix_MPIAIJ,
2540: MatDestroy_MPIAIJ,
2541: MatView_MPIAIJ,
2542: 0,
2543: MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ,
2544: /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ,
2545: MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ,
2546: 0,
2547: 0,
2548: 0,
2549: /*69*/ MatGetRowMaxAbs_MPIAIJ,
2550: MatGetRowMinAbs_MPIAIJ,
2551: 0,
2552: 0,
2553: 0,
2554: 0,
2555: /*75*/ MatFDColoringApply_AIJ,
2556: MatSetFromOptions_MPIAIJ,
2557: 0,
2558: 0,
2559: MatFindZeroDiagonals_MPIAIJ,
2560: /*80*/ 0,
2561: 0,
2562: 0,
2563: /*83*/ MatLoad_MPIAIJ,
2564: 0,
2565: 0,
2566: 0,
2567: 0,
2568: 0,
2569: /*89*/ MatMatMult_MPIAIJ_MPIAIJ,
2570: MatMatMultSymbolic_MPIAIJ_MPIAIJ,
2571: MatMatMultNumeric_MPIAIJ_MPIAIJ,
2572: MatPtAP_MPIAIJ_MPIAIJ,
2573: MatPtAPSymbolic_MPIAIJ_MPIAIJ,
2574: /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ,
2575: 0,
2576: 0,
2577: 0,
2578: 0,
2579: /*99*/ 0,
2580: 0,
2581: 0,
2582: MatConjugate_MPIAIJ,
2583: 0,
2584: /*104*/MatSetValuesRow_MPIAIJ,
2585: MatRealPart_MPIAIJ,
2586: MatImaginaryPart_MPIAIJ,
2587: 0,
2588: 0,
2589: /*109*/0,
2590: 0,
2591: MatGetRowMin_MPIAIJ,
2592: 0,
2593: MatMissingDiagonal_MPIAIJ,
2594: /*114*/MatGetSeqNonzeroStructure_MPIAIJ,
2595: 0,
2596: MatGetGhosts_MPIAIJ,
2597: 0,
2598: 0,
2599: /*119*/0,
2600: 0,
2601: 0,
2602: 0,
2603: MatGetMultiProcBlock_MPIAIJ,
2604: /*124*/MatFindNonzeroRows_MPIAIJ,
2605: MatGetColumnNorms_MPIAIJ,
2606: MatInvertBlockDiagonal_MPIAIJ,
2607: 0,
2608: MatCreateSubMatricesMPI_MPIAIJ,
2609: /*129*/0,
2610: MatTransposeMatMult_MPIAIJ_MPIAIJ,
2611: MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ,
2612: MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ,
2613: 0,
2614: /*134*/0,
2615: 0,
2616: MatRARt_MPIAIJ_MPIAIJ,
2617: 0,
2618: 0,
2619: /*139*/MatSetBlockSizes_MPIAIJ,
2620: 0,
2621: 0,
2622: MatFDColoringSetUp_MPIXAIJ,
2623: MatFindOffBlockDiagonalEntries_MPIAIJ,
2624: /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ
2625: };
2627: /* ----------------------------------------------------------------------------------------*/
2629: PetscErrorCode MatStoreValues_MPIAIJ(Mat mat)
2630: {
2631: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
2635: MatStoreValues(aij->A);
2636: MatStoreValues(aij->B);
2637: return(0);
2638: }
2640: PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat)
2641: {
2642: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
2646: MatRetrieveValues(aij->A);
2647: MatRetrieveValues(aij->B);
2648: return(0);
2649: }
2651: PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
2652: {
2653: Mat_MPIAIJ *b;
2657: PetscLayoutSetUp(B->rmap);
2658: PetscLayoutSetUp(B->cmap);
2659: b = (Mat_MPIAIJ*)B->data;
2661: #if defined(PETSC_USE_CTABLE)
2662: PetscTableDestroy(&b->colmap);
2663: #else
2664: PetscFree(b->colmap);
2665: #endif
2666: PetscFree(b->garray);
2667: VecDestroy(&b->lvec);
2668: VecScatterDestroy(&b->Mvctx);
2670: /* Because the B will have been resized we simply destroy it and create a new one each time */
2671: MatDestroy(&b->B);
2672: MatCreate(PETSC_COMM_SELF,&b->B);
2673: MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);
2674: MatSetBlockSizesFromMats(b->B,B,B);
2675: MatSetType(b->B,MATSEQAIJ);
2676: PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);
2678: if (!B->preallocated) {
2679: MatCreate(PETSC_COMM_SELF,&b->A);
2680: MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
2681: MatSetBlockSizesFromMats(b->A,B,B);
2682: MatSetType(b->A,MATSEQAIJ);
2683: PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
2684: }
2686: MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);
2687: MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);
2688: B->preallocated = PETSC_TRUE;
2689: B->was_assembled = PETSC_FALSE;
2690: B->assembled = PETSC_FALSE;;
2691: return(0);
2692: }
2694: PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
2695: {
2696: Mat mat;
2697: Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data;
2701: *newmat = 0;
2702: MatCreate(PetscObjectComm((PetscObject)matin),&mat);
2703: MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
2704: MatSetBlockSizesFromMats(mat,matin,matin);
2705: MatSetType(mat,((PetscObject)matin)->type_name);
2706: PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));
2707: a = (Mat_MPIAIJ*)mat->data;
2709: mat->factortype = matin->factortype;
2710: mat->assembled = PETSC_TRUE;
2711: mat->insertmode = NOT_SET_VALUES;
2712: mat->preallocated = PETSC_TRUE;
2714: a->size = oldmat->size;
2715: a->rank = oldmat->rank;
2716: a->donotstash = oldmat->donotstash;
2717: a->roworiented = oldmat->roworiented;
2718: a->rowindices = 0;
2719: a->rowvalues = 0;
2720: a->getrowactive = PETSC_FALSE;
2722: PetscLayoutReference(matin->rmap,&mat->rmap);
2723: PetscLayoutReference(matin->cmap,&mat->cmap);
2725: if (oldmat->colmap) {
2726: #if defined(PETSC_USE_CTABLE)
2727: PetscTableCreateCopy(oldmat->colmap,&a->colmap);
2728: #else
2729: PetscMalloc1(mat->cmap->N,&a->colmap);
2730: PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));
2731: PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));
2732: #endif
2733: } else a->colmap = 0;
2734: if (oldmat->garray) {
2735: PetscInt len;
2736: len = oldmat->B->cmap->n;
2737: PetscMalloc1(len+1,&a->garray);
2738: PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
2739: if (len) { PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt)); }
2740: } else a->garray = 0;
2742: VecDuplicate(oldmat->lvec,&a->lvec);
2743: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
2744: VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
2745: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);
2746: MatDuplicate(oldmat->A,cpvalues,&a->A);
2747: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
2748: MatDuplicate(oldmat->B,cpvalues,&a->B);
2749: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
2750: PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
2751: *newmat = mat;
2752: return(0);
2753: }
2755: PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer)
2756: {
2757: PetscScalar *vals,*svals;
2758: MPI_Comm comm;
2760: PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag;
2761: PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0;
2762: PetscInt header[4],*rowlengths = 0,M,N,m,*cols;
2763: PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols;
2764: PetscInt cend,cstart,n,*rowners;
2765: int fd;
2766: PetscInt bs = newMat->rmap->bs;
2769: /* force binary viewer to load .info file if it has not yet done so */
2770: PetscViewerSetUp(viewer);
2771: PetscObjectGetComm((PetscObject)viewer,&comm);
2772: MPI_Comm_size(comm,&size);
2773: MPI_Comm_rank(comm,&rank);
2774: PetscViewerBinaryGetDescriptor(viewer,&fd);
2775: if (!rank) {
2776: PetscBinaryRead(fd,(char*)header,4,PETSC_INT);
2777: if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
2778: if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as MATMPIAIJ");
2779: }
2781: PetscOptionsBegin(comm,NULL,"Options for loading MATMPIAIJ matrix","Mat");
2782: PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
2783: PetscOptionsEnd();
2784: if (bs < 0) bs = 1;
2786: MPI_Bcast(header+1,3,MPIU_INT,0,comm);
2787: M = header[1]; N = header[2];
2789: /* If global sizes are set, check if they are consistent with that given in the file */
2790: 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);
2791: 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);
2793: /* determine ownership of all (block) rows */
2794: if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs);
2795: if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */
2796: else m = newMat->rmap->n; /* Set by user */
2798: PetscMalloc1(size+1,&rowners);
2799: MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);
2801: /* First process needs enough room for process with most rows */
2802: if (!rank) {
2803: mmax = rowners[1];
2804: for (i=2; i<=size; i++) {
2805: mmax = PetscMax(mmax, rowners[i]);
2806: }
2807: } else mmax = -1; /* unused, but compilers complain */
2809: rowners[0] = 0;
2810: for (i=2; i<=size; i++) {
2811: rowners[i] += rowners[i-1];
2812: }
2813: rstart = rowners[rank];
2814: rend = rowners[rank+1];
2816: /* distribute row lengths to all processors */
2817: PetscMalloc2(m,&ourlens,m,&offlens);
2818: if (!rank) {
2819: PetscBinaryRead(fd,ourlens,m,PETSC_INT);
2820: PetscMalloc1(mmax,&rowlengths);
2821: PetscCalloc1(size,&procsnz);
2822: for (j=0; j<m; j++) {
2823: procsnz[0] += ourlens[j];
2824: }
2825: for (i=1; i<size; i++) {
2826: PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);
2827: /* calculate the number of nonzeros on each processor */
2828: for (j=0; j<rowners[i+1]-rowners[i]; j++) {
2829: procsnz[i] += rowlengths[j];
2830: }
2831: MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);
2832: }
2833: PetscFree(rowlengths);
2834: } else {
2835: MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);
2836: }
2838: if (!rank) {
2839: /* determine max buffer needed and allocate it */
2840: maxnz = 0;
2841: for (i=0; i<size; i++) {
2842: maxnz = PetscMax(maxnz,procsnz[i]);
2843: }
2844: PetscMalloc1(maxnz,&cols);
2846: /* read in my part of the matrix column indices */
2847: nz = procsnz[0];
2848: PetscMalloc1(nz,&mycols);
2849: PetscBinaryRead(fd,mycols,nz,PETSC_INT);
2851: /* read in every one elses and ship off */
2852: for (i=1; i<size; i++) {
2853: nz = procsnz[i];
2854: PetscBinaryRead(fd,cols,nz,PETSC_INT);
2855: MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);
2856: }
2857: PetscFree(cols);
2858: } else {
2859: /* determine buffer space needed for message */
2860: nz = 0;
2861: for (i=0; i<m; i++) {
2862: nz += ourlens[i];
2863: }
2864: PetscMalloc1(nz,&mycols);
2866: /* receive message of column indices*/
2867: MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);
2868: }
2870: /* determine column ownership if matrix is not square */
2871: if (N != M) {
2872: if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank);
2873: else n = newMat->cmap->n;
2874: MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);
2875: cstart = cend - n;
2876: } else {
2877: cstart = rstart;
2878: cend = rend;
2879: n = cend - cstart;
2880: }
2882: /* loop over local rows, determining number of off diagonal entries */
2883: PetscMemzero(offlens,m*sizeof(PetscInt));
2884: jj = 0;
2885: for (i=0; i<m; i++) {
2886: for (j=0; j<ourlens[i]; j++) {
2887: if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++;
2888: jj++;
2889: }
2890: }
2892: for (i=0; i<m; i++) {
2893: ourlens[i] -= offlens[i];
2894: }
2895: MatSetSizes(newMat,m,n,M,N);
2897: if (bs > 1) {MatSetBlockSize(newMat,bs);}
2899: MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);
2901: for (i=0; i<m; i++) {
2902: ourlens[i] += offlens[i];
2903: }
2905: if (!rank) {
2906: PetscMalloc1(maxnz+1,&vals);
2908: /* read in my part of the matrix numerical values */
2909: nz = procsnz[0];
2910: PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
2912: /* insert into matrix */
2913: jj = rstart;
2914: smycols = mycols;
2915: svals = vals;
2916: for (i=0; i<m; i++) {
2917: MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
2918: smycols += ourlens[i];
2919: svals += ourlens[i];
2920: jj++;
2921: }
2923: /* read in other processors and ship out */
2924: for (i=1; i<size; i++) {
2925: nz = procsnz[i];
2926: PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
2927: MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);
2928: }
2929: PetscFree(procsnz);
2930: } else {
2931: /* receive numeric values */
2932: PetscMalloc1(nz+1,&vals);
2934: /* receive message of values*/
2935: MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);
2937: /* insert into matrix */
2938: jj = rstart;
2939: smycols = mycols;
2940: svals = vals;
2941: for (i=0; i<m; i++) {
2942: MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
2943: smycols += ourlens[i];
2944: svals += ourlens[i];
2945: jj++;
2946: }
2947: }
2948: PetscFree2(ourlens,offlens);
2949: PetscFree(vals);
2950: PetscFree(mycols);
2951: PetscFree(rowners);
2952: MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);
2953: MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);
2954: return(0);
2955: }
2957: /* Not scalable because of ISAllGather() unless getting all columns. */
2958: PetscErrorCode ISGetSeqIS_Private(Mat mat,IS iscol,IS *isseq)
2959: {
2961: IS iscol_local;
2962: PetscBool isstride;
2963: PetscMPIInt lisstride=0,gisstride;
2966: /* check if we are grabbing all columns*/
2967: PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&isstride);
2969: if (isstride) {
2970: PetscInt start,len,mstart,mlen;
2971: ISStrideGetInfo(iscol,&start,NULL);
2972: ISGetLocalSize(iscol,&len);
2973: MatGetOwnershipRangeColumn(mat,&mstart,&mlen);
2974: if (mstart == start && mlen-mstart == len) lisstride = 1;
2975: }
2977: MPIU_Allreduce(&lisstride,&gisstride,1,MPI_INT,MPI_MIN,PetscObjectComm((PetscObject)mat));
2978: if (gisstride) {
2979: PetscInt N;
2980: MatGetSize(mat,NULL,&N);
2981: ISCreateStride(PetscObjectComm((PetscObject)mat),N,0,1,&iscol_local);
2982: ISSetIdentity(iscol_local);
2983: PetscInfo(mat,"Optimizing for obtaining all columns of the matrix; skipping ISAllGather()\n");
2984: } else {
2985: PetscInt cbs;
2986: ISGetBlockSize(iscol,&cbs);
2987: ISAllGather(iscol,&iscol_local);
2988: ISSetBlockSize(iscol_local,cbs);
2989: }
2991: *isseq = iscol_local;
2992: return(0);
2993: }
2995: /*
2996: Used by MatCreateSubMatrix_MPIAIJ_SameRowColDist() to avoid ISAllGather() and global size of iscol_local
2997: (see MatCreateSubMatrix_MPIAIJ_nonscalable)
2999: Input Parameters:
3000: mat - matrix
3001: isrow - parallel row index set; its local indices are a subset of local columns of mat,
3002: i.e., mat->rstart <= isrow[i] < mat->rend
3003: iscol - parallel column index set; its local indices are a subset of local columns of mat,
3004: i.e., mat->cstart <= iscol[i] < mat->cend
3005: Output Parameter:
3006: isrow_d,iscol_d - sequential row and column index sets for retrieving mat->A
3007: iscol_o - sequential column index set for retrieving mat->B
3008: garray - column map; garray[i] indicates global location of iscol_o[i] in iscol
3009: */
3010: PetscErrorCode ISGetSeqIS_SameColDist_Private(Mat mat,IS isrow,IS iscol,IS *isrow_d,IS *iscol_d,IS *iscol_o,const PetscInt *garray[])
3011: {
3013: Vec x,cmap;
3014: const PetscInt *is_idx;
3015: PetscScalar *xarray,*cmaparray;
3016: PetscInt ncols,isstart,*idx,m,rstart,*cmap1,count;
3017: Mat_MPIAIJ *a=(Mat_MPIAIJ*)mat->data;
3018: Mat B=a->B;
3019: Vec lvec=a->lvec,lcmap;
3020: PetscInt i,cstart,cend,Bn=B->cmap->N;
3021: MPI_Comm comm;
3024: PetscObjectGetComm((PetscObject)mat,&comm);
3025: ISGetLocalSize(iscol,&ncols);
3027: /* (1) iscol is a sub-column vector of mat, pad it with '-1.' to form a full vector x */
3028: MatCreateVecs(mat,&x,NULL);
3029: VecDuplicate(x,&cmap);
3030: VecSet(x,-1.0);
3032: /* Get start indices */
3033: MPI_Scan(&ncols,&isstart,1,MPIU_INT,MPI_SUM,comm);
3034: isstart -= ncols;
3035: MatGetOwnershipRangeColumn(mat,&cstart,&cend);
3037: ISGetIndices(iscol,&is_idx);
3038: VecGetArray(x,&xarray);
3039: VecGetArray(cmap,&cmaparray);
3040: PetscMalloc1(ncols,&idx);
3041: for (i=0; i<ncols; i++) {
3042: xarray[is_idx[i]-cstart] = (PetscScalar)is_idx[i];
3043: cmaparray[is_idx[i]-cstart] = i + isstart; /* global index of iscol[i] */
3044: idx[i] = is_idx[i]-cstart; /* local index of iscol[i] */
3045: }
3046: VecRestoreArray(x,&xarray);
3047: VecRestoreArray(cmap,&cmaparray);
3048: ISRestoreIndices(iscol,&is_idx);
3050: /* Get iscol_d */
3051: ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,iscol_d);
3052: ISGetBlockSize(iscol,&i);
3053: ISSetBlockSize(*iscol_d,i);
3055: /* Get isrow_d */
3056: ISGetLocalSize(isrow,&m);
3057: rstart = mat->rmap->rstart;
3058: PetscMalloc1(m,&idx);
3059: ISGetIndices(isrow,&is_idx);
3060: for (i=0; i<m; i++) idx[i] = is_idx[i]-rstart;
3061: ISRestoreIndices(isrow,&is_idx);
3063: ISCreateGeneral(PETSC_COMM_SELF,m,idx,PETSC_OWN_POINTER,isrow_d);
3064: ISGetBlockSize(isrow,&i);
3065: ISSetBlockSize(*isrow_d,i);
3067: /* (2) Scatter x and cmap using aij->Mvctx to get their off-process portions (see MatMult_MPIAIJ) */
3068: VecScatterBegin(a->Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);
3070: VecDuplicate(lvec,&lcmap);
3072: VecScatterEnd(a->Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);
3073: VecScatterBegin(a->Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);
3074: VecScatterEnd(a->Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);
3076: /* (3) create sequential iscol_o (a subset of iscol) and isgarray */
3077: /* off-process column indices */
3078: count = 0;
3079: PetscMalloc1(Bn,&idx);
3080: PetscMalloc1(Bn,&cmap1);
3082: VecGetArray(lvec,&xarray);
3083: VecGetArray(lcmap,&cmaparray);
3084: for (i=0; i<Bn; i++) {
3085: if (PetscRealPart(xarray[i]) > -1.0) {
3086: idx[count] = i; /* local column index in off-diagonal part B */
3087: cmap1[count++] = (PetscInt)PetscRealPart(cmaparray[i]); /* column index in submat */
3088: }
3089: }
3090: VecRestoreArray(lvec,&xarray);
3091: VecRestoreArray(lcmap,&cmaparray);
3093: ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_COPY_VALUES,iscol_o);
3094: /* cannot ensure iscol_o has same blocksize as iscol! */
3096: PetscFree(idx);
3098: *garray = cmap1;
3100: VecDestroy(&x);
3101: VecDestroy(&cmap);
3102: VecDestroy(&lcmap);
3103: return(0);
3104: }
3106: /* isrow and iscol have same processor distribution as mat, output *submat is a submatrix of local mat */
3107: PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowColDist(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *submat)
3108: {
3110: Mat_MPIAIJ *a = (Mat_MPIAIJ*)mat->data,*asub;
3111: Mat M = NULL;
3112: MPI_Comm comm;
3113: IS iscol_d,isrow_d,iscol_o;
3114: Mat Asub = NULL,Bsub = NULL;
3115: PetscInt n;
3118: PetscObjectGetComm((PetscObject)mat,&comm);
3120: if (call == MAT_REUSE_MATRIX) {
3121: /* Retrieve isrow_d, iscol_d and iscol_o from submat */
3122: PetscObjectQuery((PetscObject)*submat,"isrow_d",(PetscObject*)&isrow_d);
3123: if (!isrow_d) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"isrow_d passed in was not used before, cannot reuse");
3125: PetscObjectQuery((PetscObject)*submat,"iscol_d",(PetscObject*)&iscol_d);
3126: if (!iscol_d) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"iscol_d passed in was not used before, cannot reuse");
3128: PetscObjectQuery((PetscObject)*submat,"iscol_o",(PetscObject*)&iscol_o);
3129: if (!iscol_o) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"iscol_o passed in was not used before, cannot reuse");
3131: /* Update diagonal and off-diagonal portions of submat */
3132: asub = (Mat_MPIAIJ*)(*submat)->data;
3133: MatCreateSubMatrix_SeqAIJ(a->A,isrow_d,iscol_d,PETSC_DECIDE,MAT_REUSE_MATRIX,&asub->A);
3134: ISGetLocalSize(iscol_o,&n);
3135: if (n) {
3136: MatCreateSubMatrix_SeqAIJ(a->B,isrow_d,iscol_o,PETSC_DECIDE,MAT_REUSE_MATRIX,&asub->B);
3137: }
3138: MatAssemblyBegin(*submat,MAT_FINAL_ASSEMBLY);
3139: MatAssemblyEnd(*submat,MAT_FINAL_ASSEMBLY);
3141: } else { /* call == MAT_INITIAL_MATRIX) */
3142: const PetscInt *garray;
3143: PetscInt BsubN;
3145: /* Create isrow_d, iscol_d, iscol_o and isgarray (replace isgarray with array?) */
3146: ISGetSeqIS_SameColDist_Private(mat,isrow,iscol,&isrow_d,&iscol_d,&iscol_o,&garray);
3148: /* Create local submatrices Asub and Bsub */
3149: MatCreateSubMatrix_SeqAIJ(a->A,isrow_d,iscol_d,PETSC_DECIDE,MAT_INITIAL_MATRIX,&Asub);
3150: MatCreateSubMatrix_SeqAIJ(a->B,isrow_d,iscol_o,PETSC_DECIDE,MAT_INITIAL_MATRIX,&Bsub);
3152: /* Create submatrix M */
3153: MatCreateMPIAIJWithSeqAIJ(comm,Asub,Bsub,garray,&M);
3155: /* If Bsub has empty columns, compress iscol_o such that it will retrieve condensed Bsub from a->B during reuse */
3156: asub = (Mat_MPIAIJ*)M->data;
3158: ISGetLocalSize(iscol_o,&BsubN);
3159: n = asub->B->cmap->N;
3160: if (BsubN > n) {
3161: /* This case can be tested using ~petsc/src/tao/bound/examples/tutorials/runplate2_3 */
3162: const PetscInt *idx;
3163: PetscInt i,j,*idx_new,*subgarray = asub->garray;
3164: PetscInfo2(M,"submatrix Bn %D != BsubN %D, update iscol_o\n",n,BsubN);
3166: PetscMalloc1(n,&idx_new);
3167: j = 0;
3168: ISGetIndices(iscol_o,&idx);
3169: for (i=0; i<n; i++) {
3170: if (j >= BsubN) break;
3171: while (subgarray[i] > garray[j]) j++;
3173: if (subgarray[i] == garray[j]) {
3174: idx_new[i] = idx[j++];
3175: } else SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"subgarray[%D]=%D cannot < garray[%D]=%D",i,subgarray[i],j,garray[j]);
3176: }
3177: ISRestoreIndices(iscol_o,&idx);
3179: ISDestroy(&iscol_o);
3180: ISCreateGeneral(PETSC_COMM_SELF,n,idx_new,PETSC_OWN_POINTER,&iscol_o);
3182: } else if (BsubN < n) {
3183: SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Columns of Bsub cannot be smaller than B's",BsubN,asub->B->cmap->N);
3184: }
3186: PetscFree(garray);
3187: *submat = M;
3189: /* Save isrow_d, iscol_d and iscol_o used in processor for next request */
3190: PetscObjectCompose((PetscObject)M,"isrow_d",(PetscObject)isrow_d);
3191: ISDestroy(&isrow_d);
3193: PetscObjectCompose((PetscObject)M,"iscol_d",(PetscObject)iscol_d);
3194: ISDestroy(&iscol_d);
3196: PetscObjectCompose((PetscObject)M,"iscol_o",(PetscObject)iscol_o);
3197: ISDestroy(&iscol_o);
3198: }
3199: return(0);
3200: }
3202: PetscErrorCode MatCreateSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
3203: {
3205: IS iscol_local=NULL,isrow_d;
3206: PetscInt csize;
3207: PetscInt n,i,j,start,end;
3208: PetscBool sameRowDist=PETSC_FALSE,sameDist[2],tsameDist[2];
3209: MPI_Comm comm;
3212: /* If isrow has same processor distribution as mat,
3213: call MatCreateSubMatrix_MPIAIJ_SameRowDist() to avoid using a hash table with global size of iscol */
3214: if (call == MAT_REUSE_MATRIX) {
3215: PetscObjectQuery((PetscObject)*newmat,"isrow_d",(PetscObject*)&isrow_d);
3216: if (isrow_d) {
3217: sameRowDist = PETSC_TRUE;
3218: tsameDist[1] = PETSC_TRUE; /* sameColDist */
3219: } else {
3220: PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_local);
3221: if (iscol_local) {
3222: sameRowDist = PETSC_TRUE;
3223: tsameDist[1] = PETSC_FALSE; /* !sameColDist */
3224: }
3225: }
3226: } else {
3227: /* Check if isrow has same processor distribution as mat */
3228: sameDist[0] = PETSC_FALSE;
3229: ISGetLocalSize(isrow,&n);
3230: if (!n) {
3231: sameDist[0] = PETSC_TRUE;
3232: } else {
3233: ISGetMinMax(isrow,&i,&j);
3234: MatGetOwnershipRange(mat,&start,&end);
3235: if (i >= start && j < end) {
3236: sameDist[0] = PETSC_TRUE;
3237: }
3238: }
3240: /* Check if iscol has same processor distribution as mat */
3241: sameDist[1] = PETSC_FALSE;
3242: ISGetLocalSize(iscol,&n);
3243: if (!n) {
3244: sameDist[1] = PETSC_TRUE;
3245: } else {
3246: ISGetMinMax(iscol,&i,&j);
3247: MatGetOwnershipRangeColumn(mat,&start,&end);
3248: if (i >= start && j < end) sameDist[1] = PETSC_TRUE;
3249: }
3251: PetscObjectGetComm((PetscObject)mat,&comm);
3252: MPIU_Allreduce(&sameDist,&tsameDist,2,MPIU_BOOL,MPI_LAND,comm);
3253: sameRowDist = tsameDist[0];
3254: }
3256: if (sameRowDist) {
3257: if (tsameDist[1]) { /* sameRowDist & sameColDist */
3258: /* isrow and iscol have same processor distribution as mat */
3259: MatCreateSubMatrix_MPIAIJ_SameRowColDist(mat,isrow,iscol,call,newmat);
3260: return(0);
3261: } else { /* sameRowDist */
3262: /* isrow has same processor distribution as mat */
3263: if (call == MAT_INITIAL_MATRIX) {
3264: PetscBool sorted;
3265: ISGetSeqIS_Private(mat,iscol,&iscol_local);
3266: ISGetLocalSize(iscol_local,&n); /* local size of iscol_local = global columns of newmat */
3267: ISGetSize(iscol,&i);
3268: if (n != i) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"n %d != size of iscol %d",n,i);
3270: ISSorted(iscol_local,&sorted);
3271: if (sorted) {
3272: /* MatCreateSubMatrix_MPIAIJ_SameRowDist() requires iscol_local be sorted; it can have duplicate indices */
3273: MatCreateSubMatrix_MPIAIJ_SameRowDist(mat,isrow,iscol,iscol_local,MAT_INITIAL_MATRIX,newmat);
3274: return(0);
3275: }
3276: } else { /* call == MAT_REUSE_MATRIX */
3277: IS iscol_sub;
3278: PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);
3279: if (iscol_sub) {
3280: MatCreateSubMatrix_MPIAIJ_SameRowDist(mat,isrow,iscol,NULL,call,newmat);
3281: return(0);
3282: }
3283: }
3284: }
3285: }
3287: /* General case: iscol -> iscol_local which has global size of iscol */
3288: if (call == MAT_REUSE_MATRIX) {
3289: PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
3290: if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3291: } else {
3292: if (!iscol_local) {
3293: ISGetSeqIS_Private(mat,iscol,&iscol_local);
3294: }
3295: }
3297: ISGetLocalSize(iscol,&csize);
3298: MatCreateSubMatrix_MPIAIJ_nonscalable(mat,isrow,iscol_local,csize,call,newmat);
3300: if (call == MAT_INITIAL_MATRIX) {
3301: PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
3302: ISDestroy(&iscol_local);
3303: }
3304: return(0);
3305: }
3307: /*@C
3308: MatCreateMPIAIJWithSeqAIJ - creates a MPIAIJ matrix using SeqAIJ matrices that contain the "diagonal"
3309: and "off-diagonal" part of the matrix in CSR format.
3311: Collective on MPI_Comm
3313: Input Parameters:
3314: + comm - MPI communicator
3315: . A - "diagonal" portion of matrix
3316: . B - "off-diagonal" portion of matrix, may have empty columns, will be destroyed by this routine
3317: - garray - global index of B columns
3319: Output Parameter:
3320: . mat - the matrix, with input A as its local diagonal matrix
3321: Level: advanced
3323: Notes:
3324: See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix.
3325: A becomes part of output mat, B is destroyed by this routine. The user cannot use A and B anymore.
3327: .seealso: MatCreateMPIAIJWithSplitArrays()
3328: @*/
3329: PetscErrorCode MatCreateMPIAIJWithSeqAIJ(MPI_Comm comm,Mat A,Mat B,const PetscInt garray[],Mat *mat)
3330: {
3332: Mat_MPIAIJ *maij;
3333: Mat_SeqAIJ *b=(Mat_SeqAIJ*)B->data,*bnew;
3334: PetscInt *oi=b->i,*oj=b->j,i,nz,col;
3335: PetscScalar *oa=b->a;
3336: Mat Bnew;
3337: PetscInt m,n,N;
3340: MatCreate(comm,mat);
3341: MatGetSize(A,&m,&n);
3342: if (m != B->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Am %D != Bm %D",m,B->rmap->N);
3343: if (A->rmap->bs != B->rmap->bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"A row bs %D != B row bs %D",A->rmap->bs,B->rmap->bs);
3344: /* remove check below; When B is created using iscol_o from ISGetSeqIS_SameColDist_Private(), its bs may not be same as A */
3345: /* if (A->cmap->bs != B->cmap->bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"A column bs %D != B column bs %D",A->cmap->bs,B->cmap->bs); */
3347: /* Get global columns of mat */
3348: MPIU_Allreduce(&n,&N,1,MPIU_INT,MPI_SUM,comm);
3350: MatSetSizes(*mat,m,n,PETSC_DECIDE,N);
3351: MatSetType(*mat,MATMPIAIJ);
3352: MatSetBlockSizes(*mat,A->rmap->bs,A->cmap->bs);
3353: maij = (Mat_MPIAIJ*)(*mat)->data;
3355: (*mat)->preallocated = PETSC_TRUE;
3357: PetscLayoutSetUp((*mat)->rmap);
3358: PetscLayoutSetUp((*mat)->cmap);
3360: /* Set A as diagonal portion of *mat */
3361: maij->A = A;
3363: nz = oi[m];
3364: for (i=0; i<nz; i++) {
3365: col = oj[i];
3366: oj[i] = garray[col];
3367: }
3369: /* Set Bnew as off-diagonal portion of *mat */
3370: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,N,oi,oj,oa,&Bnew);
3371: bnew = (Mat_SeqAIJ*)Bnew->data;
3372: bnew->maxnz = b->maxnz; /* allocated nonzeros of B */
3373: maij->B = Bnew;
3375: if (B->rmap->N != Bnew->rmap->N) SETERRQ2(PETSC_COMM_SELF,0,"BN %d != BnewN %d",B->rmap->N,Bnew->rmap->N);
3377: b->singlemalloc = PETSC_FALSE; /* B arrays are shared by Bnew */
3378: b->free_a = PETSC_FALSE;
3379: b->free_ij = PETSC_FALSE;
3380: MatDestroy(&B);
3382: bnew->singlemalloc = PETSC_TRUE; /* arrays will be freed by MatDestroy(&Bnew) */
3383: bnew->free_a = PETSC_TRUE;
3384: bnew->free_ij = PETSC_TRUE;
3386: /* condense columns of maij->B */
3387: MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);
3388: MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
3389: MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
3390: MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);
3391: MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
3392: return(0);
3393: }
3395: extern PetscErrorCode MatCreateSubMatrices_MPIAIJ_SingleIS_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool,Mat*);
3397: PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowDist(Mat mat,IS isrow,IS iscol,IS iscol_local,MatReuse call,Mat *newmat)
3398: {
3400: PetscInt i,m,n,rstart,row,rend,nz,j,bs,cbs;
3401: PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal;
3402: Mat_MPIAIJ *a=(Mat_MPIAIJ*)mat->data;
3403: Mat M,Msub,B=a->B;
3404: MatScalar *aa;
3405: Mat_SeqAIJ *aij;
3406: PetscInt *garray = a->garray,*colsub,Ncols;
3407: PetscInt count,Bn=B->cmap->N,cstart=mat->cmap->rstart,cend=mat->cmap->rend;
3408: IS iscol_sub,iscmap;
3409: const PetscInt *is_idx,*cmap;
3410: PetscBool allcolumns=PETSC_FALSE;
3411: MPI_Comm comm;
3414: PetscObjectGetComm((PetscObject)mat,&comm);
3416: if (call == MAT_REUSE_MATRIX) {
3417: PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);
3418: if (!iscol_sub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"SubIScol passed in was not used before, cannot reuse");
3419: ISGetLocalSize(iscol_sub,&count);
3421: PetscObjectQuery((PetscObject)*newmat,"Subcmap",(PetscObject*)&iscmap);
3422: if (!iscmap) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Subcmap passed in was not used before, cannot reuse");
3424: PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Msub);
3425: if (!Msub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3427: MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_REUSE_MATRIX,PETSC_FALSE,&Msub);
3429: } else { /* call == MAT_INITIAL_MATRIX) */
3430: PetscBool flg;
3432: ISGetLocalSize(iscol,&n);
3433: ISGetSize(iscol,&Ncols);
3435: /* (1) iscol -> nonscalable iscol_local */
3436: /* Check for special case: each processor gets entire matrix columns */
3437: ISIdentity(iscol_local,&flg);
3438: if (flg && n == mat->cmap->N) allcolumns = PETSC_TRUE;
3439: if (allcolumns) {
3440: iscol_sub = iscol_local;
3441: PetscObjectReference((PetscObject)iscol_local);
3442: ISCreateStride(PETSC_COMM_SELF,n,0,1,&iscmap);
3444: } else {
3445: /* (2) iscol_local -> iscol_sub and iscmap. Implementation below requires iscol_local be sorted, it can have duplicate indices */
3446: PetscInt *idx,*cmap1,k;
3447: PetscMalloc1(Ncols,&idx);
3448: PetscMalloc1(Ncols,&cmap1);
3449: ISGetIndices(iscol_local,&is_idx);
3450: count = 0;
3451: k = 0;
3452: for (i=0; i<Ncols; i++) {
3453: j = is_idx[i];
3454: if (j >= cstart && j < cend) {
3455: /* diagonal part of mat */
3456: idx[count] = j;
3457: cmap1[count++] = i; /* column index in submat */
3458: } else if (Bn) {
3459: /* off-diagonal part of mat */
3460: if (j == garray[k]) {
3461: idx[count] = j;
3462: cmap1[count++] = i; /* column index in submat */
3463: } else if (j > garray[k]) {
3464: while (j > garray[k] && k < Bn-1) k++;
3465: if (j == garray[k]) {
3466: idx[count] = j;
3467: cmap1[count++] = i; /* column index in submat */
3468: }
3469: }
3470: }
3471: }
3472: ISRestoreIndices(iscol_local,&is_idx);
3474: ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_OWN_POINTER,&iscol_sub);
3475: ISGetBlockSize(iscol,&cbs);
3476: ISSetBlockSize(iscol_sub,cbs);
3478: ISCreateGeneral(PetscObjectComm((PetscObject)iscol_local),count,cmap1,PETSC_OWN_POINTER,&iscmap);
3479: }
3481: /* (3) Create sequential Msub */
3482: MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_INITIAL_MATRIX,allcolumns,&Msub);
3483: }
3485: ISGetLocalSize(iscol_sub,&count);
3486: aij = (Mat_SeqAIJ*)(Msub)->data;
3487: ii = aij->i;
3488: ISGetIndices(iscmap,&cmap);
3490: /*
3491: m - number of local rows
3492: Ncols - number of columns (same on all processors)
3493: rstart - first row in new global matrix generated
3494: */
3495: MatGetSize(Msub,&m,NULL);
3497: if (call == MAT_INITIAL_MATRIX) {
3498: /* (4) Create parallel newmat */
3499: PetscMPIInt rank,size;
3500: PetscInt csize;
3502: MPI_Comm_size(comm,&size);
3503: MPI_Comm_rank(comm,&rank);
3505: /*
3506: Determine the number of non-zeros in the diagonal and off-diagonal
3507: portions of the matrix in order to do correct preallocation
3508: */
3510: /* first get start and end of "diagonal" columns */
3511: ISGetLocalSize(iscol,&csize);
3512: if (csize == PETSC_DECIDE) {
3513: ISGetSize(isrow,&mglobal);
3514: if (mglobal == Ncols) { /* square matrix */
3515: nlocal = m;
3516: } else {
3517: nlocal = Ncols/size + ((Ncols % size) > rank);
3518: }
3519: } else {
3520: nlocal = csize;
3521: }
3522: MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
3523: rstart = rend - nlocal;
3524: if (rank == size - 1 && rend != Ncols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,Ncols);
3526: /* next, compute all the lengths */
3527: jj = aij->j;
3528: PetscMalloc1(2*m+1,&dlens);
3529: olens = dlens + m;
3530: for (i=0; i<m; i++) {
3531: jend = ii[i+1] - ii[i];
3532: olen = 0;
3533: dlen = 0;
3534: for (j=0; j<jend; j++) {
3535: if (cmap[*jj] < rstart || cmap[*jj] >= rend) olen++;
3536: else dlen++;
3537: jj++;
3538: }
3539: olens[i] = olen;
3540: dlens[i] = dlen;
3541: }
3543: ISGetBlockSize(isrow,&bs);
3544: ISGetBlockSize(iscol,&cbs);
3546: MatCreate(comm,&M);
3547: MatSetSizes(M,m,nlocal,PETSC_DECIDE,Ncols);
3548: MatSetBlockSizes(M,bs,cbs);
3549: MatSetType(M,((PetscObject)mat)->type_name);
3550: MatMPIAIJSetPreallocation(M,0,dlens,0,olens);
3551: PetscFree(dlens);
3553: } else { /* call == MAT_REUSE_MATRIX */
3554: M = *newmat;
3555: MatGetLocalSize(M,&i,NULL);
3556: if (i != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
3557: MatZeroEntries(M);
3558: /*
3559: The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
3560: rather than the slower MatSetValues().
3561: */
3562: M->was_assembled = PETSC_TRUE;
3563: M->assembled = PETSC_FALSE;
3564: }
3566: /* (5) Set values of Msub to *newmat */
3567: PetscMalloc1(count,&colsub);
3568: MatGetOwnershipRange(M,&rstart,NULL);
3570: jj = aij->j;
3571: aa = aij->a;
3572: for (i=0; i<m; i++) {
3573: row = rstart + i;
3574: nz = ii[i+1] - ii[i];
3575: for (j=0; j<nz; j++) colsub[j] = cmap[jj[j]];
3576: MatSetValues_MPIAIJ(M,1,&row,nz,colsub,aa,INSERT_VALUES);
3577: jj += nz; aa += nz;
3578: }
3579: ISRestoreIndices(iscmap,&cmap);
3581: MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
3582: MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
3584: PetscFree(colsub);
3586: /* save Msub, iscol_sub and iscmap used in processor for next request */
3587: if (call == MAT_INITIAL_MATRIX) {
3588: *newmat = M;
3589: PetscObjectCompose((PetscObject)(*newmat),"SubMatrix",(PetscObject)Msub);
3590: MatDestroy(&Msub);
3592: PetscObjectCompose((PetscObject)(*newmat),"SubIScol",(PetscObject)iscol_sub);
3593: ISDestroy(&iscol_sub);
3595: PetscObjectCompose((PetscObject)(*newmat),"Subcmap",(PetscObject)iscmap);
3596: ISDestroy(&iscmap);
3598: if (iscol_local) {
3599: PetscObjectCompose((PetscObject)(*newmat),"ISAllGather",(PetscObject)iscol_local);
3600: ISDestroy(&iscol_local);
3601: }
3602: }
3603: return(0);
3604: }
3606: /*
3607: Not great since it makes two copies of the submatrix, first an SeqAIJ
3608: in local and then by concatenating the local matrices the end result.
3609: Writing it directly would be much like MatCreateSubMatrices_MPIAIJ()
3611: Note: This requires a sequential iscol with all indices.
3612: */
3613: PetscErrorCode MatCreateSubMatrix_MPIAIJ_nonscalable(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat)
3614: {
3616: PetscMPIInt rank,size;
3617: PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs;
3618: PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal;
3619: Mat M,Mreuse;
3620: MatScalar *aa,*vwork;
3621: MPI_Comm comm;
3622: Mat_SeqAIJ *aij;
3623: PetscBool colflag,allcolumns=PETSC_FALSE;
3626: PetscObjectGetComm((PetscObject)mat,&comm);
3627: MPI_Comm_rank(comm,&rank);
3628: MPI_Comm_size(comm,&size);
3630: /* Check for special case: each processor gets entire matrix columns */
3631: ISIdentity(iscol,&colflag);
3632: ISGetLocalSize(iscol,&n);
3633: if (colflag && n == mat->cmap->N) allcolumns = PETSC_TRUE;
3635: if (call == MAT_REUSE_MATRIX) {
3636: PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);
3637: if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3638: MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,allcolumns,&Mreuse);
3639: } else {
3640: MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,allcolumns,&Mreuse);
3641: }
3643: /*
3644: m - number of local rows
3645: n - number of columns (same on all processors)
3646: rstart - first row in new global matrix generated
3647: */
3648: MatGetSize(Mreuse,&m,&n);
3649: MatGetBlockSizes(Mreuse,&bs,&cbs);
3650: if (call == MAT_INITIAL_MATRIX) {
3651: aij = (Mat_SeqAIJ*)(Mreuse)->data;
3652: ii = aij->i;
3653: jj = aij->j;
3655: /*
3656: Determine the number of non-zeros in the diagonal and off-diagonal
3657: portions of the matrix in order to do correct preallocation
3658: */
3660: /* first get start and end of "diagonal" columns */
3661: if (csize == PETSC_DECIDE) {
3662: ISGetSize(isrow,&mglobal);
3663: if (mglobal == n) { /* square matrix */
3664: nlocal = m;
3665: } else {
3666: nlocal = n/size + ((n % size) > rank);
3667: }
3668: } else {
3669: nlocal = csize;
3670: }
3671: MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
3672: rstart = rend - nlocal;
3673: 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);
3675: /* next, compute all the lengths */
3676: PetscMalloc1(2*m+1,&dlens);
3677: olens = dlens + m;
3678: for (i=0; i<m; i++) {
3679: jend = ii[i+1] - ii[i];
3680: olen = 0;
3681: dlen = 0;
3682: for (j=0; j<jend; j++) {
3683: if (*jj < rstart || *jj >= rend) olen++;
3684: else dlen++;
3685: jj++;
3686: }
3687: olens[i] = olen;
3688: dlens[i] = dlen;
3689: }
3690: MatCreate(comm,&M);
3691: MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);
3692: MatSetBlockSizes(M,bs,cbs);
3693: MatSetType(M,((PetscObject)mat)->type_name);
3694: MatMPIAIJSetPreallocation(M,0,dlens,0,olens);
3695: PetscFree(dlens);
3696: } else {
3697: PetscInt ml,nl;
3699: M = *newmat;
3700: MatGetLocalSize(M,&ml,&nl);
3701: if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
3702: MatZeroEntries(M);
3703: /*
3704: The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
3705: rather than the slower MatSetValues().
3706: */
3707: M->was_assembled = PETSC_TRUE;
3708: M->assembled = PETSC_FALSE;
3709: }
3710: MatGetOwnershipRange(M,&rstart,&rend);
3711: aij = (Mat_SeqAIJ*)(Mreuse)->data;
3712: ii = aij->i;
3713: jj = aij->j;
3714: aa = aij->a;
3715: for (i=0; i<m; i++) {
3716: row = rstart + i;
3717: nz = ii[i+1] - ii[i];
3718: cwork = jj; jj += nz;
3719: vwork = aa; aa += nz;
3720: MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);
3721: }
3723: MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
3724: MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
3725: *newmat = M;
3727: /* save submatrix used in processor for next request */
3728: if (call == MAT_INITIAL_MATRIX) {
3729: PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);
3730: MatDestroy(&Mreuse);
3731: }
3732: return(0);
3733: }
3735: PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[])
3736: {
3737: PetscInt m,cstart, cend,j,nnz,i,d;
3738: PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii;
3739: const PetscInt *JJ;
3740: PetscScalar *values;
3742: PetscBool nooffprocentries;
3745: if (Ii && Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]);
3747: PetscLayoutSetUp(B->rmap);
3748: PetscLayoutSetUp(B->cmap);
3749: m = B->rmap->n;
3750: cstart = B->cmap->rstart;
3751: cend = B->cmap->rend;
3752: rstart = B->rmap->rstart;
3754: PetscMalloc2(m,&d_nnz,m,&o_nnz);
3756: #if defined(PETSC_USE_DEBUG)
3757: for (i=0; i<m; i++) {
3758: nnz = Ii[i+1]- Ii[i];
3759: JJ = J + Ii[i];
3760: if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz);
3761: if (nnz && (JJ[0] < 0)) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,JJ[0]);
3762: if (nnz && (JJ[nnz-1] >= B->cmap->N)) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Row %D ends with too large a column index %D (max allowed %D)",i,JJ[nnz-1],B->cmap->N);
3763: }
3764: #endif
3766: for (i=0; i<m; i++) {
3767: nnz = Ii[i+1]- Ii[i];
3768: JJ = J + Ii[i];
3769: nnz_max = PetscMax(nnz_max,nnz);
3770: d = 0;
3771: for (j=0; j<nnz; j++) {
3772: if (cstart <= JJ[j] && JJ[j] < cend) d++;
3773: }
3774: d_nnz[i] = d;
3775: o_nnz[i] = nnz - d;
3776: }
3777: MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);
3778: PetscFree2(d_nnz,o_nnz);
3780: if (v) values = (PetscScalar*)v;
3781: else {
3782: PetscCalloc1(nnz_max+1,&values);
3783: }
3785: for (i=0; i<m; i++) {
3786: ii = i + rstart;
3787: nnz = Ii[i+1]- Ii[i];
3788: MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);
3789: }
3790: nooffprocentries = B->nooffprocentries;
3791: B->nooffprocentries = PETSC_TRUE;
3792: MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
3793: MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
3794: B->nooffprocentries = nooffprocentries;
3796: if (!v) {
3797: PetscFree(values);
3798: }
3799: MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
3800: return(0);
3801: }
3803: /*@
3804: MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format
3805: (the default parallel PETSc format).
3807: Collective on MPI_Comm
3809: Input Parameters:
3810: + B - the matrix
3811: . i - the indices into j for the start of each local row (starts with zero)
3812: . j - the column indices for each local row (starts with zero)
3813: - v - optional values in the matrix
3815: Level: developer
3817: Notes:
3818: The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
3819: thus you CANNOT change the matrix entries by changing the values of a[] after you have
3820: called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.
3822: The i and j indices are 0 based, and i indices are indices corresponding to the local j array.
3824: The format which is used for the sparse matrix input, is equivalent to a
3825: row-major ordering.. i.e for the following matrix, the input data expected is
3826: as shown
3828: $ 1 0 0
3829: $ 2 0 3 P0
3830: $ -------
3831: $ 4 5 6 P1
3832: $
3833: $ Process0 [P0]: rows_owned=[0,1]
3834: $ i = {0,1,3} [size = nrow+1 = 2+1]
3835: $ j = {0,0,2} [size = 3]
3836: $ v = {1,2,3} [size = 3]
3837: $
3838: $ Process1 [P1]: rows_owned=[2]
3839: $ i = {0,3} [size = nrow+1 = 1+1]
3840: $ j = {0,1,2} [size = 3]
3841: $ v = {4,5,6} [size = 3]
3843: .keywords: matrix, aij, compressed row, sparse, parallel
3845: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MATMPIAIJ,
3846: MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays()
3847: @*/
3848: PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
3849: {
3853: PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));
3854: return(0);
3855: }
3857: /*@C
3858: MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format
3859: (the default parallel PETSc format). For good matrix assembly performance
3860: the user should preallocate the matrix storage by setting the parameters
3861: d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately,
3862: performance can be increased by more than a factor of 50.
3864: Collective on MPI_Comm
3866: Input Parameters:
3867: + B - the matrix
3868: . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix
3869: (same value is used for all local rows)
3870: . d_nnz - array containing the number of nonzeros in the various rows of the
3871: DIAGONAL portion of the local submatrix (possibly different for each row)
3872: or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure.
3873: The size of this array is equal to the number of local rows, i.e 'm'.
3874: For matrices that will be factored, you must leave room for (and set)
3875: the diagonal entry even if it is zero.
3876: . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local
3877: submatrix (same value is used for all local rows).
3878: - o_nnz - array containing the number of nonzeros in the various rows of the
3879: OFF-DIAGONAL portion of the local submatrix (possibly different for
3880: each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero
3881: structure. The size of this array is equal to the number
3882: of local rows, i.e 'm'.
3884: If the *_nnz parameter is given then the *_nz parameter is ignored
3886: The AIJ format (also called the Yale sparse matrix format or
3887: compressed row storage (CSR)), is fully compatible with standard Fortran 77
3888: storage. The stored row and column indices begin with zero.
3889: See Users-Manual: ch_mat for details.
3891: The parallel matrix is partitioned such that the first m0 rows belong to
3892: process 0, the next m1 rows belong to process 1, the next m2 rows belong
3893: to process 2 etc.. where m0,m1,m2... are the input parameter 'm'.
3895: The DIAGONAL portion of the local submatrix of a processor can be defined
3896: as the submatrix which is obtained by extraction the part corresponding to
3897: the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the
3898: first row that belongs to the processor, r2 is the last row belonging to
3899: the this processor, and c1-c2 is range of indices of the local part of a
3900: vector suitable for applying the matrix to. This is an mxn matrix. In the
3901: common case of a square matrix, the row and column ranges are the same and
3902: the DIAGONAL part is also square. The remaining portion of the local
3903: submatrix (mxN) constitute the OFF-DIAGONAL portion.
3905: If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.
3907: You can call MatGetInfo() to get information on how effective the preallocation was;
3908: for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
3909: You can also run with the option -info and look for messages with the string
3910: malloc in them to see if additional memory allocation was needed.
3912: Example usage:
3914: Consider the following 8x8 matrix with 34 non-zero values, that is
3915: assembled across 3 processors. Lets assume that proc0 owns 3 rows,
3916: proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
3917: as follows:
3919: .vb
3920: 1 2 0 | 0 3 0 | 0 4
3921: Proc0 0 5 6 | 7 0 0 | 8 0
3922: 9 0 10 | 11 0 0 | 12 0
3923: -------------------------------------
3924: 13 0 14 | 15 16 17 | 0 0
3925: Proc1 0 18 0 | 19 20 21 | 0 0
3926: 0 0 0 | 22 23 0 | 24 0
3927: -------------------------------------
3928: Proc2 25 26 27 | 0 0 28 | 29 0
3929: 30 0 0 | 31 32 33 | 0 34
3930: .ve
3932: This can be represented as a collection of submatrices as:
3934: .vb
3935: A B C
3936: D E F
3937: G H I
3938: .ve
3940: Where the submatrices A,B,C are owned by proc0, D,E,F are
3941: owned by proc1, G,H,I are owned by proc2.
3943: The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
3944: The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
3945: The 'M','N' parameters are 8,8, and have the same values on all procs.
3947: The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
3948: submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
3949: corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
3950: Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
3951: part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
3952: matrix, ans [DF] as another SeqAIJ matrix.
3954: When d_nz, o_nz parameters are specified, d_nz storage elements are
3955: allocated for every row of the local diagonal submatrix, and o_nz
3956: storage locations are allocated for every row of the OFF-DIAGONAL submat.
3957: One way to choose d_nz and o_nz is to use the max nonzerors per local
3958: rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
3959: In this case, the values of d_nz,o_nz are:
3960: .vb
3961: proc0 : dnz = 2, o_nz = 2
3962: proc1 : dnz = 3, o_nz = 2
3963: proc2 : dnz = 1, o_nz = 4
3964: .ve
3965: We are allocating m*(d_nz+o_nz) storage locations for every proc. This
3966: translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
3967: for proc3. i.e we are using 12+15+10=37 storage locations to store
3968: 34 values.
3970: When d_nnz, o_nnz parameters are specified, the storage is specified
3971: for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
3972: In the above case the values for d_nnz,o_nnz are:
3973: .vb
3974: proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
3975: proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
3976: proc2: d_nnz = [1,1] and o_nnz = [4,4]
3977: .ve
3978: Here the space allocated is sum of all the above values i.e 34, and
3979: hence pre-allocation is perfect.
3981: Level: intermediate
3983: .keywords: matrix, aij, compressed row, sparse, parallel
3985: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(),
3986: MATMPIAIJ, MatGetInfo(), PetscSplitOwnership()
3987: @*/
3988: PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
3989: {
3995: PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));
3996: return(0);
3997: }
3999: /*@
4000: MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard
4001: CSR format the local rows.
4003: Collective on MPI_Comm
4005: Input Parameters:
4006: + comm - MPI communicator
4007: . m - number of local rows (Cannot be PETSC_DECIDE)
4008: . n - This value should be the same as the local size used in creating the
4009: x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
4010: calculated if N is given) For square matrices n is almost always m.
4011: . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
4012: . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
4013: . i - row indices
4014: . j - column indices
4015: - a - matrix values
4017: Output Parameter:
4018: . mat - the matrix
4020: Level: intermediate
4022: Notes:
4023: The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
4024: thus you CANNOT change the matrix entries by changing the values of a[] after you have
4025: called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.
4027: The i and j indices are 0 based, and i indices are indices corresponding to the local j array.
4029: The format which is used for the sparse matrix input, is equivalent to a
4030: row-major ordering.. i.e for the following matrix, the input data expected is
4031: as shown
4033: $ 1 0 0
4034: $ 2 0 3 P0
4035: $ -------
4036: $ 4 5 6 P1
4037: $
4038: $ Process0 [P0]: rows_owned=[0,1]
4039: $ i = {0,1,3} [size = nrow+1 = 2+1]
4040: $ j = {0,0,2} [size = 3]
4041: $ v = {1,2,3} [size = 3]
4042: $
4043: $ Process1 [P1]: rows_owned=[2]
4044: $ i = {0,3} [size = nrow+1 = 1+1]
4045: $ j = {0,1,2} [size = 3]
4046: $ v = {4,5,6} [size = 3]
4048: .keywords: matrix, aij, compressed row, sparse, parallel
4050: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
4051: MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
4052: @*/
4053: PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat)
4054: {
4058: if (i && i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
4059: if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
4060: MatCreate(comm,mat);
4061: MatSetSizes(*mat,m,n,M,N);
4062: /* MatSetBlockSizes(M,bs,cbs); */
4063: MatSetType(*mat,MATMPIAIJ);
4064: MatMPIAIJSetPreallocationCSR(*mat,i,j,a);
4065: return(0);
4066: }
4068: /*@C
4069: MatCreateAIJ - Creates a sparse parallel matrix in AIJ format
4070: (the default parallel PETSc format). For good matrix assembly performance
4071: the user should preallocate the matrix storage by setting the parameters
4072: d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately,
4073: performance can be increased by more than a factor of 50.
4075: Collective on MPI_Comm
4077: Input Parameters:
4078: + comm - MPI communicator
4079: . m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
4080: This value should be the same as the local size used in creating the
4081: y vector for the matrix-vector product y = Ax.
4082: . n - This value should be the same as the local size used in creating the
4083: x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
4084: calculated if N is given) For square matrices n is almost always m.
4085: . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
4086: . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
4087: . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix
4088: (same value is used for all local rows)
4089: . d_nnz - array containing the number of nonzeros in the various rows of the
4090: DIAGONAL portion of the local submatrix (possibly different for each row)
4091: or NULL, if d_nz is used to specify the nonzero structure.
4092: The size of this array is equal to the number of local rows, i.e 'm'.
4093: . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local
4094: submatrix (same value is used for all local rows).
4095: - o_nnz - array containing the number of nonzeros in the various rows of the
4096: OFF-DIAGONAL portion of the local submatrix (possibly different for
4097: each row) or NULL, if o_nz is used to specify the nonzero
4098: structure. The size of this array is equal to the number
4099: of local rows, i.e 'm'.
4101: Output Parameter:
4102: . A - the matrix
4104: It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
4105: MatXXXXSetPreallocation() paradgm instead of this routine directly.
4106: [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]
4108: Notes:
4109: If the *_nnz parameter is given then the *_nz parameter is ignored
4111: m,n,M,N parameters specify the size of the matrix, and its partitioning across
4112: processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate
4113: storage requirements for this matrix.
4115: If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one
4116: processor than it must be used on all processors that share the object for
4117: that argument.
4119: The user MUST specify either the local or global matrix dimensions
4120: (possibly both).
4122: The parallel matrix is partitioned across processors such that the
4123: first m0 rows belong to process 0, the next m1 rows belong to
4124: process 1, the next m2 rows belong to process 2 etc.. where
4125: m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores
4126: values corresponding to [m x N] submatrix.
4128: The columns are logically partitioned with the n0 columns belonging
4129: to 0th partition, the next n1 columns belonging to the next
4130: partition etc.. where n0,n1,n2... are the input parameter 'n'.
4132: The DIAGONAL portion of the local submatrix on any given processor
4133: is the submatrix corresponding to the rows and columns m,n
4134: corresponding to the given processor. i.e diagonal matrix on
4135: process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1]
4136: etc. The remaining portion of the local submatrix [m x (N-n)]
4137: constitute the OFF-DIAGONAL portion. The example below better
4138: illustrates this concept.
4140: For a square global matrix we define each processor's diagonal portion
4141: to be its local rows and the corresponding columns (a square submatrix);
4142: each processor's off-diagonal portion encompasses the remainder of the
4143: local matrix (a rectangular submatrix).
4145: If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.
4147: When calling this routine with a single process communicator, a matrix of
4148: type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this
4149: type of communicator, use the construction mechanism
4150: .vb
4151: MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...);
4152: .ve
4154: $ MatCreate(...,&A);
4155: $ MatSetType(A,MATMPIAIJ);
4156: $ MatSetSizes(A, m,n,M,N);
4157: $ MatMPIAIJSetPreallocation(A,...);
4159: By default, this format uses inodes (identical nodes) when possible.
4160: We search for consecutive rows with the same nonzero structure, thereby
4161: reusing matrix information to achieve increased efficiency.
4163: Options Database Keys:
4164: + -mat_no_inode - Do not use inodes
4165: - -mat_inode_limit <limit> - Sets inode limit (max limit=5)
4169: Example usage:
4171: Consider the following 8x8 matrix with 34 non-zero values, that is
4172: assembled across 3 processors. Lets assume that proc0 owns 3 rows,
4173: proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
4174: as follows
4176: .vb
4177: 1 2 0 | 0 3 0 | 0 4
4178: Proc0 0 5 6 | 7 0 0 | 8 0
4179: 9 0 10 | 11 0 0 | 12 0
4180: -------------------------------------
4181: 13 0 14 | 15 16 17 | 0 0
4182: Proc1 0 18 0 | 19 20 21 | 0 0
4183: 0 0 0 | 22 23 0 | 24 0
4184: -------------------------------------
4185: Proc2 25 26 27 | 0 0 28 | 29 0
4186: 30 0 0 | 31 32 33 | 0 34
4187: .ve
4189: This can be represented as a collection of submatrices as
4191: .vb
4192: A B C
4193: D E F
4194: G H I
4195: .ve
4197: Where the submatrices A,B,C are owned by proc0, D,E,F are
4198: owned by proc1, G,H,I are owned by proc2.
4200: The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
4201: The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
4202: The 'M','N' parameters are 8,8, and have the same values on all procs.
4204: The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
4205: submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
4206: corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
4207: Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
4208: part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
4209: matrix, ans [DF] as another SeqAIJ matrix.
4211: When d_nz, o_nz parameters are specified, d_nz storage elements are
4212: allocated for every row of the local diagonal submatrix, and o_nz
4213: storage locations are allocated for every row of the OFF-DIAGONAL submat.
4214: One way to choose d_nz and o_nz is to use the max nonzerors per local
4215: rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
4216: In this case, the values of d_nz,o_nz are
4217: .vb
4218: proc0 : dnz = 2, o_nz = 2
4219: proc1 : dnz = 3, o_nz = 2
4220: proc2 : dnz = 1, o_nz = 4
4221: .ve
4222: We are allocating m*(d_nz+o_nz) storage locations for every proc. This
4223: translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
4224: for proc3. i.e we are using 12+15+10=37 storage locations to store
4225: 34 values.
4227: When d_nnz, o_nnz parameters are specified, the storage is specified
4228: for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
4229: In the above case the values for d_nnz,o_nnz are
4230: .vb
4231: proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
4232: proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
4233: proc2: d_nnz = [1,1] and o_nnz = [4,4]
4234: .ve
4235: Here the space allocated is sum of all the above values i.e 34, and
4236: hence pre-allocation is perfect.
4238: Level: intermediate
4240: .keywords: matrix, aij, compressed row, sparse, parallel
4242: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
4243: MATMPIAIJ, MatCreateMPIAIJWithArrays()
4244: @*/
4245: 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)
4246: {
4248: PetscMPIInt size;
4251: MatCreate(comm,A);
4252: MatSetSizes(*A,m,n,M,N);
4253: MPI_Comm_size(comm,&size);
4254: if (size > 1) {
4255: MatSetType(*A,MATMPIAIJ);
4256: MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);
4257: } else {
4258: MatSetType(*A,MATSEQAIJ);
4259: MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);
4260: }
4261: return(0);
4262: }
4264: PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[])
4265: {
4266: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
4267: PetscBool flg;
4269:
4271: PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&flg);
4272: if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MATMPIAIJ matrix as input");
4273: if (Ad) *Ad = a->A;
4274: if (Ao) *Ao = a->B;
4275: if (colmap) *colmap = a->garray;
4276: return(0);
4277: }
4279: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
4280: {
4282: PetscInt m,N,i,rstart,nnz,Ii;
4283: PetscInt *indx;
4284: PetscScalar *values;
4287: MatGetSize(inmat,&m,&N);
4288: if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
4289: PetscInt *dnz,*onz,sum,bs,cbs;
4291: if (n == PETSC_DECIDE) {
4292: PetscSplitOwnership(comm,&n,&N);
4293: }
4294: /* Check sum(n) = N */
4295: MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);
4296: if (sum != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns %D != global columns %D",sum,N);
4298: MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);
4299: rstart -= m;
4301: MatPreallocateInitialize(comm,m,n,dnz,onz);
4302: for (i=0; i<m; i++) {
4303: MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);
4304: MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);
4305: MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);
4306: }
4308: MatCreate(comm,outmat);
4309: MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
4310: MatGetBlockSizes(inmat,&bs,&cbs);
4311: MatSetBlockSizes(*outmat,bs,cbs);
4312: MatSetType(*outmat,MATAIJ);
4313: MatSeqAIJSetPreallocation(*outmat,0,dnz);
4314: MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);
4315: MatPreallocateFinalize(dnz,onz);
4316: }
4318: /* numeric phase */
4319: MatGetOwnershipRange(*outmat,&rstart,NULL);
4320: for (i=0; i<m; i++) {
4321: MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
4322: Ii = i + rstart;
4323: MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
4324: MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
4325: }
4326: MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
4327: MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
4328: return(0);
4329: }
4331: PetscErrorCode MatFileSplit(Mat A,char *outfile)
4332: {
4333: PetscErrorCode ierr;
4334: PetscMPIInt rank;
4335: PetscInt m,N,i,rstart,nnz;
4336: size_t len;
4337: const PetscInt *indx;
4338: PetscViewer out;
4339: char *name;
4340: Mat B;
4341: const PetscScalar *values;
4344: MatGetLocalSize(A,&m,0);
4345: MatGetSize(A,0,&N);
4346: /* Should this be the type of the diagonal block of A? */
4347: MatCreate(PETSC_COMM_SELF,&B);
4348: MatSetSizes(B,m,N,m,N);
4349: MatSetBlockSizesFromMats(B,A,A);
4350: MatSetType(B,MATSEQAIJ);
4351: MatSeqAIJSetPreallocation(B,0,NULL);
4352: MatGetOwnershipRange(A,&rstart,0);
4353: for (i=0; i<m; i++) {
4354: MatGetRow(A,i+rstart,&nnz,&indx,&values);
4355: MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);
4356: MatRestoreRow(A,i+rstart,&nnz,&indx,&values);
4357: }
4358: MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
4359: MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
4361: MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);
4362: PetscStrlen(outfile,&len);
4363: PetscMalloc1(len+5,&name);
4364: sprintf(name,"%s.%d",outfile,rank);
4365: PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);
4366: PetscFree(name);
4367: MatView(B,out);
4368: PetscViewerDestroy(&out);
4369: MatDestroy(&B);
4370: return(0);
4371: }
4373: PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A)
4374: {
4375: PetscErrorCode ierr;
4376: Mat_Merge_SeqsToMPI *merge;
4377: PetscContainer container;
4380: PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);
4381: if (container) {
4382: PetscContainerGetPointer(container,(void**)&merge);
4383: PetscFree(merge->id_r);
4384: PetscFree(merge->len_s);
4385: PetscFree(merge->len_r);
4386: PetscFree(merge->bi);
4387: PetscFree(merge->bj);
4388: PetscFree(merge->buf_ri[0]);
4389: PetscFree(merge->buf_ri);
4390: PetscFree(merge->buf_rj[0]);
4391: PetscFree(merge->buf_rj);
4392: PetscFree(merge->coi);
4393: PetscFree(merge->coj);
4394: PetscFree(merge->owners_co);
4395: PetscLayoutDestroy(&merge->rowmap);
4396: PetscFree(merge);
4397: PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);
4398: }
4399: MatDestroy_MPIAIJ(A);
4400: return(0);
4401: }
4403: #include <../src/mat/utils/freespace.h>
4404: #include <petscbt.h>
4406: PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat)
4407: {
4408: PetscErrorCode ierr;
4409: MPI_Comm comm;
4410: Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data;
4411: PetscMPIInt size,rank,taga,*len_s;
4412: PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj;
4413: PetscInt proc,m;
4414: PetscInt **buf_ri,**buf_rj;
4415: PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj;
4416: PetscInt nrows,**buf_ri_k,**nextrow,**nextai;
4417: MPI_Request *s_waits,*r_waits;
4418: MPI_Status *status;
4419: MatScalar *aa=a->a;
4420: MatScalar **abuf_r,*ba_i;
4421: Mat_Merge_SeqsToMPI *merge;
4422: PetscContainer container;
4425: PetscObjectGetComm((PetscObject)mpimat,&comm);
4426: PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);
4428: MPI_Comm_size(comm,&size);
4429: MPI_Comm_rank(comm,&rank);
4431: PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);
4432: PetscContainerGetPointer(container,(void**)&merge);
4434: bi = merge->bi;
4435: bj = merge->bj;
4436: buf_ri = merge->buf_ri;
4437: buf_rj = merge->buf_rj;
4439: PetscMalloc1(size,&status);
4440: owners = merge->rowmap->range;
4441: len_s = merge->len_s;
4443: /* send and recv matrix values */
4444: /*-----------------------------*/
4445: PetscObjectGetNewTag((PetscObject)mpimat,&taga);
4446: PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);
4448: PetscMalloc1(merge->nsend+1,&s_waits);
4449: for (proc=0,k=0; proc<size; proc++) {
4450: if (!len_s[proc]) continue;
4451: i = owners[proc];
4452: MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);
4453: k++;
4454: }
4456: if (merge->nrecv) {MPI_Waitall(merge->nrecv,r_waits,status);}
4457: if (merge->nsend) {MPI_Waitall(merge->nsend,s_waits,status);}
4458: PetscFree(status);
4460: PetscFree(s_waits);
4461: PetscFree(r_waits);
4463: /* insert mat values of mpimat */
4464: /*----------------------------*/
4465: PetscMalloc1(N,&ba_i);
4466: PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);
4468: for (k=0; k<merge->nrecv; k++) {
4469: buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
4470: nrows = *(buf_ri_k[k]);
4471: nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */
4472: nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */
4473: }
4475: /* set values of ba */
4476: m = merge->rowmap->n;
4477: for (i=0; i<m; i++) {
4478: arow = owners[rank] + i;
4479: bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */
4480: bnzi = bi[i+1] - bi[i];
4481: PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));
4483: /* add local non-zero vals of this proc's seqmat into ba */
4484: anzi = ai[arow+1] - ai[arow];
4485: aj = a->j + ai[arow];
4486: aa = a->a + ai[arow];
4487: nextaj = 0;
4488: for (j=0; nextaj<anzi; j++) {
4489: if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */
4490: ba_i[j] += aa[nextaj++];
4491: }
4492: }
4494: /* add received vals into ba */
4495: for (k=0; k<merge->nrecv; k++) { /* k-th received message */
4496: /* i-th row */
4497: if (i == *nextrow[k]) {
4498: anzi = *(nextai[k]+1) - *nextai[k];
4499: aj = buf_rj[k] + *(nextai[k]);
4500: aa = abuf_r[k] + *(nextai[k]);
4501: nextaj = 0;
4502: for (j=0; nextaj<anzi; j++) {
4503: if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */
4504: ba_i[j] += aa[nextaj++];
4505: }
4506: }
4507: nextrow[k]++; nextai[k]++;
4508: }
4509: }
4510: MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);
4511: }
4512: MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);
4513: MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);
4515: PetscFree(abuf_r[0]);
4516: PetscFree(abuf_r);
4517: PetscFree(ba_i);
4518: PetscFree3(buf_ri_k,nextrow,nextai);
4519: PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);
4520: return(0);
4521: }
4523: PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat)
4524: {
4525: PetscErrorCode ierr;
4526: Mat B_mpi;
4527: Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data;
4528: PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri;
4529: PetscInt **buf_rj,**buf_ri,**buf_ri_k;
4530: PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j;
4531: PetscInt len,proc,*dnz,*onz,bs,cbs;
4532: PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0;
4533: PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai;
4534: MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits;
4535: MPI_Status *status;
4536: PetscFreeSpaceList free_space=NULL,current_space=NULL;
4537: PetscBT lnkbt;
4538: Mat_Merge_SeqsToMPI *merge;
4539: PetscContainer container;
4542: PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);
4544: /* make sure it is a PETSc comm */
4545: PetscCommDuplicate(comm,&comm,NULL);
4546: MPI_Comm_size(comm,&size);
4547: MPI_Comm_rank(comm,&rank);
4549: PetscNew(&merge);
4550: PetscMalloc1(size,&status);
4552: /* determine row ownership */
4553: /*---------------------------------------------------------*/
4554: PetscLayoutCreate(comm,&merge->rowmap);
4555: PetscLayoutSetLocalSize(merge->rowmap,m);
4556: PetscLayoutSetSize(merge->rowmap,M);
4557: PetscLayoutSetBlockSize(merge->rowmap,1);
4558: PetscLayoutSetUp(merge->rowmap);
4559: PetscMalloc1(size,&len_si);
4560: PetscMalloc1(size,&merge->len_s);
4562: m = merge->rowmap->n;
4563: owners = merge->rowmap->range;
4565: /* determine the number of messages to send, their lengths */
4566: /*---------------------------------------------------------*/
4567: len_s = merge->len_s;
4569: len = 0; /* length of buf_si[] */
4570: merge->nsend = 0;
4571: for (proc=0; proc<size; proc++) {
4572: len_si[proc] = 0;
4573: if (proc == rank) {
4574: len_s[proc] = 0;
4575: } else {
4576: len_si[proc] = owners[proc+1] - owners[proc] + 1;
4577: len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */
4578: }
4579: if (len_s[proc]) {
4580: merge->nsend++;
4581: nrows = 0;
4582: for (i=owners[proc]; i<owners[proc+1]; i++) {
4583: if (ai[i+1] > ai[i]) nrows++;
4584: }
4585: len_si[proc] = 2*(nrows+1);
4586: len += len_si[proc];
4587: }
4588: }
4590: /* determine the number and length of messages to receive for ij-structure */
4591: /*-------------------------------------------------------------------------*/
4592: PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);
4593: PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);
4595: /* post the Irecv of j-structure */
4596: /*-------------------------------*/
4597: PetscCommGetNewTag(comm,&tagj);
4598: PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);
4600: /* post the Isend of j-structure */
4601: /*--------------------------------*/
4602: PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);
4604: for (proc=0, k=0; proc<size; proc++) {
4605: if (!len_s[proc]) continue;
4606: i = owners[proc];
4607: MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);
4608: k++;
4609: }
4611: /* receives and sends of j-structure are complete */
4612: /*------------------------------------------------*/
4613: if (merge->nrecv) {MPI_Waitall(merge->nrecv,rj_waits,status);}
4614: if (merge->nsend) {MPI_Waitall(merge->nsend,sj_waits,status);}
4616: /* send and recv i-structure */
4617: /*---------------------------*/
4618: PetscCommGetNewTag(comm,&tagi);
4619: PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);
4621: PetscMalloc1(len+1,&buf_s);
4622: buf_si = buf_s; /* points to the beginning of k-th msg to be sent */
4623: for (proc=0,k=0; proc<size; proc++) {
4624: if (!len_s[proc]) continue;
4625: /* form outgoing message for i-structure:
4626: buf_si[0]: nrows to be sent
4627: [1:nrows]: row index (global)
4628: [nrows+1:2*nrows+1]: i-structure index
4629: */
4630: /*-------------------------------------------*/
4631: nrows = len_si[proc]/2 - 1;
4632: buf_si_i = buf_si + nrows+1;
4633: buf_si[0] = nrows;
4634: buf_si_i[0] = 0;
4635: nrows = 0;
4636: for (i=owners[proc]; i<owners[proc+1]; i++) {
4637: anzi = ai[i+1] - ai[i];
4638: if (anzi) {
4639: buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */
4640: buf_si[nrows+1] = i-owners[proc]; /* local row index */
4641: nrows++;
4642: }
4643: }
4644: MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);
4645: k++;
4646: buf_si += len_si[proc];
4647: }
4649: if (merge->nrecv) {MPI_Waitall(merge->nrecv,ri_waits,status);}
4650: if (merge->nsend) {MPI_Waitall(merge->nsend,si_waits,status);}
4652: PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);
4653: for (i=0; i<merge->nrecv; i++) {
4654: PetscInfo3(seqmat,"recv len_ri=%D, len_rj=%D from [%D]\n",len_ri[i],merge->len_r[i],merge->id_r[i]);
4655: }
4657: PetscFree(len_si);
4658: PetscFree(len_ri);
4659: PetscFree(rj_waits);
4660: PetscFree2(si_waits,sj_waits);
4661: PetscFree(ri_waits);
4662: PetscFree(buf_s);
4663: PetscFree(status);
4665: /* compute a local seq matrix in each processor */
4666: /*----------------------------------------------*/
4667: /* allocate bi array and free space for accumulating nonzero column info */
4668: PetscMalloc1(m+1,&bi);
4669: bi[0] = 0;
4671: /* create and initialize a linked list */
4672: nlnk = N+1;
4673: PetscLLCreate(N,N,nlnk,lnk,lnkbt);
4675: /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */
4676: len = ai[owners[rank+1]] - ai[owners[rank]];
4677: PetscFreeSpaceGet(PetscIntMultTruncate(2,len)+1,&free_space);
4679: current_space = free_space;
4681: /* determine symbolic info for each local row */
4682: PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);
4684: for (k=0; k<merge->nrecv; k++) {
4685: buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
4686: nrows = *buf_ri_k[k];
4687: nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */
4688: nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */
4689: }
4691: MatPreallocateInitialize(comm,m,n,dnz,onz);
4692: len = 0;
4693: for (i=0; i<m; i++) {
4694: bnzi = 0;
4695: /* add local non-zero cols of this proc's seqmat into lnk */
4696: arow = owners[rank] + i;
4697: anzi = ai[arow+1] - ai[arow];
4698: aj = a->j + ai[arow];
4699: PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);
4700: bnzi += nlnk;
4701: /* add received col data into lnk */
4702: for (k=0; k<merge->nrecv; k++) { /* k-th received message */
4703: if (i == *nextrow[k]) { /* i-th row */
4704: anzi = *(nextai[k]+1) - *nextai[k];
4705: aj = buf_rj[k] + *nextai[k];
4706: PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);
4707: bnzi += nlnk;
4708: nextrow[k]++; nextai[k]++;
4709: }
4710: }
4711: if (len < bnzi) len = bnzi; /* =max(bnzi) */
4713: /* if free space is not available, make more free space */
4714: if (current_space->local_remaining<bnzi) {
4715: PetscFreeSpaceGet(PetscIntSumTruncate(bnzi,current_space->total_array_size),¤t_space);
4716: nspacedouble++;
4717: }
4718: /* copy data into free space, then initialize lnk */
4719: PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);
4720: MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);
4722: current_space->array += bnzi;
4723: current_space->local_used += bnzi;
4724: current_space->local_remaining -= bnzi;
4726: bi[i+1] = bi[i] + bnzi;
4727: }
4729: PetscFree3(buf_ri_k,nextrow,nextai);
4731: PetscMalloc1(bi[m]+1,&bj);
4732: PetscFreeSpaceContiguous(&free_space,bj);
4733: PetscLLDestroy(lnk,lnkbt);
4735: /* create symbolic parallel matrix B_mpi */
4736: /*---------------------------------------*/
4737: MatGetBlockSizes(seqmat,&bs,&cbs);
4738: MatCreate(comm,&B_mpi);
4739: if (n==PETSC_DECIDE) {
4740: MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);
4741: } else {
4742: MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
4743: }
4744: MatSetBlockSizes(B_mpi,bs,cbs);
4745: MatSetType(B_mpi,MATMPIAIJ);
4746: MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);
4747: MatPreallocateFinalize(dnz,onz);
4748: MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);
4750: /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */
4751: B_mpi->assembled = PETSC_FALSE;
4752: B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI;
4753: merge->bi = bi;
4754: merge->bj = bj;
4755: merge->buf_ri = buf_ri;
4756: merge->buf_rj = buf_rj;
4757: merge->coi = NULL;
4758: merge->coj = NULL;
4759: merge->owners_co = NULL;
4761: PetscCommDestroy(&comm);
4763: /* attach the supporting struct to B_mpi for reuse */
4764: PetscContainerCreate(PETSC_COMM_SELF,&container);
4765: PetscContainerSetPointer(container,merge);
4766: PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);
4767: PetscContainerDestroy(&container);
4768: *mpimat = B_mpi;
4770: PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);
4771: return(0);
4772: }
4774: /*@C
4775: MatCreateMPIAIJSumSeqAIJ - Creates a MATMPIAIJ matrix by adding sequential
4776: matrices from each processor
4778: Collective on MPI_Comm
4780: Input Parameters:
4781: + comm - the communicators the parallel matrix will live on
4782: . seqmat - the input sequential matrices
4783: . m - number of local rows (or PETSC_DECIDE)
4784: . n - number of local columns (or PETSC_DECIDE)
4785: - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
4787: Output Parameter:
4788: . mpimat - the parallel matrix generated
4790: Level: advanced
4792: Notes:
4793: The dimensions of the sequential matrix in each processor MUST be the same.
4794: The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be
4795: destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat.
4796: @*/
4797: PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat)
4798: {
4800: PetscMPIInt size;
4803: MPI_Comm_size(comm,&size);
4804: if (size == 1) {
4805: PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
4806: if (scall == MAT_INITIAL_MATRIX) {
4807: MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);
4808: } else {
4809: MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);
4810: }
4811: PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
4812: return(0);
4813: }
4814: PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
4815: if (scall == MAT_INITIAL_MATRIX) {
4816: MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);
4817: }
4818: MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);
4819: PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
4820: return(0);
4821: }
4823: /*@
4824: MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MATMPIAIJ matrix by taking all its local rows and putting them into a sequential matrix with
4825: mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained
4826: with MatGetSize()
4828: Not Collective
4830: Input Parameters:
4831: + A - the matrix
4832: . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
4834: Output Parameter:
4835: . A_loc - the local sequential matrix generated
4837: Level: developer
4839: .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed()
4841: @*/
4842: PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc)
4843: {
4845: Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data;
4846: Mat_SeqAIJ *mat,*a,*b;
4847: PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray;
4848: MatScalar *aa,*ba,*cam;
4849: PetscScalar *ca;
4850: PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart;
4851: PetscInt *ci,*cj,col,ncols_d,ncols_o,jo;
4852: PetscBool match;
4853: MPI_Comm comm;
4854: PetscMPIInt size;
4857: PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);
4858: if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input");
4859: PetscObjectGetComm((PetscObject)A,&comm);
4860: MPI_Comm_size(comm,&size);
4861: if (size == 1 && scall == MAT_REUSE_MATRIX) return(0);
4863: PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);
4864: a = (Mat_SeqAIJ*)(mpimat->A)->data;
4865: b = (Mat_SeqAIJ*)(mpimat->B)->data;
4866: ai = a->i; aj = a->j; bi = b->i; bj = b->j;
4867: aa = a->a; ba = b->a;
4868: if (scall == MAT_INITIAL_MATRIX) {
4869: if (size == 1) {
4870: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);
4871: return(0);
4872: }
4874: PetscMalloc1(1+am,&ci);
4875: ci[0] = 0;
4876: for (i=0; i<am; i++) {
4877: ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]);
4878: }
4879: PetscMalloc1(1+ci[am],&cj);
4880: PetscMalloc1(1+ci[am],&ca);
4881: k = 0;
4882: for (i=0; i<am; i++) {
4883: ncols_o = bi[i+1] - bi[i];
4884: ncols_d = ai[i+1] - ai[i];
4885: /* off-diagonal portion of A */
4886: for (jo=0; jo<ncols_o; jo++) {
4887: col = cmap[*bj];
4888: if (col >= cstart) break;
4889: cj[k] = col; bj++;
4890: ca[k++] = *ba++;
4891: }
4892: /* diagonal portion of A */
4893: for (j=0; j<ncols_d; j++) {
4894: cj[k] = cstart + *aj++;
4895: ca[k++] = *aa++;
4896: }
4897: /* off-diagonal portion of A */
4898: for (j=jo; j<ncols_o; j++) {
4899: cj[k] = cmap[*bj++];
4900: ca[k++] = *ba++;
4901: }
4902: }
4903: /* put together the new matrix */
4904: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);
4905: /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
4906: /* Since these are PETSc arrays, change flags to free them as necessary. */
4907: mat = (Mat_SeqAIJ*)(*A_loc)->data;
4908: mat->free_a = PETSC_TRUE;
4909: mat->free_ij = PETSC_TRUE;
4910: mat->nonew = 0;
4911: } else if (scall == MAT_REUSE_MATRIX) {
4912: mat=(Mat_SeqAIJ*)(*A_loc)->data;
4913: ci = mat->i; cj = mat->j; cam = mat->a;
4914: for (i=0; i<am; i++) {
4915: /* off-diagonal portion of A */
4916: ncols_o = bi[i+1] - bi[i];
4917: for (jo=0; jo<ncols_o; jo++) {
4918: col = cmap[*bj];
4919: if (col >= cstart) break;
4920: *cam++ = *ba++; bj++;
4921: }
4922: /* diagonal portion of A */
4923: ncols_d = ai[i+1] - ai[i];
4924: for (j=0; j<ncols_d; j++) *cam++ = *aa++;
4925: /* off-diagonal portion of A */
4926: for (j=jo; j<ncols_o; j++) {
4927: *cam++ = *ba++; bj++;
4928: }
4929: }
4930: } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall);
4931: PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);
4932: return(0);
4933: }
4935: /*@C
4936: MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MATMPIAIJ matrix by taking all its local rows and NON-ZERO columns
4938: Not Collective
4940: Input Parameters:
4941: + A - the matrix
4942: . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
4943: - row, col - index sets of rows and columns to extract (or NULL)
4945: Output Parameter:
4946: . A_loc - the local sequential matrix generated
4948: Level: developer
4950: .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat()
4952: @*/
4953: PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc)
4954: {
4955: Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data;
4957: PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx;
4958: IS isrowa,iscola;
4959: Mat *aloc;
4960: PetscBool match;
4963: PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);
4964: if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input");
4965: PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);
4966: if (!row) {
4967: start = A->rmap->rstart; end = A->rmap->rend;
4968: ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);
4969: } else {
4970: isrowa = *row;
4971: }
4972: if (!col) {
4973: start = A->cmap->rstart;
4974: cmap = a->garray;
4975: nzA = a->A->cmap->n;
4976: nzB = a->B->cmap->n;
4977: PetscMalloc1(nzA+nzB, &idx);
4978: ncols = 0;
4979: for (i=0; i<nzB; i++) {
4980: if (cmap[i] < start) idx[ncols++] = cmap[i];
4981: else break;
4982: }
4983: imark = i;
4984: for (i=0; i<nzA; i++) idx[ncols++] = start + i;
4985: for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i];
4986: ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);
4987: } else {
4988: iscola = *col;
4989: }
4990: if (scall != MAT_INITIAL_MATRIX) {
4991: PetscMalloc1(1,&aloc);
4992: aloc[0] = *A_loc;
4993: }
4994: MatCreateSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);
4995: *A_loc = aloc[0];
4996: PetscFree(aloc);
4997: if (!row) {
4998: ISDestroy(&isrowa);
4999: }
5000: if (!col) {
5001: ISDestroy(&iscola);
5002: }
5003: PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);
5004: return(0);
5005: }
5007: /*@C
5008: MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A
5010: Collective on Mat
5012: Input Parameters:
5013: + A,B - the matrices in mpiaij format
5014: . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
5015: - rowb, colb - index sets of rows and columns of B to extract (or NULL)
5017: Output Parameter:
5018: + rowb, colb - index sets of rows and columns of B to extract
5019: - B_seq - the sequential matrix generated
5021: Level: developer
5023: @*/
5024: PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq)
5025: {
5026: Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data;
5028: PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark;
5029: IS isrowb,iscolb;
5030: Mat *bseq=NULL;
5033: if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
5034: 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);
5035: }
5036: PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);
5038: if (scall == MAT_INITIAL_MATRIX) {
5039: start = A->cmap->rstart;
5040: cmap = a->garray;
5041: nzA = a->A->cmap->n;
5042: nzB = a->B->cmap->n;
5043: PetscMalloc1(nzA+nzB, &idx);
5044: ncols = 0;
5045: for (i=0; i<nzB; i++) { /* row < local row index */
5046: if (cmap[i] < start) idx[ncols++] = cmap[i];
5047: else break;
5048: }
5049: imark = i;
5050: for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */
5051: for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */
5052: ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);
5053: ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);
5054: } else {
5055: if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX");
5056: isrowb = *rowb; iscolb = *colb;
5057: PetscMalloc1(1,&bseq);
5058: bseq[0] = *B_seq;
5059: }
5060: MatCreateSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);
5061: *B_seq = bseq[0];
5062: PetscFree(bseq);
5063: if (!rowb) {
5064: ISDestroy(&isrowb);
5065: } else {
5066: *rowb = isrowb;
5067: }
5068: if (!colb) {
5069: ISDestroy(&iscolb);
5070: } else {
5071: *colb = iscolb;
5072: }
5073: PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);
5074: return(0);
5075: }
5077: /*
5078: MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns
5079: of the OFF-DIAGONAL portion of local A
5081: Collective on Mat
5083: Input Parameters:
5084: + A,B - the matrices in mpiaij format
5085: - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
5087: Output Parameter:
5088: + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL)
5089: . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL)
5090: . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL)
5091: - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N
5093: Level: developer
5095: */
5096: PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth)
5097: {
5098: VecScatter_MPI_General *gen_to,*gen_from;
5099: PetscErrorCode ierr;
5100: Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data;
5101: Mat_SeqAIJ *b_oth;
5102: VecScatter ctx =a->Mvctx;
5103: MPI_Comm comm;
5104: PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank;
5105: PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj;
5106: PetscInt *rvalues,*svalues;
5107: MatScalar *b_otha,*bufa,*bufA;
5108: PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len;
5109: MPI_Request *rwaits = NULL,*swaits = NULL;
5110: MPI_Status *sstatus,rstatus;
5111: PetscMPIInt jj,size;
5112: PetscInt *cols,sbs,rbs;
5113: PetscScalar *vals;
5116: PetscObjectGetComm((PetscObject)A,&comm);
5117: MPI_Comm_size(comm,&size);
5119: if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
5120: 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);
5121: }
5122: PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);
5123: MPI_Comm_rank(comm,&rank);
5125: if (size == 1) {
5126: startsj_s = NULL;
5127: bufa_ptr = NULL;
5128: *B_oth = NULL;
5129: return(0);
5130: }
5132: gen_to = (VecScatter_MPI_General*)ctx->todata;
5133: gen_from = (VecScatter_MPI_General*)ctx->fromdata;
5134: nrecvs = gen_from->n;
5135: nsends = gen_to->n;
5137: PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);
5138: srow = gen_to->indices; /* local row index to be sent */
5139: sstarts = gen_to->starts;
5140: sprocs = gen_to->procs;
5141: sstatus = gen_to->sstatus;
5142: sbs = gen_to->bs;
5143: rstarts = gen_from->starts;
5144: rprocs = gen_from->procs;
5145: rbs = gen_from->bs;
5147: if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX;
5148: if (scall == MAT_INITIAL_MATRIX) {
5149: /* i-array */
5150: /*---------*/
5151: /* post receives */
5152: PetscMalloc1(rbs*(rstarts[nrecvs] - rstarts[0]),&rvalues);
5153: for (i=0; i<nrecvs; i++) {
5154: rowlen = rvalues + rstarts[i]*rbs;
5155: nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */
5156: MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
5157: }
5159: /* pack the outgoing message */
5160: PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);
5162: sstartsj[0] = 0;
5163: rstartsj[0] = 0;
5164: len = 0; /* total length of j or a array to be sent */
5165: k = 0;
5166: PetscMalloc1(sbs*(sstarts[nsends] - sstarts[0]),&svalues);
5167: for (i=0; i<nsends; i++) {
5168: rowlen = svalues + sstarts[i]*sbs;
5169: nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
5170: for (j=0; j<nrows; j++) {
5171: row = srow[k] + B->rmap->range[rank]; /* global row idx */
5172: for (l=0; l<sbs; l++) {
5173: MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL); /* rowlength */
5175: rowlen[j*sbs+l] = ncols;
5177: len += ncols;
5178: MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);
5179: }
5180: k++;
5181: }
5182: MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);
5184: sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */
5185: }
5186: /* recvs and sends of i-array are completed */
5187: i = nrecvs;
5188: while (i--) {
5189: MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
5190: }
5191: if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}
5192: PetscFree(svalues);
5194: /* allocate buffers for sending j and a arrays */
5195: PetscMalloc1(len+1,&bufj);
5196: PetscMalloc1(len+1,&bufa);
5198: /* create i-array of B_oth */
5199: PetscMalloc1(aBn+2,&b_othi);
5201: b_othi[0] = 0;
5202: len = 0; /* total length of j or a array to be received */
5203: k = 0;
5204: for (i=0; i<nrecvs; i++) {
5205: rowlen = rvalues + rstarts[i]*rbs;
5206: nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be received */
5207: for (j=0; j<nrows; j++) {
5208: b_othi[k+1] = b_othi[k] + rowlen[j];
5209: PetscIntSumError(rowlen[j],len,&len);
5210: k++;
5211: }
5212: rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */
5213: }
5214: PetscFree(rvalues);
5216: /* allocate space for j and a arrrays of B_oth */
5217: PetscMalloc1(b_othi[aBn]+1,&b_othj);
5218: PetscMalloc1(b_othi[aBn]+1,&b_otha);
5220: /* j-array */
5221: /*---------*/
5222: /* post receives of j-array */
5223: for (i=0; i<nrecvs; i++) {
5224: nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
5225: MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
5226: }
5228: /* pack the outgoing message j-array */
5229: k = 0;
5230: for (i=0; i<nsends; i++) {
5231: nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
5232: bufJ = bufj+sstartsj[i];
5233: for (j=0; j<nrows; j++) {
5234: row = srow[k++] + B->rmap->range[rank]; /* global row idx */
5235: for (ll=0; ll<sbs; ll++) {
5236: MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);
5237: for (l=0; l<ncols; l++) {
5238: *bufJ++ = cols[l];
5239: }
5240: MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);
5241: }
5242: }
5243: MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);
5244: }
5246: /* recvs and sends of j-array are completed */
5247: i = nrecvs;
5248: while (i--) {
5249: MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
5250: }
5251: if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}
5252: } else if (scall == MAT_REUSE_MATRIX) {
5253: sstartsj = *startsj_s;
5254: rstartsj = *startsj_r;
5255: bufa = *bufa_ptr;
5256: b_oth = (Mat_SeqAIJ*)(*B_oth)->data;
5257: b_otha = b_oth->a;
5258: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container");
5260: /* a-array */
5261: /*---------*/
5262: /* post receives of a-array */
5263: for (i=0; i<nrecvs; i++) {
5264: nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
5265: MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);
5266: }
5268: /* pack the outgoing message a-array */
5269: k = 0;
5270: for (i=0; i<nsends; i++) {
5271: nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
5272: bufA = bufa+sstartsj[i];
5273: for (j=0; j<nrows; j++) {
5274: row = srow[k++] + B->rmap->range[rank]; /* global row idx */
5275: for (ll=0; ll<sbs; ll++) {
5276: MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);
5277: for (l=0; l<ncols; l++) {
5278: *bufA++ = vals[l];
5279: }
5280: MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);
5281: }
5282: }
5283: MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);
5284: }
5285: /* recvs and sends of a-array are completed */
5286: i = nrecvs;
5287: while (i--) {
5288: MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
5289: }
5290: if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}
5291: PetscFree2(rwaits,swaits);
5293: if (scall == MAT_INITIAL_MATRIX) {
5294: /* put together the new matrix */
5295: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);
5297: /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
5298: /* Since these are PETSc arrays, change flags to free them as necessary. */
5299: b_oth = (Mat_SeqAIJ*)(*B_oth)->data;
5300: b_oth->free_a = PETSC_TRUE;
5301: b_oth->free_ij = PETSC_TRUE;
5302: b_oth->nonew = 0;
5304: PetscFree(bufj);
5305: if (!startsj_s || !bufa_ptr) {
5306: PetscFree2(sstartsj,rstartsj);
5307: PetscFree(bufa_ptr);
5308: } else {
5309: *startsj_s = sstartsj;
5310: *startsj_r = rstartsj;
5311: *bufa_ptr = bufa;
5312: }
5313: }
5314: PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);
5315: return(0);
5316: }
5318: /*@C
5319: MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication.
5321: Not Collective
5323: Input Parameters:
5324: . A - The matrix in mpiaij format
5326: Output Parameter:
5327: + lvec - The local vector holding off-process values from the argument to a matrix-vector product
5328: . colmap - A map from global column index to local index into lvec
5329: - multScatter - A scatter from the argument of a matrix-vector product to lvec
5331: Level: developer
5333: @*/
5334: #if defined(PETSC_USE_CTABLE)
5335: PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter)
5336: #else
5337: PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter)
5338: #endif
5339: {
5340: Mat_MPIAIJ *a;
5347: a = (Mat_MPIAIJ*) A->data;
5348: if (lvec) *lvec = a->lvec;
5349: if (colmap) *colmap = a->colmap;
5350: if (multScatter) *multScatter = a->Mvctx;
5351: return(0);
5352: }
5354: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*);
5355: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*);
5356: #if defined(PETSC_HAVE_MKL_SPARSE)
5357: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJMKL(Mat,MatType,MatReuse,Mat*);
5358: #endif
5359: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*);
5360: #if defined(PETSC_HAVE_ELEMENTAL)
5361: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*);
5362: #endif
5363: #if defined(PETSC_HAVE_HYPRE)
5364: PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*);
5365: PETSC_INTERN PetscErrorCode MatMatMatMult_Transpose_AIJ_AIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*);
5366: #endif
5367: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_IS(Mat,MatType,MatReuse,Mat*);
5369: /*
5370: Computes (B'*A')' since computing B*A directly is untenable
5372: n p p
5373: ( ) ( ) ( )
5374: m ( A ) * n ( B ) = m ( C )
5375: ( ) ( ) ( )
5377: */
5378: PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C)
5379: {
5381: Mat At,Bt,Ct;
5384: MatTranspose(A,MAT_INITIAL_MATRIX,&At);
5385: MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);
5386: MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);
5387: MatDestroy(&At);
5388: MatDestroy(&Bt);
5389: MatTranspose(Ct,MAT_REUSE_MATRIX,&C);
5390: MatDestroy(&Ct);
5391: return(0);
5392: }
5394: PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C)
5395: {
5397: PetscInt m=A->rmap->n,n=B->cmap->n;
5398: Mat Cmat;
5401: 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);
5402: MatCreate(PetscObjectComm((PetscObject)A),&Cmat);
5403: MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
5404: MatSetBlockSizesFromMats(Cmat,A,B);
5405: MatSetType(Cmat,MATMPIDENSE);
5406: MatMPIDenseSetPreallocation(Cmat,NULL);
5407: MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);
5408: MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);
5410: Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ;
5412: *C = Cmat;
5413: return(0);
5414: }
5416: /* ----------------------------------------------------------------*/
5417: PETSC_INTERN PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
5418: {
5422: if (scall == MAT_INITIAL_MATRIX) {
5423: PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);
5424: MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);
5425: PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);
5426: }
5427: PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);
5428: MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);
5429: PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);
5430: return(0);
5431: }
5433: /*MC
5434: MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices.
5436: Options Database Keys:
5437: . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions()
5439: Level: beginner
5441: .seealso: MatCreateAIJ()
5442: M*/
5444: PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B)
5445: {
5446: Mat_MPIAIJ *b;
5448: PetscMPIInt size;
5451: MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
5453: PetscNewLog(B,&b);
5454: B->data = (void*)b;
5455: PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
5456: B->assembled = PETSC_FALSE;
5457: B->insertmode = NOT_SET_VALUES;
5458: b->size = size;
5460: MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
5462: /* build cache for off array entries formed */
5463: MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);
5465: b->donotstash = PETSC_FALSE;
5466: b->colmap = 0;
5467: b->garray = 0;
5468: b->roworiented = PETSC_TRUE;
5470: /* stuff used for matrix vector multiply */
5471: b->lvec = NULL;
5472: b->Mvctx = NULL;
5474: /* stuff for MatGetRow() */
5475: b->rowindices = 0;
5476: b->rowvalues = 0;
5477: b->getrowactive = PETSC_FALSE;
5479: /* flexible pointer used in CUSP/CUSPARSE classes */
5480: b->spptr = NULL;
5482: PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);
5483: PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);
5484: PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);
5485: PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);
5486: PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);
5487: PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);
5488: PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);
5489: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);
5490: #if defined(PETSC_HAVE_MKL_SPARSE)
5491: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijmkl_C",MatConvert_MPIAIJ_MPIAIJMKL);
5492: #endif
5493: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);
5494: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);
5495: #if defined(PETSC_HAVE_ELEMENTAL)
5496: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);
5497: #endif
5498: #if defined(PETSC_HAVE_HYPRE)
5499: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_hypre_C",MatConvert_AIJ_HYPRE);
5500: #endif
5501: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_is_C",MatConvert_MPIAIJ_IS);
5502: PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);
5503: PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);
5504: PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);
5505: #if defined(PETSC_HAVE_HYPRE)
5506: PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_mpiaij_mpiaij_C",MatMatMatMult_Transpose_AIJ_AIJ);
5507: #endif
5508: PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);
5509: return(0);
5510: }
5512: /*@C
5513: MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal"
5514: and "off-diagonal" part of the matrix in CSR format.
5516: Collective on MPI_Comm
5518: Input Parameters:
5519: + comm - MPI communicator
5520: . m - number of local rows (Cannot be PETSC_DECIDE)
5521: . n - This value should be the same as the local size used in creating the
5522: x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
5523: calculated if N is given) For square matrices n is almost always m.
5524: . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
5525: . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
5526: . i - row indices for "diagonal" portion of matrix
5527: . j - column indices
5528: . a - matrix values
5529: . oi - row indices for "off-diagonal" portion of matrix
5530: . oj - column indices
5531: - oa - matrix values
5533: Output Parameter:
5534: . mat - the matrix
5536: Level: advanced
5538: Notes:
5539: The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user
5540: must free the arrays once the matrix has been destroyed and not before.
5542: The i and j indices are 0 based
5544: See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix
5546: This sets local rows and cannot be used to set off-processor values.
5548: Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a
5549: legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does
5550: not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because
5551: the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to
5552: keep track of the underlying array. Use MatSetOption(A,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all
5553: communication if it is known that only local entries will be set.
5555: .keywords: matrix, aij, compressed row, sparse, parallel
5557: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
5558: MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays()
5559: @*/
5560: 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)
5561: {
5563: Mat_MPIAIJ *maij;
5566: if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
5567: if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
5568: if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0");
5569: MatCreate(comm,mat);
5570: MatSetSizes(*mat,m,n,M,N);
5571: MatSetType(*mat,MATMPIAIJ);
5572: maij = (Mat_MPIAIJ*) (*mat)->data;
5574: (*mat)->preallocated = PETSC_TRUE;
5576: PetscLayoutSetUp((*mat)->rmap);
5577: PetscLayoutSetUp((*mat)->cmap);
5579: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);
5580: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);
5582: MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);
5583: MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);
5584: MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);
5585: MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);
5587: MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);
5588: MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
5589: MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
5590: MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);
5591: MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
5592: return(0);
5593: }
5595: /*
5596: Special version for direct calls from Fortran
5597: */
5598: #include <petsc/private/fortranimpl.h>
5600: /* Change these macros so can be used in void function */
5601: #undef CHKERRQ
5602: #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr)
5603: #undef SETERRQ2
5604: #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr)
5605: #undef SETERRQ3
5606: #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr)
5607: #undef SETERRQ
5608: #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr)
5610: #if defined(PETSC_HAVE_FORTRAN_CAPS)
5611: #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ
5612: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
5613: #define matsetvaluesmpiaij_ matsetvaluesmpiaij
5614: #else
5615: #endif
5616: 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)
5617: {
5618: Mat mat = *mmat;
5619: PetscInt m = *mm, n = *mn;
5620: InsertMode addv = *maddv;
5621: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
5622: PetscScalar value;
5625: MatCheckPreallocated(mat,1);
5626: if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv;
5628: #if defined(PETSC_USE_DEBUG)
5629: else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values");
5630: #endif
5631: {
5632: PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend;
5633: PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
5634: PetscBool roworiented = aij->roworiented;
5636: /* Some Variables required in the macro */
5637: Mat A = aij->A;
5638: Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data;
5639: PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j;
5640: MatScalar *aa = a->a;
5641: PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE);
5642: Mat B = aij->B;
5643: Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data;
5644: PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n;
5645: MatScalar *ba = b->a;
5647: PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2;
5648: PetscInt nonew = a->nonew;
5649: MatScalar *ap1,*ap2;
5652: for (i=0; i<m; i++) {
5653: if (im[i] < 0) continue;
5654: #if defined(PETSC_USE_DEBUG)
5655: 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);
5656: #endif
5657: if (im[i] >= rstart && im[i] < rend) {
5658: row = im[i] - rstart;
5659: lastcol1 = -1;
5660: rp1 = aj + ai[row];
5661: ap1 = aa + ai[row];
5662: rmax1 = aimax[row];
5663: nrow1 = ailen[row];
5664: low1 = 0;
5665: high1 = nrow1;
5666: lastcol2 = -1;
5667: rp2 = bj + bi[row];
5668: ap2 = ba + bi[row];
5669: rmax2 = bimax[row];
5670: nrow2 = bilen[row];
5671: low2 = 0;
5672: high2 = nrow2;
5674: for (j=0; j<n; j++) {
5675: if (roworiented) value = v[i*n+j];
5676: else value = v[i+j*m];
5677: if (in[j] >= cstart && in[j] < cend) {
5678: col = in[j] - cstart;
5679: if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue;
5680: MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]);
5681: } else if (in[j] < 0) continue;
5682: #if defined(PETSC_USE_DEBUG)
5683: 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);
5684: #endif
5685: else {
5686: if (mat->was_assembled) {
5687: if (!aij->colmap) {
5688: MatCreateColmap_MPIAIJ_Private(mat);
5689: }
5690: #if defined(PETSC_USE_CTABLE)
5691: PetscTableFind(aij->colmap,in[j]+1,&col);
5692: col--;
5693: #else
5694: col = aij->colmap[in[j]] - 1;
5695: #endif
5696: if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue;
5697: if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
5698: MatDisAssemble_MPIAIJ(mat);
5699: col = in[j];
5700: /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
5701: B = aij->B;
5702: b = (Mat_SeqAIJ*)B->data;
5703: bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j;
5704: rp2 = bj + bi[row];
5705: ap2 = ba + bi[row];
5706: rmax2 = bimax[row];
5707: nrow2 = bilen[row];
5708: low2 = 0;
5709: high2 = nrow2;
5710: bm = aij->B->rmap->n;
5711: ba = b->a;
5712: }
5713: } else col = in[j];
5714: MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]);
5715: }
5716: }
5717: } else if (!aij->donotstash) {
5718: if (roworiented) {
5719: MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
5720: } else {
5721: MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
5722: }
5723: }
5724: }
5725: }
5726: PetscFunctionReturnVoid();
5727: }